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Defining A Measurement Strategy, Part II
In Part I of this series (see March 2006 BI Review), we outlined the three steps needed to define a world-class measurement strategy:
- Why? Identify goals of the program
- What? Define a hierarchy of metrics for your company
- How? Implement through technology for repeatability
Because different goals require different metrics, the importance of clearly defining your goals for measuring cannot be understated. If your goal is to assess the financial health of the supply chain, for example, you'll need different metrics than if your goal is to diagnose and correct supply chain issues. The outcome of Step 1, identifying your goals becomes the input for Step 2, defining the metrics needed to achieve those goals.
In our opinion, what's needed is a metrics architecture made up of a network of metrics portfolios, providing a cohesive framework for managing each area of the business and tracking the interdependencies across them. Without this, measurement will be disconnected from the realities of your business, and you may optimize one part of the business at the expense of others.
What is a "Metrics Architecture"?
While everybody measures in most companies today, the metrics are typically either at too high or too low a level, and they're disconnected from each other. What's needed is an overarching metrics architecture (see Figure 1) that defines the metrics that matter for the different areas of the business: a network of metrics portfolios, specific to the operations of specific industries.
Figure 1: Metrics Architecture
Consider the following:
- The CFO knows earnings per share and EBIDTA (earnings before interest, depreciation, and taxes). It's highly likely that results of these metrics drive a large part of his/her incentive compensation. But will these measures act as a straightjacket for the operations groups?
- Sales management knows revenue per salesperson. Ditto on the compensation issue. But is it good business or just revenue at all costs?
- Customer service directors know how long it takes to answer a call. They live and die by this number as it is an indicator to both staffing levels and profitability. But is it the right thing to continually shorten call lengths if customers are having problems with products?
- Procurement officers know how long it takes to process the average purchase order. As a cost center in many companies, process efficiency is a proxy for service effectiveness. But are they getting the best price or best delivery options?
- Supply chain operations tracks on-time shipments, as they are judged on whether the goods leave the plant or distribution hub on time. But did they get to the customer on time?
- Manufacturing knows its first pass yield. After all, product quality is one of their key measures. But would a redesigned process deliver better quality and a more responsive manufacturing process?
What each can't clearly see is their impact on the others. The only place all the metrics come together is in the financial statements; by the time they get there, they've been rolled up, translated, and homogenized so many times they're barely recognizable. Worse, at this point they cannot be used to truly manage the business. In some cases, this causes significant conflict between constituencies within the firm that can be disruptive, even counterproductive.
The Composition of Each Metrics Hierarchy
As an example of a metrics hierarchy, AMR Research's Hierarchy of Supply Chain Metrics is a three-tiered model designed to help companies more efficiently and effectively measure and manage their supply chain operations. Based on our extensive benchmarking of nearly 100 supply chains, the model identifies the supply chain metrics that matter and their interdependencies in three levels: assess, diagnose, and correct.
Rather than trying to navigate and distill hundreds of possible metrics to understand how your supply chain is performing, you can home in on the few metrics that give you the most comprehensive, end-to-end information, allowing you to quickly identify the levers you can use to improve supply chain operations.
A network of metrics hierarchies that cover each area of the business-supply, demand, product, finance, and such-allows a company to efficiently track and analyze each area of the business while clearly seeing the interdependencies among the different areas of its piece parts. In this way, the metrics architecture can be used not only for analysis of a historical or current situation, but also to do future-facing, what-if analysis and scenario planning.
A Case Study: Connecting the Dots Across Silos of Information
Let's look at a brief example of how a metrics architecture would work. Take the case of a high-tech company that creates a high-quality new product that meets customer needs. Marketing launches an initial promotional campaign and successfully generates a spike in customer demand for the new product. However, marketing doesn't communicate this to the supply chain organization. As a result, the company doesn't have enough inventory to satisfy the heightened demand, resulting in stock-outs and unhappy customers.
How would this situation be reflected in the metrics?
- Product - The metrics hierarchy here would look great. As reflected in the first-pass yield numbers, product quality is good, incorporating a high proportion of customer needs, and time to market is short. One problem area that would show up here would be "time to breakeven," which would be longer than anticipated due to the supply shortage.
- Demand - This metrics hierarchy would also look good, and marketing would feel satisfied that its promotional campaign so successfully shaped an increase in demand.
- Supply - The metrics hierarchy would not look as stellar here. The inventory days of supply would be favorable-that is, low-because they didn't ramp up inventory, but everything else would be showing up "in the red." Because they had no visibility into the expected increase in demand, they would show poor demand forecast accuracy, and a poor perfect order rating due to the high stock outs.
- Financial - How does this all flow into the Financial metrics hierarchy? While inventory as a percentage of revenue would be low (which would make the CFO happy), other metrics would suffer: accounts receivable takes a hit, goodwill is hurt due to unmet expectations, allowances and trade promotion adjustments have to be made, and profit suffers.
What a metrics architecture allows here is an objective analysis of "what went wrong" and, therefore, the ability to accurately fix the problem. Rather than everyone pointing the finger of blame at the supply chain organization, the use of a cohesive set of metrics hierarchies would allow a clearer picture to emerge, and thus an enhanced capability to continuously improve the business.
Finding the Right Balance
A network of metrics portfolios, with metrics that are at a level of detail that's neither too high nor too low, would allow the different areas of a company to manage their operations and clearly see the impact of an event in one part of the business on all other parts. Once the metrics have been defined, the next step is to implement a metrics program that is repeatable, which we will cover in Part III.
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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