#
A MODEL OF TELECOMMUNICATIONS SERVICE PRODUCTION
Application: a Case Study
Synopsis – The paper intends to verify, using a practical example, the feasibility of the model proposed in the theoretical approach, by which, with reference to two input variables (X1 ; X2), a set of three equations is necessary and sufficient to describe the production process of a Firm. The evidence is given by comparing strategies suggested by the model with actual decisions taken, under the same conditions, by a real Service Provider. Reference is made to a period of 13 years (1983-1995) for which Provider’s statistics upon network expansion (X1) and labour engaged (X2) are available.
Practical procedures for short term planning are tested by two main approaches.
The first one takes the labour productivity as the reference indicator to derive the value of input resource X2 once the value of X1 is estimated. A detailed provisional budget is provided whose final results are checked, for consistency, with the actual ones. The second one estimates the value of both input resources (X1 and X2) by using the condition of tangency between production curve and cost line. Again, in this case, a provisional budget should be provided whose final results are checked with the actual ones.
1. Basic Data
2. Actual strategies of Service Provider
2.1 – The input variables
2.2 – Capital and operating cost
2.3 – Market preference
2.4 – Productivity of input factors
2.5 – The economical return
3. Checking the Provider’s decisions
3.1 – The production function
3.2 – The cost function
3.3 - The path function
4. Short term planning
5. Testing the model
6.1 - The first step: provisional budget (Annex 9)
6.2 – The second step: labour productivity (Annex 10)
6.3 – The third step: final balance (Annex 11)
7. First approach: analysis over time
8. Application: the tangency condition approach
9. Conclusions
1. Basic Data
The study period covers the years 1983-1995 and relates to the strategies adopted by a Service Provider, taken as a reference, to expand its network and to match the market demand. In particular, the statistics used to describe the Firm’s activity concern: historical trend of lines in operation and employment (Annex 1), historical trend of capital and operating expenses (Annex 2), historical trend in consumption (Annex 3), gross (Annex 4) and net (Annex 5) productivity of input factors, economical return and ratios price/cost over the period considered (Annex 6).
2. Actual strategies of Service Provider
The Provider, chosen as reference, developed, during the period under study, a number of strategies as to optimise its whole telecommunications business; in particular, it had to expand its network, to satisfy the market demand and to make as profitable as possible its business. The following details may help recognising its behaviour.
2.1 – The input variables
From Annex 1 it appears that the expansion of service, over the study period, was made by increasing number of lines and by keeping almost constant labour. In this way, the ratio “lines/employee” was increased almost regularly from 136,90 in 1982 to 208,27 in 1995. The practical result of such a decision was to get better efficiency of operating activity and to limit operating annual expenses for a greater profit.
2.2 – Capital and operating cost
Capital and operating total expenses increased, over the period under study, at a rate of 17% and 12%, respectively (Annex 2). Such a growth is consistent with the strategy of giving priority to capital expenses rather than to operating ones. In particular, the increase in operating expenses kept lower than the increase in unit salary (13% per year): technological progress and employment policy might have supported this result.
2.3 – Market preference
The market demand was increasing almost regularly. Annex 3 shows that, over the study period, main lines have been increasing at a rate of 3,41% per year; total consumption was growing, over the same period, by an average 4,93% per year. That was due to an almost regular change of consumers’ behaviour: the load per line moved, in fact, from 4400 minutes/year in 1982 to 5500 minutes/year in 1995.
2.4 – Productivity of input factors
Gross productivity of input factors is indicated in Annex 4. The indicator is the ratio of total revenue to the cost of single factor and measures the revenue a factor produces.
As far as network is concerned, the gross productivity per line was 177% in 1983 (unit revenue was 2,77 times greater than its cost) and was decreasing over time down to 81% in 1995 (unit revenue was 1,81 times greater than its cost).
The gross productivity of labour got a better evolution; in 1983 total revenue per employee was 2.6 times greater than average salary: it represents a reasonable profitability as to justify the presence of labour engaged. An even better situation appears in 1995 when the revenue per employee grows at 2.8 times the salary.
To be more realistic, a tentative (Annex 5) was made to assess net productivity of labour assumed as the only variable which produces revenue. The process was the following: having deducted from total revenue the annual capital expenses, the difference was assigned to labour. If we, then, exclude the annual expenses for the network (capital recovery), the productivity of labour decreases from 58% in 1983 to 20% in 1995. The policy of keeping constant employment, without increasing price or stimulating consumption, was paid, over the period, by a reduced productivity.
