Benchmarking
engineer
availability
7
Benchmarking the engineer
availability process
A case study
S. Evans
Regional Service Developnent, Automobile Association, Stanmore,
Middlesex, and
B.G. Dale
Quality Management Centre, Manchester School of Management,
UMIST, Manchester, UK
Introduction
As competition is becoming increasingly globalized more focus is being placed
on an organization’s ability to anticipate and respond to changes in customer
needs and expectations. To this end the company which is the focus of this
paper wished to understand more about the capability of its predictive
processes. The company is involved in the servicing of capital equipment and
employs over 4,000 people in 50 locations across the UK. It involves revenues of
more than £750 million per year. The company is international in configuration
and controls the activities of more than 24,000 employees in over 80 countries
throughout Europe, Asia and Africa with an annual sales turnover exceeding
£2.7 billion.
For the purpose of the paper a predictive process is defined as a business
process which seeks to forecast an element or elements of an organization’s
operation and to assist in the successful running of that business as set against
customer requirements. One such process is the engineer availability process
which seeks to predict customer demand for service calls and match these
against an available supply of engineer resource. This paper examines how a
benchmarking exercise has enabled the host company to add value to its
engineer availability process.
The engineer availability process: what is it?
The engineer availability process (EAP) seeks to predict customer demand in
terms of the incoming call rate and match this against the available supply of
engineer resources. The operation of the process differs between the host
company’s business units (BUs). However, there is an underlying assumption
that predictions of customer demand are not 100 per cent reliable and
consequently a flexible revision of supply is built into the process.
Benchmarking for Quality
Management & Technology,
Vol. 4 No. 1, 1997, pp. 7-17.
© MCB University Press, 1351-3036