Getting Analytics Right

Chapter 4. Procurement Analytics

Matt Holzapfel

Procurement makes an excellent example of an analytics use case because, like so many analytics projects, the first step is simplifying the complexity and cutting through a vast quantity of data. Data-complexity problems are particularly large in procurement because procurement interacts with every function in an organization and must analyze internal and external information to be effective. Fortunately, the reward of effective procurement analytics is large, as improvements in procurement performance have an immediate and direct impact on profitability.

Defining Analytics for Procurement

“Are we going to be predicting commodity prices?”

That was the first thought that came to my mind when my manager told me he wanted my help to build the analytics capabilities of our sourcing team. I had a tough time understanding how we would use analytics when so much of my job involved negotiating with suppliers and debating internally which supplier should win an RFQ.

After a lengthy conversation with my manager, I realized he was struggling with an overwhelming amount of complex information being sent to him by suppliers and colleagues—from lead-time reports to technology roadmaps. He didn’t need someone to help him predict the price of copper. He needed help simplifying the information flow so that he could make decisions more quickly and confidently. In other words, analytics weren’t supposed to replace the need for judgment, they were an enabler for making better decisions.

This chapter will explore a few of the ways analytics can be used to help procurement leaders make better decisions.

Starting with Analytics

Mike Tyson famously said, “everyone has a plan until they get punched in the mouth.” In procurement, everyone has a plan until suppliers decide to raise prices.

Sourcing managers start the year with a good sense of how they’re going to achieve their savings goals. Unfortunately, things don’t always go as planned. One painfully memorable experience came when I ran an RFQ on one of my company’s highest-volume products. I expected the RFQ to follow its historic pattern—initial prices might be 5–10% above our target, but with some negotiation, final prices would reach our target. Instead, initial quotes came in 40–50% above our target. Despite our best efforts, we weren’t able to get close to our price target, threatening our ability to meet our annual savings goal.

We had to throw out our plan for the year and quickly devise a new plan for bringing down costs somewhere else to make up for the price increase. The number of options were overwhelming. Do we bundle spend on other product lines to get better pricing? Do we dual-source more components to put pressure on suppliers?

Fortunately, we made significant investments in our analytics capabilities and could estimate the impact of each option before making a decision. This saved us from chasing insignificant opportunities, and helped us identify opportunities that we had been neglecting. Further, it taught us the importance of having a holistic plan for sourcing, instead of relying on the same behaviors to continue to produce the same results.

Analytics Use Case 1

Estimate the impact of strategic sourcing initiatives and prioritize appropriately.

Procurement teams that start the year by analyzing a variety of cost savings opportunities, before making prioritization decisions, put themselves in a great position to achieve their goals. The number of possible initiatives a procurement team can prioritize is high; and this problem is exacerbated by a constant inflow of email from colleagues and executives with ideas on ways to improve.

Procurement teams that make data and analytics a core part of how they prioritize decisions benefit from having a roadmap they can share internally, that outlines when they will be tackling opportunities in their spend. This has the dual benefit of deflecting one-off, and potentially distracting requests, while establishing procurement as a thought leader in the company.

Using Analytics to Do More with Less

A comprehensive study done by AT Kearney in late 2014 showed that 75% of procurement organizations have not improved their productivity since 2011. This seems hard to believe given procurement’s constant push for efficiency gains, declining commodity prices, and the rise of technology designed to make businesses more efficient. This is especially troubling with sales growth stagnating at the world’s largest companies.

One reason for this slump is that spend is becoming more difficult to analyze. Record levels of M&A and the growth of outsourcing have significantly increased the number of data sources and variety of data formats needed to gain full spend visibility. As a result, many organizations struggle to answer basic questions like, “how many suppliers do I have?,” and “what’s my spend per category?”—let alone answer more complex questions like “what’s the impact on my spend if the price of steel rises 10%?” If procurement teams are going to be able to do more with less, they need to be able to answer these questions quickly, so that they can spend less time debating decisions and more time acting on insight.

One of the biggest opportunities missed by sourcing teams without full spend visibility is cost savings in the long tail of spend. The average organization has only 55–60% of its spend under management, while best-in-class performers manage close to 85%. If we assume a procurement organization can achieve 5–10% savings on spend that it brings under management, then bringing an additional 20% of spend under management can lead to an additional 1–2% of total annual savings on all spend.

