4 Roadblocks to Strategic Spend Management

Manufacturers and distributors often begin a spend management initiative by starting a labor-intensive data-gathering project. Asking questions like What do we spend, with whom, why, and on whose authorization gives companies a better understanding how money flows through their organization and supply chain. Which materials and services, once the procurement is automated, will yield the quickest results? The fastest?

Purchasing professionals can get a clear look at how their vendors impact their spending habits. At first glance, one may think that finding the answers to these questions is easy. However, many companies have implemented division-based systems that make achieving cross-enterprise visibility a challenge. The supply chain crosses departments and silos, so only looking at one component doesn’t give companies the 360-degree view they need to achieve strategic spend management.

Here are 4 of the biggest roadblocks to strategic spend management:

Disparate Data

Data is spread across multiple, disconnected systems (e.g., Accounts Payable, Enterprise Resource Planning, corporate purchasing, eProcurement systems, and electronic funds transfers). An effective spend management strategy must support the automated extraction of 100% of spending information from internal and external business systems to provide an enterprise-wide view into supply base spending. Data must be centralized in order for purchasing professionals to make well-informed decisions based on accurate data.

Inaccurate Information

Spending data is often recorded inconsistently with errors, duplicates and misspellings, leaving a large amount of unclassified “other” spend. Imagine how much impact on your spending a misplaced comma could have, turning a vendor order from 1,000 to 10,000! A spend management strategy must ensure that spend data files are accurate and complete, as well as based on consistent data validation, cleansing and classifications adopted by the entire enterprise.

Inconsistencies in Vendor & Product Information

Incorrect naming conventions for vendors (along with erroneous or non-defined associations between a supplier’s business units or distributor channel) further corrupt the spending data pool, limiting the enterprises’ visibility into true spending patterns and decreasing negotiation leverage with individual suppliers. Single products may also appear multiple times in multiple enterprise systems, purchasing systems, e-Procurement systems, etc…and be described in different ways. This could lead to duplicate purchases that unnecessarily tie up more of a company’s cash flow.

Limited Analytics Capabilities

Research has shown that more than 80% of companies still use basic spreadsheet applications or reporting tools for data analysis, limiting the breadth and sophistication of analyses that can be executed. These types of tools do not aggregate data from multiple systems and are generally inflexible in how they capture and display information. In addition, they do not offer a repeatable process for collecting information, making it purchasing-relevant and taking into account the ever-changing dynamics of new suppliers, product designs and purchasing practices. Manual manipulation of Excel spreadsheets is usually good enough for a smaller business, but mid-to-large-sized manufacturers and distributors with complex supply chains need something much more advanced in order to properly analyze their data and uncover areas of opportunity.

These roadblocks prevent manufacturers from achieving a complete understanding of their supply base spending, making it impossible to create a savings plan or make sound decisions about which initiatives to pursue. With incomplete expense information, excess spending remains hidden, and companies are unable to capitalize on all available savings opportunities

To overcome these four roadblocks companies are now employing spend analytics within business intelligence software to better organize, analyze and manage their spending data. With these types of analytical applications, companies can achieve a 5% to 15% reduction in materials costs that then translate into a dollar-for-dollar increase in profits. BI software provides companies with the information they need to reduce purchase prices, rationalize supplier relationships, and improve the utilization of corporate contracts by decreasing (or eliminating) “maverick” buying.