IT Procurement’s Pursuit Of The ‘Long-Term Quick Fix’

How well companies succeed in handling their IT procurement in large part reflects on their ability to make the best technology/business trade-offs and to pick the right tool for the job. But it also requires having someone within IT and within procurement tasked specifically to serve as an architect to ensure procurement can attain the elusive “long-term quick-fix,” a recent report suggests.

“If nobody is the designated driver, then decisions are, at best, sub-optimal,” Pierre Mitchell, chief research officer at Trend Matters, noted in his report “Procurement Analytics: How to Plan (and Optimize) Your Process.”

For example, IT may have some budget that procurement may be able to access, and there might be a broader IT initiative that procurement can use to latch onto for its own purposes, he noted.

Indeed, using a multi-part analytics architecture helps break the IT/procurement logjam and provides more flexibility in vendor selections, according to the report, which breaks down the process into three different parts.

Supply data analytics

The analytic data model should not just be derived based on what the various vendors have in place, but perhaps instead it should come primarily from the efficient and effective business decisions that need to be made, according to the report. “That said, procurement-information architects should use the data models from packaged applications to help paint the “art of the possible” in terms of broader analysis,” it notes.

The process starts with defining the data model needed to provide the analytics to support specific purchasing decisions. Such models can come in different forms, such through basic spend analysis of transaction histories stored in accounts payable and purchase-order data, purchasing card feeds, supplier master data, and other sources. It also can include a supply-base analysis of supplier types, risk types, spend types, regulations and other factors, according to the report.

Other models focus on working capital analysis, payment terms such as discount and net payment dates and external supplier data. “In strategic sourcing analyses beyond spend analysis, the data starts broadening to cost types, material types, commodity codes, market indices, item codes, and a variety of user-defined (or system derived) codes for market complexity, category impact, project-specific attributes, etc.,” according to the report.

Data transformation

Once the data have been aggregated, the information has to be transformed so that it can be analyzed properly to derive value, the report notes.

“Transformation” represents the post-aggregation work where the data are cleansed, de-duplicated, enriched with external content, and harmonized before it can be properlyanalyzed. “You can certainly try to analyze the data before it is transformed, but we don’t recommend it other than to highlight the level of source data sparseness, toxicity, etc., that has to be remedied, the report states.

Data analysis

The moment of truth rests where the various users determine whether the application is providing insights needed for reporting, discovery, simulation, and other purposes.

“The idea is to provide mass democratization of the analytics to all the potential users who can have an impact and to give them the horsepower they need to truly uncover the opportunities latent within the data,” the report notes. “‘Big Ass SpreadSheets’ (the BASS system) and simple databases are certainly democratized, but (they are) not as powerful as purpose-built analytic applications with strong [online analytical processing] capabilities.”

Applying sourcing principles creates the optimal “market basket” for supply analytics. The whole point in defining the supply analytics area in these three parts is to provide flexibility in how to mix and match approaches and individual vendors, according to the report.

“Don’t create one giant ‘market basket’ of vendors and choose a ‘winner take all’ approach,” the report recommends. “Put all the applicable vendors in the hopper and then see which ones optimize the total end user priority (procurement, IT and other stakeholders) for time-to-benefit, strategic priority, adherence to standards, cost, etc.”