Avoiding the Big Bang Backlash of MDM Implementations

Taking an evolutionary approach to deploying master data management ensures clear, incremental value, and spend analysis can be a perfect launching point


First, let's define spend analysis and why it's important.

Spend Analysis: Taking the Pain out of Procurement

A report by industry research firm Aberdeen noted that CFOs believe corporate procurement suffers from a lack of clear visibility into spend across various commodities, factors that hurt corporate competitiveness by preventing procurement from driving strategic initiatives such as supply base rationalization or commodity normalization. Spend analysis can be the remedy. Put simply: Spend analysis entails taking the existing information that companies track in the form of invoices, purchase orders and receipts and "cleansing, normalizing, categorizing and enriching the data," as marketing research firm Forrester Research defines the process. After doing so, companies will be better able to find sourcing opportunities that reduce cost, track non-compliance with purchasing policies and improve data management. With this approach, businesses could save 2-6 percent of their total spend by improving the way their procurement organizations secure products and services, according to both the Aberdeen Group and AMR Research.

The reasons why businesses fail to collect accurate, useful procurement information in the first place is not a lack of tools and applications to manage spend. The heart of the problem is data complexity, and that is exactly what an MDM strategy sets out to solve. For example:

  • Different codes are often inadvertently used to describe the same supplier or item across divisions or even within the same division, making the broad set of data seem inaccurate when it is analyzed. For example, one plant might code HP as HP, while another might record it as Hewlett-Packard. Without a standard way to name a company, aggregate totals can be off, weakening a company's leverage with its suppliers.
  • Item codes are used to define products, but these codes don't always connect an item to an industry-standard classification. This makes it difficult to aggregate similar types of data and combine spending across commodities, locations, suppliers and programs. If an item master record contains industry-standard classification, aggregation of spend at various levels of category will become possible.
  • Relationships between suppliers aren't defined or are hard to decipher in a business application such as ERP. Understanding these relationships — such as the fact that Lab Safety Inc. is a subsidiary of W.W. Grainger — can help provide leverage when negotiating bulk deals or rationalizing per-vendor spend.
  • Many crucial bits of information, such as the minority status of a supplier, might not exist within an ERP system. This information can help a company take advantage of tax breaks or be used for regulatory compliance. Without it, supplier rationalization initiatives can fall short of company-wide goals.

These pain points are leading the smartest procurement executives to initiate spend analysis initiatives, the key to which will be identifying, normalizing and connecting data. While the data may come from multiple catalogs or business applications, this is a very contained, finite set of data that can be readily cleansed by automated tools and subject matter experts. Once the initial cleansing and framework is in place, ongoing data management becomes simply a maintenance issue.

Implementing a Successful Spend Analysis Campaign

Whether an organization accomplishes this internally or works with a service provider, three key phases are required to implement a successful spend analysis campaign.

Phase I — Extract and cleanse vendor and spend data

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