Page 278 - Operations Strategy

dEvEloPIng oPERATIons CAPAbIlITIEs 253
branches it serviced. Over time it learned how to organise itself and to use the machines
effectively. Although the data in Figure 7.9 stops at a point in time, future learning
can be extrapolated from the operation’s ‘learning history’. This enabled the bank to
establish its capacity requirements for the future, work out the cost savings from using
such large processing operations and provide improvement targets for this and other
similar operations.

Limits to experience-curve-based strategies
There are clearly risks associated with any strategy that is based exclusively on one form
of analysis. In this instance, basing the long-term competitive viability of a firm solely
on the potential for ongoing cost reduction is open to a number of serious criticisms:
● Attributing specific costs is notoriously difficult and overhead costs are often arbi-
trarily allocated. In addition, units may perform poorly because they have the oldest
capital equipment and their volume–variety mix may be inappropriate – factors that
the experience may not capture.
● The product or service may be superseded. Innovation from within or, even less pre-
dictably, from outside of an industry can shift the competitive ‘rules of the game’.
● Relentless pursuit of cost reduction (to the detriment of all the other key perfor-
mance measures) can lead to operational inflexibility. Although traditional trade-off
models are questioned in the ‘world-class operations’ paradigm, there remains an
inevitable link between cost and flexibility.
● The control of cost is not the only way that an operation can contribute to the com-
petitive position of the firm. Competing on quality, service, speed etc. are all equally
viable strategic options.

process knowledge
Central to developing operations capabilities is the concept of process knowledge.
The more we understand the relationship between how we design and run processes
and how they perform, the easier it is to improve them. No process will ever reach the
point of absolutely perfect knowledge – but most processes can benefit from attempt-
ing to move towards it. Moreover, few if any processes operate under conditions of total
ignorance. Most operations have at least some idea as to why the processes behave in
a particular way. Between these two extremes lies the path of process improvement
along which operations managers attempt to journey. It is useful to identify some of the
points along this path. One approach to this has been put forward by Roger Bohn. He
6
described an eight-stage scale ranging from ‘total ignorance’ to ‘complete knowledge’
of the process (see Table 7.4).
● Stage 1: Complete ignorance – There is no knowledge of what is significant in processes.
Outputs appear to be totally random and unconnected with any phenomena that
can be recognised.
● Stage 2: Awareness – There is an awareness that certain phenomena exist and that they
are probably relevant to the process, but there is no formal measurement or under-
standing of how they affect the process. Managing the process is far more of an art
than a science, and control relies on tacit knowledge (i.e., unarticulated knowledge
within the individuals managing the system).

M07 Operations Strategy 62492.indd 253 02/03/2017 13:06