2.5 – The economical return
The Economical Rate of Return, calculated as ratio between profit and Value of Plant, (Annex 6) was reducing all over the period. It was decreasing from 7.61% in 1983 to 3% in 1995: the ratio of profit to revenue was, as well, decreasing from 23% in 1983 to 7,6% in 1995. As the ratios decrease regularly, there is no way to recognise effects of external factors (such as transition from monopolistic to competitive regulation).
Average cost per minute, ratio between total annual expenses incurred and total traffic routed, moved from 0,0468 US$/minute in 1983 to 0,1391 US$/minute in 1995. Over the period, the price per minute was gradually approaching the unit cost: even in this case, no effect can be reasonably assigned to the change of external factors.
3. Checking the Provider’s decisions
The application of the production model to the case study starts from the definition of theoretical functions: production function, cost function and path function. The approach was made on the basis of statistics available and without the direct support of Firm: such a limitation was assumed acceptable to produce the example.
3.1 – The production function
The main constants of the production function Q = f(X1,X2) are shown in Annex 7. They have been calculated, from statistics available, using the following system:
R1X1/R2X2 = a/b
a + b = 1
Q = A(X1)a(X2)b
The trend of exponents “a” and “b” over time is consistent with the strategy, used by the Provider, of favouring plant expansion rather than operating activity. Production function did not keep constant parameters over time: isoquants did not simply shift upward in the X1X2 quadrant (Annex 8, Table 1). They gradually rotated as Annex 8, Table 2, shows: the Provider, starting from a situation in 1983 where operating expenses were greater than capital expenses (a<b), was gradually reversing such strategy by giving priority to capital expenses and by constraining the growth of personnel (a>b).
3.2 – The cost function
In the quadrant X1X2, the cost function (isocost):
X1 = C0/R1 – R2X2/R1
changed its slope over time from 158,3 (R2/R1) in 1983 to 139,6 (R2/R1) in 1995. This is consistent with the condition of tangency to the isoquant curve: the cost line modified its shape according to the changing in shape of relevant isoquant.
3.3 - The path function
Along the period under study, the path function shows a non linear trend and this is in line with the conditions of passing through the points of tangency between isocost and isoquant lines. As the apportionment of input variables (X1 and X2), did not follow a linear pattern, the path function:
R1X1/R2X2 = a/b
did change slope, in the quadrant X1, X2, as the ratio “a/b”.
4. Short term planning
When planning its future activity, the Producer chooses the strategies necessary to improve his business. We suppose that a general plan to expand the network exists and that the detailed decisions are taken with reference to some key indicators. So, the process involves: a tentative provisional budget based upon the final results of previous year, the analysis of reference indicators and an adjusted final provisional budget.
5. Testing the model
In the following, two approaches of the process are used to estimate the input resources X1 and X2. The first one takes as reference the optimisation of operating efficiency (X1/X2) and of the labour productivity (revenue-salary). The shape of production function is adjusted (exponents) as to produce the value of indicators chosen as objectives.
The second one is based upon the mathematical condition of tangency between production function and cost line. Again the shape of production function is adjusted (exponents) as to match, in the tangency point, the level of budget available.
6. Application: the productivity approach
With reference to Annexes 9,10 and 11, a full example is given relevant to year 1984.
We assume that the following variables are known or can be estimated:
6.1 - The first step: provisional budget (Annex 9)
The Production function 1984 and its relevant isoquant are assumed to keep the same parameters (A0, a0, b0) as in the previous 1983. That is: the isoquant curve 1984 simply shifts upward (Q1984 > Q1983) keeping the same shape as in 1983.
6.2 – The second step: labour productivity (Annex 10)
Actual productivity of labour is calculated as:
P = (pA(X10)a(X2)b-R1X10)/R2X2 -1
where X10 is constant and X2 varies. The formula produces values of productivity which do not decline, after the maximum, as it would be expected: the function, in fact, does not account for constant revenue after the maximum consumption “Q” is reached. As this might be misleading, the actual productivity curve is approached by a 2nd degree curve (y=ax2+bx+c) which better describes the pattern of productivity as a function of labour: together with the correlation coefficient, the fitting is verified when the maximum value of X2 produced by the function (condition y=0) equals the maximum value of X2 calculated by the condition: productivity/employee = salary/employee.
