Wednesday, 19 September 2012

Data Quality - the Missing Dynamic

When monitoring the productivity of your workforce, there are many tools that can help you to manage their workflow. One of the favourable outcomes of these workflow systems is the ability to generate management information on the productivity of your colleagues.

There are two basic measures that typically arise from workflow as MI - Efficiency and Effectiveness. Efficiency is a measure of the time they are actually working expressed as a percentage of the time they are available for work. Things that affect efficiency are unplanned interruptions in work. Effectiveness is the volume of work completed as time, expressed as a variance of the time available for work. Highly effective colleagues achieve a high volume of work in a shorter timescale.

With the drive for ever greater efficiency and effectiveness, data quality can suffer greatly. To get around this, the easiest way is to set up sampling plans for each colleague. However, when deadlines get stretched, this is usually the first thing to be de-prioritised. With sampling, you are also relying on luck to capture errors.

This is where data quality tooling can become a valuable asset for your organisation. Building business rules for processes, capturing the data and scoring each colleague on the quality of their work is a valuable and powerful addition to your productivity measures. It ensures that the drive for throughput does not adversely affect your quality. This will deliver greater efficiency by enabling more time to be spent delivering your services and less time remediating data.

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