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How predictive analytics enables greater insights for procurement processes

How predictive analytics enables greater insights for procurement processes

Procurement traditionally has been managed through legacy ERP (enterprise resource management) systems. These ERP systems provide few insights into business processes; in fact, they end up being the cause of—rather than the solution for—bottlenecks in the order-to-delivery pipeline. That’s because traditional procurement processes cannot analyze data in real time and provide insights to guide future decision-making. Traditional procurement essentially relies on human intelligence (with all of its imperfections and limitations) to drive performance, efficiency, and cost savings.

Predictive analytics, by contrast, collect huge quantities of data on supply chains, delivery networks, billing, and customer sales, then send this data through powerful computer algorithms that mine for insights, trends, and other intelligence. These analytics happen continuously, in real time, ensuring organizations can immediately apply them to improve performance, reduce costs, and gain maximum efficiencies. Let’s explore the specific ways that predictive analytics help businesses gain insights into procurement processes:

  • Organizations gain intelligence into their supply chains: Supply chains offer a wealth of data generated through various tracking systems, inspections, and audits. While this data traditionally was too voluminous to analyze by hand, computer analytics have made it possible to derive meaningful, holistic conclusions. Analytical tools can help with scenario planning and optimization, demand forecasting, supplier collaboration, and integrating planning into the overall organization. Ultimately, they improve supply chain performance, efficiency, and quality.
  • Delivery networks can be optimized with geoanalytics: Delivery networks traditionally have been optimized through manual test-and-adjust planning. As much as humans are able to eliminate bottlenecks and anticipate problems, human planning is inherently limited. By contrast, computer geoanalytics can analyze a limitless number of scenarios and aggregate real data from hundreds or even thousands of past delivery transactions to produce optimal recommendations for optimizing delivery networks.
  • Transactions become more focused on collaboration: The traditional approach to procurement focuses on the simple act of completing and closing transactions. Assuming all goes well, both parties walk away satisfied, but they don’t get any meaningful information on how they can improve and streamline future transactions. Consequently, most organizations simply use past transactions as a template for future transactions, oblivious to the opportunity to improve. Predictive analytics enables both parties to look at transaction data in a meaningful way, and when they do, it fosters dialogue and information sharing, which leads to collaboration and increased attention to improving procurement processes.
  • Outcomes can be traced back to individual procurement decisions: Procurement decisions are traditionally made with little accountability; managers do the best job they can based on personal experience and perhaps some limited data, but no one follows up in a systematic fashion to understand how those decisions played out. Predictive analytics enables procurement teams to predict how the individual decisions they make now will play out over the full procurement lifecycle. Then, these same analytical capabilities also let organizations compare the predictions to the actual results, further driving process improvements.
  • Predictive analytics can drive daily decision-making: The idea of taking a systematic approach to procurement is often more feasible than the reality of it. Procurement managers are human, and that means they can be opinionated, capricious, and unfocused in their decision-making, with their decision-making authority often going unchecked. Predictive analytics replaces human decisions entirely, changing the whole culture of an organization. All employees, no matter their rank, begin to ask the question: “What does the data say?” Everyone learns to trust the data because they know it yields powerful and reliable results.

Predictive analytics and big data have incredible power to drive procurement performance, and it’s easy to see why. Indeed, one study found that big data analytics led to more than a four-fold improvement in procurement order-to-delivery times. Predictive analytics offer unparalleled intelligence into supply chains and delivery networks, lead to a culture of collaboration with suppliers, enable individual procurement decisions to be scrutinized retroactively, and eliminate human error in daily decision-making.

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