As mentioned in Designing scorecards and generation of scorecards, its not only 'what has happened?' which is important, but also 'why it has happened?' and 'what are we going to do about it?’
The issue is- In typical KPI definitions, we provide the details on
- What that KPI means?
- What are the standards and expectations around the KPI?
- What will be defined as the exceptional performance (below and above expectations) to KPI?
- Data Sources for the KPI
- Functional linkage
The above information is required to generate a KPI and its position in a scorecard or a dash-board. However, this information is not enough to enable the business management around the KPI. It is assumed that managers will manage their performance by their own methods. However, it may help greatly, if some level of documentation can be created on 'KPI management' as well. The KPI management will include the answers to the following:
Interpretation of the KPI performance: for example- what should be the interpretation of a low sales productivity?
If the KPI performance is coming lower than expected,
- Check on the pipeline status – If the pipeline status is higher than usual, it might be just a timing issue and you may catch-up next period)
- Any significant attrition of high quality sales force.
- Any sales campaign finishing in the previous period
- Higher proportion of new sales force
- Higher proportion of new sales offices
If the KPI performance is higher than expected:
- Any sales campaign in the period
- Any recent geographic expansion in past few periods (as a new office takes some time to start adding value)
Action to take on the basis of interpretation-
- Speeding up the training of the new sales staff
- Manage the attrition for sales force. Review the incentives and sales compensation
- Review the competition landscape. Are we moving to the flat product life-cycle?
Linked Metrics- the KPIs with which this KPI is linked. For example the sales productivity in value can be linked to:
Cuts across dimension- Though a KPI can be cut across many dimensions, but there might be few more important ones. For example:
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