Procurement Data Standards Can't Rely on Duct-Tape Solutions
Stopgap. Jury-rig. Makeshift. And yes, quick-fix. When you find yourself in a bind, you’re sometimes tempted to opt for a fast and easy solution that offers the prospect of almost instantaneous relief. There’s nothing so terrible about the concept of a quick-fix — until you forget that this is only a temporary remedy that isn’t going to address the underlying problem.
In the context of supplier data management, there are various types of “quick-fixes” that can tempt procurement organizations when they realize that poor data is causing them to make ill-informed decisions. An example would be manually editing data ad-hoc in a report or dashboard to produce a specific intended result. Data quick-fixes, including corrections done outside proper protocols, can later introduce potential disruptions in data processes and procurement analytics. What happens upon the next refresh of the report or dashboard? Is the team now stuck relying on manual steps in the future?
Big problems — and major costs — can emerge when a temporary solution is left in place long enough to appear to be the actual solution. A leaky pipe in the basement, taped shut, might be enough to stop the flow of water until a trained professional attends to it. But if you decide that a taped-up pipe is good enough to stop that leak, don’t be surprised if one day soon you’re waking up to a flooded basement.
Procurement Data Management: The Struggle Is Real
This is not to downplay the magnitude of the data management challenges procurement teams face. In Dun & Bradstreet’s recent survey of CPOs and procurement leaders in the United States and United Kingdom, fully 97% of survey respondents indicated that management of supplier data is an area of struggle for their teams. Nearly a quarter of respondents said that inconsistent or inaccurate data is one of their biggest challenges to operational efficiency. And 40% indicated that their 2021 plans for improving supply management operations would include a data quality improvement initiative.
Other authoritative sources echo these messages about procurement and supply management data value. According to one report from Deloitte, the single most cited challenge for mastering digital complexity was poor master data quality, standardization, and governance, at 60%.1 This was followed by the inability to generate procurement analytics and insights across systems, cited by 40% of survey participants.2 One could argue that these are serious manifestations of pervasive data quick-fix overdependence.
Here are some of the main hazards (or costs) from data quick-fixes that you might already be facing, regardless of whether your focus is on direct or indirect procurement:
Deficient Sourcing Process
The foundation of an efficient and effective sourcing operation is a reliable supplier selection process. The market and its players are in constant movement, and your suppliers (current or potential) are no different. Which of these companies are still in business, experiencing M&A or divestiture, or have shut down operations? Your supplier selection data is the lifeline of your sourcing success.
Here’s an example: you’ve been relying on one vendor for your logistics needs. For years, your organization and this vendor have functioned almost as partners, and they’ve become an integral part of your operations. What happens if your main competitor acquires the company? How unprepared will you be for this event?
But imagine if you have your vendor master externally refreshed periodically — perhaps once a quarter — with firmographic, trigger, news, and ownership data. You would have received the triggers of impending M&A discussions, gaining time to line up possible replacements and initiate a vendor replacement process at scale.
Incoherent Spend Management
One of the fundamental responsibilities of procurement is to manage spend and contribute to the enterprise’s cost savings goals. These goals are already in jeopardy if the organization is taking shortcuts to avoid investing in data quality and establishing data governance standards.
In one Massachusetts-based software company, the procurement team is tasked with managing digital tools being purchased throughout the company by various groups and/or individuals. Procurement receives no data on these vendors until after the purchases. The players in this space are typically new and do not exist in procurement’s manually-managed vendor list.
Because of this slapdash approach to data governance — which does nothing to promote procurement’s potential role as a strategic partner with senior management — the company is missing the opportunity to address its needs and vendors at enterprise scale, such as by consolidating licenses, contracts, and purchases. This is a clear-cut case of data quick-fix tactics undermining cost avoidance efforts and ultimately hurting margins.
Feeding the Competition (Unknowingly)
Understanding company hierarchies (organization ownership structures) has very real applications in the procurement world. Using second-rate data that doesn’t provide this visibility presents risks not only to procurement management but also potentially to enterprise strategy and image. As a procurement leader, do you know who you’re purchasing from? Of course, the name of the vendor is in the purchase order. But do you know who the owners or the parent companies are? Large conglomerates may own several large companies and perhaps more companies underneath them. Have you analyzed your vendor master to understand the true destination of your accounts payable transactions? With quick-fix tactics, you might not have a scalable way to know if any of your competitors are on your vendor list through their subsidiaries.
Data Security Risk
Procurement has an important role to play in helping the company enforce compliance for both internal and external data security policies. Actively maintaining a vendor list that would need deeper scrutiny with ever-changing data policies would be a challenge with quick-fix tactics.
One procurement manager noted that through “dumb luck,” her team found several purchase orders for a company whose data transfer policies had been red-flagged by her legal department. She observed that an active vendor management process using comprehensive and continuously updated data would have saved her and her colleagues “unnecessary heartburn” from this event.
ESG and Supplier Diversity Goal Attainment
Using ESG (Environmental, Social, Governance) as a business metric isn’t just a trend; it’s increasingly being recognized as a source of competitive advantage, not simply a way to encourage greater social consciousness in commerce. There is a demonstrated correlation between a company’s ESG rankings and its overall performance. This is valuable information that can be used strategically to make better business partnership decisions.
Procurement and supply management leaders are especially well positioned to capitalize on ESG data and metrics to make supplier networks stronger and more resilient. But using this data to drive sourcing and procurement programs can be risky with data collection processes that don’t scale and rely on quick-fix methods that yield incomplete or out-of-date data. If this is your situation, you won’t just fail to meet enterprise goals related to corporate social responsibility — you’ll sacrifice an important opportunity for value creation and direct contribution to top-line growth.
When we speak about the dangers of data quick-fixes for procurement and supply management organizations, we’re really talking about removing a significant obstacle preventing these organizations from becoming truly data-driven. There’s a data journey that all businesses must embark upon sooner or later if they’re going to embrace transformation, foster continuity and succeed amid stronger competition than ever before. This journey is inevitable if a company aspires to reap the full rewards from digital tools such as artificial intelligence and machine learning; before these can be fully enabled, the business must accept a cultural shift where data is concerned. Data governance matters, and so does data quality.
Dun & Bradstreet helps procurement and supply management organizations at all stages of the data journey to build their analytic capabilities to better manage risk and ultimately create more value for the business — not just in terms of its margins but also its reputation as well as its legal standing.
1 Deloitte Insights, “Complexity: Overcoming Obstacles and Seizing Opportunities: The Deloitte Global Chief Procurement Officer Survey 2019,” p. 32. Retrieved 7 June 2021 from https://www2.deloitte.com/content/dam/insights/us/articles/2019_CPO-Survey/6267_CPO-Survey-Collection-Page/DI_CPO-Survey.pdf