Scaling up semiconductor production while divesting from Chinese supply chains could present a serious procurement challenge for Japan’s AI sector.

Increasingly Japan is committing public and private sector resources to secure both the resurgence of the country’s semiconductor manufacturing sector and a significant portion of the burgeoning generative artificial intelligence (AI) market. 

On 19th April, Sakura Internet secured around 10,000 next-generation NVIDIA B200 GPUs for roughly 20 billion yen ($130 million). Sakura is one of five Japanese companies receiving government subsidies as it expands its cloud services to support AI workloads. 

Japan invests in domestic AI capabilities 

This investment marks a significant move by the nation to strengthen their position in the field of AI. Sakura, in partnership with the Japanese government, is spearheading this latest initiative to bring the country to the forefront of the rapidly developing market. 

Sakura’s Operating Officer, Yohei Ueno, referenced the difficulties of procuring such a significant number of semiconductors, whilst underpinning its necessity: “We feel a sense of urgency that not many generative AI [products] have materialised in Japan despite the global trend.” 

Beyond Japan’s domestic market

However, the procurement of the highly sought-after chips could likely echo beyond Japan’s domestic market. Not only did Jensen Huang (NVIDIA’s CEO) pledge in December 2023 to “prioritise Japan’s GPU requirements” in talks with Japan’s Prime Minister Fumio Kishida, but also, earlier this month, Kishida engaged in talks with US President Joe Biden to outline ongoing international relationships in light of the investment. 

“We welcome cooperation between US and Japanese companies toward the development of foundation models for generative AI, including contribution of NVIDIA’s GPUs to Japanese computational resources companies such as Sakura Internet,” a White House spokesperson said in an official statement. The statement also referenced contributions of “other computational resources from Google and Microsoft to Japanese AI foundation models development companies.”

Kishida’s state visit coincided with the announcement that Microsoft would invest $2.9 billion over the next two years in efforts to develop its AI and cloud infrastructure in Japan. As it stands, the investment would be the US tech giant’s largest injection of capital into the Japanese market to date. 

In its statement, the Biden administration also stressed the importance of building strategic partnerships between US and Japanese universities and corporations. “The United States and Japan welcome a new $110 million joint Artificial Intelligence partnership with the University of Washington and University of Tsukuba as well as Carnegie Mellon University and Keio University through funding from NVIDIA, Arm, and Amazon, Microsoft, and a consortium of Japanese companies.” Collaboration within the education sector heralds promising developments for both countries’ expanding influence within AI. 

Tension ahead

That said, the journey ahead does not appear smooth as trade relationships between Japan, China and North America remain tense. These geopolitical tensions could potentially jeopardise Japan’s efforts to both scale up semiconductor manufacturing and leverage its close relationship to the US to catalyse the development of its AI sector. 

From August 2023, China began to impose export controls upon rare minerals inextricably connected with the global production of semiconductors. Restrictions deepened as of December 2023 as the country announced further export controls on high-grade graphite. 

Subsequent trade statistics released by Chinese customs authorities showed a 40% quantitative decrease in China’s exports of graphite and related materials to Japan. Historically, Japan has relied upon China for 90% of its graphite imports. The country’s need to diversify is more pressing than ever in light of China’s growing export restrictions.

Furthermore, future US trade agreements will likely hinge on Japan’s ability to divest from Chinese supply chains. Whilst the US is an enthusiastic advocate for Japan expanding its AI capabilities, Japanese overdependence on China in order to procure the necessary materials for AI development could be a critical source of friction in the future. 

The US has already been taking steps to destabilise China’s influence in the chipmaking industry. This is echoed in Japan’s recent trade agreements for the supply of graphite in the EV sector. 

Over the last two months, Panasonic Energy Co., Ltd. announced agreements with NOVONIX Limited (Queensland, Australia) and Nouveau Monde Graphite Inc. (Quebec, Canada) for the supply of synthetic and natural graphite respectively. Previously, it has been noted by Kishida and Canada’s Prime Minister Justin Trudeau during a state visit that China is a “central challenge” for both countries. 

An uncertain future

It is unclear whether Panasonic’s recent trade agreements will relate to the field of semiconductors but it is evident that Japan intends to make its mark upon generative AI. Political and corporate sentiments, within Japan and beyond, show vested interest in reducing Japan’s involvement with China.

It remains unclear whether Japan will be able to circumvent China whilst strengthening its position in artificial intelligence and cutting-edge computing. What is certain is that, regardless of government subsidies, international support or investments in education, without the ability to procure the necessary products and materials, Japan’s efforts will be rendered ineffective. 

Artificial intelligence has the power to combat procurement pain points with Predictive Procurement Orchestration.

The 2020s represent a decade of newly realised potential for procurement to drive new sources of value creation, reduce costs across the supply chain, and be a leader of sustainable reform. 

However, equally significant pain points and challenges stand in the way. From inflation, rising costs, political turmoil, and an increasingly strict regulatory landscape, to the looming reality of the climate crisis and a widespread skill shortage, procurement leaders have a lot to contend with. 

Much of the digital transformation aimed at creating greater visibility and efficiency in the procurement process is, some argue, targeted more at providing executives with glossy dashboards than meaningful ways to reduce procurement workload. The result is that, while both procurement departments and budgets are increasing in size, it’s nowhere near enough to account for the increase in the amount and complexity of procurement work itself. 

A recent report by the Hackett Group found that “the procurement workload is predicted to increase by 10.6%.” This figure reflects the broadening of priorities with only a little increase in headcount and operating budget. As a result, McKinsey analysts expect the industry to suffer from a productivity gap of 7.4% and an efficiency gap of 7.8%.  

Some argue that CPOs could face the issue by working smarter not harder, leveraging artificial intelligence (AI) to power new technology applications like predictive procurement orchestration in an effort to increase efficiency and circumvent risk before it appears. The Hackett Group’s report argues that procurement is likely to “rely on technology and digital transformation to close the gaps” and “do more with less through better intelligence and increased speed, customer-centricity, and competitive advantage.” 

What is predictive procurement orchestration? 

Using AI and machine learning, predictive procurement orchestration analyses large amounts of data to identify the most successful purchases in an organisation’s history from the companies with the highest quality products and services. 

A predictive procurement orchestration system then uses that historical data to optimise an organisation’s procurement strategy, described by software vendor Arkestro as “a combination of behavioural science, game theory, and machine learning that helps procurement teams predict and win faster value across every category of addressable spend.” 

In short, AI and machine learning combine to predict which outcomes will be better for the business. The technology then uses human behaviour and game theory to create competition among suppliers. The process then encourages these suppliers to engage more closely with the company by means of dynamic feedback. Lastly, an embedded intelligent platform can make resources go farther without increasing the number of employees needed by the business. 

In field trials of its own predictive procurement orchestration system, Arkestro reportedly achieved over $8 million in savings for one company, while another achieved 88% savings on individual purchases.

From simple prompt engineering to autonomous sourcing bots, here are three ways generative AI can be deployed to support procurement.

If 2023 was the year of Generative AI hype, 2024 (and probably 2025, 2026 and maybe 2027, if we’re being honest) will be the year(s) where we have to figure out if this shiny, incredibly expensive (and morally dubious) new technology actually has real world applications that are worth the price of admission. 

Where procurement is concerned, given the mixture of factors creating new and interesting pain points for the sector, the benefits of generative AI can’t arrive soon enough. These factors range from the skills shortage to an overall strategic shift in the nature of sourcing and ongoing political (and economic) tensions, all of which have the potential to create profound pain points for industry leaders.

The risks of generative AI investment are not to be taken lightly, despite the allure of greater efficiency and lower costs. Specifically, risks range from AI “hallucinations” and unreliable unreliable outputs, to issues of IP ownership, inherent bias, and cybersecurity threats. However, the benefits are, some would argue, well worth the risk. This is especially true if the nature of generative AI deployment is well suited to the task at hand. 

Here are three levels to which Generative AI can be used throughout the procurement process: 

 1. Shallow deployment 

This is probably the least intrusive and easiest to execute in terms of Generative AI deployments. A shallow deployment might simply provide a superficial gateway to ChatGPT or other external GenAI tools. 

Results mirror those obtained by directly interfacing with ChatGPT outside of the procurement application. Solutions could be used for rephrasing communications, generating early-phase ideas, and other simple, language-related tasks. 

2. Contextualised and optimised deployment

The next level optimises the large language model underpinning a generative AI deployment. It does this by training it using specific data relevant to the procurement function or company as a whole. 

Essentially, a contextualised Generative AI deployment involves furnishing the GenAI model with information derived from data within the solution. This can include sources of information like raw sales data and compliance documents. The solution employs prompt engineering to enhance output quality. User prompts undergo repackaging or reformatting before being forwarded to ChatGPT or another external GenAI tool. A single user request may trigger multiple GenAI prompts managed concurrently. 

3. Tailored deployments

Lastly, a much more in depth deployment involves a solution that utilises its own LLM (a pre-trained language model that has been further refined) to enhance outputs and dramatically reduce the risk of hallucinations. Using AI in this way can also allow for a hybrid approach, in which the solution employs either the internal LLM or an external one depending on the specific use case. 

Overall, tailored generative AI solutions offer a range of benefits, including improved performance, reduced risks, increased efficiency, enhanced contextual understanding, and greater flexibility, making them valuable tools.

Procurement teams are increasingly selling to a new class of customer: machines with the authority to buy and sell products autonomously.

The procurement landscape is undergoing a period of radical change. Pressure is growing for procurement teams to operate more efficiently and strategically. However, this trend is also growing in tandem with the complexity of procurement teams’ workloads. At the same time, the severity and variety of pain points faced by procurement functions have never been more disruptive. 

At the heart of this sector-wide transformation is technology. This trend is reflected in a recent report by Deloitte. Researchers note that the rapid advancement of technologies like automation, AI, and machine learning is remaking business supply chains. Their implementation is “poised to transform how the procurement function delivers value.” For many organisations, “the application of these disruptive technologies to procurement is already fundamentally altering the impact of this function.” 

One pivotal way that procurement is being altered by the changing technology landscape relates to the emergence of “machine customers.” 

What are machine customers? 

The concept of machine customers has been around for several years. Now, however, the technology is hitting an inflection point where its impact on the procurement sector has become undeniable. 

Machine customers are nonhuman economic actors capable of selling or purchasing goods or services autonomously. Examples of machine customers are varied. They can include IoT devices capable of placing independent orders, intelligent replenishment algorithms maintaining product availability, and automated assistants suggesting new deals to consumers. 

Machines can conduct procurement functions from both sides of the table, and the increasingly capable automation of sourcing and procurement could have a dramatic impact on the procurement sector. 

Some industry experts argue that machine customers could account for trillions of dollars in revenue by 2030. Automating the process of buying and selling could completely change the nature of the procurement process. CEOs believe that by the end of the decade machine customers will account for 20% of their companies’ revenues. 

The risks and rewards of machine customers 

The study projects that, by 2026, more than 15 billion connected products will have the potential to behave as customers. These machine customers will be able to buy and sell goods and services autonomously.

These machine customers would, theoretically, have significant advantages over a human. Machine customers are unaffected by the cultural, emotional and sensory triggers that are used to manipulate humans into buying one product over another. Of course, cyber attacks that could influence the behavioural parameters of a machine customer could result in far greater misappropriation of spend. 

Machine customers are also supposedly more efficient and methodical, with the ability to weigh up much larger sets of data to make more informed decisions in real time. The obvious criticism of this is that decision-making AI is limited by the scope of its programming and directives. The ethical concerns that could arise over the procurement practices taken by an AI told to prioritise low costs without sufficient guardrails are obvious. Machine customers will need to be increasingly regulated the more autonomy and agency they are given.

In short, machine customers are undeniably on track to have a meaningful impact on the procurement process. However, while automating sourcing in this way carries obvious advantages, widespread implementation of machine customers also creates new threats to the integrity of the supply chain.

Artificial intelligence could deliver “best-of-the-best” analyses in seconds to automate and enhance the generation of RFPs.

Generative artificial intelligence (AI) is being explored for its potential applications throughout the sourcing and procurement sector. Potential uses for the technology range from improved compliance to threat modelling and supplier relationship management. 

However, the most impactful application of generative AI—not to mention the one with a good deal of potential to be applied now, not in some indeterminate amount of time when the technology matures—could be to the request for proposal (RFP) process. 

What is an RFP? 

An RFP is a formal document than procurement teams issue to potential vendors. The issuer details the product or service they are looking to acquire and vendors place bids in order to secure a contract. 

An RFP takes the form of a questionnaire-style form requiring potential vendors to enter data about the product or service they can provide. This allows procurement teams to more effectively gather and analyse data from multiple potential vendors in order to make an informed decision. 

RFP pain points 

In both the public and private procurement sector, RFPs are a central element of the procurement process. As such, the manual RFP creation process consumes significant time and resources for procurement departments. 

Delays can derail sourcing cycles and disrupt supply chains. As with any repetitive manual process, RFP writing is also an error-prone process. The consequences can range from an improperly sourced service to a dangerous and expensive breach in compliance. 

Also, the quality of the RFP can affect the quality of vendors who respond to it. As a data gathering tool, a poorly constructed RFP will also produce poor quality data, which can lead to hiring a poor quality vendor. 

Generative AI and the RFP process

The ability for generative AI to rapidly analyse and synthesise information could not only automate and standardise the RFP creation process, but qualitatively improve the design of the RFPs themselves. 

According to McKinsey, generative AI can serve as an invaluable tool when prioritising categories and suppliers based on market development, spend analysis, and supplier leverage. “This analysis prioritises spending with the highest potential to drive value for the organisation, while deprioritizing categories or suppliers where value will be more challenging to obtain,” their analysts note

The client team behind the report developed this generative AI powered “RFP engine” to use anonymised and sanitised RFP templates and cost drivers from “more than 10,000 RFPs and their responses” in order to identify and replicate the “best of best” analyses in a fraction of the time. “It also learned what drove winning bids and redesigned future RFPs for optimal bid structure and cost granularity. Finally, it predicted, and prevented, omissions and mistakes in the bids,” note Aasheesh Mittal and Jennifer Spaulding Schmidt, McKinsey analysts.

By intaking vast amounts of data in the form of successful and unsuccessful RFPs, generative AI could potentially allow procurement teams to both automate and enrich their RFP generation processes.  

A new report suggests procurement leaders are a driving force of sustainable practice and digital transformation within their organisations.

Chief Procurement Officers (CPOs) and other procurement leaders may be the new drivers of not only sustainable but technological reform within their organisations, says a new report conducted by Icertis

The report surveyed supply chain, procurement, and risk management leaders from companies across the U.S. and Canada. Respondents came from sectors spanning manufacturing, pharmaceutical, aerospace, automotive, and more. The report “uncovers the transformation of Chief Procurement Officers (CPOs) into key influencers shaping company strategies and the role of AI in navigating challenges and opportunities related to procurement processes, technology implementations, and sustainability initiatives.”

The report’s findings included the fact that procurement teams are increasingly a significant driver of strategic value within businesses. A marked 46% more CPOs were found to be wielding influence in high-level decision-making compared to two years ago. 

CPOs in the driver’s seat

This finding goes hand in hand with the revelation that CPOs are becoming technology adoption leaders within their organisations. The report found this was particularly true in relation to artificial intelligence (AI). Reportedly, 44% of CPOs have been responsible for leading AI adoption efforts in their organisation over the past year. Whether leading AI adoption or not, CPOs widely recognise the importance of AI as a supporter of procurement transformation. 

Another area where CPOs are driving adoption is in the are of sustainability initiatives. Icertis’ report found that 86% of CPOs play “a moderate to large role” in driving sustainability in their organisation. Additionally, 46% of procurement leaders confirmed that they would be prioritising ESG and sustainability goals in 2024. However, accurately assessing and extracting ESG data from the supply chain is an ongoing, thorny, process for supply chain and procurement leaders. Just under half (43%) of CPOs surveyed confirmed that they would be enhancing capabilities to extract and interpret ESG metrics from data going forward. 

“Especially in times of volatility and change, the organisational significance of the procurement department continues to grow, spanning contract creation and approvals to surfacing untapped savings, avoiding missed obligations, and ensuring ongoing compliance throughout supplier relationships,” said Bernadette Bulacan, Chief Evangelist, Icertis. “As the global regulatory landscape undergoes dynamic changes and businesses grapple with challenges like supply chain disruptions, inflation, ESG audits, and market volatility, the expectations of CPOs have never been higher.” She adds that 2024 represents a pivtal moment for the sector. She adds that CPOs will need to “assert their influence,” in order to steer their organiations. Those who succeed will have a defining role in “shaping business-critical initiatives with AI technology, particularly in contract management.”

New AI tools could empower the next leap forward in low-carbon procurement by improving the the accuracy and time to delivery of critical data.

Across the manufacturing, retail, FMCG, and agricultural sectors, the push towards Net Zero is starting to gather momentum. Driven by both stricter regulations and consumer demand, the trend promises to drive sweeping change throughout the procurement process. However, there are benefits to a more sustainable procurement process beyond remaining compliant. A recent Amazon Business report noted that “more sustainable supply chains and inclusive vendor ecosystems … support compliance with these guidelines and also grant businesses a competitive advantage—helping them form deeper, value-based relationships with customers and employees.” 

Despite the appeal of a more sustainable procurement process, many procurement leaders are struggling to clean up their value chains. Amazon’s report found that 85% of procurement leaders say the difficulty of sourcing suppliers that follow sustainable practices prevents their company from setting or achieving strategic sustainability goals for procurement. This frequent lack of actionable data is a major contributor to the lack of sustainable options within the supply chain. Without good data, distinguishing an ethical, sustainability focused supplier from an organisation that is merely paying lip service to the concept, and greenwashing their numbers, is next to impossible. 

Aster Angagaw, a VP at Amazon Business, argues that “buyers need enhanced visibility into purchasing data and supplier information to cultivate the ability to make swift and assured decisions.” Accurately collecting and assessing supplier data from a long, historically opaque value chain presents some meaningful complexities for procurement teams. 

AI: A Magnifying Glass For The Procurement Process 

In cutting through the murky modern supply chain, artificial intelligence (AI) may have a role to play. In January 2024, manufacturing services company thyssenkrupp and CarbonChain partnered to release a carbon traceability and intensity tool. The software, powered by AI, uses asset-specific emissions factors and activity-based methods, instead of relying on global averages. The result is a product that allows organisations seeking lower-carbon materials to easily identify, compare and select them. At the same time, users can leverage this data to build sustainable procurement strategies to achieve their net-zero goals.

“Procurers can’t meet their net-zero targets without knowing the carbon footprint of the goods they buy. Meanwhile, metals producers who are decarbonising their industrial processes are facing barriers to quantifying and reporting their emissions reductions,” said Adam Hearne, founder and CEO of CarbonChain. 

Cutting through the “jungle of data”

AI has the ability to sort through what Amazon Business’ Rajiv Bhatnagar, calls the “jungle of data”. This “jungle,” created by the modern, digitalised supply chain, is a huge barrier to accurately calculating emissions. A tool that can accurately pars and create insights from such a complex environment is of immense value to CPOs.

Similarly, in November of 2023, supply chain SaaS company Exiger partnered with Muir AI, merging their databases. The resulting tool allegedly allows companies to more accurately reduce their emissions. 

