AAOM Handbook

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Operations experience special causes as part of production and service strategies or random operational risks. Special causes are identified on the control chart of the process that is modelled. For example, an operation can experience an extended number of rain days each year or face seasonal changes that significantly affect performance output and hence confidence to meet Business Expectations. The BSP model must take this into consideration, service strategies, recurring operational risks and seasonal or mining domain operating levels to be representative of the shape of the output distribution. The accountable person must use discretion to assess once-off and recurring events and their frequency and impact. This is done because SPT scenarios guide strategies and the OMS/SES. Upon studying the data using control charts, the accountable roleholder must assess data points that are zero or fall above the UCL or below the LCL, including points above and below the mean. These data points are considered as special causes and need to be incorporated into the BSP model calibration as they affectthe performance output. Step 1: Count the number of special causes and separate them into their respective special cause classification, see Table 2 below:

Table 2 - Special Cause Classification

In this example there were 47 special causes due to data points being below the LCL and 10 special causes due to data points at zero over a 365 days period as analyzed from the control chart in Figure 7.

Figure 7 – Control chart to analyze special causes

Operational Planning: Building a Business Structure Performance Model Page 12 of 39