Supercharging Spend Analytics

Companies with advanced sourcing and procurement strategies are using spend analysis tools to drive bottom-line savings. Now it's time to take spend analytics to the next level


Kirk Peterson offers a straightforward explanation of why his company, Owens Corning, sees value in arming its sourcing and procurement executives with spend analysis tools. "The company would much rather have our sourcing people acting on data rather than digging for data," says Peterson, who is e-sourcing project leader with the Toledo, Ohio-based manufacturer of glass and composite materials for the building products and industrial materials markets.

Tools Not Widely Used

Spend analysis tools have been around for several years, riding the wave that brought e-procurement and e-sourcing solutions into the spotlight at the end of the 1990s. But analytical tools still make up only a fraction of what Boston-based technology consultancy AMR Research has estimated to be a $2.0 billion market in 2005 for procurement and sourcing solutions, and benchmarking data suggest that many companies are not employing spend analysis solutions.

Atlanta-based business advisory firm The Hackett Group, for instance, has reported that just 40 percent of world-class companies — those rating in the top 25 percent in terms of efficiency and effectiveness — have the necessary reporting tools in place to enable them to do spend analysis, and only half of those top performers have the ability to view spending data by supplier across the enterprise's total spend. Below the level of these world-class organizations, even fewer "average" companies are using spend analysis: Hackett found that "average" procurement organizations are less than half as likely to be using sophisticated tools for spend analysis as their world-class counterparts.

The primary function of spend analysis tools is to tell a company how, where and on what it is spending its money, and as Kirk Peterson suggests, much of the value of these solutions derives from their ability to automate the collection, cleansing, classification and reporting of spend information. This automation alleviates sourcing and procurement staff of the task of manually assembling the data from various systems across the enterprise, a time-consuming, labor-intensive process that frequently involves bringing in staff from the information technology department to structure and run reports from multiple enterprise systems. Kirk Peterson says, for example, that Owen Corning's adoption, in March 2004, of the Emptoris Spend Analysis Module (itself part of the Emptoris 5 solution) has allowed the manufacturer's sourcing staff to obtain, in minutes, information about the company's $3 billion-plus spend that previously might have taken months to pull together. "With this tool, the information really is at your fingertips," Peterson says, noting that the Emptoris solution is getting data feeds from Owens Corning's SAP enterprise resource planning system, as well as J.D. Edwards and MAPICS systems running in individual business units.

Mittal Steel Eyes Visibility

This ability to pull together data from a variety of systems makes spend analysis solutions particularly useful for companies that have grown through merger and acquisition, bringing numerous back-end systems into a single enterprise. Case in point: Rotterdam, Holland-based Mittal Steel Co. N.V., the largest steelmaker in the world, with revenues of over $22 billion in 2004. Caspar Vrensen, a business analyst with Mittal Steel, explains that his company has grown through a series of acquisitions during the past 25 years, creating a global concern spread across continents, languages, cultures and currencies. Not surprisingly, the company's 36 production units and 10 mine operations in 14 countries use a variety of back-end systems. This created two challenges for Mittal Steel's staff as they worked to analyze the company's substantial global spend: first, collecting data from all of Mittal Steel's geographically dispersed units in a timely manner, and second, comparing data that might come in different units of measure, formats, currencies or nomenclature, depending on the information's country and system of origin. "Bringing it all together took us so much time that in the end we were simply not able to do the analysis," Vrensen says.

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