The mechanics of making a capacity expansion decision in the traditional capital budgeting sense are quite straightforward—any finance textbook will supply the details. Future cash flows resulting from the new capacity are forecasted and discounted to weigh them against the cash outflows required for the investment. The resulting net present value ranks the capacity addition against the other invest–ment projects available to the firm.
However, this simplicity masks an extremely subtle decision-making problem. The firm usually has a number of options for add-ing capacity which must be compared. In addition, to determine fu-ture cash inflow from the new capacity the firm must predict future profits. These will depend crucially on the size and timing of capa-city decisions by each and every one of its competitors, as well as on any number of other factors. There is also usually uncertainty about future trends in technology, as well as about what future demand will be.
The essence of the capacity decision, then, is not the discounted cash flow calculation but the numbers that go into it, including prob-ability assessments about the future. Estimating these is in turn a subtle problem in industry and competitor analysis (not financial analysis).
The simple calculation presented in finance textbooks does not allow for uncertainty and alternate assumptions about competitors’ behavior. In view of the complexity of the discounted cash flow cal-culation that properly includes these elements, it is useful to model the capacity decision with as high a precision as possible. The steps in Figure 15-1 describe the elements of the modeling process.
FIGURE 15-1. Elements of the Capacity Expansion Decision
The steps in Figure 15-1 must be analyzed in an interactive fash-ion. The first step is to determine the realistic options available to the firm in adding capacity. Usually the size of the additions can vary, and the degree of vertical integration of the new capacity may be a variable as well. The addition of unintegrated capacity can be a hedge against risk. Since the firm‘s own decision about how much capacity to add can influence what its competitors do, each of its op–tions must be analyzed separately in conjunction with competitor behavior.
Having developed the options, the firm then must make predic-tions about future demand, input costs, and technology. Future tech-nology is important because it is necessary to forecast the likelihood that present additions to capacity will be made obsolete or that de-sign changes will allow effective increases in capacity from in-place facilities. Forecasting input prices must account for the possibility that increased demand due to new capacity may increase input prices. These predictions about demand, technology, and input costs will be subject to uncertainty, and scenarios (Chapter 10) may be used as a device for coping with this uncertainty for analytical purposes.
The firm must next forecast how and when each and every one of its competitors will add capacity. This is a subtle problem in com-petitor analysis, which must draw on the full range of techniques presented in Chapters 3, 4, and 5. Competitors’ capacity moves will, of course, be determined by their expectations about future demand, costs and technology. Thus, predicting their behavior involves un-covering (or guessing) what these expectations are likely to be.
Predicting competitors’ behavior is also an iterative process, be-cause what one competitor does will influence the others, particular-ly if that competitor is an industry leader. Therefore, competitors’ capacity additions must be played against each other to predict a probable sequence of actions and resulting responses. There is a bandwagon process in capacity expansion, to be discussed later, which is important to try to forecast.
The next step in the analysis is adding competitors’ and the firm‘s behavior to yield aggregate industry capacity and individual market shares, which can be balanced against expected demand. This step will allow the firm to estimate industry prices, and in turn, expected cash flows from the investment.
The whole process must be scrutinized for inconsistencies. If the result of the predictions is that one competitor fares poorly by not adding capacity, for example, the analysis may have to be adjusted to allow that competitor to see the error of its ways and add capacity late. Or if the entire process of predicted expansion leads to condi-tions that violate most firms’ predicted expectations, it may have to be adjusted. The modeling of the capacity expansion process is com-plex and will involve a great deal of estimation. However, the proc-ess gives a firm a great deal of insight into what will drive expansion in the industry, as well as possible ways to influence it in its favor.’
A model of the capacity expansion process reveals that the degree of uncertainty about the future is one of the central determi-nants of the way the process proceeds. Where there is great uncer-tainty about future demand any differences in risk aversion and fi-nancial capabilities of firms will usually lead to an orderly expansion process. Risk taking firms, those loaded with cash or with high stra-tegic stakes in the industry, will jump in, whereas most firms will wait and see what the future actually brings. However, if future de-mand is perceived to be fairly certain, the capacity expansion process becomes a game of preemption. With known future demand, firms will race to get the capacity on stream to supply that demand, and once they do so it will not be rational for others to add still more ca-pacity. This game of preemption will generally be accompanied by heavy market signaling to try to deter other firms from investing. The problem occurs when too many firms try to preempt, and capacity is overbuilt because firms mistake each others’ intentions, misread sig-nals, or misjudge their relative strengths and staying power. Such a situation is one major cause of the overbuilding of industry capaci–ty, which I will explore further.
Source: Porter Michael E. (1998), Competitive Strategy_ Techniques for Analyzing Industries and Competitors, Free Press; Illustrated edition.