Getting the Most out of Your Business Intelligence

By Editorial Staff

Procurement solutions have existed for static commodities for some time, but only in the last dozen years has technology enabled the automation of the extraordinarily complex services procurement category, also known as human capital or contingent workforce management. The combination of the complexity of this category and the relative novelty of solutions for services procurement has meant that business intelligence (BI) capabilities to support strategic purchasing of temporary and project labor have lagged behind the well-developed BI capabilities served up as adjuncts to static commodities procurement solutions.

“It’s not that most services procurement providers haven’t claimed to offer business intelligence as part of their solutions,” says Elliot Owens, BI director at ProcureStaff, a global services procurement solution provider. “Rather, most providers tout their internal benchmarking and reporting capacities as a BI solution.”

The problem with this approach, according to Owens, is that while internal benchmarking is a fundamental element of a robust BI offering, it stops well short of providing the broader context that enables an organization to make market-informed purchasing decisions supported by statistical evidence. Linear reporting of historical data is not a surrogate for statistical, predictive and interpretive analysis, Owens says. Beyond the obvious infrastructural requirements of this kind of analysis, true BI requires a comprehensive understanding of the business drivers within the services niche and a foundation of statistical expertise to guide the most effective “slicing and dicing” of the data collected.

Businesses Don’t Operate in a Vacuum

To better understand why it is an ineffective strategy to rely on business intelligence based solely on internal, transactional benchmarking and reporting, imagine that your organization’s human capital procurement program is a competitive swimmer alone in an Olympic pool clocking his time for the 100-meter freestyle. As he continues to practice the 100 meters, the swimmer keeps track of improvements in his time and his confidence is boosted as he can clearly measure the seconds he shaves off his personal best. His improvements may appear dramatic to him and imbue him with a sense of accomplishment. But the swimmer might be bitterly disappointed when seven other swimmers enter the pool and each completes the 100-meter freestyle at times well below our solo swimmer’s best. While our swimmer may have dramatically improved his time, he is still behind his competition. Once provided the ability to measure his rank relative to the others in the pool, he can truly work towards achieving competitive time.

Similarly, most services procurement solutions provide an organization with the ability to view progress in terms of rate savings, supplier performance, fill times and a host of other metrics contrasted against their own past performance. But these improvements occur in a vacuum because they are not contrasted against true, best-in-class market data. As services procurement has grown into a mature industry, procurement organizations are beginning to realize that internal benchmarking and reporting are simply the first step in achieving best-in-class rates, candidates, fill times, compliance, etc. It is becoming clear to procurement organizations that they have not achieved true BI.

Owens explains: “Intelligence is transitioning from a ‘nice to have’ to a ‘must have’ element of the modern human capital solution. Especially in the face of extraordinarily difficult economic times as companies are grappling with unprecedented financial challenges, it is critical to identify opportunities for cost savings and efficiency improvements using the best possible tools. The ability to be strategic in the administration of contingent workforces is one such opportunity, and I think we will see more and more providers attempt to satisfy this critical business requirement.”

Boris Evelson, principal analyst at Forrester, agrees. In a July 2008 Forrester report titled “The Forrester Wave: Enterprise Business Intelligence Platforms, Q3 2008,” Evelson writes: “With most products and services being highly commoditized, more and more businesses are competing on analytics. Getting better insight from information based on richer data sets, more complex models, or even making the same decisions as everyone else but before everyone else makes them — this is how most advanced enterprises compete in today’s world. Business intelligence tools and technologies form the major components of the foundation that supports and enables such competitive differentiation.”

More Data for Better Intelligence

As an example of how he sees BI solutions developing, Owens points to the business intelligence solution that he and ProcureStaff have spent the last five years developing to help their clients measure results against the market at large and, through expert statistical analysis, make strategic planning decisions. Owens and his team have developed a data warehouse (DW) and spent the last five years populating it with anonymous program data from the dozens of Global 1000 companies that use ProcureStaff’s services procurement solution, a managed services program (MSP) that includes their Vendor Management System (VMS) application.

Aggregating the data from every program in the DW along with external market data from various industry sources allows Owens’ team to provide each client with a more accurate understanding of how their individual program performance stacks up against the broader market. This aggregation, Owens says, is the key to enabling companies to view their metaphorical swim times against those of other companies in the market. The question for a procurement officer is no longer, “How much less did we pay this quarter for IT project workers than last quarter?” The much more pertinent question enabled by the warehousing and analysis of aggregate data becomes, “How close is the rate we pay for IT project workers to true market rates?” The difference could add up to millions of dollars saved each year.

Owens suggests several reasons why more services procurement providers have yet to commit to developing the kind of BI offerings that ProcureStaff offers. For most, it comes down to expertise. Building a data warehouse is itself a difficult task, and populating it with cleansed data is extraordinarily time consuming and perhaps cost-prohibitive for some companies. The work involved in normalizing the data collected from dozens of programs across numerous clients in disparate industries is a daunting task.

“It’s not as easy as simply compiling the data in a warehouse and then slicing it to provide reports,” says Owens. “The data must be cleansed and classified for analytical purposes, and that process requires expertise in human capital.” He explains that it’s not as simple as mapping what one organization refers to as “Programmer Level I” to another organization’s “Application Developer Level I.” Job categories and titles used by different companies are incomplete at best and often over-generalized or inaccurate.

Furthermore, the individual business practices of each company are varied, and these too must be cleansed to avoid incongruent comparisons and flawed analyses. Supplier performance analyses will be skewed if not based on statistically validated metrics and unless the situations being measured do not truly reflect the actual performance of the supplier. For example, simply dividing the number of candidate submittals by the number of orders a supplier receives does not yield a valid metric. Measuring a supplier based on contractors provided through an approved pass-through arrangement (i.e., corp-to-corp or payrolled contractors) will yield invalid results not reflective of true supplier performance. Deep domain expertise in services supply chain practices – understanding how contractors are sourced and how the orders are conducted – is as important to executing BI as expertise in statistics and data management.

Owen’s BI process automates the extraction and cleansing of transactional data from the VMS and loads them into the warehouse automatically. Thus, the data enter into the warehouse according to consistently verifiable protocols, regardless of how each individual client organization refers to a position and/or sources a candidate. After this entire process is complete, Owens and his team keep a vigil for “red flags” or anomalous outliers that trigger the deeper analyses yielding potent BI product.

Once the proper infrastructure outlined above is in place – including the data warehouse, access to aggregated data for external benchmarking, and the data cleansing practices – then a company is well on its way to achieving true BI capabilities. Yet Owens asserts that leveraging a highly valuable BI solution for services procurement requires more than just the technology infrastructure and related processes. Professionals with experience in the areas of statistical analysis as well as deep knowledge of human resources and procurement practices are required to transform all the information available in the warehouse into intelligence that provides actionable decision support. Monitoring the information flow for anomalies, performing statistical analyses, extrapolative forecasting and predictive modeling are the ultimate ends to all the aforementioned means.

Few supply chain solution providers today offer these kinds of external benchmarking capabilities in their BI solutions. But procurement organizations are beginning to realize the enormous savings potential and obvious necessity of BI for services procurement, and as demand grows, more providers are likely to follow in the footsteps of innovators like Elliot Owens and ProcureStaff.

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