Having spent the past two months knee deep in vendor demonstrations, practitioner discussions and introspective spend soul searching, I'm increasingly convinced that many of us are living in a state of denial about how beneficial spend analysis and spend visibility systems have been. In fact, I've come to believe that many are actually failing us, perpetuating an orientation of elementary sourcing cost savings strategies that often prove short-lived and are nearly always a distraction from targeting the broader cost savings and spend picture. Now, don't get me wrong. It's often possible to ascribe a very significant indirect ROI to spend tools, based on the basic savings they allow us to generate from activity after the fact (e.g., one-off sourcing initiatives, invoice audits, etc.). But I think we're missing out on a much bigger opportunity by heading down the current path we're marching on like procurement lemmings.
In other words, spend analytics tools are keeping us on life support based on the elementary savings they help generate. In rare cases, however, spend analysis efforts are changing and shaping our business outside of procurement, showing us what's truly possible tomorrow versus helping identify missed savings opportunities of the past. In short, most current spend tools are failing to help reshape the roll of procurement into a function focused as much on top-line and company transformation as bottom-line CPR. Since the Friday Rant column structure gives me an excuse call things as I see them in a more informal op/ed style, I won't hold back any punches in this series. Let's start by examining some of the reasons that spend analytics approaches and implementations are failing us. Next week, we'll continue the analysis and begin to offer up a prescription for pushing our efforts to an entirely new level.
Perhaps the most obvious failure of the current generation of most spend analysis deployments is that they're built around unit-cost orientation. It's the exceptional organization – versus the typical one – that integrates both internal and third-party information that transcends purchasing transactions to understand the total cost of what they're buying outside of unit cost. This total cost data should include such considerations as commodity pricing indices, supplier performance data, inventory data, logistics costs, etc. This lack of a broader picture leads us to superficial analyses that can help us put out cost fires (that often should have been extinguished long ago) but fails to address the hazards that require us to put up a firewall between procurement and the rest of the business.
The next area I take issue with is that 99% of spend/supply chain analysis implementations I'm aware of take a batch-based approach to data access. Honestly, given the technology that's available to us elsewhere today in the enterprise for those in the search/data access know, the thought of getting excited about "monthly" refresh rates is the equivalent of getting excited that your favorite professional sports team winning more than it loses is the be-all, end-all accomplishment (that is, unless your team is the Cubs, but don't get me started).
As I've written about before, we need to move to either a real-time approach that customer data integration (CDI) and enterprise master patient index (EMPI) type approaches enable to data acquisition and analysis or, at the very, to enable weekly (or nightly) refreshes. Maybe for periodic and basic strategic sourcing exercises a batch approach that updates data once a month or quarter is enough, but when it comes to reacting quickly to changes in the market (e.g., quality, performance degradations or raw materials price volatility in regional markets when we have an option of shifting production to suppliers in other regions) our current spend analysis systems leave us amongst the spend dinosaurs.
The last criticism I'll leave you with today is our overt focus on systems-based financial data to drive our analyses. We need to quickly move to a point where we're integrating additional internal information about what our suppliers are providing like production defect rates, warranty claims data, service level adherence, inventory requirements (to compare LCCS suppliers vs. local ones), etc. into the mix. And we need to combine these types of insights with third-party information that melds both structured (e.g., D&B, Equifax, Panjiva, etc.) information with unstructured (e.g., new resumes posted from a supplier on Linked-In, news feeds about suppliers and where our suppliers operate, etc.).
Gathering, aggregating, cleansing and classifying on-the-fly and looking at this information in a single place will be essential. But so will the actual analytics and visualization of it (another realm we're failing horribly within for the most part). Check back next Friday as we talk about what it really means to both visualize and drill into data (which are two very separate but equally important things, a fact we often forget).