This last requirement—that of linking through the use of cause-and-effect relationships—
is the most important requirement. Cause-and-effect relationships are the means by which
lead and lag measures are integrated and simultaneously serve as the mechanism for expressing
and revealing the firm’s strategy. Outcome measures are important because they
reveal whether the strategy is being implemented successfully with the desired economic
consequences. Lead measures supposedly cause the outcome. For example, if the number
of defective products is decreased (a lead measure), does this result in a greater market
share (an outcome measure)? Does a greater market share (acting now as a lead
measure), in turn, result in more revenues and profits (lag measures)? These questions
reveal the vital role of cause-and-effect relationships in expressing an operational model
of a strategy—a strategy that can be expressed in a testable format. In fact, a testable
strategy can be defined as a set of linked objectives aimed at an overall goal. The testability
of the strategy is achieved by restating the strategy into a set of cause-and-effect
hypotheses that are expressed by a sequence of if-then statements.9 Consider, for example,
the following value-growth strategy expressed as a sequence of if-then statements