Managing more of this long tail spend is often an analytics problem. Sourcing managers can’t manage this spend at the same level of depth as their top spend items, and must instead rely on analytics to help them identify savings opportunities, such as removing a category from their budget, outsourcing the management of the category to a third party, consolidating the supply base, or aggregating bundles of spend into a single contract. Sourcing leaders should dedicate their most data-driven sourcing managers to get this spend under control by using analytics that help answer critical questions about their long tail spend, such as “why are we buying these items?” and “can we be solely focused on cost?”

Analytics Use Case 2

Reduce long tail spend by identifying categories and suppliers that can be removed, consolidated, or offloaded.

Luckily, sourcing teams don’t need to solve this problem alone. Spend analytics solutions from providers such as Tamr, Rosslyn Analytics, and Opera Solutions can pull information from across many different types of internal and external sources—from ERP and Excel to third-party financial databases—and standardize this information to make it easy to spot spend overlaps or supply chain risks. This means procurement leaders no longer need to wait for IT to consolidate technology infrastructure, to reap the benefits of clean, consolidated spend data.

Getting a Voice at the Table, Through Analytics

The term “strategic sourcing” has permeated the procurement function for the past 20 years, but is often hard to describe and even harder to achieve. A survey of Chief Procurement Officers (CPOs) conducted by Deloitte in 2014 showed that 72% of CPOs rated their procurement functions as having mixed or poor effectiveness as strategic business partners. One reason for this deficiency is that strategic sourcing requires managers to have a holistic view of their business, one that goes beyond procurement.

In addition to spend data, strategic sourcing managers need on-demand access to information such as commodity trends, product quality data, supply data, and sales performance. On-demand access to this data is essential for procurement to serve as a trusted advisor to engineering and finance, and be viewed internally as an important strategic function.

A strong relationship between engineering and procurement for direct spend is essential to delivering a great customer experience. If engineering has too much clout, it can be impossible for procurement to maintain the respect of its suppliers. For example, the suppliers who recognize engineering’s power will spend their time catering to all of engineering’s needs, knowing they can charge whatever prices they want.

Procurement can mitigate this risk by serving as strong partners for engineering. This includes engaging with engineering early in the product design cycle to inform them of key cost trends that could impact how they design the product. This also includes sharing detailed, fact-based supplier scorecards so that everyone has the same understanding of supplier performance and can make decisions that optimize the entire product lifecycle.

Analytics Use Case 3

Provide fact-based insight, such as cost trends, that can influence design decisions and position procurement as a trusted advisor for engineering.

Procurement should also be looking for ways to enhance its relationship with finance. Procurement teams who successfully create value for their finance colleagues enjoy the benefits of seeing increased investment in the procurement function and are given more input into strategic decisions. Two ways procurement can improve this relationship is by communicating cost forecasts, even if they are only directional estimates, and staying ahead of trends in technology and third-party services.

The idea of cost forecasting sounds intimidating when so much of a company’s spend relies on a wide range of factors. For example, the amount a company spends on travel is influenced by the cost of travel as well as the amount employees need to travel. Both of these factors vary with the global economy, the health of the airline industry, commodity prices, and the company’s priorities. The key to simplifying this exercise is classifying spend at a granular level. It’s extremely difficult to identify patterns in “travel and entertainment” costs. If spend is classified into more detailed categories, such as “air travel for a conference” and “air travel for a customer visit,” it becomes easier to understand the drivers of spend and to forecast future spend.

Analytics Use Case 4

Forecast costs using a granular level of spend classification.

Another way procurement can become a better partner for finance is by monitoring trends in technology and third-party services. This enables procurement to advise finance on how to budget for these products and services in coming years. It also helps procurement and finance have better conversations with colleagues about the impact of purchasing these products or services, so that money is used most effectively and colleagues begin to think of procurement as thought partners instead of red tape.

Procurement teams looking to improve their relationships with finance and engineering must make it a priority to think about their business holistically. This often requires behavior change, as lower importance procurement initiatives must get deprioritized to make time for preparing information that is valuable to other functions. Fortunately, the reward for being a good partner can be significant. Procurement teams who successfully establish themselves as strategic business partners to finance and engineering enjoy the benefits of being judged by more than just the savings numbers they report and get to take part in strategic discussions about the future of their companies.

Procurement Analytics as a Starting Point

“Getting analytics right” in the context of procurement means using analytics to simplify the vast amount of complexity inherent to the function. Other functions in an organization suffer from these same problems, and solving them for procurement first can serve as a blueprint for other functions. Further, improving the analytics capabilities of procurement can drive immediate cost savings, which can be reinvested into other areas of the business to improve their capabilities.