Supply Excellence — Future Shock: Avoiding the Hazards of Spend Analysis

Future Shock: Avoiding the Hazards of Spend Analysis

June 14th, 2007 · by Tim Minahan · No Comments · Supply Management 2.0 Forum, best practices, spend analysis

“It all starts with spend.”

That’s how Hess Corporation Supply Chain Leader Carl Tatum summed up his company’s current supply management transformation initiative at the Supply Management 2.0 Forum in Houston last week.

Unfortunately, like most companies, Hess has relied on a mish-mash of automated tools and manual processes to aggregate and analyze its spending. This process was time-consuming and resulted in a snapshot of its spending that was limited, incomplete, and often inaccurate. “We use [a major ERP's] materials master to analyze our spend,” said Tatum. “But 75% of our spending is on services. We tried to use [the ERP's] service master but it lacks the detail we need for effective analysis.”

Worse yet, this classic case of Garbage-In-Garbage-Out (GIGO) syndrome caused concern and backlash from Hess’ supply chain team and other internal stakeholders. “The real danger of GIGO becomes garbage in Gospel out,” quipped Tatum. (I love that line. The other supply managers in the audience did too.) He adds that, if a teammate or stakeholder finds a flaw in your spend data or analysis it “leads to a real danger of them saying, `I don’t believe any of it.’”

A long time user of e-sourcing tools, the Fortune 100 energy giant aims to overcome these challenges by adopting software to automate spend data extraction, cleansing, classification, and analysis. The Web-based solution is part of a larger, integrated technology platform - which also includes e-sourcing, contract management, and supplier management capabilities - that Hess has adopted to support is transformation initiative.

Tatum is quick to point out that Hess’ approach to spend analysis is much broader than the traditional definition: “Spend analysis by itself is not enough. It’s backward looking. I want to know what I’m going to source next year and the year after that and the year after that,” said Tatum.

To illustrate his point, Tatum pointed out that Hess’ capital expenditures nearly tripled between 2004 and 2006. “If we had blindly looked at our 2004 spend and done our analysis looking backward we would have had some holes in our sourcing strategies.”

Instead, Hess is referring to its program as a “spend intelligence” initiative. Tatum defines spend intelligence as spend data that is “global, clean, categorized, and enriched with vendor-parent linkage” as well as linkage to other associated business information, such as contract details, supplier and market intelligence, and projected demand. (Tatum was kind enough to point out that this approach is an expansion upon a moniker first defined by a former Aberdeen Group analyst.)

Its newly adopted spend analysis solution allows Hess to cleanse and classify data to a common and more accurate classification schema that is currently based on material groups. (Tatum says Hess is in the process of mapping spend data to the UNSPSC schema.) Hess cross-references this spend data with market factors and its own proprietary forecasting model to determine projected demand (and future spending) up to four years out. According to Tatum, blending historical spend data with future demand projections is what is truly required to manage spend and become the “Customer of Choice” among suppliers. Considering the huge variability in supply markets these days, Hess is certainly onto something.

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