“With over 80% of carbon emissions coming from the value chains organisations are connected to – rather than the organisations themselves — a company’s ability to reduce carbon emissions is entirely dependent on their ability to gain transparency into multi-tier supply chains,” said Erika Peters, Exiger’s ESG lead and SVP, Head of Innovation and Operations. “This partnership further expands our environmental risk scoring and Scope 3 capabilities ahead of the 2027 deadline, not only providing granular carbon emissions data across products, suppliers and geographies, but also streamlining the data collection process, automating and documenting how emissions are calculated, and surfacing real-time insights into the strategies that will drive the greatest impact.”

The fast-moving-consumer-goods market is turning to AI to procure produce when it’s at its cheapest and freshest

Artificial intelligence (AI) could have an increasingly vital role in produce procurement.

Few markets move faster than produce. What is a delicious, enticing and, above all, valuable piece of tropical fruit one morning could, by the next, be quite literally a pile of rotten garbage. 

A lot has been done throughout the agricultural sciences over the centuries to lengthen the amount of time fruit varietals stay edible.

This is also true in the logistics sector. Thanks to modern techniques, cold chains and complex shipping networks can get a fresh picked tomato from the south of Spain to the north of Sweden before its leaves start to wilt. However, procurement—especially when it comes to produce—is fundamentally about balancing the cost of a product with the quality that can be attained within the regulatory, environmental, and physical contextual constraints of the market. 

Produce is fast moving and complex. Increasingly, the sector also faces criticism for its environmental impact and record of abysmal human working conditions. For large scale retailers with national, or even international, footprints, produce procurement is a challenging prospect. Some CPOs believe the process is better left to the machines. 

Dollar General taps AI for produce procurement

In January, US discount retailer Dollar General rolled out a new program in about 3,000 of its US stores—a pilot which would use AI to fully automate the procurement of produce.

The AI ordering system aims to “optimise in-stock levels” and replenish shelves to “fight food insecurity”. It could also save Dollar General a lot of money in unsold stock. Dollar General, which is currently being sued over allegations that it has been routinely scamming tens of thousands of customers by charging more money for items than their listed prices, made $11.9 billion in profit last year.

In Rhode Island, United Natural Foods also implemented AI as a way of automating elements of its distribution process this January. In November of 2023, grocery retailer Albertsons also announced the introduction of AI solutionss. The retail giant is using AI to automate store ordering and inventory management across its meat and seafood operations—another area with narrow margins for error with regard to the delicate balance between demand and supply. 

The platform adopted by Albertsons aims to help meat and seafood teams “keep coolers and freezers light while boosting in-stock rates” using AI-powered recommendations for high-value, hyper-perishable items like fresh poultry and prefilled order quantities for slower-moving, prepackaged items such as bacon. Susan Morris, EVP and Chief Operations Officer for Albertsons also added that the platform would help “significantly reduce food waste as Albertsons continues to make progress toward our goal to have zero waste going to landfill by 2030.”

Generative AI has the potential to improve efficiency in an understaffed public sector

Last year was undeniably the year of Generative AI (hype). According to Muhammad Alam, President and Chief Product Officer of SAP’s Intelligent Spend and Business Network, “generative AI was like a bolt of lightning that compelled every business and technology leader to sit up and take notice.” 

Now the first flurry of investment and breathless hype seems to be settling down. This leaves organisations interested in the potential applications of generative AI to try and figure out what that might actually look like.

AI is only as good as its data

Alam notes that those looking to adopt will “see firsthand that AI is only as effective as the quality and availability of data.” 

One class of organisation with access to vast amounts of data is government and other public sector entities. This class of organisation also cursed with a host of problems ranging from inefficient organisation to compliance and shrinking budgets.

As researchers at Deloitte noted in a recent report, “Government procurement professionals need help.” According to experts, generative AI could hold the solution to these problems.

“If government is to achieve the ambitious aims that the public expects, procurement professionals need tools to process large volumes of data with precision and with attention to the unique circumstances of every contracting action,” the report adds. 

Public procurement under strain

Procurement is currenting caught in a rising tide of complexity. Over the past 10 years, government spending has grown around 4.5% each year in the US. Over the same period, the total number of contracting actions has increased by more than 22% each year.

Public procurement is drowning under layers of complexity which are growing faster than the public sector procurement workforce.

At the same time, workforce headcounts are being stymied by budgetary concerns and an industry wide talent shortage. This is being exacerbated by the fact the private sector has and always will pay better. Therefore, the amount of work being done by individual public sector procurement staff is rising.  

In 2022, for every Federal contracting officer, an average of 2,000 contracting actions had to be executed per year. Comparing that number to the 300 actions per year in 2013 reveals the scope of the problem. If government procurement departments are going to avoid buckling under this growing strain, technology in the form of automation, advanced analytics, and other potential generative AI applications could have a role to play. 

Generative AI still has optical (and ethical) problems

Generative AI is a somewhat nebulous umbrella term. It is often conflated with its most public-facing examples: Chat-GPT and image generators like Midjourney. This is why there appears to be a disonnect between what generative AI promises and what it delivers.

These models are less effective than humans at doing a lot of things like making art, generating movie scripts, and accurately retrieving or summarising information from the internet, etc. In addition to untrustworthy results and “hallucinations”, large language model AIs and imager generators also have significant ethical issues baked in. These stem from the uncredited work by writers and artists used to train these models.  

Applications for a generative Ai layer in public procurement

However, this doesn’t mean that generative AI is a useless or irredeemably immoral technology. Under the right regulatory constraints and in the correct context, Generative AI can create a vital unifying layer between several other pieces of technology. (Obviously more AI regulation is something to which tech industry people seem more reflexively averse than ipecac).

However, generative AI shows promise as an intermediary layers between automation tools, big data analytics, and e-procurement platforms. Deployed correctly, it could alleviate the growing complexity that plagues public sector procurement. 

Deloitte’s researchers note, similarly, that “the emergence of gen AI has put a missing puzzle piece on the table that can allow several different types of tools to fall into place. Because gen AI works differently than previous generations of AI, it has different strengths and weaknesses. While gen AI can do things that traditional machine learning (ML) cannot, such as creating new text or images, it can occasionally struggle with accuracy in ways that traditional ML does not. Similarly, all forms of AI can exceed a human’s ability to handle large volumes of data, but humans naturally excel at tasks that strain AI, such as highly variable or social tasks.” 

By contrast, tasks like documenting and reporting are hugely time consuming.

“From using gen AI to generate documents and reports to having ML produce demand forecasts, AI can help reduce the time needed to create and process procurement request documents such as market research reports, statements of work, and purchase requests,” notes the report. 

Could generative AI be the answer to procurement’s problems: fewer workers, more work, and a rising bar for digital literacy.

It’s news to no one that the nature of the procurement industry has changed.

Spurred by the COVID-19 pandemic, an industry-wide surge in digital transformation, and the rising immediacy of the climate crisis, procurement has never been more important, or more complicated. However, as the industry’s demands grow and evolve, many procurement teams find themselves in need of skilled individuals that simply aren’t there.

A recent study conducted by Gartner found that just one in six procurement teams believe they have “adequate talent” to meet their future needs. That means just 15% of CPOs were confident in their future talent pools and ability to recruit skilled individuals, even if they believed their current staffing was sufficient to meet demand today.

Concerns over “having sufficient talent to meet transformative goals based around technology, as well as the ability to serve as a strategic advisor to the business,” were the primary cause of skill shortage stress, according to Fareen Mehrzai, a Senior Director Analyst in Gartner’s Supply Chain Practice. Essentially, the changing nature of procurement means not only that today’s procurement teams are unprepared for the discipline’s continued transformation from back office buyer to “orchestrators of value” in the executive team, but face an increasingly sparse hiring market as the requirements for a new procurement recruit become increasingly complex to satisfy.

Generative AI: Making digital accessible

Generative AI exploded into the public consciousness in 2023 with the launch of image generation tools like Midjourney and DALL.E, as well as chat-bots like Chat-GPT, powered by large language models. Investment has been immediate and almost unthinkably massive. In late 2023, it was estimated that generative AI startups were attracting 40% of all new investment in SIlicon Valley, and Bloomberg Intelligence estimates that the market for generative AI, valued at $40 billion in 2022, will be worth as much as $1.3 trillion in the next decade.

In the procurement and supply chain sectors, specifically, CPOs are reportedly dedicating 5.8% of their function’s budget, on average, to generative AI, according to a Gartner report from January.

Now, whether or not generative AI has the society-spanning, epoch-disrupting economic and social impact people are predicting (personally, I remain unconvinced, and anyone who disagrees can either fight me in the metaverse or try to run me over with a self-driving car) actually manifests, there’s no denying generative AI’s potential as a useful tool if adopted correctly.

Especially in an underskilled, rapidly digitalising procurement sector.

How can generative AI help procurement?

While Generative AI will never write a (good) movie script or create a piece of art that anyone with any taste would find genuinely moving, there are some things it does very well. Namely, it is very good at not only taking in and processing huge (and I mean huuuuge) amounts of chaotic, poorly structured information and answering questions about it, but most importantly, it can understand prompts and give results in simple, conversational language. There are still limitations and kinks to work out, however.

Generative AI still deals with hallucinations. However, the ability to input huge amounts of data and analyse that data in a conversational format could alleviate a lot of the technological literacy related teething problems that appear to be at the heart of the procurement skills shortage.

An EY report notes that, in the Supply Chain and Procurement space, generative AI has massive potential to: “Classify and categorise information based on visual, numerical or textual data; quickly analyse and modify strategies, plans and resource allocations based on real-time data; automatically generate content in various forms that enables faster response times; summarise large volumes of data, extracting key insights and trends; and assist in retrieving relevant information quickly and providing instant responses by voice or text.”

The future of Gen AI

Generative AI can be a source of simplicity for procurement teams at a time when new technologies often add complexity and necessitate upskilling or new hires. EY notes that a biotech company using a generative AI’s chat function has had positive results when using it as a way to inform its demand forecasting. “For example, the company can run what-if scenarios on getting specific chemicals for its products and what might happen if certain global shocks occur that disrupt daily operations. Today’s GenAI tools can even suggest several courses of action if things go awry,” write authors Glenn Steinberg and Matthew Burton.

Adopted correctly, generative AI could not only empower procurement teams to handle the pain points of today, but also tackling the looming threat of the skills shortage in an industry facing a relentless demand for skills that may not be in adequate supply for years to come.

By Harry Menear

Interest and investment in generative AI has been massive, but does the technology actually have the capacity to meaningfully change the procurement industry?

Since the arrival of large language model-powered chatbots, like OpenAI’s ChatGPT, the corporate landscape has been frantically striving to invest in and adopt generative AI.

Executives floated (I mean salivated over) the possibility that generative AI could replace a staggering number of roles throughout virtually every sector from law to content creation and entertainment. Well, just look how well that turned out. The legal backlash has, in many cases, been severe and, just over six months into the generative AI hype cycle, cracks are beginning to show.

Whether we’re talking about the ethical issues of training LLMs and image generators on the work of artists and writers without their knowledge or consent, the fact generative AI will just make stuff up sometimes, or the revelation that running something like ChatGPT consumes the energy equivalent of 33,000 US households per day, the issues with generative AI just keep mounting. Despite these issues, generative AI is monopolising the tech investment landscape, with 40% of all Silicon Valley investment in the first half of 2023 being poured into GenAI startups.

But what about the applications? Surely all these issues and all this money is going into generative AI technology for a reason, right? Surely we all learned our lesson from the Metaverse, the crypto bubble, NFTs, and streaming and… I guess we didn’t, did we?

Well, actually, there are a few, but they won’t look like the Wild West of content generation we’ve seen so far.

In the retail sector, for example, 98% of companies plan on investing in generative AI in the next 18 months, according to a new survey conducted by NVIDIA (a company with an admittedly vested interest in selling shiny new GPUs). Early examples of adoption in the sector have included personalised shopping advisors and adaptive advertising, with retailers initially testing off-the-shelf models like GPT-4 from OpenAI.

However, many retailers are recognising that the strength (and weakness) of generative AI is that you only get out what you put in. That’s why the technology is, ultimately, useless as a way to replace creative roles like writers and artists. However, as a brand communicator meticulously trained on a specific set of data with carefully updated parameters, it could be invaluable. NVIDIA’s report notes that “many are now realising the value in developing custom models trained on their proprietary data to achieve brand-appropriate tone and personalised results in a scalable, cost-effective way.”

Generative AI trained on a company’s internal and customer-facing databases, web presence, and curated information resources could conversationally recommend, educate, and explain critical information to employees, customers, and business partners effectively and consistently. In an industry where communication relies on clarity and an understanding of large quantities of information, like procurement, the applications suddenly start to look a lot more appealing.

Chatbots and negotiation bots trained to converse with suppliers, programmed with company approved negotiation tactics and the latest pricing information, could automate a great deal of complexity out of the Source to Pay process.

I think the looming issue is the impact of generative AI adoption on a company’s Scope 3 emissions, as 2024 will unquestionably be defined by greater scrutiny on these sources of pollution. However, it seems that however many issues the more widely known aspects of generative AI have, the technology itself could still have a role within the procurement function of the near future.

Does it justify all the investment, hype, and endless industry media thinkpieces? I guess only time will tell. 

By Harry Menear

The assistant will use natural language processes and AI to perform “thousands of procurement tasks”.

The latest in a small flurry of generative AI-powered virtual procurement assistants is hitting the market. Earlier this month, Relish, a B2B app developer based in Ohio, announced the release of its new procurement assistant—a virtual assistant product powered by generative artificial intelligence and designed to intuitively interact with users while performing “thousands of procurement tasks”.

“What we’re offering is a solution that truly frees users from the menial to engage in the meaningful,” said Ryan Walicki, Relish CEO, in a statement to the press. He added that the Relish Procurement Assistant would revolutionise the way businesses handle their procurement systems and processes, claiming: “By leveraging large language models, this single interface spans all procurement systems and platforms and can be custom fit to any enterprise solution ensuring workflows are never interrupted.”

The rise of generative AI

Relish isn’t the first company to utilise a combination of generative AI and large language models, like ChatGPT, to create a more naturalistic interface between users and complex systems for managing data. In November, Californian tech firm Ivalua released an Intelligent Virtual Assistant powered by generative AI as part of its platform, making similar claims that the technology would eliminate busy work, freeing up employees for more strategic activities.

Relish works in a similar way, plugging into an existing procurement management platform, and using artificial intelligence and natural language processing to “intuitively interact” with users in a conversational way, giving them detailed insight into their workflows.

According to Relish, the technology can perform numerous tasks, including supplier management, sourcing, contract management, supply chain, and purchasing.

Where Relish differs from other offerings on the market is in its alleged ability to “[adapt] to any platform and workflow preference.”

According to Jeremy Reeves, Relish Senior Vice President of Product: “The adaptability helps users get the most out of their procurement enterprise software, maximising their return on the investment… It brings a new dimension to how users will go from being taskmasters to being conductors of their enterprise systems.”

By Harry Menear

Procurement teams are under mounting pressure to minimise disruption and contribute value to the business. Here’s how Generative AI could help.

Across all industries, the unprecedented disruption caused by the COVID-19 pandemic, along with the “growing need for procurement to enable growth, mitigate inflation/risk, and drive significant levels of value” has, according to Deloitte’s 2023 Global CPO Survey, afforded businesses’ procurement function “a seat at the table.” However, with the recognition of procurement’s importance comes responsibility and, increasingly, pressure.

The procurement function of a modern enterprise is one of the final remaining frontiers where truly value additive transformations can occur. Cutting costs, identifying new efficiencies, and pursuing more sustainable practice throughout the supply chain are non-negotiable KPIs for all procurement teams.

Artificial intelligence (AI) and machine learning (ML) have long been a part of successful procurement and logistics strategies—automating manual and menial tasks, freeing up professionals to focus on more strategic objectives. The recent advent of generative AI, underpinned by natural language processing (NLP), pattern recognition, cognitive analytics, and large language models (LLMs), however, has the potential to support procurement professionals in new, more impactful ways than ever.

Here are our top X ways that generative AI can help procurement professionals deliver on the demand for smarter buying, more ethical sourcing, and the holy grail of an unshakably resilient supply chain.

1. Predicting Disruption

If the last three years have taught us anything, it’s that the supply chain is a fragile thing. Organisations struck by the pandemic that failed to adapt and recover as fast as their competitors are, at the very least, facing a harsher world today than they were in 2019, with many having been absorbed by more resilient, faster-moving competitors. Even with the pandemic behind us, its effects are still being felt, and disruptions are a fact of life.

In case of a disruption, procurement teams need to be able to identify and respond quickly—something only 25% of firms are able to do, according to Deloittle’s 2023 procurement industry survey.

AI tools bring a heightened ability to identify patterns and analyse large data sets to the procurement department, dramatically increasing procurement professionals’ ability to identify disruptions (both within the organisation and in the market as a whole) before they happen and adapt accordingly.

2. Textual Data Analysis

Artificial intelligence has been used to sift through large data sets for years, but Generative AI may allow the scope of those data sets to expand by orders of magnitude. The ability for ML-powered LLMs to analyse large amounts of unstructured textual data, such as news articles, social media posts, contracts, and customer feedback could create a wealth of new insight and recommendation generation opportunities to benefit businesses’ procurement functions.

Procurement professionals will have an additional angle from which to evaluate vendors, examine their compliance status, gather market intelligence, and assess risk. Unstructured text remains one of the great untapped data resources, and LLMs have the ability to convert that raw data into actionable insights for the procurement function. 

3. Intelligent Recommendations

In addition to internal purchasing recommendations based on compliance, generative AI could also be used to create highly personalised, granular criteria for business buyers. An AI-powered buying tool could, for example, scrape hundreds of thousands of item listings, eliminating results based on millions of data points, to create proposed shopping carts for particular applications weighted by any number of criteria determined both by company policy and the buyer’s own preferences.

4. Automated Compliance

Generative AI’s ability to analyse large, unstructured data sets and draw complex, human-like conclusions from them that are then translated into insights and decision recommendations could be transformative for handling compliance in procurement.

A generative AI model could be used to monitor company-wide activity for anomalous or non-compliant purchasing behaviour—alerting the procurement department if an issue arises. In addition to creating more freedom for buyers outside the procurement function, and freeing up time within procurement that would otherwise be spent reviewing company spend for compliance, a Generative AI could be used to make intelligent spending recommendations in order to increase compliance with minimum spend contracts, for example. 

By Harry Menear

CPOstrategy explores this issue’s big question and uncovers what the impact of gen AI is in procurement.

The true possibilities of what can be achieved via AI is still being unearthed.

Indeed, the influence of new technology will only grow from here and new digital tools are being introduced all the time.

When it comes to generative AI, there is perhaps a misunderstanding that it is a new innovation. But the history of gen AI actually dates back to the 1960s. Among the first functioning examples was the ELIZA chatbot which was created in 1961 by British scientist Joseph Weizenbaum. It was the first talking computer program that could communicate with a human through natural language. It worked by recognising keywords in a user’s statement and then answering back through simple phrases or questions, in likeness to a conversation a human would have with a therapist. While ELIZA was seen as a parody and largely non-intelligent, its introduction has paved the way for later advancements in Natural Language Processing (NLP) and the future of generative AI.

