There can seem like there is a significant gap between the rhetoric that big data analytics will unlock the secrets of efficient, optimised, resilient procurement, and the reality: that the process of leveraging procurement data into positive business outcomes is a lot more fraught than expected.
Procurement sits at the intersection between the business and its upstream supplier ecosystem. For this reason, the function has access to more (and potentially better) data than many other parts of the business. However, according to a report released last year by SpendHQ, 79% of non-procurement executives lack confidence in using procurement data to make strategic decisions.
The issue doesn’t lie with CPOs, who on the whole understand the importance of accurate data. The problem is that the industry as a whole is clearly grappling with ensuring that procurement’s data is reliable. Not only does procurement data struggle with the reliability of its data, but this issue also undermines the efficiency with which it’s used. Here are 3 actionable steps procurement leaders can take to make better use of their data.
1. Identify trustworthy data sources
Procurement has access to vast amounts of data—from suppliers, from the business, and from within its own records. Used together, this information can create meaningful advantages. Data-driven analytics can drive more efficient decision-making, identify potential disruptions ahead of time, and help manage the supplier ecosystem. This process is often more complex in practice than in theory, however.
Data within the organisation often becomes siloed between departments. A worrying majority of procurement teams still use solely email and spreadsheets to handle the RPF process, supplier management, and purchasing—siloing huge amounts of data. Lastly, the supplier ecosystem is famously opaque, with a 2023 survey of CPOs by Deloitte finding that fewer than 3% of procurement leaders felt they had “high visibility” beyond the first tier of their supplier network.
CPOs hoping to make better use of their data must first adopt a comprehensive data organisation and quality control policy. When successfully implemented, such a policy ensures information can be trusted and subsequently acted upon.
2. Look at the big picture
Leveraging data requires a comprehensive top-down view of said data. Procurement analytics dashboards are vital tools that provide real-time insight into spending patterns, allowing procurement to manage and understand spend.
By providing a comprehensive overview of spending details, such as the parties involved, items purchased, reasons for spending, locations, and timing, these dashboards enable procurement teams to negotiate better with suppliers and collaborate internally on cost-saving initiatives.
3. Automate repetitive, high volume activities
When applied to a comprehensive, reliable dataset, machine learning is an effective procurement augmentaiton tool. The technology excels at automating highly repetitive activities that consume the most time for procurement teams. Not only are these types of task time consuming, but their repetitive nature makes them the type of work most prone to human error.
AI and machine learning are very good at simple procurement tasks like cost comparisons, tracking raw material prices, and predicting how small changes will affect the larger landscape of the supply chain.
