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Abstract
Rating tendencies of Managers in an
organization vary from a 'very lenient' rate to a 'very harsh' rate.
The employees reporting to them experience the impact of these
variations. This impact becomes crucial in an environment where
employees are given performance based remuneration/ incentives.
Normalization of scores is intended to introduce greater objectivity in
the Employees Performance Management (EPM) System of an organization.
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Rating Patterns of Managers
It may be observed from the figure
above that Manager 'A', compared to Manager 'B', has the tendency to
rate most of his subordinates at 7 to 8 points on a Performance rating
scale of 1 to 10. Manager 'C', on the other hand, is highly
conservative and awards given to the best of his subordinates are in
the range of 5- 6 points. Thus an average performer with Manager 'B'
gets equated with the Best employee reporting to Manager 'C' and with a
low average subordinate of Manager 'A'. The training of Managers A, B
& C on the rating norms may improve this trend marginally
during the subsequent years. But what happens to the evaluations
already done by them? How has the company management looked into this
problem which has an impact on promotions, compensations and career
management of all employees? Some outstanding performers (placed under
a harsh rate like Manager 'C') may quit the organization and some low
caliber people (placed under a lenient rate like Manager 'A') may
themselves be the Managers of tomorrow. This vicious cycle tends to
boost the average performers who cling to their jobs and promote
mediocrity in the organization. A performance driven company can ill
afford the luxury of losing their best talent. They have to normalize
the rating trends of their Managers and weigh employees performance in
the correct perspective.
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What does normalization mean?
Assume there are ten Managers in an
organization who are reporting on 10 different executives each and
these Managers, in turn, report to three different Senior Managers, in
their respective departments. In this scenario of EPM, there are 13
different 'Appraisers' who are reporting on 110 employees in the
organization. Amongst these employees, 100 are at the same level (ie,
Executives) and 10 are at the level of Managers. Each of the thirteen
Appraisers has a rating style which is different from the others. So
the employees reporting to them have a high degree of variability in
their performance appraisal scores. The process of balancing this
variability is called 'Normalization'.
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Normalization Process
The process comprises of the following
steps:
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Statistical
Mean' of organizational rating pattern of all the Managers (ie,
Appraisers) at the same level, across various departments, is computed.
Let this Mean be 'M'. |
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Statistical
Mean for each of the Appraisers at the same level (ie, for all the 10
Managers in the example given above) is computed. Each Manager should
have done the Appraisal for 40 to 50 employees (may be over the last 5
years). Let this Mean be 'Mi' (i = 1 to
10). |
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A
correction Factor (CF) for each of these
Managers (Appraisers) is then computed = Mi/M.
Its value, for example, will be 1.0 if the rating pattern of a Manager
is the same as the statistical Mean for all the Managers. |
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Performance
Score of each individual employee is divided by CF for his/ her Manager
to compute its normalized value. This normalized score is utilized for
all management decisions. |
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Connected issues
- To implement the normalization
process, there may be a need to extract information from the Appraisals
completed during the last few years so that the statistical Mean for
each Manager could be computed based on the 40 - 50 appraisal reports
written by him/ her. This requires a data base approach.
- When a Manager has not completed 40
to 50 appraisals, how to find out his/ her Correction Factor (CF)? The
approach, normally adopted, is to compute the mean Mi & CF for
the Manager based on the number of Appraisals so far completed, but not
to apply the CF to the Performance scores of the employees without
discreet approval by the Management. (Note:
Some organizations prefer to use in such cases, the normalized score
awarded by the Reviewer).
- Since the Appraisers tend to refine
their rating tendencies automatically as the years roll by, some
organizations prefer to use the Moving Mean concept (MMi)
for each Manager rather than the Mi. The
moving mean for a Manager is an indicator of the improvement in his/
her rating trend. CF = MMi/M is the
computing algorithm used in this case.
- In mid to large organizations, with
4 to 5 different levels of Appraisers, a number of departments/
functions and employees varying in strength from 200 to 5000 (+), it is
not possible to normalize the Appraisal scores without automation of
the entire process.
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Conclusion
In some organizations, normalization
of performance scores is managed by a high level committee and the
process is not made transparent to the employees. If such committees
keep in view the rating patterns of various managers such as MMi
(discussed above), their decisions would be data based & hence
objective.
'EmpXtrack Employee
Appraisal' caters, in its enterprise level solution,
all the normalization features discussed above. Whether to utilize the
auto-normalization process or not is an option available to the client.
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