Fast forward to today and the gen AI conversation and wider tech landscape looks very different. In late 2022, OpenAI launched ChatGPT – technology which has shaken the procurement function and beyond. ChatGPT interacts in a conversational way with its dialogue format making it possible for users to answer follow-up questions, admit mistakes, challenge incorrect answers and reject unsuitable requests. As such, the chatbot has created quite a buzz which has been felt across the globe.

Generative AI’s misconception

Speaking to us exclusively at DPW Amsterdam, Gregor Stühler, CEO at Scoutbee, believes there are some misconceptions around ChatGPT and the nature of how accurate the data it provides actually is. As is the case with any new technology, these things take time. “It’s always the same. It happened with electric cars, nobody thought that would solve the battery issue,” he discusses. “I think we are right at the peak of the hype cycle when it comes to those things and people have figured out what they can use it for. With wave one of gen AI, it is fine to have hallucinations of the model and if something is spat out that is not supported by the input. 

Gregor Stühler, CEO at Scoutbee

“But by the second use case, hallucinations are not okay anymore because it’s working with accurate data and should not come up with some imaginary creative answers. It should be always supported by the data that is put in. This is very important that people understand that if you train the model and if you have the right setting, those hallucinations will go away and you can actually have a setting where the output of the model is 100% accurate.”

Data security

Michael van Keulen, Chief Procurement Officer at Coupa, agrees with Stühler and despite obvious benefits such as time and cost, he stresses caution should be used particularly when it comes to valuable tasks. “If you look at ChatGPT, it’s fine if you’re looking for recommendations for something low-risk. I need something for my wife’s birthday next week, you input three things that she loves and ask it to help. It’s great,” he tells us. “But it comes from data sources on the web that aren’t always governed, controlled or trustworthy. It’s whatever is out there. What about the algorithms that come with ChatGPT? I don’t know what’s influencing the search criteria. On Google, if you pay you are at the top of the search bar. But I don’t know what ChatGPT is governed by.”

Michael van Keulen, Chief Procurement Officer at Coupa

Managing data leakage

Danny Thompson, Chief Product Officer at apexanalytix, explains that one of the biggest challenges with generative AI is being aware of a leakage of sensitive information combined with a contamination of important data. “We have a database of golden records for 90 million suppliers who are doing business with Fortune 500 companies and that is the best information we’ve been able to accumulate about the suppliers and their relationships as a supplier to large companies,” he tells us.

Danny Thompson, Chief Product Officer at apexanalytix

“We want to make sure we’re not loading sensitive information into a generative AI function that might allow just random people to access that data. Ultimately the customers in the space that we’re operating in are serious companies moving around large amounts of money and facing real risks that they have to manage. It’s really important that the data that they have is either highly accurate or at least they understand the degree to which it’s accurate. This means if you’re using the solution that you don’t understand the level of trust you can have in it, then you shouldn’t be using it yet.”

Can generative AI bridge the talent shortage?

Amid talent shortages in procurement, there are some sections of the procurement space questioning to whether AI and machine learning can plug the gap and reduce the necessity of recruitment. Naturally, this raises the debate of whether robots will replace humans. Stefan Dent, Co-Founder and Chief Strategy Officer at Simfoni, adds that while AI and machines won’t replace humans, it will mean people will need to find new forms of work and take on higher-value roles.

Stefan Dent, Co-Founder and Chief Strategy Officer at Simfoni

“The shape and structure of the modern procurement function will change quite dramatically and people will need to upskill,” he discusses. “A lot of the work will be taken over by the machine eventually either 20%, 50%, and then a hundred percent. But the human needs to have that in mind and then plan for that next three to five years. The procurement function of the future will be smaller, and they should purposely be doing that, to then look at solutions to find a way to enable it to happen naturally.

Future proof procurement

“For someone who’s joining procurement now, you’ve got this great opportunity to embrace digital. Young people can question ‘Well, why can’t it be done by a machine?’ They’re coming in with that mindset as opposed to fighting being replaced by a machine. I think for graduates coming into procurement, they’ve got the opportunity to play with digital and actually change the status quo.”

As we look to the future, gen AI and new forms of technology will continue to change the world and the way we work. In the short term, work is expected to continue to upgrade the user experience and workflows through gen AI in order to build greater trust for the end user. As transformation continues to happen, businesses and wider society must embrace new types of AI to thrive and stay ahead of the latest trends. The potential that gen AI tools possess is expected transform the workplace of tomorrow while delivering value-add such as time and cost savings on a day-to-day basis.

Given the speed of evolution and development, it is yet unimaginable exactly what form the digital landscape will take in years to come. However, that horizon brings with it fresh opportunity and excitement revolving around a whole new world of technology at our fingertips. The future is digital.

As AI continues to emerge in a big way, Vicky Kavan, Vin Kumar and Nicolas Walden explores what the AI opportunity is in procurement?

Procurement is a hard function to impress. Other parts of the business can afford to get carried away now and then, but not procurement. Everything in procurement comes down to finding value and then making sure you don’t overpay for it.

Artificial intelligence (AI) might seem like just the kind of emerging new technology that procurement would shy away from. But, as many procurement leaders already understand, this would be a big mistake. In our work with the world’s largest companies, we see two kinds of major emerging AI opportunities you won’t want to miss. The first group – how we execute our procurement using, for example, new autonomous sourcing systems – can save millions today. While the second – the advent of AI-driven automation and enhancements across almost every industry and areas of spend – will help save you even more tomorrow.

Savings today

In terms of the impact of AI, procurement executives predict that supply market intelligence (50% of respondents), contract management (43%) and bid optimization (37%) will be some of the greatest opportunity areas for AI technology.

Despite this, and even as most AI and generative AI systems remain pilot projects, autonomous sourcing systems are already transforming how procurement functions operate at large multinationals. Many procurement executives have told us that they find these systems, which can automate execution in either tactical or strategic areas and provide enhanced decision support, extremely valuable:

  • Clients tell us these systems are helping them reduce cycle times dramatically – from months to weeks or weeks to days – and cut costs by 10% or more. Supplier discovery?  Shorter. E-sourcing? Shorter. Contract development? Shorter. While it is in the early days, time savings of 30% or more can be possible.
  • When MTN Group, an African multinational telecommunications giant, installed its Procurement Cockpit platform, the system paid for itself in four weeks because the AI-enabled software quickly identified new opportunities, consolidated pricing insights from around the sprawling corporation and accelerated negotiation preparation.
  • These systems are now making themselves useful across a range of sectors. Procurement executives at a major U.S. retailer, major European telecom and major European energy company all told us that these systems have saved time and money. Use cases include replacing the need to write detailed requirements, sourcing questions and even contracts through the use of modified templates through to tactical price negotiations.

Strategic drive

From strategy to insights, sourcing and negotiating ­– to contract drafting and supply risk management – AI-enhanced systems will make procurement faster and simpler. Although feature sets and value propositions vary from vendor to vendor, promising  autonomous sourcing systems fundamentally change how technology engages with stakeholders using chatbot-style interfaces to summarise requirements as an output of discussions; search and identify providers of products based on a variety of market, process and business considerations; prepare request for proposals and contracts; and maintain a higher degree of compliance with regulations. Some of these systems can even execute simple one-round negotiations. At the moment, Globality, Fairmarkit and Pactum (for negotiations) are three of the biggest names in this space.

Savings tomorrow

Eventually, we expect that AI-enhanced functionality is likely to yield major cost savings in almost every spend area, business function and industry sector.

Contact centres or marketing services, for example, could already send out automated posts and even voice responses that mimic the voice of your choice. A travel agency might be able to supplement human customer service with a robot concierge, making it possible to achieve a much greater level of service than ever before. Such changes won’t happen immediately – implementing them is not a quick win – but AI enhancements will be a huge source of value and service improvements down the line.

Category managers, be advised: the general consensus among purchasing executives we polled recently is that fleet, digital tech, advertising and general equipment are the categories that will benefit most from AI-enabled technology.

Of course, as with most powerful tools, AI-powered services also create new sets of potentially considerable risks. For example, you will need to make sure that your contracts are clear about what your vendor can do with your data – can it be aggregated in a large language training model? If that model leads the company to develop a more advanced service, do you want to be compensated for your contribution? Are you covered for potential liabilities if you transfer customer data to your AI vendor and your customer’s information is somehow revealed? If you work with an AI vendor and create intellectual property on its platform, who owns that new product? There are many new angles and issues that you will need to consider.

Looking ahead

Over the next five to 10 years, AI is likely to transform many aspects of business, including procurement. Based on The Hackett Group’s analysis of 44 Level 2 processes across the source-to-pay, end-to-end process – for a company performing at the median of our database – there is a potential to reduce staff by up to 46% over the next five to seven years.

Clients have told us they see digital technology (including AI) as the most transformative trend facing procurement in the next few years (71%) – more important than data (51%) or environmental, social and governance, and sustainability (47%). For procurement professionals, how the work is done and where they will find value are both likely to change dramatically. Given the speed with which we expect these opportunities and their attendant risks to develop, now is a good time to start thinking about the opportunities AI can create for your team.

By Vicky Kavan, Vin Kumar and Nicolas Walden

Just how much of the procurement process can be automated, and who does it help?

It’s hard to argue that 2023 will be remembered as the year that generative AI exploded into the public consciousness. Image and text generation in the form of ChatGPT and Midjourney ignited excitement, controversy, contempt, and a fervour to adopt in equal measure. The generative AI industry is predicted to be worth more than $660 billion per year by the end of the decade.

But while there’s no denying that generative AI will be a part of the economic landscape of 2024 and beyond, it’s not yet clear what that will look like. More importantly, it’s no guarantee that generative AI will, uh, generate any ways for the technology to make back the hundreds of billions already spent to develop it. 

It wouldn’t be the first major trend to be backed to the hilt by big tech firms, only to dissolve into nothingness like that racoon who drops his cotton candy in a puddle. In stark contrast to 2022, this year’s tech roundups and trend predictions have put a conspicuous lack of emphasis on the metaverse. Now, to be clear, the fact that Yahoo Finance calculated that “Mark Zuckerberg’s $46.5 billion loss on the metaverse is so huge it would be a Fortune 100 company” is great news for those of us who didn’t want to spend our thirties attending meetings in a glowing virtual mallscape surrounded by cutesy, animated versions of our bosses and coworkers. Huge relief. It’s also quite funny. More relevantly to the topic of generative AI is the cautionary tale that, unless big, expensive technological developments can be monetised, they will disappear.

So, how do we monetise generative AI?

How to make generative AI useful

Technology is most valuable when it solves problems, and saves time and money, or at least improves people’s quality of life—when there’s a measurable benefit of some kind, sometimes to humanity, and usually to shareholders. That’s the stuff that sticks around.

While its applications and capabilities—especially when it comes to creative tasks or just the ability to make something actually original—are limited, generative AI may actually be a good fit for the procurement sector, potentially solving a major issue the industry is currently experiencing.

Generative AI and the Procurement Skill Shortage

The procurement sector is short on talent—with five out of six procurement leaders claiming they will lack skills, staff, and other vital human resources in the near future. This is the case for several reasons, but primarily: an ageing workforce is starting to retire faster than new hires can skill up; also, the requirements of the job are becoming more technology centric as procurement digitally transforms, leaving departments underskilled even if they’re no understaffed; and lastly, the amount of work for procurement functions is increasing overall, as it becomes more of a driver of business efficiency and innovation.

If generative AI could be used to reduce procurement teams’ workload by automating certain aspects of the job, it could be a key piece of the puzzle when it comes to solving the skill shortage.

Retail giant Walmart has been successfully running pilot projects using its AI-powered Pactum solution to automate supplier negotiations. According to Deloitte, not only did Walmart find it “helpful for landing a good bargain, three out of four suppliers prefer negotiating with AI over a human. This strongly indicates that the ecosystem is ready to embrace this disruption.” While I’m not sure if this example is an endorsement of AI or an indictment of Walmart’s procurement team, the ability for generative AI to take over routine communication, negotiation, and other interactions in the source-to-pay process could free up huge amounts of time to focus on more strategic activities.

Gen AI’s future

It’s not hard to imagine that both buyers and suppliers could input their desired results and parameters into a generative AI negotiator and outsource the relationship management entirely. Out of curiosity, this morning I set up ChatGPT in two windows and had it conduct an RFP, tender negotiation, and sale agreement for the sale of an order of self-sealing stem bolts between O’Brien Enterprises and Quarks. It was a very civil, if slightly roundabout affair, and everyone seemed to come away happy—hacky business journalists especially.

Goofy demonstrations aside, there’s real potential for significant elements of routine communication and relationship management in the procurement process to be automated, or at least assisted by generative AI. If correctly combined with data analytics on contextual information ranging from weather patterns, commodities pricing, and supplier behavioural history, a generative AI could offer useful insights to procurement professionals while its generally low threshold for usability allows less tech-savvy procurement professionals to harness more powerful digital tools.

By Harry Menear

Ask Procurement—a generative AI procurement solution—is being developed for the market by IBM using Dun & Bradstreet’s “huge data cloud”.

In order to develop more effective and market ready digital solutions for supply chain and procurement professionals, IBM is partnering with Dun & Bradstreet, a data-dealer with access to vast quantities of raw information gathered from a wide variety of sources, as well as cutting edge analytical tools. Together, the companies will work on expanding the capabilities of IBM’s watsonx to expand their use of generative artificial intelligence (AI).

Through the collaboration IBM and Dun & Bradstreet intend to develop multiple offerings for clients to incorporate into their AI workflows, leveraging IBM’s AI and data platform, and fueled by Dun & Bradstreets’.

Ask Procurement

The leading solution in development, according to an IBM press release, is Ask Procurement, a generative AI-powered procurement solution that will “help empower procurement professionals to unlock new data and insights with a 360-degree view into all aspects of a company’s business relationships to help increase savings, reduce time, and mitigate the potential for risk.”

Ask Procurement is expected to use Dun & Bradstreet’s platform, but feature watsonx supported models and other generative AI capabilities “fueled by Dun & Bradstreet’s vast Data Cloud.” The solution is expected to be available to procurement teams in the second half of 2024, integrated with Dun & Bradstreet solutions or an enterprises’ existing ERP or procurement solution.

“At Dun & Bradstreet, being a trusted data partner and a responsible AI partner to organisations are synonymous,” said Ginny Gomez, President, North America, Dun & Bradstreet. “As two trusted brands that bring nearly 300 years of combined experience to the businesses we serve, Dun & Bradstreet and IBM are ideally suited to help companies responsibly navigate the rapidly evolving generative AI space because we know their business environments and processes well. And with hundreds of thousands of organisations globally relying on us every day, we believe there is no better company than Dun & Bradstreet to lead the industry and our clients into the future.”

By Harry Menear

At DPW Amsterdam, Kathryn Thompson and Fraser Woodhouse, Partner and Director at Deloitte, discuss the rise of generative AI and the impact on procurement.

Procurement is changing.

That’s something that isn’t lost on Kathryn Thompson, a Partner at Deloitte.

As part of her role, she leads the Sourcing and Procurement Market Offering within Deloitte’s Consulting division in Europe, Middle East and Africa. Originally from Australia, Thompson has worked in procurement since 1996 and has observed quite the evolution over the past two and a half decades.

Procurement’s transition

Over the years, procurement has shifted from a traditional back-office function to an entity operating at the fore of a company’s strategy. Having been involved in the industry for more than 25 years, Thompson has had a front-row seat to procurement’s digital transformation. While she affirms that AI has changed procurement, she isn’t convinced that generative AI is changing the space – yet.

Kathryn Thompson speaking at DPW Amsterdam 2023

“We see lots of AI tools pulling from different data sources to apply intelligence to different decisions,” she explains. “But the generative part, beyond contract summaries or pulling together draft RFPs, remains to be seen at scale.  One of my more sophisticated clients has run 300+ Proof of Concepts in AI across their business, including and beyond procurement, and admits they are yet to scale or drive meaningful ROI from any POC. At the moment, the generative AI side for us, isn’t getting past proof of concept or the pilot stage yet.”

Fraser Woodhouse is a Director at Deloitte and has been with the firm since February 2019. He believes that procurement and sales teams will use gen AI for RFPs over the next six months. “I think they’ll do it without telling anyone,” he explains. “It will eventually get to a point where I think that sort of crutch will become a necessity. When it’s built into the enterprise platforms, people will forget how to write contracts because the AI does it automatically. People will even use it to write their emails.”

The AI dilemma

AI on its own is pointless – it simply doesn’t operate the way you need it to. That’s why the importance of making tech work in a way that creates efficiency has never been more important. For Woodhouse, he insists it’s about putting a human at the right place in the process. “One of the solutions I saw was a gen AI assistant helping write an RFP built in, but then the supplier has a gen AI assistant helping do the response to the RFP as well,” he tells us. “Very quickly you’ve got two AIs negotiating with each other, and that doesn’t work unless a human is curating stuff at that point in the middle.”

Given the ease of AI usage, there is a discussion as to whether tech implementation could go too far the other way. Could humans lose the ability to perform simple tasks they previously wouldn’t have thought twice about? But Woodhouse is quick to dispel that myth and believes that despite the growing reliance on technology, people won’t be rendered useless. “People didn’t forget how to communicate when spellcheck came around, they could communicate better,” he explains. “If you are a supplier and are responding to an RFP and you’re pressing their generative AI button to build the response and five of the other suppliers are doing the same thing, who’s going to stand out? The ones who wrote it themselves or at least edited it and had meaningful input.”

“You can use AI for the transactional, easy stuff but there must be a value underpinning it,” adds Thompson. “The winners are going to be the ones that are human about things.”

Fraser Woodhouse and Kathryn Thompson speaking to CPOstrategy at DPW Amsterdam 2023

Procurement’s place

With such significant innovation happening, it is seen as a transformative time to be in procurement. As automation speeds up, the necessity to upskill new graduates coming into the workforce and encourage them to learn higher-value work earlier in their career journeys is becoming increasingly important.

“Covid and the following work from home attitude has a lot to answer for,” explains Thompson. “Pre-Covid, you would rarely work from home. Consultants, suppliers, delivery partners always went to the client’s site. That’s where innovation, creativity, results that are more than the sum of their parts happen. That’s not replicable by generative AI. We need to get everyone back out there and doing things. Rather than replacing jobs, we’re replacing tasks. The tasks that we’re replacing are the likes of data analysis, synthesising, and summarising. Hopefully, it means we’re doing real-life negotiations, brainstorming and innovation instead which are the things that people love to do. Fingers crossed, it just means the bar goes up.”

At DPW Amsterdam 2023, Prerna Dhawan, Chief Solutions Officer at The Smart Cube (a WNS company), tells us about the importance of remaining focused on fixing the problem and not leveraging technology for technologies sake.

“You don’t need AI or even gen AI for the sake of it.”

In today’s world, everyone is obsessed with what’s new and fresh. Like in most other functions, in procurement, the latest craze is generative AI, with ChatGPT being one prominent example. Despite new technology’s clear benefits, such as cost and time savings, it’s important to keep the problem you’re trying to solve and the business impact you’re looking to make front of mind.

Prerna Dhawan is the Chief Solutions Officer at The Smart Cube. Like many of her peers, Dhawan recognises the potential that new technology brings but also shares concerns. “Like everyone else, we’ve been on that bandwagon as well,” she tells us. “For us, there have been two key learning so far. We have already done one live deployment of gen AI. We went live with our gen AI model earlier this year, which enables users to skip the stage of manually searching for content on Amplifi PRO, our on-demand procurement intelligence platform. You just ask the question and our platform leverages a custom NLQ framework and gen AI to provide a natural language response. Using a combination of our own AI models and gen AI provides a more dependable, accurate response as pure Gen AI isn’t fully functional for all types of analysis and can’t be trusted completely.”

