Project Practitioners > Are Your Metrics Meaningless?

Are Your Metrics Meaningless?

By Patti Gilchrist

Data is an essential corporate asset, critical for the continued success of any business. Data empowers organizations to make critical decisions and drives strategy. Thus, organizations often enthusiastically collect and report a variety and abundance of data, with the mindset that more is better. However, if not managed effectively, this mass of data may not provide enough meaningful or measurable value and may actually produce misleading conclusions.

When implementing a system of metric collection and reporting, there are potential roadblocks that can derail the entire process, leading to meaningless metrics.

A common cause of error is an inadequate data collection plan. Another potential cause of failure is using metrics to focus more on the performance of people rather than on the process itself.  While individual performance is significant, it is more beneficial to examine the process, since the process drives the performance of people. A culture which uses metrics in this manner will risk creating an environment in which those who are performing and/or managing the work may actually impede and undermine the data collection process by creating workarounds in their work procedures to distort metric reporting in order to show an overstated sense of accomplishment.

Recently, I experienced an example of this phenomenon in action when I called an outsourced support center to resolve a customer service issue. My issue was assigned a ticket number for tracking. At the end of the call, although my issue was not satisfactorily resolved, I was informed that my ticket would be closed at this time. When I vociferously objected, stating that my ticket was not ready to be closed because my issue had not been resolved, I was abruptly informed that the process requires all tickets to be closed at the end of each call regardless of status. I was further instructed to call back at another time to open a new ticket if the issue persisted. Hearing this, I was more than a bit suspect of this process. Needless to say, I was frustrated at this blatant attempt by this department to overstate accomplishment at the expense of customer satisfaction. 

The metrics produced by this department would be unreliable, inaccurate, and essentially provide an exaggerated sense of accomplishment and an understated failed customer interaction (FCI) rate. These metrics would show an:

  • Artificially high volume of tickets handled.
  • Inflated resolution rate.
  • Inadequate representation of rework.

In this case, the organization is collecting an abundance of data. However, the organization lacks a sound data collection plan. The resources performing and/or managing the work are actually impeding and undermining the data collection process in an effort to report overstated progress and accomplishment. As a result, the metrics lacked data quality (data quality refers to how closely data reflects or represents actual events and trends) and date integrity (data integrity refers to how accurate and correctly data mirrors the source of data). More is not always better. The focus should be on data quality rather than quantity.

To ensure your metrics are meaningful, consider the following:

  • Focus on improving the underlying process vs the people.
  • Focus on data quality and integrity vs data quantity.
  • Develop a sound data collection plan to gather reliable and statistically valid data. A data collection plan must identify:
    • What are sources of data?
    • How will data be collected?
    • Who will collect the data?
    • Validate the accuracy and reliability of data.      

Otherwise, your organization may not realize the true potential of the data, and essentially your metrics will be meaningless.

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