Case Synopsis
Deutsche Allgemeinversicherung (DAV) is one of the world’s largest insurance companies. In 1996, 51%
of DAV’s business was in Germany in which 60% was in retail insurance. Managers of other firms say
DAV’s strengths lie in both “sound, traditional insurance management” and “outstanding customer
services”. The insurance company has cutting-edge technology. Insurance service products are
increasingly becoming homogeneous (and easy to replicate), and not only does DAV compete against the
other giants of the industry, but in addition the company has many smaller insurance companies as
competitors. Differentiating DAV’s customer service can be used as an advantage over competitors. DAV
had decided to adopt a new quality improvement initiative; PMV in order to maintain its prominent position
due to the looming competition and increasingly customer demands. Annette Kluck, the architect behind
PMV, was head of Operation Development at DAV. The PMV project was a revolutionary effort which
used manufacturing-style improvement techniques to make improvements in insurance services; it will
differentiate DAV in the industry and hopefully help the company maintain its prominent position. Kluck,
however, was facing a number of difficult problems with the improvement phase of the project. Prior to
1994, correct transcription from forms had been assured using a method called Double-key entry. There
were two problems with this method of assuring accuracy. First, it was very expensive, since it essentially
demanded that work be done twice. Second, it was found that first-pass quality actually deteriorated over
time when the double-key method was used. To find out what accuracy levels were like throughout DAV,
Peter Kolb and Kluck selected New Policy Set-up as a pilot measurement project. The plan was to take a
sample of the work carried out by the associates, and use that sample to infer what the general accuracy
rate was in the New Policy Set-up process. To carry out the experiment, Kluck decided to use SPC which
has traditionally been used for continuous variables such as the diameter of a piston. According the SPC
practice in manufacturing, a p-chart is used to measure processes. In such a process, a person would
measure five components every few hours, and mark the sample average and range of the measurement
on the p-chart. The PMV project was launched and divided into two phases- Measurement and
Improvement. Inconsistencies in service quality require systematic monitoring to see if they are random,
regular, or indicative of a problem. However would these improvement techniques work, and if so, how
will DAV use this information to actually improve the performance of the various processes and therefore
improve customer service? In achieving this goal, DAV set out to improve on the quality of its service by
reducing variability in its process. Organizations typically move through four quality improvement cost
stages:
Prevention cost: At this stage, the organization incurs these costs while preventing variations that leads to
loss of quality of its service.
Appraisal cost: This is an assessment cost. Organization incurs this cost while trying to evaluate the
current position of its process.
Internal cost of defect: These costs are incurred when organization tries to correct an error in its process
before delivery to its customers.
External cost of defect: These are damage control cost. Organization incurs these costs trying to deal with
the consequences of delivery of poor products or customer service.
Quality control means organizations must be proactive by constantly appraising their quality control
processes with the goal of avoiding both the Internal and External costs of defects by preventing defects
and errors in their processes. At the moment, in an attempt to maintain their dominant position in the
industry and also to differentiate the company from the competition by developing a company-wide
capability, DAV is trying to reduce their internal and external costs of defects by incurring more prevention
and appraisal cost. A shift in this direction is necessary for the company to achieve its goal.
Statistical Process Control
Statistical Process Control (SPC) holds the basic idea that it is extremely expensive to inspect quality into
a company’s outputs and much more efficient and effective to produce them right in the first place. SPC is
a tool of the Six-Sigma Improvement Methodology, also known as Total Quality Management (TQM).
Though originally developed for quality control in manufacturing, it is applicable to all sorts of repetitive
activities in any kind of organization. Thus, TQM effectively switches appraisal emphasis from inspection
to process control. SPC is a method for achieving and maintaining quality control. It is a set of methods
using statistical tools such as mean, variance, and others to detect whether the process observed is in
accordance to standards. The goal of statistical process control is to make a process stable over time and
to alert management if the variation is excessive. For Kluck, SPC tracks the proportion of applications
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inputted correctly and incorrectly in each sample in order to measure, analyze and improve the quality of
customer service. SPC, traditionally used in the manufacturing industry for the measurement of
continuous variables, can be tailored to the service industry, but this can prove to be rather challenging. In
comparison to SPC application in the manufacturing industry, the service industry is harder to measure. In
the case of DAV, SPC implementation for the New Policy setup group was not straightforward. Items that
DAV needed to measure were not on a sliding scale- a new policy request was either entered correctly or
incorrectly. The Human Factor, unavoidable in the service industry, makes it difficult to determine how to
measure, what to measure, what values are acceptable and when a problem actually is a problem. There
is significant chance of motivational use of data and there are many sources of variation in this industry,
which could possibly lead to dysfunctional measurement and the misuse of SPC. Methods were
developed for measuring the quality of a number of process steps at DAV, such as the process for
