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Defining A Measurement Strategy, Part III

In Part I of this series (BI Review, March 2006) we outlined the three steps - why, what, and how - needed to define a measurement strategy. Once measurement goals are identified, the next step is to define the metrics needed to achieve these goals.

That was the subject of Part II (BI Review, May/June 2006), where we emphasized the requirement for an overarching metrics architecture that defines the key performance indicators (KPIs) that matter for the different segments of the company. A network of metrics that covers each area of the business - supply, demand, product, finance and such - allows a company to efficiently track and analyze each area, clearly seeing the interdependencies among these different areas.

Any measurement of performance at this point would be a baseline set of metrics that can be used for comparative purposes, potentially as a benchmark against peer companies or even different divisions within the same company. But for your measurement strategy to come alive, it should be implemented in technology for repeatability. Only then will it become a real decision support system that will help guide, even direct your organization to increasingly better performance.

Taking the pulse of the business on a continuous basis allows you to make course corrections as early as possible, take advantage of opportunities that present themselves mid-stream and even rethink components of your company strategy. Better information to support more thorough understanding of cause-and-effect fuels knowledge, and knowledge coupled with action equals power.

The Performance Management Model

The three-step process outlined in this series of articles is encapsulated in AMR Research's Performance Management Model (see Figure 1). Starting with strategy (step 1), metrics are established and initially measured (step 2). But measurement alone won't improve performance in the business; it requires an ongoing, repetitive cycle of performance measurement implemented for repeatability through technology.

Figure 1: AMR's Performance Management Model

In order to make performance management a reality, the following activities are required:

  • Effective goal setting - sticking a flag in the ground as a target gives the organization something to rally around, providing managers and workers guidance on what constitutes success.
  • Consistent monitoring of process and outcomes - repetitive measurement establishes a history of performance over time-potentially in real time, if desired-and gives process owners feedback on what's working and what's not.
  • Performance notification - if something is out of whack, proactively informing the metric owner(s) of the anomaly allows for action to be taken in time to have some effect. This can also cut down on the noise in the system by bringing problem areas to the attention of managers without them having to stumble on the processes that need it.
  • Course correction - whether slight adjustments are called for to tweak performance or wholesale changes in strategy are necessary to achieve overall performance goals, feedback from the measurement system gives managers the necessary input to make that call and change/adjust business activities.

Technology Components That Can Help

Nearly every software vendor has some play in making performance management programs a reality, but the major areas of emphasis should include some or all of the following:

  • Business process applications - Applications that deliver information about specific processes and outcomes in the context of their content area. Examples of these specific content areas include supply management, workforce management, and supply chain planning and execution systems. In many cases, these business process applications are industry-specific, reflecting core activities of your business.
  • Enterprise applications - These products support a swath of content areas from finance, and human capital, to customer management and supply chain and beyond. They can provide the framework for performance management and much of the business content to fuel the program(s).
  • Business Intelligence tools - This class of product delivers the query, reporting, and analysis capabilities to analyze data wherever it may exist in the enterprise. Because the outputs of these products are used by a vast array of individuals within and outside the company, they must serve many masters-from report author, to expert analysts, to executives, to casual consumers. Increasingly, these products are coupled with templates and/or applications supporting analysis for specific content areas or industry scenarios.
  • Dedicated performance management products - applications and tools to monitor and enable specific activities in the business including: planning; budgeting and forecasting; financial consolidations and management reporting; and the super-hot dashboard and scorecard models used across many businesses today.
  • Analytic infrastructure - All the components needed to store, organize, and prepare the system of record for enterprise reporting and analysis. This includes data warehouse/data marts; data integration capabilities (including data cleansing); and multidimensional databases that the company custom built or purchased as a packaged application.

After years of advisory work in this area, we see virtually all companies using pieces from each area to build their performance measurement strategy and system.

Seeking Professional Help When Necessary

No one will argue that this can be a significant, even complex, undertaking. As such, consultants and systems integrators play a big role in helping companies define any performance management and system that really works for them. From planning through execution, expert advice and guidance can significantly speed up deployment. At the end of the day, it's rapid time to value that really matters.

In Conclusion...

Measurement for measurement's sake will certainly consume lots of time and energy, but may have little payback to your organization. Taking the time to strategize on measurement goals, tying a set of action-oriented metrics to those goals, then automating the measurement of those metrics for repeatability and improvement will guarantee a successful program. You can then focus your energies on performance improvement and moving your business forward, not just seeing where you've been.


John Hagerty (jhagerty@amrresearch.com) is VP of research at AMR Research.

Debra Hofman (dhofman@amrresearch.com) is service director and head of benchmarking analytix at AMR Research.

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