Navigating AI adoption

Indeed, there has been criticism from some sections about ChatGPT providing hallucinations and making key data up. For multi-million pound organisations responsible for high levels of spend, this isn’t good enough. A second learning Dhawan is keen to get across is that she believes that gen AI is being dominated by hype. She explains that with any “new shiny object”, it should be treated with caution.

“I’ve tried to explain this a little bit, but everyone is excited about new things. A recent example is another use case where we were experimenting with our digital assistant,” she explains. “There was a point where we used a 100% gen AI approach, and we were still getting issues and hallucinations where the queries weren’t being answered correctly. The team said we needed to make it work and I explained that, ultimately, a client needs to solve the problem, they’re less hung up on how this is done. Sometimes people get lost with the technology and the approach. You have to ask yourself, are you solving the problem? If the answer is to just input a human and you don’t need AI, then do that.”

Prerna Dhawan, Chief Solutions Officer at The Smart Cube, sits down with CPOstrategy at DPW Amsterdam 2023

The journey

Armed with more than 16 years of experience in developing client solutions, managing strategic relationships, defining product strategies and driving profitable growth, Dhawan has worked with procurement, supply chain and corporate strategy teams across many global 2000 companies. Throughout her career, she has helped them embed intelligence and analytics as enablers of competitive differentiation and business transformation, along with The Smart Cube’s co-founders Gautam Singh and Omer Abdullah.

The Smart Cube is a WNS company and is considered a trusted partner for high-performing intelligence that answers critical business questions. The Smart Cube works with clients to figure out how to implement answers faster through customer research, advanced analytics and best-of-breed technology. The firm transforms its data into insights – enabling smart decision-making to improve business performance at the top and bottom line. Together with WNS, expert resources are combined with leading digital technologies, merging human intelligence and AI with innovation.

Digitally-enabled future

While AI’s challenges should be acknowledged, Dhawan is in no uncertain terms about the importance of stepping out of comfort zones and meeting fear head-on. Change can be a divisive topic with human nature being to cling on to what’s familiar. However, this can result in becoming reactive and failing to keep up with competitors.

Prerna Dhawan, Chief Solutions Officer, The Smart Cube

“As leaders, if we want to change the game of procurement and redefine the value we create for a business, we have to be more open to embracing new things,” she explains. “If you learn what the capabilities of new technology are and where you can actually use it, everything has strengths and weaknesses. Ask yourself – do you want to be an early adopter or do you want to be a laggard in your industry? All of this has the potential to give you that competitive advantage. It’s about being open, experimenting at pace, but also not being blinded by the magic and assuming everything will just work. There will be changes needed to your processes and people’s mindsets.”

Procurement’s future

With the future of procurement set to continue to be digitally-enabled and full of innovation, Dhawan believes the function now has its seat at the table and is ready to thrive.

“If I look at my journey from when I started in procurement, clients were asking questions like ‘Who are the suppliers in the market? How do I get the best price?’ Procurement is now getting involved at the new product development stage and is even advising the business on what ingredients to use while taking a more total value approach,” she discusses. “When you’re thinking about the product, do you want to put in palm oil or sunflower oil based on sustainability considerations, and how can you justify additional costs of a sustainable supply chain? Procurement isn’t just supporting the bottom line but also influencing the broader business goals of sustainability, innovation and resilience. It’s a great time to be here.”

In this article, Veridion’s CEO unveils the exciting world of AI in Supplier Discovery, shares the company’s journey into data enrichment, and concludes with some behind the scenes of how the company is enhancing its Search API with natural language capabilities, paving the way to data-driven future in procurement and beyond.

In today’s world, global supply chains are facing persistent volatility and disruptions, leaving procurement companies extremely exposed to the fluctuations of markets and the associated risks from vendors. This unstable environment highlights the necessity of innovative approaches in procurement management, particularly the adoption of AI-powered intelligent data.

Deloitte’s 2023 Global Chief Procurement Survey reports that 89% of companies worldwide have been negatively impacted by inflation-related cost risks in the last year, with 79% also facing substantial supply shortages. These figures underscore the critical need for innovative strategies and technologies to address these challenges in procurement.

Embracing AI for supplier discovery: A game-changer in procurement

Perspectives from Veridion’s CEO, Florin Tufan

As procurement firms aims to master the complexities of the evolving supply chain landscape, artificial intelligence (AI) emerges as a transformative solution that promises significant benefits, especially in enhancing supplier discovery.

Veridion, a company at the forefront of data enrichment and innovation, is leveraging AI to streamline data-driven growth across many areas within industries. Florin Tufan, Veridion’s CEO, offers candid perspectives on the opportunities and challenges presented by AI in procurement, with a special focus on its capacity to refine the supplier discovery procedure.

Tufan talks about how leveraging AI for supplier discovery is transforming procurement from a process constrained by limited information and relationships to one that is dynamic, informed, and resilient. AI-enabled data allows companies to comprehensively understand the supplier landscape, enabling them to analyse and evaluate a vast array of suppliers quickly and efficiently.

“We come from a world where it wasn’t possible to learn everything about the entire universe. If you had three suppliers for one highly important thing, you’d much rather spend a lot of time strengthening that relationship and putting better protection in place. There was no easy way to ask about others and question whether you were working with the right ones while finding out if you had enough resiliency. No, you want to work with the best ones so that you’re covered and get on with the work no matter what.”

However, Tufan also highlighted that while AI has the potential to significantly cut down the time companies spend searching for new suppliers, it’s not a magic wand that instantly fixes all procurement issues. There are still things to be fixed in the supplier discovery process.

CPOstrategy speaking with Veridion CEO Florin Tufan at DPW Amsterdam

Veridion’s approach:  Addressing the need for a more proactive and comprehensive approach in supplier risk management

Tufan’s insights suggest a pressing need for a more proactive and comprehensive approach in supplier risk management.

Tufan pointed out a critical shortfall in the procurement strategies of many large companies—they lacked sufficient redundancy in their supply chains. When the pandemic struck, these companies scrambled to identify and connect with the best possible suppliers in various regions. However, the process was fraught with inefficiencies. “The discovery phase alone took weeks, and that was before even determining if those suppliers were a suitable match. By the time companies could establish redundancy, it could be two years later, and that’s simply too late,” Tufan explained.

He observed that the focus in procurement has traditionally been on what is known about the top suppliers based on past interactions, often neglecting the broader, more holistic view of a supplier’s status and potential risks. “There are numerous instances where companies face downturns or disruptions due to economic or political factors, and their clients often find out too late,” Tufan noted.

Who is Veridion? The company’s journey to data enrichment in procurement

Veridion, a Romania-based company, operates in the segment of source-of-truth business data, providing comprehensive and up-to-date insights on private companies. The company’s solutions are addressing particularly procurement, insurance, and market intelligence data challenges and are powered by AI and machine learning capabilities. This technology enables Veridion to extract maximum value from data, enabling efficiency and innovation for their customers.

One of Veridion’s earliest projects in procurement, which significantly contributed to its exploration of data enrichment solutions, involved collaborating with semiconductor companies seeking to diversify from China and US manufacturers planning to onshore to South America. This experience gave CEO Florin Tufan and his team deep insights into the complex challenges of global supply chain relocation. Tufan described this journey as both humbling and enlightening, particularly in understanding the significant impact of supply chain shifts on everyday products.

The company’s approach to addressing these challenges has been methodical and innovative. By leveraging AI and machine learning, they have developed more efficient ways to harness data, enabling businesses to make informed decisions in rapidly changing environments. This approach is not just about providing data but enriching it to offer meaningful, actionable insights.

Veridion has become a key player in transforming how companies approach procurement and supply chain management. By focusing on data enrichment and leveraging advanced technologies, they have positioned themselves at the forefront of this critical industry, offering solutions that are as dynamic as the markets they serve.

This “incredible journey”, as described by Tufan, exceeds the goal of business expansion. It’s about comprehending and effectively responding to the complex challenging of global with real-time, accurate data.

Looking forward: Veridion’s CEO perspectives on latest technology innovations

“I’m 99% percent excited! At the core, we’re an AI company.”

Florin Tufan’s vision for the latest cutting-edge technologies and innovations such as generative AI is one of optimism and excitement. He sees it not just as a technological leap, but as a tool that will become integral to daily life and business operations, enhancing efficiency and connectivity across the globe.

When asked what big news is coming soon, Florin announced an upcoming enhancement to their Search API, set to launch this year. This significant update introduces semantic search capabilities, leveraging natural language processing to enable more intuitive, human-like search experiences. With this advancement, users will be able to conduct searches that closely align with their specific needs and queries.

Veridion’s Search API is modernising multiple procurement processes from supplier search to enrichment, setting a new standard of excellence with first-class vendor data. By incorporating advanced AI capabilities, this intelligent search engine has made significant strides in deduplication, cleansing, and enriching master data, addressing a critical challenge many companies face. Organisations often struggle to understand the full potential of their existing supplier networks for sourcing opportunities. Veridion’s data-centric approach ensures that companies can now leverage their current supplier base more effectively or find new ones, uncovering hidden opportunities and driving efficiency in procurement strategies.

It looks like Veridion is reshaping the procurement landscape, turning complexity into clarity and offering an unparalleled user experience. The company is marking a paradigm shift towards a more efficient, data-driven future in procurement and beyond.

At DPW Amsterdam 2023, Danny Thompson, Chief Product Officer at apexanalytix, tells us about the art of developing trust amid significant innovation in procurement.

Trust.

Apexanalytix needs to build quite a bit of it. As a company which protects $9 trillion in spend and prevents or recovers more than $9 billion in overpayments annually, its client portals actively support over eight and a half million suppliers.

Indeed, apex has revolutionised recovery audit with advanced analytics and the introduction of first strike overpayment and fraud prevention software. Today, apex is a leading global force in supplier management innovation with apexportal and smartvm, now the most widely used supplier onboarding, compliant master data management, and comprehensive third-party risk management solution in global procure to pay. With over 250 clients in the Fortune 1000 and Global 2000, apex is dedicated to providing companies and their suppliers with the ultimate supplier management experience. A big part of that experience is based on building trusted supplier-buyer relationships.

Danny Thompson is the Chief Product Officer at apexanalytix and has been with the organisation since July 2015. Now in his third role with the company in eight years, Thompson reflects on his journey with the organisation with positivity. “I came in as a product manager working on our portal product,” he tells us. “And after a short time, because I was a former customer, at Pfizer and International Paper Company, and was an internal voice of the customer, they ended up having me drive messaging with marketing. Recently, we hired a great new leader of marketing who has taken that over fully so I’m dedicated full time to product again. So it’s been a great experience for me.”

Gen AI surge

One of the hottest topics on the CPO agenda in recent months has been ChatGPT. Wherever you go within the industry, you’ll likely find a conversation being had about the technology’s possibilities, as well as perhaps its limitations or challenges – and Thompson is equally keen to explore.

Danny Thompson speaks with CPOstrategy at DPW Amsterdam 2023

“There is certainly a lot of attention being paid to gen AI in the industry, and within our company as well,” says Thompson. “I think it’s because of the shock value of ChatGPT hitting the world and people are really stunned by its ability to interpret natural language and come back with really good information in response to questions that are being lobbed at it. There’s a lot of excitement around what it could do as well as what other generative AI solutions can do to help solve procurement, supplier risk and supplier information problems. We are making progress, and have introduced some generative AI functions, but Generative AI presents some challenges right off the bat that we are working hard to solve as quickly as we can.”

One of these issues is the hallucination problem that is being questioned within the space. This is where AI tools like ChatGPT lack factual support for some of the information provided. “There’s a statement at the bottom of the page which states you can’t rely on results being factual,” Thompson affirms. “When it comes to supplier information and risk management, that’s a problem.”

Managing risk

And it is such an important sticking point that Thompson stresses when it comes to supplier risk information, it is about being careful that the usage of generative AI, in its current state, is used for guidance rather than fact-finding. “Another challenge is around leakage of sensitive information combined with contamination of sensitive or important information,” reveals Thompson. “We have a database of golden records for 90 million suppliers who are doing business with Fortune 1000 and Global 2000 companies. That is the best information we’ve been able to accumulate about suppliers and their relationships as a supplier to large companies. Some of that data is publicly available and some of it is more sensitive. We want to make sure we’re not loading that sensitive information into a generative AI function that might allow random people to access that information. We’ve got to be careful about that leakage of data.”

The opposite is true, as well.  Thompson reveals that his team asked the generative AI-tailored questions which they assumed would be pulled from their own database. The findings were less than ideal. “The responses had been contaminated with public information which was full of inaccurate data,” he tells us. “We’re figuring out how to draw those boundaries, as well—to protect sensitive data while also preventing contamination.”

Trust first

This showcases the importance of trust once again to an organisation like apex. The companies it serves are moving significant sums of money around and the potential risks are sizeable. For Thompson, there can be no greater responsibility when using AI tools. “The data must be either highly accurate or at least they understand the degree to which it’s not,” he says. “If you don’t understand that level of trust you can have in it, then you shouldn’t be using it yet.”

With an unprecedented amount of technological innovation at procurement’s fingertips, the industry is evolving at a rapid pace. It’s placed at a unique moment with digital transformation being swept up throughout the space. While this brings obvious advantages such as time and cost savings, it also means increased cybersecurity threats. “There are more threats coming in as a result of AI,” says Thompson.

“One of the biggest challenges our clients us our solutions to solve for is fraudsters trying to take over a supplier’s account and intercept their payments by submitting fraudulent account change requests. One of the typical ways companies catch these is very often the request is coming through very poorly formatted emails with bad grammar. But what we’re seeing is the bad guys have started using generative AI to create really convincing bank account change requests so there are increased threats to be aware of. But this increase in the availability of information is also make easier the whole process of knowing your supplier and knowing the risks associated with them. And Generative AI is going to allow you to quickly get help to understand how to mitigate a given risk much faster and easier than it’s ever been before.”

At DPW Amsterdam 2023, Daniel Barnes, Community Manager at Gatekeeper, discusses the evolution of the procurement function and the influence tools such as generative AI are having in the space.

“It might sound harsh, but people just won’t have a job if they don’t change.”

For Daniel Barnes, Community Manager at Gatekeeper, his thoughts are clear. Technology is here and it’ll only get more advanced.

Barnes has been the Community Manager at Gatekeeper since June 2022. The company he works for is a next-generation Vendor & Contract Lifecycle Management (VCLM) platform that was born in the cloud and works on any device. Gatekeeper has a strong focus on collaboration, clear actionable data, obligation and compliance tracking, email alerts and most of all ease of use. The firm has a ‘zero training’ mantra driving a fanatical focus on usability that results in an application internal stakeholders and suppliers can use effortlessly.

The Gatekeeper Platform provides a suite of vendor management, contract management, kanban workflow, collaboration and reporting features. Customers can extend the functionality of Gatekeeper with additional modules to meet their required use cases, as well as integrating with over 220 third-party solutions.

Technology potential

Since joining the company, a key consideration for both Barnes and Gatekeeper has been the influence of generative AI. However, Barnes explains that while the potential of the technology is exciting, they are being strategic about how to leverage AI.

“We’re probably taking it a little bit more of a slower approach,” he tells us. “We have a contract summary function at the moment which means for any contract we summarise it so that anyone in the business can get a really quick understanding of that contract. We’re also exploring whether we’re going to bring in a Gatekeeper bot that allows us to get insights analysis in a very conversational manner. One thing we really believe is that contract and vendors aren’t just for procurement or legal. Everyone in the business has to contribute to make these successful. A lot of the issues, data and information behind these are legally complex. Procurement language is difficult when you’re talking about RFPs or you’re talking about risk. Someone in the business doesn’t care about that, they just want to get whatever they have brought, they want the service, they want it performed, they want it on time and they want a good relationship. We’re trying to figure out how to use AI like that.”

CPOstrategy speaking with Daniel Barnes at DPW Amsterdam 2023

The rise of Gen AI

Generative AI isn’t exactly new. In fact, it actually dates back to the 1960s. Among the first functioning examples was the ELIZA chatbot which was created in 1961 by British scientist Joseph Weizenbaum. It was the first talking computer program that could communicate with a human through natural language. But, given the introduction of a far more advanced model – ChatGPT – gen AI is the name on not only procurement’s lips but the wider world too. Barnes questions what you need to make AI successful at implementation.

“You get data and most procurement and legal teams have an issue with data because they don’t have it in one place,” he explains. “We fundamentally believe in this three-pillar approach. It’s to restore visibility and to have all your vendors and their contracts in one place. From there, you take control of that by digitalising all of your processes. Once they’re digital, you can track and automate them from various data points that you have in your vendor and contract records. That allows you to safeguard compliance, whether that’s regulatory, legislative or by contractual obligations. They’re all different forms of compliance that you need to track. Most teams are really struggling just with those. When we talk about gen AI, the reality is most teams are still so far away from even being able to realise those benefits. Today, gen AI looks powerful once you have the pillars in place and I’m really excited about its future.”

Procurement’s evolution

Indeed, procurement stands at a unique moment. With some in the space used to operating a certain way through legacy systems and others embracing a digital transformation and the technological innovation that brings with it, Barnes recognises that people who are reluctant to change could be left behind. “I think there has to be a willingness to change,” he tells us. “I’ve been talking about change in procurement since 2019, and I would say 80% of people who are engaged are hesitant and don’t want to change. That’s a really big concern. But my biggest worry is they don’t want to know in the first place. One of my fears is you’ve got so many solutions that genuinely can eliminate work in procurement teams. I’m worried for those people who don’t want to change because what are they doing when their work’s automated?”

The future

Barnes, who also hosts the World of Procurement podcast and YouTube channel, believes there is a current cultural divide in procurement and the industry is at a make-or-break moment. He affirms procurement will go “one of two ways”.

“You’ve got people who are stuck in the past that are archaic with what they’re doing. Then there’s those who are really pushing the profession forward,” he explains. “I see it as a moment in time where procurement kind of goes one in two ways. It’s extinct in terms of how it used to be. There’s solutions that I’ve seen which have automated workflows and are doing the work that traditional procurement people used to do. We can pull people along, but there has to be an initial willingness to change too or it’s not going to happen. That’s why I think it’s great to see people that are showing that willingness. They may not have the answers, but they want to learn.”

Michael van Keulen, CPO at Coupa, discusses the emergence of gen AI and whether procurement is in a golden era amid technology transformation.

Generative AI, or gen AI for short, is one of the hottest topics in procurement today.

Indeed, the introduction of ChatGPT has only accelerated its prominence into wider consumption. Gen AI allows its users to quickly generate new content based on inputs. These models could include text, images, sounds, animation, 3D models or other types of data. One of its biggest draws is the ability to understand different learning approaches and allows organisations to move quickly to leverage large quantities of data.

But despite obvious benefits such as time and cost, Michael van Keulen, Chief Procurement Officer at Coupa, stresses caution should be used particularly when it comes to valuable tasks. “If you look at ChatGPT, it’s fine if you’re looking for recommendations for something low-risk. I need something for my wife’s birthday next week, you input three things that she loves and ask it to help. It’s great,” he tells us. “But it comes from data sources on the web that aren’t always governed, controlled or trustworthy. It’s whatever is out there. What about the algorithms that come with ChatGPT? I don’t know what’s influencing the search criteria. On Google, if you pay you are at the top of the search bar. But I don’t know what ChatGPT is governed by.”

