Applied project management #16. The control chart
The Control chart and the rule of seven
One of the contractual clauses of a project is strict adherence to a schedule variance within +- 10 percentage. The customer will do the review of the project every fortnight, and if the schedule variance is above 10% then there is a penalty clause. That is the customer specification limit. Will you go for that project or not?, that is the question.
If the supplier's capability limits (UCL - Upper control limit, LCL - Lower control limit) is within the customer's specification limit, then there is no risk involved. If the suppliers capability is below the customer specification limit, then there is a risk. We may still go ahead with the project, by taking appropriate risk response planning, and contingency planning.
Once the project starts, the fortnightly reviews start and we get data points a,b,c,d,e,f,g,h,i,j,k. Data points a and b are within the customer specification limits and within the organisations capability limits (LCL, UCL). So the customer and the quality control department will not complain. The data point 'C' is outside the organisations capability limit, so the QA department will complain. Since it still within the customer specification limit, the customer will not complain. In this case we have to perform a root cause analysis (RCA) to understand the root causes leading to this deviation, in order to correct it.
The data point 'D' is surely an outlier. It is lying beyond the customer specification limit. The customer will complain. Again we have to perform a root cause analysis to understand the real root causes and correct them. The root causes can be random or assignable. For random causes we will not be able to take corrective / preventive actions, where as for assignable causes we can.
After the corrective action, the subsequent data points e,f,g,h,i,j,k are within the customer specification limits, hence there wont be any customer complaints. Of these f,g,h,i,j,k are happening next to each other. Whenever we see a cluster of seven data points happening next to each other we call it as 'Rule of seven'. A rule of seven can happen anywhere on the control chart. Whenever we observe a rule of seven, we must perform a root cause analysis to find out why it is happening. If the rule of seven is happening within the UCL and the LCL, then we can infer that something good (best practices) are happening, and we must investigate so that we can institutionalise them. If the rule of seven is happening outside the LCL and UCL, then it could be because of some bad practices. In this case, we must correct and prevent them from future occurrence.
All the quality gurus like Deming, Juan, Crosby were dead against slogans of improvement. They always believed in measurements. Without a control chart , no reliable and sustainable improvement is possible.
One of the contractual clauses of a project is strict adherence to a schedule variance within +- 10 percentage. The customer will do the review of the project every fortnight, and if the schedule variance is above 10% then there is a penalty clause. That is the customer specification limit. Will you go for that project or not?, that is the question.
Once the project starts, the fortnightly reviews start and we get data points a,b,c,d,e,f,g,h,i,j,k. Data points a and b are within the customer specification limits and within the organisations capability limits (LCL, UCL). So the customer and the quality control department will not complain. The data point 'C' is outside the organisations capability limit, so the QA department will complain. Since it still within the customer specification limit, the customer will not complain. In this case we have to perform a root cause analysis (RCA) to understand the root causes leading to this deviation, in order to correct it.
The data point 'D' is surely an outlier. It is lying beyond the customer specification limit. The customer will complain. Again we have to perform a root cause analysis to understand the real root causes and correct them. The root causes can be random or assignable. For random causes we will not be able to take corrective / preventive actions, where as for assignable causes we can.
After the corrective action, the subsequent data points e,f,g,h,i,j,k are within the customer specification limits, hence there wont be any customer complaints. Of these f,g,h,i,j,k are happening next to each other. Whenever we see a cluster of seven data points happening next to each other we call it as 'Rule of seven'. A rule of seven can happen anywhere on the control chart. Whenever we observe a rule of seven, we must perform a root cause analysis to find out why it is happening. If the rule of seven is happening within the UCL and the LCL, then we can infer that something good (best practices) are happening, and we must investigate so that we can institutionalise them. If the rule of seven is happening outside the LCL and UCL, then it could be because of some bad practices. In this case, we must correct and prevent them from future occurrence.
All the quality gurus like Deming, Juan, Crosby were dead against slogans of improvement. They always believed in measurements. Without a control chart , no reliable and sustainable improvement is possible.
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