In the last issue, this column discussed the need to implement measurement systems in a participatory manner, rather than impose measures entirely "from the top down." In this issue, we'll focus on measures and measurement systems as tools for improving the processes of team problem solving and team collaboration. Measurement can improve problem-solving and team-communication processes in several ways by helping you to:
* develop a common understanding of the problem,
* signify that a solution has been found,
* test potential solutions,
* deal with objections that stall the problem-solving process,
* share and clarify information through networked, desktop measurement systems.
All too often, teams start searching for solutions before they have a clear, shared understanding of the problem. One useful technique is to ask the group members to each describe what would be different if the "problem" were solved. The different responses can lead to a great deal of clarifying conversation. Further crystallization occurs when the team is asked to agree on one or more measures it could use to prove the problem is fixed.
This visioning exercise can surface very different perceptions of the dimensions of the problem. After the group listens to each of its members' response, it can begin to search for a tangible (i.e., measurable) description of the current problem on which it can agree. For example, a team might declare that its quality problem will be fixed when the number of production rejects drops from five parts per 100 to one part per 100. This measure tells us what gap must be closed to solve the problem, how big the gap is, and how we'll know when the problem is fixed.
Another useful technique is to ask the group to list its assumptions about the problem or about the potential solutions. Having identified the assumptions, it is then possible to look for proof, in the form of objective measures, that the assumption is valid. For example, if the problem is stated as a potential solution, (such as:"we need more training") the team can identify and test its implied assumption (that training will solve what is really a quality problem) by comparing the quality of output from trained versus untrained workers.
Many of us have hit a logjam while identifying potential solutions when someone says something like, "That will never work, we've tried that and it failed." This type of objection is very difficult to …