Van Keulen is a passionate and seasoned procurement evangelist with a comprehensive track record of driving value through business transformation at global companies. Since March 2020, van Keulen has been the Chief Procurement Officer at Coupa, a leader in cloud-based business spend management software, where he is responsible for driving best-in-class procurement practices across the company, supporting business development and being a source for peers looking to elevate and transform procurement. Van Keulen is especially passionate about building teams, driving value, organisational transformation, CSR, and diversity and inclusion.

CPOstrategy speaks with Michael van Keulen, CPO at Coupa, at DPW Amsterdam

The rise of AI

In the case of Coupa, the firm has been conducting its community.ai platform for the past decade which has been at the heart of the company’s strategy. Community.ai analyses real-time spend data, applies AI to compare company’s metrics against others and offers ways for organisations to be more efficient, profitable and sustainable. Van Keulen believes that the biggest difference between what Coupa offers and what gen AI provides is the trust factor.

“At Coupa, we measure information based on real spend, data and suppliers that are doing real business together – the internet isn’t doing that,” he discusses. “We’ve got nearly $5 trillion of spend under management from real transactions and real suppliers. That number continues to grow as customers and suppliers join the Coupa community. Pretty much all of our customers have trusted us with access to their sensitive data which we anonymize and then share back with the entire Community.  As a member of the community I know I can trust it because it comes from a source that is reliable, sanitised, relevant and well-governed. As well, we have certain standards and algorithms that we built-in all based on outcomes that our customers are looking to receive.”

Van Keulen believes there is a misconception in procurement that ready-made data sets are out there that are capable of meeting customer requirements. “The truth is most tech companies out there today don’t have access to customer data because their customers won’t let that happen,” he explains. “But at Coupa, our customers have already given us access to their data. This means we now have a real, reliable, accessible, governed and structured data set that has been anonymized.  When we then apply AI, you actually get prescriptions that are meaningful and relevant to procurement. I think the misconception is that this type of data set is easily found, but it’s not, we’ve been building this for over 10 years. There’s no other company out there that has the same level of spend data as Coupa.

“It’s the same as Google Maps. The only way that Google Maps works is because everybody uses it.  It allows me to get from A to B to C to D, back to A in the quickest time and with the least amount of disruption. The only way that that works is because we’re all using it. And I look at AI no differently in spend as I do with AI in my private life.”

Michael van Keulen, CPO at Coupa

Bridging the talent gap via AI

The need for fresh talent in procurement has never been so important. Procurement, like many industries, is lacking a defined path to welcome the next generation of talent, a feeling which has only been amplified on the back of COVID-19. This means the need to find ways to meet that shortage head-on, whether that’s through education, an industry rebrand or via AI. In van Keulen’s mind, he believes developing the correct tech landscape could hold the key.

“I’ve actually said this for a while,” he explains. “For too long, we brought in super smart people and then we would let them work in some antiquated old-school ERP, in Excel and run RFPs in emails. Nobody wants that, especially the current workforce because they’re used to and have been raised with Amazon, they all have TikTok accounts and are used to all these other e-commerce websites which have very seamless systems. If they come into the workforce and I let them work in some outdated ERP environment with email as the means of communication, that talent is either going to leave procurement because they think it’s boring or they’re just going to leave the overall organisation and work somewhere else. We don’t want that to happen, so you need to have the right tech landscape in place.”

Once the strategy is formed, van Keulen explains that is where the fun of procurement begins. “Then procurement’s the coolest function in the world and we will close the talent gap,” he says. “The talent is out there, they’re just not coming to procurement. They’ll go to finance, marketing, legal or IT instead. If you execute procurement properly, it’s the best because you’re right at the heart of everything. But you need the right people, operating model and operationalisation of your procurement process as well as the right technology. You need all of those elements or it’s never going to work.”

The greatest time in procurement?

Given the disruptive nature of global challenges and its ripple effect on procurement and the supply chain over the past few years, organisations are increasingly waking up to the importance of developing greater strategic relationships with suppliers. COVID-19, inflation issues, natural disasters and wars have meant today’s CPOs have been forced to firefight and think more strategically than ever before. Van Keulen recognises the turbulent nature of recent years and believes major transformation is already underway in procurement. “Historically most executives in any company would pay very little attention to their supply chain,” he reveals. “Due to recent events, companies are realising that they need to be closer to their suppliers. Perhaps in the past, the CEO would only spend a small fraction of their time with suppliers but those metrics are changing rapidly.”

As the ground lies in procurement, some sections of the industry now believe it is the industry’s greatest era given the level of possibilities. Widely considered a back-office function tucked in a corner and working in a silo, procurement is a totally different beast in today’s world. For van Keulen, he likes the variety.

“I wear so many different hats every single day,” he explains. “I always say sometimes I’m an accountant, others I’m an environmentalist. Sometimes I’m the treasurer or a finance person, but I’m also sometimes a psychiatrist. Sometimes I’m a doctor, a nurse, a lawyer, a judge, an environmentalist and yes even a wizard. I never know what my day looks like. I can plan it, but something may happen where everything goes out the window. Procurement will always be going through some type of disruption and it’s about how you drive the competitive edge and how you drive value despite that. Procurement really is the best gig in the world and it’s great that more people have started to see that now too.”

CPOstrategy compiles five ways that ChatGPT can transform procurement amid the rise of generative AI in the space.

ChatGPT is seen by many as a catalyst for the next wave of technology transformation.

The technology, which was developed by OpenAI, has quickly become the buzzword of the year and one of the hottest topics on the c-suite agenda.

And its promise extends to procurement – an industry that relies heavily on the need for achieving efficiency, transparency and cost savings. Having already made its mark on a variety of industries already, procurement hopes that by embracing ChatGPT it will allow teams to make greater strategic decision-making to drive long-term value.

Here are five ways ChatGPT can transform procurement.

1. Rapid research

Through ChatGPT, time-consuming and cumbersome tasks such as research can now be completed almost instantly. Generative AI tools such as ChatGPT can analyse significant amounts of data and provide insights on market fluctuations while also searching for new suppliers, products and capabilities to secure better deals.

2. Automated procurement processes

ChatGPT can be used to discover patterns and identify trends which will allow procurement teams to make data-driven forecasts. Through leveraging predictive analytics, organisations can anticipate demand, optimise inventory levels and manage their supply chain more effectively.

3. Easier communication with suppliers

Tools such as ChatGPT can improve supplier performance tracking through automating data collection and analysis. Its focus on cooperation and transparency throughout the procurement process allows for stronger supplier relationships and more innovative thinking.

4. Enhanced risk management

A major benefit of generative AI in procurement is improved risk management and the ability to foresee potential dangers. Through identifying potential hazards such as financial instability among suppliers or non-compliance with procurement processes, ChatGPT can help businesses manage and reduce risks.

5. Cost savings and increased efficiency

ChatGPT can help organisations to save costs by automating operations, increasing stakeholder participation and allowing real-time data analysis. By reducing the amount of time and effort for tasks like evaluating bids and selecting a vendor, ChatGPT could shake up the procurement process immeasurably.

At DPW Amsterdam, Gregor Stühler, CEO and Co-founder of Scoutbee, and Karin Hagen-Gierer, CPO and Strategic Advisor at Scoutbee, discusses the rise of chatbots and their influence in procurement.

Scoutbee was created with the idea of improving supply chain resilience through AI and big data to transform the way organisations use supplier data to discover and connect with suppliers.

The company, which was founded in 2015, offers an AI-powered Scoutbee Intelligence Platform (SIP) which uses graph technology and predictive and prescriptive analytics to deliver holistic supplier visibility that helps procurement make confident supplier decisions, drive cross-functional efficiency and optimise existing technology investments.      

Scoutbee’s AI-driven data foundation connects teams to any data point, internal, external, third-party and more, as well as any data combination necessary to orchestrate a resilient, competitive and sustainable supply base.

Gregor Stühler is the CEO and Co-founder at Scoutbee. He believes that waiting to invest in AI tools and underlying data training will be companies’ greatest sustainable disadvantage of the next decade. “AI is not an off-the-shelf product, so you can’t buy AI unless it’s a pre-trained AI on a specific use case but then it’s not a competitive edge,” he tells us.

“A competitive edge only emerges when you have a clear use case and training on top of that. The companies that start using those AI solutions sooner with their data have much better training in place. As a result, they’ll always be ahead of the game quite significantly. Companies that use off-the-shelf AI products will do well, but the ones that actually take it meaningfully and start trading on their own use case and their own data will be the ones that will be accelerating.”

Gregor Stühler, CEO and Co-founder and Karin Hagen-Gierer, CPO and Strategic Advisor, at Scoutbee

AI – Changing the game?

Karin Hagen-Gierer is CPO and Strategic Advisor at Scoutbee. She explains that there are a multitude of ways in which tools such as generative AI are having an impact on procurement to change the game.      

“AI is great to help with mundane and boring tasks,” she discusses. “It can help us with vendor requests that come in and can be appropriately channelled. It can help your colleagues to navigate procurement. When they have questions, they can interact with a chat solution and be guided in a much better way to find what they want much quicker. I think if we look at how it can enhance our teams’ effectiveness, it is really in market analytics, supplier searches, supplier evaluations, and ChatGPT that could help us broaden the spectrum. If you then look to more tailored solutions like Scoutbee then it’s a very different ball game that procurement professionals have at their fingertips. I’m noticing a drive on both efficiency and effectiveness in this space.”

Despite AI’s draws, Stühler is well aware of the challenges and hesitations around digital technology. As far as he is concerned, there are two waves of generative AI to be aware of.  “Wave one is about having a prompt and how tools such as ChatGPT can help with that,” he says. “For example, what are 10 RFI questions for aluminium cans?

“Wave two is where I merge and synthesise all of my data into our large language model and it has reasoning to drive decision-making and scenario planning. You do have to be careful though because you have to give the system all your critical data but you don’t want to input this into an open model. This means the use case has to be that you deploy a large language model in your own infrastructure, and own your own graphic card that will never actually leave your organisation.

Gregor Stühler, CEO and Co-founder at Scoutbee

“This is the biggest concern that we’re seeing because ChatGPT has brought a lot of progress but also a lot of questions. Now, when people hear that we want them to merge their data into a large language model that’s completely private, we’re met with some resistance when we explain to them that their large language model is running on their very own graphics card that we don’t have access to. That tends to give them more comfort to put their data into it,” he continues.

Stühler adds that he believes there are some misconceptions around ChatGPT and the nature of how accurate the data it provides actually is. As is the case with any new technology, these things take time. “It’s always the same. It happened with electric cars, nobody thought that would solve the battery issue,” he discusses. “I think we are right at the peak of the hype cycle when it comes to those things and people have figured out what they can use it for. With wave one of generative AI, it is fine to have hallucinations of the model and if something is spat out that is not supported by the input.

“But by the second use case, hallucinations are not okay anymore because it’s working with accurate data and should not come up with some imaginary creative answers. It should be always supported by the data that is put in. This is very important that people understand that if you train the model and if you have the right setting, those hallucinations will go away and you can actually have a setting where the output of the model is 100% accurate,” he further emphasises.

Procurement’s potential

According to Karin Hagen-Gierer, there is an incredible opportunity to create value in procurement today. Following unprecedented global challenges over the past few years, CPOs have never been in the boardroom so often – something she’s keen to stress.      

“The value of procurement through crisis has been proven,” she says. “We tend to say, it’s not a core business, but very often if things don’t go right, it becomes core very quickly and you are in the CEO’s office more than you might like. It’s the breadth of the role that allows to drive value: You impact the P/L impact, topline, and the ESG agenda to name a few. But then there is a need to future-proof your team’s skill set around how you can drive more impact from being more effective in the respective tool sets you’re using, the questions you’re able to solve solutions for. Additionally, you have to work on improving your efficiencies. Teams are not getting bigger, so you need to be enabled in a very different way to really drive all this value.”

Karin Hagen-Gierer, CPO and Strategic Advisor at Scoutbee

Stühler reflects on the past and admires the transformation procurement has undergone in the past decade since he joined the industry. “I came to procurement in 2012 and even then I remember this function being solely responsible for paying invoices and calling trucks to arrive sooner – at first glance,” he says. “Combined with the crises that now happened over the last couple of years, post-Covid has proven procurement’s value – and the impact organisations such as Scoutbee can make.    

“I think two key things will happen in the future. Firstly, the tech landscape is exploding so quickly that there must be a consolidation that will happen. Secondly, when it comes to generative AI I think those pragmatic use cases will become the new normal. ChatGPT will be like Google today to get insights. Generative AI and large language models will get increasingly powerful over time and will help if you feed it the right data and connect it to different data streams that you have internally. It can become this true copilot and help you with complex scenario planning and make you aware of weak spots in your supply base while helping you to strategically take the right steps. The future is exciting,” he concludes.

Stefan Dent, co-founder at Simfoni, and Richard Martin, CEO at Thinking Machine, discuss the power of data in procurement and the future of AI.

“See spend differently”.

Simfoni is revolutionising how businesses spend their money – via data. In today’s ever-changing world, everything is underpinned by data at Simfoni.

Founded in 2015, Simfoni is a leading provider of spend analytics, Tail Spend and eSourcing solutions to global businesses. Simfoni’s platform utilises machine learning and AI to accelerate and automate key parts of the procurement process which saves time and money while creating a pathway for supply chain sustainability. Its solution quickly distils and organises complex spend data to help discover opportunities and savings. It also gets up and running in days with an on-demand spend automation solution.

Indeed, Simfoni aims to take the hassle out of procurement through its automated, fluid platform that offers a unique pay-as-you-save pricing model which reduces barriers to technology adoption. Through fused revolutionary technology with AI-enabled content and deep expertise to automate, streamline and simplify procurement. Simfoni’s composable platform provides a selection of advanced automation modules that help customers sky-rocket savings and achieve sustainability objectives.

Stefan Dent, co-founder, Simfoni

Stefan Dent co-founded Simfoni and now serves as Chief Strategy Officer. He tells us his organisation was created ‘with a purpose to be different’. “A lot of customers have been working on full suite solutions for some time, which was seen as a sort of panacea for all ills that would solve everything,” says Dent. “It solved some areas such as direct spend, but these are large, mega expensive solutions that aren’t particularly agile. Ultimately, we came up with our own solution which is purposely different. We launched as a composable, agile solution that works with existing systems to boos ROI on tech spend. We apply next-gen technology to procurement that democratizes access to digital procurement tools – opening-up digital solutions to organizations of any size and across any sector. It means we can open our solution up to the masses and not just for large organisations.”

Relationship with Thinking Machine

Simfoni is powered by analytics. Its analytics solution informs spend, as well as watching how change is measured and performance is tracked over time. Now eight years old, Simfoni has fostered alliances with several younger companies offering specialist tools which have been embedded within the Simfoni platform. One such company is Thinking Machine, led by CEO and Founder Richard Martin.

Thinking Machine was founded in 2019 by Martin after he discovered the industry needed to find a better use of data to address ‘complex spend’ such as in Telecoms where you have multiple vendors, manual and frequent billing, changing tariffs and users. Martin explains that he witnessed all types of companies going through the same problems instead of only large companies. “Thinking Machine was developed as a way to give customers a single source of revenue across all services, pricing and demand but in a way that can be done at the very lowest level,” says Martin. “We would take all that complexity and be able to roll it up into actionable evidence that could be reconciled against their top-level financial numbers. It gives procurement directors the tools they need to actually be in the driver’s seat when it comes to their procurement operations.”

Developing key, strategic relationships with partners that can be depended on is an essential component to the success of any long-term business relationship. Simfoni relies on Thinking Machine to help manage its load and enable customers to go deep with Thinking Machine to extract even more value from their data. “We offer our clients the opportunity to go deep within certain domains,” discusses Dent. “We can then bring in Thinking Machine to help extract even more value from the data on complex spend.

Stefan Dent and Richard Martin speaking to CPOstrategy at DPW Amsterdam

“Thinking Machine’s application will ingest a large quantum of complex data. Their tools work like magic and allows data to be put into a readable format so they can make sense of the actual spend and quickly identify optimisation opportunities. This is part of our philosophy to work with niche technology partners because we shouldn’t do everything, so we need to put our resources where it counts. Resources like Thinking Machine work well by plugging into us, which means we offer incremental value to our clients without them going to market separately.

“It can also be very hard for a young company to work with large corporates because they’re untried or untrusted. This means for a company like Thinking Machine to connect with Simfoni is a win-win for everyone.”

Procurement’s bright future

Given the space procurement finds itself in today, the future is set to continue to be transformative. For Martin, he believes the introduction and influence of generative AI tools will help meet challenges in procurement head-on. “For the first time you see how it’s actually possible to be a unicorn with a 10-person team,” he explains. “The scales of efficiency are just out of this world. In terms of the procuretech industry, I think we’ve had a problem for a while now because there’s been all these best-of-breed solutions that are doing bits and pieces but is very difficult to stitch together into one cohesive platform that customers can make use of without having to know how to use 50 different tools.

“I think Gen AI offers a path to helping to smooth over some of those challenges and figuring out how to bring these things together. I think enterprises are going to start finding a lot more value in having all these best-of-breed solutions, such as Thinking Machine and Simfoni, while being able to use AI as a way to put this together into more of a single common layer that they can access. It is a very exciting time.”

For much of the past decade, Dent explains that he has believed that machines will take over mundane and outdated ways of working. Now, with the influence of tools such as Open AI’s ChatGPT, that digital future has only been accelerated and change the workforce of tomorrow. “Most CPOs of today are saying they need more headcount but I think they will soon be thinking very differently,” he discusses. “We predicted some time ago that Procurement departments will get smaller in headcount, maybe by even up to 50%. The procurement function of the future will be a lot smaller, leaner, and meaner.  Procurement teams will be more intelligent and strategic, in terms of both the people employed, and the digital tools used to manage spend.”

While Dent believes AI and machines won’t replace every human in procurement, it will mean forward-thinking teams need to embrace new technology with humans taking on higher-value roles. “The shape and structure of the modern procurement function will change quite dramatically, and people will need to upskill,” he discusses. “A lot of the work will be taken over by the machine eventually either 20%, 50%, and then a hundred percent. But the human needs to have that in mind and then plan for that next three to five years. The procurement function of the future will be smaller, and they should purposely be doing that, to then look at solutions to find a way to enable it to happen naturally.

“This is arguably the best time for people to join procurement, as you’ve got this great opportunity to embrace digital and make it happen. Young people can question ‘Well, why can’t it be done by a machine?’ They’re coming in with that mindset, as opposed to fighting being replaced by a machine. I think for graduates coming into procurement, they’ve got the opportunity to play with digital and change the status quo which is a wonderful thing.”

Scott Mars, Global Vice President of Sales at Pactum AI, discusses his organisation’s solution amid procurement’s digital transformation.

AI. It’s everywhere, all at once.

Procurement is one of the leading industries when it comes to embracing new solutions and ways of working. The space is waking up to the massive value that can be created through autonomous negotiations. And making a name for itself in the procuretech ecosystem is Pactum.

