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In this guest post, Procurement Leaders invites Tamr's Matt Holzapfel to make the case for why procurement needs to take a more deliberate, invested approach to data analytics.
Too often, analysts looking at procurement data are sent out like Lewis and Clark to explore data on foot when the equivalents of satellite imaging, geological surveys and Google Maps are easily accessible.
I talk to many procurement executives who feel fairly confident that they have spend analytics covered, but if you ask them specific questions about their plans, it becomes clear they have a macro-view at best. It's time to dispense with broad stroke analysis based on field-of-view data capture and educated guesses. It's time to take the shackles off procurement analysis.
The primary challenge to good analytics is limited data. Too often executives accept the analysis tools provided by large software suites as authoritative when they only analyze the data in that software. It's certainly the easiest path, but about as useful as monitoring the status of your car solely based on how much gas is in the tank.
Years ago, adding diverse data sets was very difficult, manual work that never promised to justify the cost of the work. Today, there is no excuse for excluding valuable information from inside your organization or outside sources just because it isn't in the same proprietary format as your procurement software. It's a solved problem.
The second biggest challenge is time. While procurement analysts have proven their value many times over, there is so much more they can do given more time. The driving question of procurement analysis is not "where are the limits?" but "what can we get to?" I've yet to meet a CFO who has determined he or she has saved enough money. There may be a point where increasing the efficiency of spend analysis does not result in better fiscal health, but we aren't anywhere near it.
The convenience of “free” analysis tools has contributed to procurement teams missing developments in data analysis. Tools and strategies that were novel in recent years have proven themselves —even by early adopters in spend analysis. Data unification is particularly relevant to procurement analysis, which can benefit from sources as varied as PDF contracts, commodity pricing, financial reports on vendors and much more. Pulling these data sources into an analysis can make the difference between reporting on outcomes and improving them.
Data unification is a two-step process that catalogs all data sources and uses that information about data to build a global reference that shows how all of the data relates to the questions at hand. This resource is typically built through a combination of machine learning and smart sourcing of human experts, and provides three clear benefits: making exponentially more data available for analysis, eliminating the biggest contributor to analysis time overhead – data preparation, and building in repeatability so any analysis that has been done can be rerun at anytime with no repeat of the data preparation.
Modern data analysis is putting procurement teams in position for big wins, including giant leaps in spend under management, and replacing general strategies (reduce stockpiles of low volume parts) with specific recommendations to save money (eliminate these three SKUs to save $2m; retire these nine contracts to save $7.3m). Data unification creates a data playground for analysts to do what they do best - find value for the company.
It's like giving Lewis and Clark an RV, weather updates and a GPS.
Matt Holzapfel is product marketing lead at Tamr.
View the Procurement Leaders Webinar: Data for Analytics on-demand here.
This contributed article has been written by a guest writer at the invitation of Procurement Leaders. Procurement Leaders received no payment directly connected with the publishing of this content.