Exhibit 1.7 shows how this (as yet unquantified) advantage of vertical integration can be compared with the cost penalty which it carries (due to failure to exploit economies of integration with the telecommunications network). If the cost penalty is large, it will result in a net drop in the number of customers served despite the outward movement of the demand curve (case 1). If the cost penalty is sufficiently small, it will be outweighed by the revenue gain consequent on this outward demand curve shift (case 2).
In Chapters 3 and 4 we quantify the cost penalty illustrated on Exhibit 1.7. While not being able to draw on any directly applicable data, we would tentatively suggest that a cost penalty significantly less than 5% is likely to be outweighed by the revenue benefits of improved coordination of a vertically integrated business. The sensitivity of cable television demand to the quality of the overall marketing effort (including the ability to coordinate marketing closely with physical development of the network) is such that a 5% shift of the demand curve could easily follow from better coordinated business management. Conversely, if the cost penalty is substantially larger than 5% it would be necessary to call seriously into question the ability of a vertical integrated company to offset this cost disadvantage through better business coordination. A larger cost penalty, say one closer to 10%, represents a large extra drain on the cash flow of such a business.
We provide some quantitative evidence bearing on these points in Chapter 4.
1.3.6 Data collection
All cost and revenue data used in this study are taken from a combination of three sources: data supplied by HKT, data supplied by HCV, and data obtained by BAH from internal files and miscellaneous industry sources around the world.
Although data relating to some of the policy outcomes have been provided in greater detail by HKT and data relating to other outcomes by HCV, it is important to note that both sources have been used to evaluate each of the future scenarios under study. Thus, for example, the cost comparison between monopoly and competitive supply of telecommunication services has not been based on data supplied by HKT for the monopoly case and by HCV for the competitive one. Instead, models have been created of the technical components required to provide services under the monopoly and competitive scenarios, and then data supplied by HKT and HCV have been used to identify the cost of each component. Data from international sources collected by BAH were also used to further refine these two estimates. In this way, any tendency by one party or the other to forecast costs higher or lower than the other has not biassed the measurement of cost advantage or disadvantage associated with the monopoly or competitive solution.
The same method of data collection applies in the case of revenue forecasts. While HKT has understandably provided more detail on revenue forecasts in the case of the monopoly scenario and HCV in the case of competitive outcomes, we have not based analysis of the extent of demand stimulation due to competition on the difference between these two sets of numbers. Instead, we have estimated the degree of demand stimulation on the basis of data from various sources (such as international
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