Pactum is an AI-based system that helps global companies to automatically offer personalised, commercial negotiations on a significant scale. The system adds value and saves time for both the Pactum client and their negotiation partner by aligning values to determine win-win agreements via easy-to-use chat interface that implements best-practice negotiation strategies.

Scott Mars has been the Global Vice President of Sales at Pactum AI since December 2022. He explains that his organisation is always striving to grow and expand its service offering. “At Pactum AI, we’re defining the space,” explains Mars. “We’re a creator for autonomous negotiations, we work with some of the world’s largest organisations and we’re really looking to expand the pie. The name Pactum originates from the Latin definition of an informal agreement between two parties. We can do up to 10,000 negotiations at once and unlock hundreds of millions of dollars of savings for our clients. We’re typically looking at tail-end suppliers and tail-end spending that no one’s touching. In many cases, that represents 80% of the negotiations.”

Exponential savings

Mars highlights a recent example of incredible savings achieved through Pactum AI’s solutions in a short space of time. Recently, Pactum worked with a travel and leisure firm in the UK to introduce its autonomous procurement solution. “We conducted a very brief implementation over two weeks, which led to a much larger enterprise rollout,” he discusses. “The CPO was actually on holiday while we implemented the autonomous procurement solution with his team. This involved optimizing payment terms with some of his long-tail suppliers.

“When he got back from holiday, there were 50 DocuSigns sitting in his emails, all related to extending payment terms. Many of them were remarkable successes, resulting in an average extension of negotiated payment days by more than 30 days and a 3% average gain from negotiated discounts and discount periods. This means we secured an average discount of 3% on each invoice when paid within the agreed-upon discount term. Our unwavering commitment to enhancing overall value not only positively impacts our clients but also extends to their suppliers, creating a win-win scenario for all involved.”

With AI having such a transformative effect on procurement, achieving efficiency and cost-effectiveness is more streamlined than ever through digital tools. But being alert to new threats, particularly in a space that is so open to innovation, does bring data security concerns. Mars recognises the challenge of cybersecurity and affirms Pactum ensures the safety and confidentiality of sensitive procurement data remains secure in chatbot interactions.

Digital future

“Everything is hosted in a private cloud, so each customer has a private instance. It means all of our data is secure from a generative AI perspective,” he tells us. “Large language models (LLMs) are great, they’re creative but they have their problems which means we’re only using safe LLMs. All of our negotiation design is kept in-house, and we use rule-based explainable AI which means all the data is secure per each customer. We have the largest repository of behavioural science, so those learnings are shared across our customer base, but all the customer data and all their negotiations are private to each customer.”

Looking ahead, Mars is excited about procurement’s digital future and explains Pactum AI’s vision is to transform global commerce. “At the moment, we’re only doing buying, but we are looking to move into the sales side as well,” he discusses. “Large companies have a huge footprint. For example, the Fortune 500 is 66% of the US economy. The plan is for us to move into selling which will give us the scale to transform global commerce. It’s definitely a grand vision, but we do feel that we’ll move from buying into selling and transform global commerce.”

For procurement generally, Mars is adamant that the space is in its “golden age” with the magnitude of vendors within the procuretech ecosystem hitting unprecedented numbers. “I was speaking with a CPO recently and he said 10 years ago you could name the procure to pay and ERP vendors on one hand, now there’s hundreds of them and all these periphery vendors for AI and spend,” he reveals. “The most visionary procurement leaders aren’t just looking at these all-encompassing solutions, they’re bolting on niche solutions into their ecosystems to make their teams more efficient. I think we’ll start to see a consolidation in the coming years of all these little companies into a few larger players to do really an end-to-end type solution. I expect someone to come up with a solution to close the loop in procurement.”

Shaz Khan, CEO of Vroozi, discusses why AI is the great equaliser for companies to optimise procurement.

In today’s ever-evolving business landscape, companies are facing a multitude of challenges when it comes to managing and controlling their spending. From global supply chain disruptions, outdated technology solutions, labor shortages and much more, these challenges have an immense impact on a company’s financial health and overall efficiency. Additionally, procurement teams are regularly tasked with new responsibilities beyond spend management and purchasing, such as managing supplier risk, building, and implementing CSG and ESG initiatives, studying economic trends to determine price elasticity, finding new sources of supply, and cleaning up disparate and dirty data. Yet most companies simply do not have the human capital or bandwidth to execute these areas with quality and control.

When it comes to bridging the gap between the obligations that procurement teams are tasked with and efficiently executing on these tasks, AI may be the great equaliser to help solve these problems. While AI has turned into somewhat of a buzzword in today’s market, there’s no doubt that the technology has powerful capabilities to truly transform procurement in the foreseeable future. For those changes to take place, it is important for procurement professionals to continue to articulate the problems they are facing on a daily basis, as this will force the industry to evolve and adopt the proper solutions for better business outcomes.

Shaz Khan, CEO and co-founder, Vroozi

The problems: Unchecked spending, outdated tech, and lack of governance

Irresponsible spending can wreak havoc on a company’s financial well-being. With non-managed indirect and direct spend categories, companies experience up to a 40% increase in costs, consequently eroding their gross margins and increasing operating expenses. This usually stems from lack of visibility into non-payroll spend categories, combined with old and antiquated technology solutions within enterprise infrastructure that makes it difficult to extract data, analyse spending patterns, and generate meaningful reports on total addressable spend (sound familiar?). Poor data quality and the need for data cleansing can impede effective spending management, leading to faulty decision-making that hinders procurement efforts.

Unchecked spending can also foster a culture of mistrust and overall decreased morale among employees. When employees perceive that their hard work and dedication are being undermined by wasteful spending practices, workers begin to feel disengaged — which leads to reduced productivity. When spending is not carefully managed, there is a risk that critical projects or departments may not receive the resources they need to thrive. This not only causes anxiety about the organisation’s financial health, but it also can lead to concerns about resource allocation and fairness. Therefore, it creates broader mistrust in organisational leadership.

One of the biggest culprits in inefficient spending management comes from a lack of visibility into supplier contracts, which stifles a company’s ability to identify cost-saving opportunities. Hidden fees, price escalations, and unexpected cost structures can be buried in supplier contracts. A lack of visibility can result in unexpected cost overruns, impacting the organisation’s budget and profitability. Departments may also struggle to fully understand the terms and conditions within these contracts, including performance expectations, delivery schedules, and penalty clauses. This lack of clarity can increase the risk of contract breaches, quality issues, or delivery delays.

The long-term benefits of incorporating AI into procurement

With more at stake within procurement departments than ever before, AI serves as a turbocharged catalyst for procurement teams to optimise their processes. Procurement leaders are increasingly delegated additional responsibilities and AI offers an invaluable assistant that can process, predict, and deliver information and outcomes without exhausting human resources. For example, predictive and smart reordering can keep items that require ongoing restocking on a regular purchasing cycle. AI can also help identify alternative sources or suppliers for this item that may offer additional cost-savings and attractive incentives. As this technology becomes increasingly more capable, it’ll save procurement departments hours of time — freeing up employee bandwidth to then focus on optimising supplier relationships and other strategic tasks.

Earlier, we discussed how unchecked spending leads to mistrust and disengagement within an organisation. AI can help re-establish morale and an engaged staff by gamifying the procurement process. For example, a company can create a scenario where employees and teams are rewarded with soft benefits for complying to procurement policies, reducing maverick spend, improving supplier relationships, or negotiating a new deal with a strategic supplier. These soft benefit rewards can be programmed into the system to track and signal when teams are hitting these goals. Gamification, particularly when entire teams are rewarded together, can foster camaraderie and a dynamic culture built around the thrill of victory, aligning employees with the company’s procurement strategies.

Ensuring a smooth transition to AI-driven procurement processes

When beginning the transition towards an AI-infused process, it requires an honest assessment of existing processes, data quality, and technology infrastructure to identify pain points and areas where AI can provide the most value. Integration will require some level of customization to meet the specific needs of your business, such as custom algorithms, workflows, or user interfaces. This is an ongoing process. Optimisation requires the continuous gathering of feedback from users and stakeholders to identify which areas are working well and which features need improving. Be prepared to adapt as you go along. AI is a rapidly evolving field, and we are in the very early stages of realising the true potential of this technology.

As the AI revolution takes place in procurement, employees need to be introduced to new technologies to understand the strengths and more importantly the limitations. However, when thinking of the big picture, Procurement teams must be prepared to upskill their talent pool and recruit new talent to maximise AI’s potential including investing in certifications in data science, cloud platforms, supply chain management, and data analytics. To reap the benefits of automation, data-driven insights, and enhanced decision-making, leadership requires teams that have skills to use and interpret AI tools effectively — particularly when it comes to data management. AI solutions rely heavily on data and procurement teams must know how to effectively manage this data, including data cleansing, integration, and analysis to ensure that the algorithms receive high-quality input data and large language models for accurate results and the promise of real predictive analytics.

The promise of a brighter future

This is also why collaboration between departments is essential. For AI technology to be implemented effectively, it requires synchronisation and cross-functional collaboration between IT, data science, corporate procurement, finance, and other departments. Companies that cultivate these collaborative ecosystems within their departments gain a strategic edge in terms of stability and future growth.

It’s important to note that while AI is a productivity and enablement tool, it is not a replacement for human intellect, willpower, and execution. Therefore, it’s essential to seek knowledge and expertise from insights from companies, networking groups, and individuals with practical experience in AI and GenAI capabilities. Remember, it’s important that you do not let AI drive your business, but rather let your business needs drive AI adoption. Define the specific problem that you aim to solve and determine if AI is the right tool to boost these areas.

Ultimately, the incorporation of AI into procurement processes holds the promise of a brighter, more efficient future for businesses. Procurement departments face many challenges but if they address these pain points with a strategic approach that involves the adoption of modern technology solutions while upskilling their workforce, businesses can expect to soon see enhanced visibility into their spending and gain a strategic edge in a competitive market.  One thing is certain, AI will transform the procurement professional and function into a data analytics and supplier relationship mastermind.

By Shaz Khan

At DPW Amsterdam, Ashwin Kumar, vice president at GEP, discusses procurement transformation and what tomorrow’s challenge could look like.

Transformation. Procurement has witnessed quite a bit in recent years.

Given the widespread adoption and acceleration of AI and data-driven processes over the past decade, change has been a necessity rather than a nice to have.

Evolution of AI transformation

Ashwin Kumar is not unfamiliar with change. Having worked at GEP since May 2008, he has had a front-row seat to the transformation and change procurement has overseen. Now Vice President, he tells us about the evolution of the procurement function and how the landscape is shifting to meet future market demands.

“I think the way we see the industry evolve over time is because we started with web 1.0, simple ERPs that were fragmented with no easy way to connect systems,” he tells us. “Data was all behind firewalls and it was very expensive to manage or mine data. Then we had a big technology breakthrough in cloud systems where the people who were managing the storage said they had a solution. You can just simply push data out of the cloud and what we saw was a lot of that control that the CIOs had on data architecture and the software systems and solutions was being given to different functions.

“A lot of that enrichment of data happened because of the cloud platform that enabled it. Back in 2010, we made the decision to move away from a SaaS platform because even then we believed the future was cloud and that’s where data is going to be which could mean a gold mine. Our CEO made a very conscious decision to basically stop a really good product that was working and move to the cloud platform.”

Ashwin Kumar, Vice President, GEP

The GEP difference

Today, a global leader in AI-driven procurement and supply chain transformation, GEP helps enterprises take the lead and, using the power of data and digital technology, to stay ahead in the connected global economy. More than 1,000 engineers have spent the last 7 months to design and launch GEP’s new AI-native, low-code platform for sustainable procurement and supply chains, GEP QUANTUM. This new platform, launched last week, powers GEP SMART, the industry’s leading source-to-pay procurement application, GEP NEXXE, its next gen supply chain solution, and GEP GREEN, enabling companies to track, measure and achieve their ESG goals.

With the transformative power of AI, GEP enables businesses to operate with greater efficiency and effectiveness, gain competitive advantage, boost profitability and maximise both business and shareholder value. GEP helps global enterprises across industries and verticals build high-performing, resilient and sustainable supply chains.

Investing in dedicated spend analytics and solutions has become an essential part of the procurement process. Data is king and ultimately the more companies know and can predict, the better off they’ll be. However, some companies are still lagging behind when it comes to adopting digital tools created for better visibility and transparency. Kumar questions the reason for this and points to the possibility that there could be a perception that digital tools were hype or a fad – but affirms spend visibility is the real deal.

“If you look at spend data, if I’m the business stakeholder, you’re coming and showing me things that happened six months before,” he tells us. “One of the things we actively tell customers is to understand that there is a difference between spend and cost. Spend is basically the last AP data that you get, which means it’s not even current.”

Procurement’s greatest time?

Given the disruptive nature of the past few years, procurement has had to stand up and be counted. For Kumar, he reflects on global challenges such as Covid, a war in Ukraine and inflation and its knock-on effect on procurement and the supply chain. He maintains that it’s a “difficult time” to be in the industry at the moment given the hurdles procurement and the wider world has faced head-on recently.

“We started off with Covid where we went and told suppliers, sorry, I don’t have money to spend so I’m going to stop spending,” he tells us. “Two months later, you tell them there’s a supply shock and since I’m your preferred customer, can you do something for me? Make sure my products are getting to me on time. Then six months later, there was a war in Ukraine where you were testing suppliers to see which side they were on and questioning whether or not to do business with them. After that, there were inflation concerns so things are constantly changing and you’re pivoting from one problem to another.

“It now means you need to have a platform ecosystem with multiple solution options so that there isn’t a single point of failure and avoid the need for a “transformation” every two years. Given the pace at which things are changing in the macro environment, those single points of failure are quickly going from lack of supply to resilience to risk to people to visibility. It could be something else tomorrow, it could be ESG tomorrow, we simply don’t know. I could have a really good risk assessment tool, but that might not be my focus six months from now – it could be something else. So resilience in the form of digital ecosystem housing different point solutions is paramount.”

Koray Köse, Chief Industry Officer at Everstream Analytics, speaks to us exclusively at DPW Amsterdam and discusses the importance of leading from the front in the supply chain

Everstream Analytics sets the global supply chain standard.

Through the application of AI and predictive analytics to its vast proprietary dataset, Everstream delivers the predictive insights and risk analytics businesses need for a smarter, more autonomous and sustainable supply chain. Everstream’s proven solution integrates with procurement, logistics and business continuity platforms generating the complete information, sharper analysis, and accurate predictions required to turn the supply chain into a business asset.

Koray Köse is a supply chain expert, futurist and multi-lingual thought leader, CPO, researcher, and published author. He specialises in working with CSCOs, CPOs, CIOs and other c-level executives while possessing more than 20 years of success in developing global supply chain and sourcing strategies, re-engineering and transforming business processes, and maximising financial resources. Köse is experienced in designing new business frameworks, risk and governance processes and deploying full-scale ERP and procure-to-pay systems to drive efficiencies through digital transformation. He is an expert in industries such as automotive, pharma, life sciences, IT, electronics and FMCG and has served as Chief Industry Officer at Everstream Analytics since June 2023.

Koray Köse, Chief Industry Officer, Everstream Analytics

World’s first Slave-Free Alliance

Recently, Everstream became the world’s first Slave-Free Alliance (SFA) validated modern slavery and forced labour technology provider. Everstream’s collaboration combines the firm’s multi-tier supplier discovery and AI-powered risk monitoring and analytics with SFA’s proprietary forced labour intelligence to expose unknown risks and protect global supply chains from modern slavery and exploitation.

“We’ve had issues in supply chain before, like conflict minerals for instance was a big topic,” Köse tells us. “Legislation came that was rather weak, where companies can say we can’t confirm nor deny that we have conflict minerals in our products. Modern slavery takes it to a whole different level. In essence, you may get import issues the moment that you might be suspicious, or the government import controls may say, ‘this comes from a specific region that has general exposure’. You basically have a disruption in your supply chain.

“If you forget about the business side, your business is actually promoting ethics that your own company in its statement and the way you live don’t align with and you didn’t know about it. So unknowingly you have actually incremented the issue that you are tackling on your own and within your environment. For us it was important to live up to the promise and look for an NGO that is impactful, has a mindset that is all about partnership and not blaming or shaming, it’s about changing the environment.”

Breaking down barriers

Around 50 million people worldwide are living in modern slavery. It remains a serious problem in nearly every region, with over 40% occurring in upper-middle to high-income countries. Due to the opacity and complexity of today’s global supply networks, companies are increasingly vulnerable to the risk of forced labour. According to a study cited by Slave-Free Alliance, 77% of companies expect to find modern slavery somewhere in their supply chain. Through this alliance, Everstream will actively contribute to enhancing capabilities and eradicating modern slavery and forced labour from global supply chains.

“We started that partnership to transfer our knowledge and also get insights from their end and understand what the upcoming issues were in the arenas of modern-day slavery that we should keep an eye on and how to help our clients to be informed and avoid getting exposed,” says Köse. “That’s where I started to talk with Hope for Justice and have collaborated with them during my time at Gartner as well. Then legislation is pushing the matter to the forefront of supply chain issues.

“Now, there is also financial impact and disruption and there’s the ability to do good and live up to the promise of your own vision and the way you want to conduct your business. Then I wanted to put our product to test and make sure that it lives up to the promise and if it doesn’t then we fix it. We went through a validation process and we got 90% plus accuracy in the feedback, which is important as it’s another confidence boost that we’re doing the right thing and we should continue on that path. We are the first world’s first validated modern-day slavery solution to tackle the issue – we’re very proud of that.”

The value of due diligence

In today’s fast-paced world, due diligence has become more important than ever. Companies must ensure they are generating the best value for money and that the product that they’re purchasing actually meets their needs. Köse believes companies almost have no choice in 2023.

“It’s an element that is not only preserving value, but it also creates it too,” he explains. “In the past it was more like a checkbox exercise that you conducted because everyone thought it was the right thing to do. Meanwhile, you had spillovers that you didn’t know about. It’s almost like what I don’t know, I don’t care. Since transparency requirements have been augmented significantly and the realisation of transparency as a value driver has dropped through Covid almost instantaneously in the c-level boardroom, compliance has become a value driver.

“It’s not just a checkbox exercise where you say that you are compliant. It is an affirmation of your product quality, brand and innovation that speaks to the customers and the choice they make. If you are concatenating beliefs and values to your product in that moment, you just have created a customer and that customer will be retained throughout the lifetime that you actually care about what they care about.”

CPOstrategy examines 10 of the best ways to use artificial intelligence (AI) in procurement

Artificial intelligence (AI) is one of the biggest buzzwords in procurement. Everyone wants to get their hands on it and introduce it into their strategies.

Particularly in procurement, AI is often talked about being the answer to all challenges. It can be used to overcome complex problems and deliver efficiency while also being introduced within software applications such as spend analysis, contract management and strategic sourcing.

In this article, we will list 10 of the best ways to use AI in procurement.

1. Machine learning spend classification

AI algorithms can help categorise, clean and classify data automatically. Machine learning spend classification helps detect patterns and uses them for prediction while allowing for better decision-making. Examples of spend classification techniques include supervised learning, unsupervised learning in vendor management and classification reinforcement learning. 

