Editorial

Citation

Bourne, M. (2003), "Editorial", Measuring Business Excellence, Vol. 7 No. 4. https://doi.org/10.1108/mbe.2003.26707daa.001

Editorial

Mike BourneCentre for Business Performance at Cranfield School of Management.

There is an old adage in performance measurement, "What gets measured, gets done". This has been the guiding principal behind much of performance measurement over the last decade. "Deciding what matters and measuring it" was the principal behind many a balanced scorecard implementation in the private sector. The public sector have taken up this principal too and in the UK we have league tables for schools, hospital waiting lists and a whole raft of measures imposed on public sector organizations by central government.

And then it occasionally goes wrong. The USA recently experienced wide spread power outage across a wide number of states. Lack of investment in transmission infrastructure has been suggested as a possible cause, but why should this happen? Did the measures imposed by the regulator have any influence on investment decisions? A similar but smaller incident occurred in south London and some politicians were quick to criticize the power companies for their lack of investment. At the time of writing the cause actually appears to have been two unconnected breakdowns in the system that happened to have occurred in a very short time period – causing the power cut. The cause was therefore a random fault which could have been predicted, but whose likelihood of occurrence was extremely small. Should we have invested to prevent this occurrence? We expect the power companies could have done, but that this would probably have been a waste of scarce resource.

So how does performance measurement help us in these situations? The answer is that our guiding principal is not always correct. We need a different way of using performance measures.

Douglas McGregor proposed two theories for performance management, Theory X and Theory Y. Here we want to take a similar approach to performance measurement, but we will call them "Theory M" and "Theory P".

Theory M

"M" is for motivation. Theory M is therefore all about our guiding principal of "What gets measured, gets managed". It assumes that people are inherently lazy and so need to be measured. If they are not lazy, the theory assumes that the individual's goals may not align with those of the organization, so organizational measures need to be implemented to direct individual's actions towards meeting organizational goals.

The practices associated with theory M are well known. We teach target setting based on this principal. Targets should be stretching – high but obtainable. We expect these goals to be achieved simply by setting a target, devising a measure and ensuring encouragement through reward and punishment.

Theory P

"P" is for process. Theory P is therefore all about processes, their measurement, management and capability. Theory P comes from a totally different academic discipline, operations management. It assumes that processes deliver performance and that processes have a natural capability. Output from a process will vary, but this variation is natural and can be measured statistically. The capability is then the normal output of the process between the normal limits of its variation.

The practices associated with Theory P are not so well known – certainly to the general public. Statistical process control is one example and tools such as Shewhart charts. Theory P proponents improve performance through improving the processes. They would argue that motivation has little place here. All Theory M practitioners do is distort the measurement system without delivering sustainable performance improvements!

The theories in practice

In the private sector we regularly see the use of both theories. The classic use of Theory M is on sales force re-numeration. Double-glazing salesmen and financial consultants have been motivated this way. It promotes competition and rewards sales success – although if not managed properly there can be undesirable side effects. In the private sector too, we also see the use of Theory P in the operations of the business. Process measurement and management is widely practiced in manufacturing but also used in more integrated service functions where coordination is important. Business process engineering is one example of tools used by Theory P practitioners.

The public sector is slightly different. There is now widespread use of Theory M, particularly in the UK. Government appear to believe that targets, league tables and thousands of quantified measures will force organizations to perform. Additional funding or special status is accorded to the best performers, closure and reorganization to the poorest performers. Restructuring does occur, but much more emphasis is placed on restructuring the reward systems than on the fundamental underlying processes. This may be why some of our infrastructure services do not always deliver what we expect.

Further, the two approaches produce fundamental differences in the way we manage; specifically:

1. 1.

   Theory M practitioners pay for results. Money is paid after the event as a reward for performance.

2. 2.

   Theory P practitioners pay for process improvement. Money is paid (or invested) in the process before the performance is achieved.

So we have some interesting tensions between these two approaches. Balance may be the answer, but more interestingly we should consider the appropriateness of each situation and mix and match our use of theory accordingly.

This issue

In this issue we look at a broad spectrum of performance measurement and management practice.

We start with Ken Euske's paper on the use of performance measurement in the public and private sector from a USA perspective. He argues that often we emphasize the differences and ignore the similarities. Hence we forego the opportunity to learn.

This is followed by James O'Kane's paper on simulation, an author taking a Theory P approach.

Arezes's paper is on safety culture and takes an interesting approach to measurement in this field. Are our traditional measures sufficient to give us confidence that we will not have accidents, or do we need a different approach?

This is followed by Castka's article on the performance measurement of teams, an often-neglected area sandwiched between organizational and individual performance measurement.

Mike Kennerley, Andy Neely and Chris Adams then write about the evolution of performance measurement systems in companies and in particular they focus on the capabilities companies need to have to keep their measurement system current.

Finally, we have a paper from Chang on the integrated circuit industry in Taiwan. This paper takes a resource based approach.

So this edition is very Theory P biased. Looking ahead, the next edition will be more balanced, as we will be focusing on the conflicts found in planning and budgeting, an area where Theory M and Theory P collide. The second edition in 2004 will then focus on compensation in performance measurement, redressing the balance in Theory M's favor.