A new value of labour is obtained from the productivity function, consistent with the wanted value of labour productivity. The number of employees arrived at is 18015 (at a productivity of 57.2%): the figure confirms the value of labour calculated in 6.1. The final value of 18031 is retained.
6.3 – The third step: final balance (Annex 11)
To check whether the model provided appropriate suggestions to orient the Firm’s decisions, a comparison was made between the final provisional budget and the actual results obtained by the Provider at the end of the year 1984.
The balance shows that the economic and operating results of the two budgets are very close to each other: among the main indicators, it is important to remark that the parameters of estimate production function, the labour productivity expected and the provisional profit/revenue ratio are consistent with the actual ones.
7. First approach: analysis over time
It is not always so easy to get a good approach between the provisional budget and the final actual results. The process shown in details for the year 1984 was repeated for the years included in the period under study and the provisional results were compared with the final available results over time.
The tables in Annex 12 show the summary.
Revenue. Revenue, shown in the “Budget Reference” (Table 1), have been greater than actual ones because of price adjustment adopted as a function of wanted productivity. The model assumes that the Provider has the freedom of fixing prices.
Employment. In absence of any information about the Provider’s policy, the strategy suggested by the model is to reduce labour by 400 units over the whole period: the decision lets increase efficiency which is, in fact, a little greater than the actual one.
Productivity. Together with the increase in price, the decision of reducing personnel lets keep, in the model, the ratio “revenue to salary” at reasonable level up to 1988. Successive values slowly decline over time. The model was used with excessive prudence: it provides productivity only a little greater than the actual one.
8. Application: the tangency condition approach
An alternative way of estimating the value of input resources X1 and X2 relates to the principle enunciated in the theoretical section. That is: once the production function and the available budget are known, the optimum solution X1, X2 is found by checking the point of tangency between the isoquant curve and the isocost line. Examples of such approach are shown in Annexes 13 (year 1984) and Annex 14 (year 1995).
We assume that the variable X1, the expected size of plant for the new market date, is known; the other input data to use, in this approach, are:
the unit cost per line R1 = annual capital cost per line
the expected salary R2 = unit salary per employee
the expected consumption t0 = minutes per line
total annual cost C0 = annual budget available
Other parameters, necessary to carry out the example, are calculated as follows:
a = R1X1/C0 = exponent of production function
b = 1 – a = exponent of production function
Q = t0*X1 = total traffic in minutes per year
A = Q*(R2)b/(b*C0*(X1)a) = constant of production function
In the X1X2 quadrant, production function and cost function are described, as a function of X2 assumed as independent variable, by the following:
X1 = (Q/A)1/a*(1/X2)b/a
X1 = C0/R1 – R2*X2/R1
The point of tangency is given by:
X10 = X1
X20 = (Q/A)1/b*(R1/a*C0)a/b
Calculations made for the year 1984 (Annex 13) show that the optimum combination of variables, as tangency point, are: X1 = 2.636.000 lines, X2 = 18.210 employees. Labour is greater than the actual one, nevertheless either operating efficiency (about 146,44) and profitability (about 58,31%) almost equal the ones calculated under the first approach. In the year 1995 (Annex 14), the optimisation of process gives a value for X2 reduced, with reference to year 1984, by 370 units: this produces an increase (about 227,55) in the operating efficiency. Productivity ranges between 32% and 39%. Again, the model suggests the opportunity of reducing personnel to increase operating efficiency and to reduce, as much as possible, the operating annual expenses.
9. Conclusions
The decisions of Provider took place in a scenario initially controlled by Government Authority (monopoly) and, subsequently, subject to market forces (competition); the model should, then, have been framed into the actual situations the Provider had to face. This lets understand which of the variable included in the process can be changed to respect rules and to satisfy objectives.
In particular, if the profit is the main objective of the Provider, the personnel policy becomes an important part of the whole strategy; it has impact upon both the output provided and the earning. It should not be ignored that, even if the personnel is kept constant over time (which would be impossible in the long run) the salary per employee is, anyway, increasing making the relevant expenses increasing.
itc/casestudy 27/2/2002