Key Performance Indicators (KPIs) for Land Release and Stockpile Destruction Operations

  • Version
    Ed. 1
  • Latest amendment
    01 Mar 2021

We cannot really understand and manage the work we do unless we measure it. This means using indicators, some of which may be important enough to be designated as Key Performance Indicators (KPIs). KPIs help us understand performance. They are essential, not only for the day to day management of operations, but also for the monitoring and evaluation of operations.

 

Within mine action KPIs are primarily operational analysis tools. They provide a framework for analysing data. Without appropriate data subject to credible Quality Control (QC), a KPI will be of limited or negative value. Indicators are dependent on the collection of accurate and relevant data from the field. This requires well designed forms that capture data whilst not overburdening field operators. There is a finite amount of data that can practically be collected from the field. Invariably, not everything that is desirable to know is practicable to collect. Overambitious levels of data collection can result in lower quality data collected. What data is prioritised for collection is a choice. Operations managers should be clear about exactly what they want to measure and ensure that no superfluous data is collected. Field staff ought to fully understand that the data they collect is fundamental to their operational efficiency and effectiveness and not simply an Information Management (IM) concern.

 

Operational KPIs should be routinely used by operational staff. Furthermore, data should be subject to effective QC, by both operations as well as IM staff.

 

In the history of mine action use of KPIs has been limited. Often this has been justified by a concern that statistics, including KPIs, can easily be misrepresented or not presented in a fair context. This is usually summarised by the apocryphal phrase “lies, damned lies and statistics”. This is not a justification for not using KPIs. It is a justification for using them appropriately by making sure the supporting data is as accurate as possible, and that the KPIs are always viewed strictly in context.

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