Why Procurement Optimization Must Go Beyond Spend Analytics

Today’s modern, digital-first corporate has procurement expectations far beyond what the average business would have had only about five years ago. Like so many other areas of the enterprise, initiatives to optimize procurement activity have only taken greater precedence in the midst of the global pandemic.

As a high-spend business function, procurement is embracing the opportunity of data analytics to understand spending patterns and identify potential areas to cut costs. But analytics technologies can — and must — go beyond spend assessments in order to meet the rising demands of corporates navigating market volatility and supply chain disruptions.

Johan-Peter Teppala, CEO of Sievo, recently told PYMNTS why analytics solutions have to go beyond spend, and beyond simply providing insights into past trends, in order to add true value to the enterprise.

Accelerating Optimization

According to Teppala, even before the pandemic, corporates had begun to press forward with efforts to optimize procurement operations by ensuring their spend remains controlled, vendors become strategic partners, sourced products meet their standards and workflows are as efficient as possible.

With the COVID-19 crisis, supply chain disruptions and cash flow crunches have intensified that effort, with a particular focus on mitigating risk and volatility.

“Before the pandemic, we already saw a lot of interest toward more active risk management, but the pandemic boosted that even further up,” he said. “Savings [has stayed] on top of the procurement agenda, and an economic downturn has even increased the need for tools to manage a savings pipeline, and measure savings achieved.”

Data analytics technology is key to understanding those spend and savings patterns, and for organizations in the midst of disruption, having access to those insights is even more important. As Teppala noted, even in the case of mergers and acquisitions (M&As), organizations aren’t settling for sluggish procurement analytics.

“If five years back companies settled for six-months’ grease time before having access to the data of the new company to start synergy projects, today, the expectation is to have this in place on day one,” he said.

Beyond Cost Savings

Procurement’s impact on the bottom line will always remain at the top of organizations’ priority lists when it comes to how they unlock value from procurement data. Yet Teppala emphasized that today, the need for insights into spend patterns is far from the only analysis businesses seek.

While spend analytics are “cornerstone,” firms also need to “look much deeper into their data than just spend to find optimization opportunities,” he said.

For example, while it’s valuable to understand how much spend has been attributed to commodities procurement, what’s even more valuable is understanding how commodity price volatility on the global markets has affected overall spend in the last year. At the same time, not only should organizations focus on spend, but also expand the power of their analytics technologies to offer actionable insights and guide decision-making.

Understanding commodities’ price fluctuations “is great,” noted Teppala, “but what you really should be after is: how will the future development on those external factors affect me going forward? And how should I prepare?”

For this reason, organizations need to expand the scope of their procurement analytics technologies to include both internal and external data, which can offer valuable views into how businesses are spending money and on what, as well as how trends outside of the enterprise should affect or guide procurement activity in the future.

This is one of the largest challenges for businesses, because while the availability of both internal and external data is on the rise, being able to bridge the two together isn’t always clear-cut.

“Think, for example, supplier risk information,” said Teppala. “You can easily get supplier risk scores to suppliers you are doing business with, but how do you assess the impact of that risk to your supply chain without your own data?”

Driving Bottom Line Impacts

Spend analysis isn’t the only way procurement data analytics tools can affect company bottom lines. By mixing internal and external data, and by expanding the scope of metrics assessed, businesses have the opportunity to bolster their bottom lines in far more ways than before.

With a focus on understanding which decisions to make today in anticipation of the future, procurement teams have the chance to optimize their payment terms or and timing with strategic suppliers, or become proactive at switching vendors or products based on external market factors.

According to Teppala, the pandemic has already begun to separate the market leaders from laggards when it comes to procurement analytics, revealing which organizations have been able to take advantage of “turning data into actions” the fastest.

Everything from commodity price fluctuations to negotiation with suppliers can affect the bottom line and unless procurement analytics goes beyond spend analysis, businesses will fall short of their optimization goals. Equally important, said Teppala, is that key decision-makers within the enterprise are all on the same page — a feat only attainable through access to timely, holistic data.

“If an organization does not have a single source of truth for the numbers, people form their own views by collecting data in their own way from their own sources,” he said. “They form their own view based on ‘their’ number, which can significantly vary [based] on what others in the organization might have been looking at.”