The roles and functions of Procurement have evolved over the decades, and it is hard to overstate the value of analytics has played in this evolution. We have seen a shift from spreadsheet-driven, manual spend analysis to automated, predictive and prescriptive data analytics. While it may seem like analytics can grant Procurement professionals a magical crystal ball, be wary of relying too heavily on data analytics, especially when those data sources are less than reliable. Let’s take a look at the benefits and pitfalls of analytics within the Procurement function.
AI-driven and automated tools have proven crucial for almost everyone within Procurement. From Category Managers applying predictive analytics to the AP team measuring cycle times to assisting strategic sourcing lock in better payment terms and discounts, when used properly analytics can build trust and confidence within your Procurement organization. But, let’s consider the foundation for predictive and prescriptive analytic models: data sets from multiple sources. How accurate is the data you are plugging into your cloud-enabled or platform-driven analytics tool? How do you verify the validity and authenticity of the data sets? It is no surprise that bad data can lead to bad decision making.
The purpose of these analytical models is to guide our decision making, and if the data we are using isn’t accurate or outdated, the results certainly will vary. Be sure you are vetting and validating your data before you begin to make decisions regarding large contracts or strategic initiatives. This may mean frequent audits or higher accountability on those inputting your data. Save yourself the frustration and hassle associated with “bad data.”
Moreover, if your team is inundated with data or analytic models, you potentially may be causing more harm than good. The same way consumers may feel overwhelmed in a super-store, so might the Category Manager with a variety of dashboard views and filters.
Establish three or four key metrics you wish to report out on and use these small sets to guide thinking or decision making before opening to flood gates. If cycle time is important to your organization, start by measuring your average contract lifecycle or average sourcing event duration to help plan any corrective action. But, spending time digging through different filters and dashboard views isn’t productive and will likely cause resistance from those providing the reporting. Also, understand how different metrics may overlap or work with one another. For example, forecasting and benchmarking are separate metrics you can report on, both help build your market intelligence and equip your team with the tools to be trusted consultative advisors for stakeholders.
While predictive analytics can provide a Procurement team with valuable insights, be careful not to rely too heavily on these insights and mistake predictive for prescriptive models. If you trust your data, then your analytics and reporting capabilities influence strategic decisions, but if you are unsure of the validity of your data sets then it is time to revisit where and how you capture your data – manual inputs, ERP systems, source-to-pay platforms, etc.
Once you are confident you are capturing and vetting all data sets, start small with key metrics and reports before applying any overly corrective actions. These strategic steps can help make the most out of your analytics and reports while avoiding any over-reliance on easy-to-use reporting features.
This article was originally published on the Corcentric Blog