The procurement industry is at a crossroads. Procurement executives are tasked with delivering value that impacts the bottom line, but demonstrating that value to stakeholders, finance and other departments is easier said than done. Almost every CPO strives to lead a best-in-class function, but how do we know what best-in-class actually looks like?
Complicating the issue further is the digital transformation organizations everywhere are experiencing, forcing procurement teams to modernize or fail. Organizations that embrace digital transformation and the enormous amount of data that comes from new technologies like machine learning and AI gain a leg up on the competition – but only if they turn that data into action. Put another way: data that fails to drive action is useless. In a similar sense, organizations that want to drive real competitive advantage – and prove it – must look beyond their own data sets. Solely relying on one’s own data to assess performance is shortsighted. For procurement leaders that truly want to get ahead – and create a best-in-class team – there’s a new strategy that needs to be prioritized: procurement benchmarking.
Static benchmarking has been available for quite some time for organizations looking to see how they stack up to the competition, but it typically requires costly and time-consuming consulting engagements, essentially putting projects like this out of reach for many organizations. These projects also usually result in static reports that provide high-level, moment-in-time pictures that become out of date before they are even finalized. However, with digital transformation making machine learning and procurement analytics more readily available, on-demand benchmarking has the potential to revolutionize procurement and change the game forever.
Imagine the possibilities if organizations were equipped to monitor performance metrics and sourcing opportunities in real time with a benchmarking solution powered by machine learning. With such technology, procurement professionals would gain on-demand insight into category performance, peer benchmarks and financial metrics, including supplier payment terms, number of suppliers accounting for 80 percent of spend, spend as a percentage of revenue, spend per employee and more. On-demand benchmarking enables procurement leaders to more intelligently and efficiently set targets, prioritize strategic opportunities and adjust their sourcing strategies to generate more value and savings.
The secret ingredients to a powerful benchmarking tool are automation, machine learning and advanced analytics. Without these technologies, extracting the data necessary to successfully benchmark against industry peers would be impossible, due to the sheer volume of data that is available at our fingertips. To benchmark effectively, procurement needs to account for external data sets like supplier information, credit ratings, currency rates, publicly-traded commodities and risk and CSR profiles. This picture is impossible to create without the help of emerging technologies.
Measuring procurement performance against industry peers is a critical starting point for every high-performing organization, but that’s only the first step. The next step, and where the real value of benchmarking lies, is acting on the insights to improve performance – whether that be spend, payment terms, etc. The great thing about benchmarking is that procurement organizations can unveil value from insights about categories that previously may not have been considered. Organizations could go into the benchmarking process with certain metrics in mind but come out with insights about a different set of KPIs that could improve.
Procurement executives are constantly looking for their next big competitive advantage, and finally, AI-driven procurement benchmarking is offering just that. In the era of Big Data, automated procurement benchmarking provides a way for organizations to integrate and analyze internal data sets with external sources and identify real opportunities for improvement. Procurement digitization isn’t going away, which is why successful organizations will embrace machine learning and data-driven technology – and turn that data into dollars.