2. Natural Language Processing (NLP)

National Language Processing (NLP) is the branch of artificial intelligence focused on understanding, interpreting and manipulating human language. It can be used to gain valuable data and information to streamline time-consuming processes. Information contained in legal documents can be interpreted through AI for the procurement of relevant data. It allows procurement professionals to get ahead and use an AI assist engine to receive alerts to proactively monitor progress. It also allows for compliance over the life of multiple agreements with the same or several vendors.

3. Robotic Process Automation (RPA)

Robotic Process Automation (RPA) mimics human actions to eradicate repetitive tasks. While not strictly AI in the traditional sense, RPA does provide procurement with opportunities to improve process efficiency and is part of the wider family of AI. It can assist with the likes of contract management, input identification as well as purchase request and order submission, among more benefits.

4. Anomaly detection

With AI being able to process vast amounts of data quickly, it is able to stay up to date on the latest developments and changes in the procurement space at speed. Automated notifications on things such as anomalies, new opportunities and recommended activities allows for immediate action to be taken and provide suggestions on what should be done instantly. Rapid detection will ensure risks are mitigated and resolved before they become problems.

5. Purchasing

AI can be utilised to automatically review and approve purchase orders. Chatbots can be used to check the status of acquisitions or automatically approve virtual card payments. AI can analyse data and assess the reliability and quality of suppliers based on predefined criteria. This helps the purchasing team select the best suppliers quickly and accurately.

6. Contract management

Contract management can benefit through using AI to create, store, review, index, retrieve, analyse, negotiate and approve agreements. A big benefit delivered by contract management solutions that use AI is standardised metadata reporting which eliminates the need for category managers and legal counsels to manually read contracts to gain insights into the commercial part of their supplier relationships.

7. Supplier risk management

Supplier risk management is an important part of the procurement process and is around understanding what happens if a supplier fails to meet its obligations. To combat this, AI can be used to monitor and work out potential risk position through Big Data. Millions of different data sources are screened in order to provide alerts on potential risks within the supply chain.

8. Accounts payable automation

AI can automate most manual tasks in accounting such as data entry and invoice routing. Using AI for this substantially reduces procure-to-pay cycles, minimises the need for humans to get involved and integrates multiple workflows into a seamless process.

9. Strategic sourcing

Using AI in strategic sourcing is a key tool in a procurement practitioner’s arsenal. AI can be used to manage and automate sourcing events while also leveraging machine learning for the recognition of bid sheets, as well as specialised category-specific e-sourcing bots such as raw materials and maintenance.

10. Automated compliance

AI can also be used as a valuable tool for compliance officers to help work out potential risks, monitor employee behaviour, generate reports, provide recommendations as well as educating employees about the importance of compliance. For organisations without a source-to-pay system, compliance is a useful alternative and allows procurement teams to seamlessly compare payment terms, identify duplications as well as determine non-compliance.

It’s time to admit it: Procurement has a long way still to go…

Where are we really when it comes to embracing innovative technology in procurement?

In the latest episode of The Digital Insight, we welcome Greg Watts, CEO of Findr – an AI platform that allows fintechs to identify, assess and connect with prospective partners. 

In this episode we explore the notion that, while digital transformation is touted as the solution to back-office procurement functions, there hasn’t yet been enough attention to how AI-driven tools can affect the strategic issues that underpin procurement and supply chain management, hampering the sector’s ability to truly reap the rewards of AI.

Nick Pike, Chief Revenue Officer at Vizibl discusses how companies should find their new normal, build supply chain resiliency and innovation and how there are no second chances if your supply chain is not reliable.

Innovation in procurement technology has not moved on much in the past decade, however the impact of COVID-19 and supply shortages expected as a result have certainly focused minds and shone a light on procurement sourcing. In fact, according to the UN’s Deputy-Secretary-General, Amina J. Mohammed: “Companies should focus on scaling up production, making sure supply chains are reliable.”

Finding the route to the ‘new normal’

What we are seeing is that organisations are trying to get a handle on the route back to the ‘new normal’ and emerge out of this crisis stronger than before. This means we will see a couple of years of real accelerated change, in fact according to Arvind Krishna, CEO of IBM, COVID-19 is likely to push companies to speed up their adoption of modern technologies like artificial intelligence and cloud.

For many procurement and supply chain professionals, the dramatic events of the last couple of months – including lockdowns, quarantine, production stops – were a wake-up call. Following the firefighting mode during the pandemic, companies have realised that they can no longer afford to be unprepared for such an event in the future.

Building resiliency into the supply chain 

Securing the supply chain to ensure that it is not negatively impacting the ability to meet customer commitments will be crucial. CPOs & CSCOs will want to know if there are any supply chain issues so they can quickly source alternative solutions. They also want to know what projects they need to prioritise following the crisis because, compared to earlier in the year, priorities have more than likely changed.

CPOs will be keen to understand what key projects they need to undertake to drive the organisation’s revenue and success. Outside of this, CPOs & CSCOs will also be looking at how to extend and enhance their supply network and how they can better understand their dependence on that network. Ultimately, short term they will be looking at how they transform their supply chain risk management processes and build in resiliency to not only survive but thrive. 

To this point, Deloitte recently published an excellent overview around managing supply chain risk during COVID-19, and I would highly recommend this report to anyone involved in developing improved supply chain practices for their business.

Resiliency will be the post COVID-19 watchword

This need for resiliency provoked us to develop a bespoke version of our Vizibl Supplier Collaboration and Innovation solution (Vizibl Resilience) that focuses on the need for companies to address these issues. We expose the critical projects that customers need to work on in the supply chain and have easy to use dashboards to be able to report critical information to the Board.

It is important to ensure that everyone is sharing information in an efficient way rather than individual-by-individual via email or phone. Businesses need to have the right collaboration technology to underpin their procurement sourcing, to solve problems faster. For many CPOs working remotely with their teams, perhaps for the first time, this level of shared visibility is vital.  

Vizibl Resilience ensures that all communication, actions, and results from vendors working throughout the supply chain are captured in real-time within a single, easy-to-navigate platform. Dashboards give the leadership team transparency around where the business is at in any point in time on any number of projects. This enables the organisation to identify any issues within those projects and quickly triage those that need attention.   

Building supply chain innovation

Of equal importance to visibility, collaboration and control is building innovation into the supply chain. 

If we look at an industry such as telecommunications and take Vodafone as an example – historically, generating revenue for the business has been very network bandwidth-orientated. Now Vodafone and its peers are required to build additional services on top of these networks, enabling them to differentiate. We are working with Vodafone looking at the new projects and innovations which are coming from their suppliers such as Huawei, Google, Nokia and establishing how Vodafone can bring those to market faster. We have been helping them to identify which ones are aligned to their business goals and how they can accelerate these projects.  

Removing costly duplication  

But what we have seen historically is that as companies start to do this, so duplication creeps in. Often, we find that a very similar project is happening in a different part of the organisation at the same time. By deploying Vizibl, we are able to shine a light on the duplication and show that elsewhere in the organisation there are two or three projects which are the same or very similar, which could be brought together.    

While saving money is one aspect, the other aspect is about getting various project teams to collaborate and get projects to market faster. 

No second chances

In just a few months, COVID-19 has triggered sweeping changes in how we all do business. This massive scale disruption created a succession of different supply chain issues. These issues are not necessarily new, but what has changed is that, going forward, not being prepared for such issues is no longer an acceptable position. With supply chains firmly in focus boards are pushing for a more proactive approach and level of insight and visibility.

Now the CEO will be asking the CFO, COO and CPO: is the supply chain prepared? During the pandemic, companies scurried to secure supply. During recovery, the CPO needs to initiate measures that lead to preparedness. They’ll be no second chances for CPOs going forward. This means being prepared must be an integral part of sourcing and supply chain management.

Leading U.K. retailer selects Blue Yonder’s end-to-end Luminate platform to power its supply chain strategy

Blue Yonder Tech, today announced that Sainsbury’s, one of the United Kingdom’s leading multi brand, multi-channel retailers across food, clothing, general merchandise and financial services, has selected its end-to-end supply chain platform as the foundation of its supply chain transformation.

Sainsbury’s will deploy Blue Yonder to power its end-to-end supply chain strategy, on a single artificial intelligence (AI)-powered platform. To support the business’s future supply chain program, Sainsbury’s will benefit from extending its current Blue Yonder solutions footprint, with powerful new capabilities. These current and new capabilities will now span AI-powered demand forecasting and replenishment, digital control tower, space management, macro space planning, range management, warehouse management, labor management and yard management.

Sainsbury’s is a leading multi brand, multi-channel retailer based in the U.K., operating more than 2,000 stores across its Sainsbury’s, Argos and Habitat brands. Sainsbury’s also operates a number of wholesale partnerships globally.

By partnering with the in-house engineering expertise of Sainsbury’s Tech, together the two businesses will create an autonomous self-learning supply chain platform with advanced machine learning capabilities. This step forward will enable Sainsbury’s colleagues to spend more time on the store floor and serving customers. Sainsbury’s chose Blue Yonder for its leading machine learning (ML) capabilities and SaaS-based solutions that uniquely power an end-to-end supply chain experience.

“We relentlessly seek to improve the way we serve the needs of our customers. Having a predictive, autonomous and adaptive supply chain powered by world class technology products and Sainsbury’s Tech engineering means we can show up for our customers whenever and however they shop with us,” said John Elliott, chief technology officer – Retail at Sainsbury’s. “Blue Yonder provided a strong balance of advanced capabilities, ML experience and a culture and value set closely aligned to our own, including a commitment to sustainability.”

By implementing Blue Yonder’s solutions, Sainsbury’s will further enhance its ability to monitor and respond to ever-changing customer needs, predicting and preventing potential supply chain disruptions. Blue Yonder’s Luminate platform includes ML-based forecasting and ordering solutions that help stores better manage fresh and perishable products. It also includes Blue Yonder’s crisis control center – Luminate Control Tower – which provides complete supply chain visibility, orchestration, and collaboration across the end-to-end supply chain and prescribing more automated, profitable business decisions.

“We are thrilled to expand upon our long-standing partnership with Sainsbury’s by offering iconic, game-changing, and customer-centric solutions that meet consumers’ daily and ever-changing needs, particularly in the critical environment in which we are all living today,” said Mark Morgan, executive vice president and chief revenue officer, Blue Yonder. “We know how important Sainsbury’s supply chain is to the company’s rich history of success and the loyalty of its customers. Our innovative AI and ML capabilities have a proven track record of real results, and our end-to-end platform is unmatched in the market. Our goal is to make AI and ML become key enablers of Sainsbury’s future digital transformation as the company expands its remarkable, trusted, multi brand, multi channel business.”

Additional Resources:

Technology and trade have always advanced hand in hand. From the magnetic compass and astrolabe that enabled the Age of…

Technology and trade have always advanced hand in hand. From the magnetic compass and astrolabe that enabled the Age of Discovery to the canals and railways of the Industrial Revolution to the digital revolution: all have brought us to today’s globalised economy. 

But the invisible threads that crisscross the planet do not represent trade’s “end of history”; rather, they represent a major new era of complex challenges for the global supply chain which necessitates not only a major new technological revolution, but an equally fundamental cultural one.

Making sense of an unstable world

The term “supply chain” conjures up images of forged, unbreakable links crisscrossing the planet. In fact, these networks are less like steel and more like gossamer: invisible, delicate and easily-disrupted strands that can break for any number of reasons. 

America’s trade war with China may have reached something approaching a truce, but the spectre of global pandemic has replaced it almost immediately as a source of supply chain disruption. Entire cities have been closed off as China attempts to contain the spread of the virus, while countries from Russia to the UK have effectively walled off the country while they assess the severity of the situation. The effect on supply chains is already being felt by a variety of industries who rely on China for the provision of everything from semi-conductors to car parts. 

Add in consumer-led issues such as forced labour, unsustainable methods of production and CO2 emissions, and it’s obvious that the multitude of threads that make up the fabric of global trade are delicate and vulnerable to a host of factors outside our control. 

To make the picture even more complex, extended supply chains are no longer about simply procuring and transporting ingredients, raw materials and components. The rise of offshoring and outsourcing now means that critical business functions like HR, legal, IT and even manufacturing have become an issue for Chief Procurement Officers (CPOs) who are charged with managing vastly more complex supply chains with technologies designed for a simpler age. 

Building suppleness into supply chains

Most supply chains and the technology that underpins them were designed for a much more static, slow-moving world. As a result, making even small changes is often a painstaking process requiring months or even years to register new suppliers and integrate them within the business’ supply chain infrastructure. 

That’s little use when today’s businesses might need to switch to a new source of supply – or even a different end-to-end supply chain – at a few day’s notice. The most urgent priority for CPOs is therefore to build much greater agility and suppleness into supply chains through digitisation. Not only does this streamline operations by removing paper-based processes and enabling much more rapid onboarding; it also provides the foundation for further transformational technologies such as artificial intelligence, machine learning and robotic processing automation (RPA). 

Just as important in this ecosystem of interlocking relationships is the greater visibility into, and communications with the wider network of your supplier’s suppliers, giving you a hawk’s eye view of all operations and enabling you to quickly quantify all the factors that add to your total risk exposure.

With change being the only constant in global trade for the foreseeable future, businesses must take advantage of technology platforms, that digitise the entire end-to-end supply chain, giving them the agility to keep the wheels of commerce turning, in the face of any conceivable disruption.

Reimagining relationships

Crucial as new technology will be in underpinning tomorrow’s supply chains, it will only deliver meaningful value if businesses make similarly bold changes to their supplier relationships by putting them right at the very heart of business strategy.

The increasing symbiosis between consumer and supplier means that, to get the most out of the relationship, both parties need to be much more closely aligned in areas such as strategy and even values. The impetus towards greater sustainability provides a great example: a business needs to know that its suppliers share the same commitment towards, say, cutting carbon emissions and other pollutants, or building better traceability into the supply chain.   

The successful supply chains of the future will be marked by true teamwork where each organisation in the chain is on exactly the same page – not just agreeing on quotidian matters of procurement, but sharing a common vision, strategy and set of values. In these times of ever-greater uncertainty, it is these trusted relationships – underpinned, of course, by the latest digital technologies – that provide the best chance of thriving in the Age of Disruption.

George Booth, Chief Procurement Officer at Lloyds Banking Group explores risk assurance and whether it’s become a top priority for…

George Booth, Chief Procurement Officer at Lloyds Banking Group explores risk assurance and whether it’s become a top priority for the CPO of today.

How has the perception of sourcing and procurement changed, and how the role itself has changed and become more strategic to a business?

There is no doubt in my mind that procurement has firmly established itself at the board table in most organisations as they better understand organisations compete through their supply chains. Procurement drives competitive actions for organisations in gaining first mover advantage to access supplier’s technology innovation, risk assure extended supply chains, secure value and build in sustainability. In addition, the profession has had to become very international in your outlook, understanding different cultures, working across multiple time zones where relationships skills have evolved from being able to do business face to face every day, to having supply chains and factories and clients that are global, often communicating through technology. You have to be able to adapt and evolve in that world as it’s much higher paced. Procurement leaders have to understand global macro-economic and geopolitical factors and the impact they have to the supply of your goods and services. Being a business professional, ultimately delivering through sourcing or procurement, the core skills are commercial business acumen, supply risk assessment, your ability to build and forge strong, deep relationships, your ability to manage multiple tasks, operating in a 24/7 environment.

London. May 2018. A view of the office building at 10 Gresham street in the City of london.

The sourcing skills have also evolved from looking at one or two local suppliers where you had long term arrangements, to a much more agile world where you’ve got consortium buying and many new players coming into various technology markets. All of the big established suppliers are changing, disrupted, and even going out of business, alongside many new entrants coming in. It remains a very exciting, challenging, ever evolving career path.

With constant disruption and evolution in the industry how do you stay in touch with what’s going on?

I always remain plugged into our business clients, colleagues and suppliers to understand their business drivers and what innovation is landing. I also meet new entrants in the market and I regularly go to industry forums. I’m part of the World Procurement 50, so that’s a peer group of CPOs from all different industries, all geographies, all cultures and backgrounds around the world on a range of subjects from talent, ERP technology, supply market innovation etc.

In addition,I keep tuned in, I look at Ted talks, I’m regularly on YouTube. I read a lot of industry articles, and I talk to my team. I’ve got 340 practitioners in my function, and every day there are various conferences with all the well known brands. They’re talking to my business clients, but ultimately solving customer problems. So it’s just constantly tuning in with what’s evolving, what’s changing, and understanding things like blockchain, AI, big data. What are these things and how do they impact my function?  What are the tools and activities that drive us versus how they are transforming our ultimate customer’s lives? Within that, the supply chains between us, how do we shape them, evolve them? So it’s just keeping plugged in and being rooted in the reality that the very basics of what we do remain consistent.

How do you communicate to the wider business the value and importance, and the strategic nature of procurement?

I spend half my life probably talking internally to business clients and executives, selling what we do, talking to them to understand the business problems they’re trying to solve, and giving them a sense of the value we bring. Five years ago we changed the title of our function from procurement to sourcing, because procurement had evolved out of purchasing and it was very functional and we felt sourcing better reflected that at the core of what we do, it’s all about understanding the business problems and matching them to supply side solutions vs. the businesses bringing us the answers to put a contract in place for!

Being able to speak the language of your business in the context of the customer issues they’re trying to solve, and how we go and source in a very complex supply chain environment is crucial. A lot of the procurement/purchasing practitioners were very functional in their language and approach. They would talk about a process where, “once you’ve decided what it is you want to buy, you can come and speak to us, and we’ll help you find the right supplier, put a contract in place, get you the right commercials, and we’ll help you manage that through its life cycle in terms of supply chain or supply and relationship management”.

What we wanted to do was move the dial to say, “We understand the market you’re in, and the evolving customer challenges that are out there. We believe there are solutions that are rooted in the supply chain that we can help you access and source in a much more collaborative way.”

It was all about becoming more proactive as opposed to being seen as red tape or a transactional functional role, and that’s been a massive breakthrough. We are rebranding sourcing, having much more proactive deep and meaningful, richer conversations with the business. That’s upped the game in terms of capability in the team as we need professional business people who have particular sourcing, procurement, purchasing skills, but very much as a secondary consideration as opposed to the primary of business acumen, relationship building and innovation curiosity. If they don’t understand the supply markets alongside the business markets, then they’re not going to source the best outcome.

London, UK – June 22, 2018: Low angle, looking up view on Lloyds Bank sign, branch, office in city

With a number of financial crises in recent years, how has that shaped and influenced the role of the CPO?

I think there’s always that absolute truth or truism within sourcing, that you have to deliver on your numbers, you have to deliver value and you have to deliver savings. If you do that you get to play with the business. That’s being replaced with managing supply chain risk, and knowing who you’re forth/fifth tier suppliers are, driving sustainability in everything we do. For us in financial services we’ve outsourced many banking functions over the years. That includes credit and debit cards processing, ATM maintenance, the cash that we print and issue out, right through to all sorts of very intimate customer services that we rely on others to perform. We are also increasingly leveraging SAAS solutions that are out of the box and hosted in public cloud so we are able to access the very latest technologies.

We are also more thinking about who’s got our customer data our corporate data, who ultimately services our customers? There’s the potential for customer detriment or conduct risks. We think about who’s got a permanent or intermittent connection to the group. If somebody is going to pipe into the group or connect with us through a VPN, we need to know about it to assess the cyber threat and we need to know who services our ability to constantly provide 24/7 online digital banking.

