AAOM Handbook

[OFFICIAL]

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Step 2: Set up table or use a similar method of that depicted in Figure 8 below. This table is used to determine the probability of a special cause occurring and the impact the special cause will have if it does occur.

Figure 8 - Incorporation of special causes into stable data distributions The probability column of Zero days was calculated using a Binomial distribution (a 1 or a 0) with a probability of number of zero days divided by total number of days. This distribution is used over the period of 365 days.

The percentage impact column for zero days is 100% throughout, as any zero day will have a 100% impact on the performance and throughput of the operation. The probability column of days below LCL was calculated using a Binomial distribution (a 1 or a 0) with a probability of: = total days below LCL = 47/365, the function typically looks as total number of days follows:

The distribution will generate random statistical percentages according to the impact parameters used, i.e. biggest impact percentage of a special cause, least impact percentage of a special cause and the average impact that a special cause has.

The parameters are described as follows:

PERT(X, Y, Z) X – The special cause that has the least impact in terms of percentage. Y – The most likely impact that the special cause has in terms of percentage. Z – The special cause that has the highest impact in terms of percentage.

It is also important to observe from the control chart whether summer and winter periods, for example, (or other prevailing scenarios) have different operating levels. If the operating levels are significantly different then roleholder should be able to input separate parameters for each season operating level as depicted inFigure 17 below:

Operational Planning: Building a Business Structure Performance Model Page 13 of 39