Planning and Control Systems

Reliance on planning and control systems—forecasting and measuring—has mushroomed since the dawn of the computer era. Retailers, for example, need to know what’s selling and what isn’t. Point-of-sale terminals now yield that information instantly. Data flow freely up and down the hierarchy, greatly enhancing management’s ability to oversee performance and respond in real time.

Mintzberg (1979) distinguishes two major approaches to control and planning: performance control and action planning. Performance control imposes concrete outcome objectives (for example, “increase sales by 10 percent this year”) without specifying how the results are to be achieved. Performance control measures and motivates individual efforts, particularly when targets are reasonably clear and calculable. Locke and Latham (2002) make the case that clear and challenging goals are a powerful incentive to high performance. Performance control is less successful when goals are ambiguous, hard to measure, or of dubious relevance. A notorious example was the use of enemy body counts by the U.S. Army to measure combat effectiveness in Vietnam; field commanders became obsessed with “getting the numbers up.” The numbers painted a picture of progress, even as the war was being lost.

Action planning specifies methods and time frames for decisions and actions, as in “increase this month’s sales by using a companywide sales pitch” (Mintzberg, 1979, pp. 153–154). Action planning works best when it is easier to assess how a job is done than to measure its product. This is often true of service jobs. McDonald’s has very clear specifications for how counter employees are to greet customers (for example, with a smile and a cheerful welcome). United Parcel Service has a detailed policy manual that specifies how a package should be delivered. The objective is customer satisfaction, but it is easier to monitor employees’ behavior than customers’ reactions. An inevitable risk in action planning is that the link between action and outcome may fail. When that happens, employees may get bad results by doing just what they’re supposed to do.