My number one priority as a CPO is ensuring that we manage that supply chain risk. We help educate our business colleagues who work with us to choose suppliers and then manage these suppliers on a day to day basis. We still deliver savings value, we still look to achieve optimal outcomes with our suppliers and we look at sustainability, we look at innovation. But of all the things we do, which is deliver value, innovation and manage a sustainable and resilient supply chain, risk is definitely the one that tops the pole right now. You just have to look at the global nature, and the depth and breadth, the complexity in interdependent supply chains to you understand the reasons behind that.

What do technologies such as big data and artificial intelligence mean to you in sourcing?

What it ultimately means to me is that it gives us the chance to go beyond human limitations in terms of compute power, knowledge and an aggregate awareness. As an example, let’s say I’m looking to solve an issue to ensure ongoing supply for our data centres. Our data centres run computation and data storage for, in the case of Lloyds Banking Group, 30 plus million UK customers. If that supply chain is in any way threatened in terms of assurance of supply or compromise, I need to be able to know who supplies the first tier suppliers we deal with. Who supplies the second, third, fourth, fifth tier?

Whenever there is an issue that arises globally, by accessing the big data available through a number of tools monitoring global supply chains 24/7, it’s possible to take effective and pro-active action to avert disaster. It can be impossible for a humans to analyse at the scale and pace we need in order to convert data into insight at the scale and pace required.

The challenge for the industry is to find the optimal blend and mix of human awareness and monitoring, coupled with the technology and what it gives us. There are huge strides being made but there are still issues in integrating it all and giving you the risk vectors down to supplier brand in the scale of what we want. There’s a lot promised, but I’d say we’re probably 50-60% of the way toward optimised solutions, but we have to keep pushing it.

It is here to stay, we’re going to become more and more reliant on it. I’m a big fan, I just wish we could get to some of the nuances being wrinkled out of it, otherwise we’re not far away.

How much do you invest in bringing your team along this transformational journey of sourcing and procurement?

I run monthly colleague engagement calls and site visits and I always bring the latest technology thinking. We invite our teams to tell the story of the technology insight they’ve gained and/or the technology breakthrough they’ve made. It doesn’t always happen within the IT teams. It’s happening more and more across the different sourcing teams. Right across my entire team we’re uplifting their awareness of the digital transformation that’s around them, because everybody is doing digital today. The key is that everyone has to develop and learn and evolve their skills so they can speak the language of the business and their supply chains and they ultimately become an even better sourcing professional.

What would you say is the key to achieving success in a disruptive marketplace?

Ensure that you remain relevant in the conversation by experiencing disruption yourself – it will be there in your supply chains, you just have to look for it.. As a procurement or sourcing professional by nature, you’re going to buy different things, some are human capital in nature, some are more physical, parts and products that you can touch, other things are more virtual like software. My advice is to understand the common language of digital technology and the digital age that we’re in, and its potential to dis-aggregate the supply chains. Think about what customers, your peers and competitors use it for, what you could use it for? What are the risks and issues with it? Ultimately, always remain agile and nimble in your approach and be prepared to rip up what worked in the past and build a new approach for the future.

By Dave Brittain, Head of Amazon Business UK It is well-known that machine learning is used today in Amazon Alexa…

By Dave Brittain, Head of Amazon Business UK

It is well-known that machine learning is used today in Amazon Alexa and other virtual consumer assistants, but it also plays an important role for businesses looking to save time and money when it comes to procurement. 

Procurement is a key player in the broader transformation and growth story for organisations, but it can be a costly exercise for both large and small companies. Companies of all sizes are looking for ways to drive cost and time savings, process efficiencies, and better control and visibility for procurement teams. For larger companies, this is particularly true in tail spend – this means all the unmanaged and seemingly insignificant purchases that often occur outside of the normal procurement processes. This can add up and accounts for 20 to 40 percent of the gross purchasing volume of a company. For smaller companies with tight budgets it’s important to find the best deals – mistakes can be costly, but the time it takes to find the best products can be costly too.

The benefit of machine learning is that it can improve efficiencies and help businesses make better procurement decisions. This is why more than 60 percent of purchasing managers and chief procurement officers are currently learning about artificial intelligence and machine learning or are currently implementing the technologies – according to a study published by Amazon Business and WBR Insights.

How machine learning can help

This is where digital technologies such as artificial intelligence and machine learning can help. The field of artificial intelligence refers to solving cognitive problems associated with human intelligence, such as learning, problem solving and pattern recognition. Machine learning is a subfield where data captured from past experiences enables learning to happen automatically. 

Amazon Business is constantly expanding the use of machine learning to automate manual and time-consuming tasks for its customers. Looking for ways to predict product trends and leverage these results to better forecast the required quantity of a certain product, which reduces storage costs in Amazon’s fulfilment centres, streamlines fulfilment processes and ultimately lowers the price of an item for customers. For consumers, but also for business customers. 

Constantly learning and improving 

Another example is that purchasing managers can submit their preferred products and machine learning can then assess this catalogue to automatically identify the same or similar items on Amazon Business and provide purchasing managers with cost effective alternatives. One more field is search. The search on Amazon Business is the starting point for most business customers on Amazon. Machine learning continually learns from search and purchasing behaviour and the provided information – and combines industry-specific parameters to identify products that may be interesting to customers. In understanding a search query, natural language processing algorithms can distil semantic information and present suitable products for the queries. In this way machine learning helps searchers obtain context-relevant results and suggests recommendations and products and suppliers that they might not have considered before. 

This ensures that products are ranked and optimised in a highly relevant way, which helps the business customer to find the item that they are looking for more quickly. 

Curated and supported shopping 

A further field for machine learning is “curated buying”. The technology helps businesses to drive process efficiencies by automatically prioritizing products that they do need and prefer based on their order history, the buyer’s budget, industry classification systems, and company-related buying guidelines provided by the business customer. In the future, machine learning could set up and apply purchasing guidelines on its own, based on the provided business goals of an organisation – and provide the required flexibility to continually adapt these guidelines to ensure that the goals will be achieved. Additionally, when it comes time to restock the products, automated repeat purchases could be made simpler by enabling a customer inventory demand to forecast and automatically reorder items on the buyer’s behalf.

Machine learning also helps to presume the needs of business customers and suggests features to help meet them – for example: considering Business Prime to save shipping costs; setting up the pay-by-invoice feature to streamline processes; or adding additional users to enable other departments to buy on their own. 

In the past, when it came to evaluating procurement data, companies would need to invest in experts such as business intelligence engineers, data scientists and IT professionals who would create complex analysis models from the data. Today thanks to machine learning procurement managers don’t need to be an expert to take complex data and build narratives – buyers can just evaluate the order history data of thousands of employees to make purchasing decisions.

At Amazon Business, we’re excited to see procurement teams enable more modern ways of working, drive greater employee and organisation productivity across the board, improve operating effectiveness, and play a key part in achieving greater business agility and velocity – from sole proprietors to small businesses, hospitals, universities, and even large enterprises with tens of thousands of employees.  

The landscape of procurement is undeniably changing. Digitalisation of the supply chain is transforming the industry and organisations should be…

The landscape of procurement is undeniably changing. Digitalisation of the supply chain is transforming the industry and organisations should be preparing themselves for this shift. 

Robotic Process Automation (RPA) removes the need for employees who are responsible for repetitive transactional, operational and administrative tasks. Not only will this have an impact in back office functions and similar set-ups, but it will also impact all levels of procurement functions. 

The conventional view is that modern technology will flip a traditionally bottom-heavy, administrative employment structure on its head, with procurement only requiring those in senior positions with strategic roles. However, this assumption isn’t really the case. Digitalisation has not only introduced RPA, but also technologies such as Artificial Intelligence (AI) and Machine Learning. These solutions are capable of replacing the roles that we deem to be higher end, such as creative thinking and negotiating.  

I’ve witnessed an AI robot read inbound emails and support negotiations with a supplier by informing the recipient of the sentiment of the email and advising on the best method of negotiation. I’ve also seen another read a 150 page contract in a matter of seconds and highlight the areas that need attention. This means that you only need to read seven clauses rather than 150 pages – very real world, practical business improvements.

The application of AI allows for complex decision making to be achieved at a much faster rate. While in the past one person could have completed ten tasks per month, now they are capable of 500. 

The constant evolution of the internet is also reducing the need for as many procurement professionals. Knowledge is a key frontier for those in the industry, as we are expected to be experts in various markets. Gaining this level of knowledge used to take years, but access to the internet means you now have a wealth of information at your fingertips, speeding up the process. This allows you to work across many varied supply markets, rather than a smaller set. Faster knowledge uptake isn’t a bad thing, as long as the quality of advice being given continues to be held to a high standard.

An ever-changing global market place is actually reducing the need for standalone procurement functions within a business. The likes of Amazon, Ali Baba and eBay have transformed the way commerce is conducted and suppliers can now reach buyers much more easily with a fully automated process. 

Buyers can appoint Amazon as a supplier for their goods. For example, a company that purchases computer technology may decide that it wants to use Amazon as its supplier for computer consumables, allowing internal users to effectively purchase these goods directly with no or minimal overhead. In this way, there is actually no procurement involved for the company, besides appointing Amazon as the supplier. This all falls under the umbrella of digitalisation, and something we’re going to see more and more of in the months and years to come.

Of course, the tendency may be to read the above and panic about the potential job losses. Yes, fewer roles may eventually be required, however procurement is still going to need to employ those with the right skills to oversee this ever more complex industrial ecosystem.

Procurement is going to become much more of a commercial function within a business, to the extent that it may not even be called ‘procurement’ anymore. It could instead be known more commonly as ‘commercial support’ or perhaps become subsumed as part of a broader commercial group focussed on suppliers and buyers. This transformed function would require two different types of people to operate effectively. 

Firstly, the increased use of technology will require digital experts who are able to analyse and run advanced technical solutions. People that will thrive in these positions will have an entrepreneurial flair to them and be able to envision how new technology can be deployed as well as implement it. They will also need to be commercially savvy. As procurement as a whole reduces its relative scale, stakeholders will need influencing by those who know their numbers. Being able to market procurement and communicate the benefits of technology to these decision makers will be essential.  

On the other side of procurement, we will need market-focused innovative experts in their spend category. These will be people who understand their spend area technically, have a vision for what the future holds and know how they will reduce costs.

In order to recruit people with these skill sets, organisations need to be looking towards younger professionals who have gained a few years’ experience within these functional areas as analysts and the like. This means placing less emphasis on hiring those with direct procurement experience. Looking towards big consultancies would also be wise, as such organisations produce technical experts who possess both commercial and sales skills.  

This is, of course, a vision of the future. However, businesses should prepare their existing talent for this shift by moving away from conventional training, instead encouraging analytics training and digital awareness. If you are a procurement professional yourself, you should be considering your personal development and what skills you’ll be able to bring to this industry of the future. This includes attending talks and conferences that don’t necessarily revolve around procurement, but instead centre on technology and digitalisation. 

Eventually, businesses will be able to almost eliminate the need for procurement through automation. Those that will survive and thrive will be the ones that encourage, promote and invest in digitalisation and the benefits it will certainly bring.

John Cushing, CEO and Founder of Qynn, explores how AI and data analytics can help companies combat the increasing challenge…

John Cushing, CEO and Founder of Qynn, explores how AI and data analytics can help companies combat the increasing challenge of procurement fraud

Protecting business and supporting growth through finding the best market rates and products has always been procurement’s main objectives. However, achieving this is a lot more difficult than it may seem. Scouring the market, conducting due diligence and compiling historic data on other companies can be very resource intensive and time consuming, particularly for small businesses. With so much to keep track of, inconsistencies or unscrupulous activity can easily go undetected during the Know Your Supplier process, which can unfortunately see companies sleepwalk into doing business with a malicious organisation or individual.

A report released by Crowe LLP, in partnership with Experian and the University of Portsmouth, revealed the annual cost of private sector procurement fraud is estimated to be £121.4 billion each year. Meanwhile, PwC estimates that nearly 30 percent of organisations have been victims of procurement fraud in the last year, highlighting the scale of the problem. 

Yet, risks exist even within a company’s own supply chain. Typically, companies have large supply chains that span multiple suppliers and contractors across the world. As such, it is very difficult for a procurement officer to get a clear view of exactly what is going on at every part of the chain. Amidst this lack of clarity and communication, a supplier could easily sell the same equipment at a higher price to one department than it sold to another. This amounts to fraud and if not stopped could cause businesses to lose thousands of pounds.

Procurement leaders need to build a complete picture out of this complex and ever-changing puzzle. Sound decision making requires insight and clarity, which is becoming easier through data analytics and artificial intelligence.  

How can analytics help?

Carrying out checks on existing and prospective business partners has never been more important. This is where artificial intelligence (AI) data analytics can provide a lifeline and an all-seeing eye into business networks. AI can harvest company information from various sources, and analyse in real-time any changes in shareholder structure, country of operations or incorporation; which can help raise red flags in a timely fashion and so reduce the opportunity for fraud. Importantly, this can be done in an instant, reducing the time and resource required by orders of magnitude compared to manual due diligence methods.

All this enables procurement teams to paint a clearer picture of where a potential supplier sits within a group structure. This can be particularly helpful when understanding whether your contract should be held further up the group structure or with the supplier itself. It can also help understand the backgrounds of individuals within the company, which is an incredibly important part of due diligence. Finding out their employment history, who they were associated with and who they have done business with can shed light on any suspicious activity and alert procurement teams well in advance. 

Further, analysing both structured and unstructured data from within the company as well as externally could also help to reduce in-house fraudulent collusion; whether as part of bid rigging, bribery, phantom vendors or split purchases. 

Having all the right data is just one half of the battle though – ensuring the right people are on board to draw out insights and act on them to combat fraud is essential. Procurement professionals still need to decide whether there are any systematic problems that have been highlighted by the data that need addressing. Does the organisational structure lend itself to fraudulent cases? Are there any changes that could be made to counteract these issues? Analytics by itself cannot answer these questions nor implement the solutions – but it can point experts in the right direction to implement positive change.

We have seen AI and data analytics disrupt industries across the world, and it is set to help procurement professionals as well. Thanks to the automated ability to identify anomalies within the entire procurement supply chain, detecting fraud will be simpler and easier for all. 

From fragmented thinking, to out of date infrastructures and poor processes, there is a long list of reasons why supply…

From fragmented thinking, to out of date infrastructures and poor processes, there is a long list of reasons why supply chains can become unsustainable. But, according to a luxury packaging provider, digitalised data is set to transform the industry in a big way.

With over 30 years’ experience in the supply chain and distribution industry, Stuart Gannon, commercial director of Delta Global, a packaging distributor in the luxury retail sector, was keen to point out the impact these digital changes might have on the industry.

“The more mindful the consumer the more analytical we have to be in our approach to truly tackling environmental and ecological issues,” he said.

“Data gives us the ability to quickly spot and react to shifts in buying behaviours and stay ahead of the game when it comes to the sourcing of raw and sustainable materials, right through to tracking and improving the last mile journey of the goods.”

Stuart went on to highlight the main benefits digitization will have on the industry as well as new challenges it will pose.

What are the benefits of data driven supply chains?

Data can enhance the delivery and distribution of goods, ensuring faster, more economic and more sustainable delivery, as well as reduce time consuming inventory taking.

“When you are data enabled, you will increase value throughout your entire supply chain. The production line becomes more customer focused and data helps us to address what’s happened in the past and flag up risks for the future.

“Better forecasting and stock control will inevitably help us reduce waste, improve traceability of goods in the manufacturing and delivery process and release any tied up working capital.

“Data can also optimise and maximise valuable assets such as waste throughout the supply chain, churning left-over materials into product such as paper handles and other accessories.”

What are the challenges?

While these revolutionary advances have clearly had a positive effect on supply chains, not everything will be quite so plain sailing.

There are fears that the automation of data could introduce new risks with no human input into the elements of the supply chain.

“Old-fashioned tracking systems and global supply chains can mean many businesses are failing to harness data in the right way.

“There are many elements to a supply chain, but without building strong and communicative relationships amongst all partners involved, brands will be restricted by their capabilities which will influence the service and product delivered to the end customer.

“Brands need to be aware of the risks false claims can have, while it is true that your end-product may be completely eco-friendly in its materials, if it was not made, sourced or delivered in an eco-friendly or socially acceptable way your risk any reputation your product once upheld.

“There are also challenges in which the flow of information can affect accuracy and speed. When dealing with global supply chains we must be alert of time-zones and how this can affect real-time data feeds if there are delays due to working hours overseas.

“We advise investing time in getting information displayed and shared in the right way which speaks to people across borders. It guarantees alignment in all functions end goal and what we are required to do in order to advance. Data should act as the fuel for bringing supply chain partners together.”

It can be hard to keep up with all of the latest developments in the world of digitalization. Particularly when buzzwords such as AI, blockchain and real-time data are dominating the technological sector.

So, what do these words really mean?

“Artificial Intelligence (AI) learns what the data means and assists how it’s used. Machine learning enables more data to be processed in one go, enabling efficiency and speed.

Blockchain is the way to secure and transfer data, whilst real-time data is the ‘now’ and is much quicker to react to.

“Heralded as the next big thing is Robotic Process Automation (RPA), this could dramatically change the way supply chains work, introducing software which can communicate with other digital systems to capture and interpret data in order to process, manipulate and trigger a reaction.

“Then there is ‘big data’. This describes a large volume of data that is used to reveal patterns and trends depicted from human behaviour and interactions.

“An example of where this is being used is in the retail industry. Here data is giving brands a greater understanding of consumer shopping habits and will make several improvements to their infrastructure and processes.

“Digitalising the supply chain is a key area where retailers can ensure they continue to attract both new and existing customers.”

How important are relationships within the supply chain?

“Strong relationships and constant communication is paramount to ensuring all partners are invested in the same end goal.

“Businesses should take a holistic approach when managing costs, improving the quality of goods and tackling the volumes of secondary packaging waste that is generated.

“We look at ourselves as consultants as well as partners, analysing the methods, materials and designs suggested by the client and then advising on how we can better the sustainability aspect.

“Whilst some brands can source a beautifully packaged product made entirely out of sustainable materials, often corners are cut during production. This includes shipping around the world during different stages of the process.

“This results in a completely unsustainable end-product with heightened carbon emissions and more waste at multiple facilities – each costing you a pretty penny.

“Data can be difficult to read and huge volumes of transactional data in the wrong format is near useless.

“The information is only as good as the data entry and only as good as the people who are looking at that data. Therefore, good communication is vital and human intervention is still required to prioritise actions off the back of what the data is telling us.”

How else do you use data?

“We interpret our data visually, not just in terms of supply chain development, but also with the brands we create packaging for. We conduct in-depth research of the marketplace, studying the audiences we are attempting to reach, building an idea of personal profiles that analyses the end-consumer – their values and what defines good service and returnability for them.

“This integration between supplier and end-consumer influences the design process and deliverability of each project and is a much more people-led approach, making our clients stand-out amongst their competition.

“Data helps manufacturers to stay ahead when it comes to tracking where a product is in production stages and stay on target to make delivery or even beat it where possible. 

“While a business must onboard costs, in the long-run these will be reduced with less waste to get rid of and more profit from newly committed customers due to smoother services and selling or utilizing waste back into the supply chain.

“By introducing data-driven supply chains, we not only focus on the sale for today, but the sale for tomorrow.”