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September 17, 2003

What Are You Measuring?

Before you can create a useful analytic application, you must first analyze the business effectively. A method of business assessment developed two decades ago can form the foundation for the most cutting edge of today's strategic IT applications

by Creighton Lang

The synonymous terms enterprise performance management, corporate performance management, and business performance management are hard to miss in most business and technology publications today. Enabling technologies such as balanced scorecards, closed-loop strategic planning, and digital dashboards sound easy enough to implement, but the old saying "you can't manage what you can't measure" illustrates why it's not quite that simple. In reality, getting a single version of the numbers is the hard part for most organizations that collect vast amounts of transactional data from dozens of operational and enterprise resource planning systems.

While data warehousing and business analytics software is constantly improving, it's already relatively stable and mature within the overall technology landscape. So without technical excuses, why doesn't your organization practice advanced analytics and engage in performance management? For most organizations, the answer lies in the size of the problem and an inability to easily break it into manageable pieces that will eventually form a unified solution. What you need is a framework for determining which metrics and measurements are the most valuable to performance management initiatives and business analytics programs in general.

When discussing this problem with clients, my consulting company finds it helpful to analyze the organization's business; from procurement of raw materials to delivery of the final product to customers, including the many activities such as finance and human resource management that collectively define a firm's culture and dictate its success in the marketplace. Too many times we see customers focused on specific business processes and functions without stepping back to see the bigger picture. For instance, a healthcare products distributor may focus on using analytics to improve its on-time delivery rates, without seeing the more innovative opportunity of providing critical purchase and inventory data to the hospitals and clinics it serves.

Origins of Value Chain Analysis

Lucky for us, Michael E. Porter, the guru of corporate strategic thinking, has provided a framework that can be applied to our BI problems. Porter published Competitive Strategy (The Free Press) in 1980. This seminal work ushered in the era of business strategy as an MBA discipline. In it, Porter explained that five forces determine the degree of competition within an industry. (See Figure 1.)

A firm can choose from several competitive strategies. It can be a cost leader in the industry. Alternatively, it can sell its goods or services at a premium to the cost leader by pursuing a strategy of differentiation. A third choice includes focus, whereby a company can segment the overall market and focus on a particularly attractive and defendable position.

Still, a firm must choose whether to focus on cost or differentiation. As Porter explains, if a firm doesn't choose between the two strategies, it will achieve suboptimal returns.

Porter then published Competitive Advantage (Free Press) in 1985. This book built upon his earlier work by detailing how a company achieves cost leadership or differentiation. The generic value chain Porter defines in this book is a framework for decomposing all the activities a company engages in. (See Figure 2.)

With the value chain as the backdrop, Porter contends that strategic planners can identify opportunities for cost leadership or product differentiation within the specific activities, or in areas where two or more activities intersect. By identifying and implementing incremental improvements across all the firm's activities, leading organizations can achieve and maintain competitive advantage.

Porter's value chain is also a valuable framework to use when evaluating a company's opportunities for using data warehousing and BI to uncover and measure activities that create competitive advantage.

Taking the process one step further, it's useful to analyze not only your own value chain, but also those of your suppliers and buyers. This is the basis for identifying B2B and B2C business intelligence opportunities. (See Figure 3.)

Technical Benefits of a Value Chain Approach

Approaching your business from a value chain perspective not only helps uncover opportunities that were previously hidden, but it also has an added technology benefit. By using the value chain framework, you will enable iterative development of your enterprise data warehouse while preventing the proliferation of independent data marts, often termed stovepiped applications.

You can map out the opportunities across the value chain, detailing the common sources, data, and business information found within separate business processes and at key intersection points between functions.

This mapping process lets you see the whole and prioritize opportunities to create an overall blueprint for architected data mart development, a methodology pioneered by data warehousing guru Ralph Kimball. By developing business subject areas in iterative releases, you gain the benefits of your collective team experiences and make your project team more efficient and successful. As additional segments of the value chain are brought into the data warehouse environment, you can use already published dimensions, further increasing your ability to rapidly deploy analytic solutions.

Where you start to develop your performance management capabilities will depend on a specific activity's overall cost or importance to the organization, in combination with the number and complexity of shared dimensions the activity has with other high-value business processes.