The beliefs and assumptions underlying the managers’ responses to the CEO’s directive at Gamma are all plausible, but they are not grounded in an analysis of data. We can use assumptions like these, however, to help us determine what kinds of data we need to gather in order to explore as many dimensions of a situation as we can without assuming we know the answers. The managers’ ”solutions” were likewise plausible but were proposed at the final stage of the problem-solving process instead of at the problem formulation stage where they could be most useful. In similar situations, we can use our imagined solutions as a way of testing whether we have thought of all the data we need to gather in order to adequately support them.
Briefly describe how you would gather the data needed to test the assumptions/beliefs of X, Y, and Z.
NOTE: If a particular belief or assumption does not seem to be particularly helpful for collecting the kind of data you need, explain briefly why not and move on to the next one.
| Manager | Belief or Assumption | Data Needed or Explanation |
| X | Age discrimination is a problem |
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| Young workers are unfriendly toward older workers |
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| Unfriendliness is due to age discrimination |
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| Sensitivity training curbs age discrimination |
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| Y | Older workers are under-represented at Gamma |
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| Gamma is at risk of a lawsuit |
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| Z | Under-representation may be due to more than just unfriendliness |
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Explain below why you think that the data you listed above will help you gather enough data to assure that you have gotten beneath the perceived problem to the real problem (they may be one and the same, of course).
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