Framework for analyzing technological choice

Managers are commonly faced with the problem of choosing which among competing process technologies should be installed. This can be complex problem because of several factors. First, they may be several alternatives that should be considered. In addition, there may be uncertainties about either the performance of one or more of the alternatives or about future events that could affect the final choice. Second, technological choice usually involves investments over a considerable time horizon, raising the question of how to evaluate the economic effects of the alternatives; that is, what criteria should be used. Finally, the alternatives are commonly not strictly comparable. There may be advantages and disadvantages to each that that cannot be reduced to simple economic terms, yet they can be very important in the final choice. Our framework must accommodate these complexities and help to simplify and clarify the process.

Structuring Alternatives:

We must first identify the decision that must be made and the feasible alternative technologies that should be considered. Often, someone is proposing a specific system, and it may become a “favorite” because it has a champion. But good managers should want to compare the economic and other measures of performance of the challengers to the favorite. The development of viable alternatives that really accomplish the processing objectives may be the most important step. The minimum level of comparison should also be considered; that is to do nothing and keep the existing technology.

When the basic alternatives have been developed, the “chance points” should be identified. Here we are attempting to shed light on the uncertainties that may accompany a given alternative. For example, if a given technological alternative still has some development work that must be completed before it could be actually installed that is a chance point, and we need to assign a probability that it will be successful or that it will be completed by a given time; otherwise, the economic benefits might be affected negatively.

The decision, the alternatives, and the chance points with their probabilities can be represented by a decision tree. In this example, we show the decision box, the two alternatives new technologies, A and B, and the “do nothing” alternative. Following alternative A, there is a chance point because there is the possibility that there will be a breakthrough in the design of A that will make it more economical to operate than it is currently. After consultation with experts in this technology, we assign a probability of p = 0.4 to its success and p = 1 – 0.4 = 0.6 that it will not be successful. A succession of such chance points might be structured if the situation were more complex.

Horizon and choice of Criteria for decision:

The horizon over which we should consider the comparative costs, revenues, and non-quantitative advantages and disadvantages of competing technologies is usually fairly long in technological choice problems. The cost, revenues, and investment amounts are not simply to be added; that is, it would not be meaningful to add annual costs and revenues to the fixed investments of alternatives in order to compare them. Therefore, the relatively long horizon and the presence of investment costs dictate the use of present values as the criteria for measuring the economic costs and benefits of the alternatives.

One more complication is imposed by the occurrence of chance points in the decision tree. We must weigh the costs and benefits that are affected by the probabilities of occurrence of these chance events. This simply means that, for our example, the present values of the costs associated with successful breakthrough are multiplied by 0.4 whereas those associated with an unsuccessful effort are multiplied by 0.6. Since there is risk in these values, they are termed expected monetary values (present monetary values in this instance). The total of these weighted present values can then be compared with the present values of B and the do nothing alternative. The alternative with the lowest expected monetary value is favored on economic terms, assuming that costs dominate the comparative evaluation. If the financial flows are dominated by revenues, then the alternative with the highest expected monetary value is favored.

“What? Gaming in the workplace? No way!” This is something that we hear from Corporate
Closely tied to the question of how much capacity should be provided to meet forecasted
The notion of focus naturally, almost inevitably from the concept of fit. Just as a
At its heart a capacity strategy suggests how the amount and timing of capacity changes
However, as with most strategic decisions, the issue is more complex than it first appears.

  • prashant

    Really good article. What I understand from the article is “you should take risk if you have good back up to accomodate negative outputs”. But I am not completly agree with this. While comparing two or three things we must consider the negative side of ‘B’ too. Say for example if I have risk of 0.6 in ‘A’ but if it is successful then the quality is best whereas risk is 0.4 in ‘B’ but if successful the quality is better then I would say that we should go ahead with higher risk although we dont have good back up. The reason for opting ‘A’ is not only quality but it includes future perspective where you can stand with competitors.