Strategic consensus on manufacturing competitive priorities, страница 6

According to theory in operations management (Hayes and Wheelwright, 1984), managers and employees in our hypothetical example should be knowledgeable not only of the strategic importance assigned to each of the three performance areas (Q, D, C). They should also be aware of the reasons behind the strategic importance (or non-importance) assigned to each of them. In other words, employees should know that the reason why C is not strategically important is because it is in a trade-off situation with Q and D, which are considered as strategically important. It should also be clear to employees at all levels that since there is no trade-off relationship between Q and D, both of them are considered strategically important by the firm.

If enquired about the strategic importance of the three performance areas, top management in our imaginary firm ideally would rate Q and D as very important and would assign a value of “3” to both of them and would also give C a value of “1” in a scale of 1 (no importance) to 3 (high importance). The difference between the “3” assigned to Q and D and the “1” assigned to C is what we call the “trade-off distance” (TOD). This TOD depicts the incompatibility that exists between a pair of manufacturing performance areas. In our example, the TOD between Q and C and between D and C would be “2” (3-1). TOD between Q and D would be “0” (3-3). By doing this, we can obtain a metric that can assist us in subsequent numerical analyses. However, in order to facilitate these analyses, we transform the scores obtained here to eliminate potential TOD values of “0”, as was the case between Q and D in our example. Thus, we assign a value of “1” to every TOD value of “0”, “2” to every TOD value of “1” (not applicable in our example), and a value of “3” to every TOD of “2”. This transformed new metric can be called “transformed trade-off distance” (TTOD).

Once the TTOD between each pair of competitive priorities has been obtained, we proceed now to confirm whether this metric is accurately reflected and acknowledged by the rest of the employees in our example. In other words, we aim at corroborating whether employees in our imaginary firm are knowledgeable of the relationships between each pair of strategic competitive priorities. In order to measure this, the following questions can be proposed:

1.  Is quality (Q) in a trade-off situation with:

2.  3         2           1   Delivery (D)

3.  3         2           1    Costs (C)

4.  A great deal = 3  Moderately = 2  where not at all = 1     

Knowledge about trade-offs implies knowledge about compatibilities. Thus, since Q and D are considered strategically very important (3), the ideal answer to the question of whether Q is in a trade-off situation with D would be 1 “not at all”. Also, the ideal response regarding the trade-off situation between Q and C would be 3 “a great deal”. We call these scores “employee's assessment of trade-offs” (EATO). Once the EATO scores are obtained, the real knowledge that an employee has of the relationships between each pair of competitive priorities can be assessed by dividing the EATO score of each pair of relationships by the TTOD of that same pair. We call this score the “employee's real knowledge of trade-offs” (ERKTO).

As seen before in our imaginary example, the TTOD between Q and D was “1”, and ideally, every employee would have an EATO score of “1” for Q and D. Thus, in a perfect scenario, every employee would have a ERKTO score of = EATO/TTOD = 1/1 = 1 for the “quality” and “delivery” relationship. Obviously, this score could vary according to the EATO scores that employees obtain. In our example, since the EATO score ranges from “1” (not at all) to “3” (a great deal), the potential ERKTO scores would be “1”, “2” (EATO of “2” divided by TTOD of “1”), and “3” (EATO of “3” divided by TTOD of “1”). The ERKTO score can then be obtained for each individual relationship that every competitive priority has with every other competitive priority (e.g. “quality and delivery” and “quality and costs”). Once these scores are obtained, a number of numerical analyses can be performed (regression, correlation analysis, t-tests, categorisation, etc.) using the ERKTO scores as the explanatory variables and measures of manufacturing performance as the dependent variables.