“Change” was the slogan of the British Labour Party in the recent General Election. It certainly didn’t do serious damage to electoral prospects; but it is a curious slogan nonetheless. Change, after all, can be for the better or the worse and, irrespective of the directional movement, it generally entails costs of varying types.
We have mentioned two examples of those costs in previous Insights blogs. Here, after summarising the earlier examples, we take a wider look at the matter.
The first example was from a study for the Cabinet Office of the burdens of regulation on small manufacturing businesses. It found that changes in regulations were viewed by managers as more burdensome than was compliance with well established regulations. They required the attention of more senior personnel, whose bandwidths (time and attention) were diverted toward working out, and then adjusting to, the implications of new regulations for their businesses. Bandwidth devoted to the actual operations of the business was correspondingly reduced, with negative consequences for performance.
The second was the ‘Penrose effect’ (named after Professor Edith Penrose). In this case, the proximate stimulus for change is a decision to attempt faster business growth — although that decision may itself be prompted by external changes in the market environment such as the availability of a new technology or a shift in customer requirements. Again, growth places demands on senior management bandwidth which pull attention away from other business activities like improving the productivity of existing assets. There is, therefore, an opportunity cost of growth.
The two examples differ only in the proximate stimulus for change, one external to the firm (new regulations), one internal (a decision to expand the business). In both cases, the focus is on the re-allocation of limited bandwidth at the top of the managerial tree, but the reasoning generalises to all other re-allocations or re-configurations of resources within a business.
The costs of such re-configurations can be viewed as akin to the ‘exchange transactions costs’ introduced into economics by Ronald Coase in his seminal paper ‘The Nature of the Firm’. Like those market transactions costs, they are largely neglected in the teaching and practice of economics, which is typically based on an assumption that change is frictionless. Thus, the optimised cost function of a firm is usually specified in terms of output, q, and a binary time variable, B, that distinguishes between a ‘short’ run and a ‘long-run’, C(q,B).
In more specialised analyses the notion that change has costs has been recognised and cost functions, including for investment costs, have been adjusted to C(q, dq/dt), where dq/dt is the rate of change of output. In these contexts they are usually referred to as ‘adjustment costs’. We, however, prefer the expression ‘reconfiguration costs’, to emphasise two things: (a) the networked structure of the deployment of assets within a business and (b) the conceptual similarity to ‘exchange transactions costs’, which themselves are entailed by the re-allocation of economic resources that occurs when a buy/sell transaction is effected.
Adding the rate of change to the analysis dispenses with the requirement for the binary short-term/long-term variable and, more importantly, introduces an explicit time-cost trade-off into the analytics, albeit in a rather simplistic way. This reflects a reality that is to be found across a wide range of contexts: the more quickly you want to do something, the more costly it will be to do it. Pressure of time can bring more mistakes in the execution of a planned re-configuration; a higher cost technology may be adopted by virtue of its immediate availability; and so on.
The time variable now represents real time, not the hypothetical time of the binary variable, and there will be rates of change that are simply infeasible to achieve. The point is captured in the old saying ‘Rome wasn’t built in a day’. Re-configuration of the internal resources of businesses takes (real) time.
This time-cost trade-off figures most prominently in public policy today in the area of decarbonisation, with its heavy focus on the setting of dates by which specified changes are to be made. We do not ourselves favour such heavy reliance on this quantitative targeting approach, but, if it is to be adopted, it requires the paying of particular attention to the setting of target dates. The shorter the time period specified, the higher the rate of change that is mandated, and the higher the rate of change the higher will typically be the costs of meeting the target. At least some attempt to quantify the cost function is therefore essential for better decision making, yet it is rarely doje.
If it is asked, how do the estimated costs of achieving net zero by 2045, 2055 or 2060 compare with the costs of achieving it by 2050, considered answers are not to be expected. More than that, it may be treated as a question that should not be asked. But it should be.