Metric selection is a vast topic, but when managers approach the effort with deliberateness and reasoning, they set their company on the right path. First, note that the primary measures executives should consider at each level are those which tie directly to the higher-level measures under which they're subordinate; but they will also select “local” operating measures. For example, since exhibit 1's level-one measure P1.2 — Time to market — is concerned with speed to market, the candidate subordinate measures in exhibit 2 do not include productivity gauges such as hours per project, even though hours per project might affect the corporate objective P1 — Execute world-class internal product development. Instead, all relate to speed to market, and their quality as level-two and -three metrics is affected by the closeness of their relation to metric P1.2.

The first category of metrics in exhibit 2 — product development success rates — is concerned with measuring the effectiveness, or win rate, of the development process. These measures focus on employees achieving design goals, but they lack the sense of urgency for these goals' accomplishment that is inherent in the P1.2 — Time to market metric. Employee design teams could attain 100 percent success but take three years to bring a new product to market, thus missing the strategic intent of the higher-level measure. Therefore, category one in exhibit 2 receives low marks for inclusion in lower-level scorecards as part of the P1.2 metric family.

The second category of measures in exhibit 2 — product development cycle times — is focused on the number of days required to achieve product development milestones. Thus, in spirit, it aligns with the top-level measure. However, this group of measures does not provide visibility into the success of product-development initiatives, so it will not identify products that are off track, and thus may miss a substantial hidden obstacle in the company's quest for speed. This group of measures receives average marks by the leadership team.

The third category of measures — product development success rates on time — tracks both the speed and effectiveness of the product-development process. Essentially, these metrics measure what, at a given speed, is the yield or value of the process. The leadership teams at levels two and three believe this category provides them with two key factors that indicate the company's performance in terms of its product development time to market. These metrics then can be further broken down into constituent components as scorecards move even lower into the company.

Balanced scorecards at levels two, three, and four produce more frequent reports, which contain more detail, than those at level one. A shop floor supervisor may use minute-by-minute run charts to redirect behaviors of her teams. And level three and four balanced scorecards break measures into submeasures, each of which has corresponding targets. Although our example has been focused on speed, companies will often include productivity measures (e.g., hours per product phase, step) in lower, operational-level scorecards to ensure that they do not achieve speed “at any cost.” While cost minimization is not the primary strategy, costs are still managed in our case company at the lower levels. Including financial measures in a balanced scorecard's process perspective is a common mistake in scorecard design. Some mixed financial/process metrics that are commonly used to measure product development effectiveness include NPV (net present value), ROI, or time to break even; the percentage of sales dollars resulting from products released in the previous three years; the percentage of products sold that were released in the previous three years; the percentage of sales dollars or products sold resulting from new products released in the prior year; and time to profitability for new product/service development projects. The true value of the Balanced Scorecard process perspective lies in its ability to provide an early warning system for process problems or opportunities. Financial information, by definition, is lagging; financial results may not show up in a product development cycle until years after the cycle begins. Financial measures may indicate a problem too late for a company to make course changes. But nonfinancial, leading process measures like those in exhibit 2 can provide insight into a product's strategic value months, sometimes even years, before the accountants can sound the alarm bells.

A company choosing metrics should rigorously evaluate the correlations among its selected measures using the logic embedded in the linked strategy map objectives. Over time, these correlations — and the metrics' predictive value — should become clearer. The value of the strategy map/Balanced Scorecard approach is that a company can leverage correlations to proactively understand the likelihood of customer and financial results (lagging indicators) months, even quarters, in the future — or at least to spot trends before the competition sees them. In order to accomplish this, one needs robust BI tools to capture data sets and enable predictive analytics.