Going Beyond Lean Six Sigma and the Balanced Scorecard

QUESTION: I want to produce subgroup samples for statistical process control (SPC) purposes. I have a database from our call centre that holds information on the following: time call received, type of call (response graded 1-5 in order of severity – 1=emergency call, 5=call taker resolved with no police attendance required), time resource allocated to incident, time of arrival, time resource left incident, time incident closed, etc.

From calls received, we create approx. 30,000 incidents per month. If I take one month’s worth of data and import it into Minitab, how can I filter it to create a subgroup sample? Based on my (somewhat limited) knowledge of statistical process control, what I think I want to do is create a subgroup sample that takes n measurements every x minutes (e.g. say 10 measurements every hour), over the course of a day and then over the days in the month. I’d like to use this sample to determine what is currently ‘normal’ in our response process so that I can show how the time taken between call receipt and police attendance differs by type of call, hour of day, day of week, etc.

Is there a simple way in Minitab to achieve this type of sample?

RESPONSE: Control charts are set up to check for process stability, not assess inputs that can impact a response. You should be able in Minitab pull a sample and put it into a control chart. However, for what you want to do I suggest decrease your frequency of subgroup (30,000-foot-level control chart format) so that potential common-cause input variability occurs between subgroups; e.g., might subgroup weekly. Process capability can also be assessed as described in: x-bar and R charts and alternative

You should then pull data from regions of stability to statistically test hypotheses that you mentioned above using tests such as Analysis of Means, which can help gain insight to what you might be done to improve.

In his state of the union address, President Obama said that he is open for suggestions to address the problems that we are currently having. However, with our current Congressional procedures, suggesting and implementing some of the right things to do for the country, as a whole beyond party boundaries, could be individual political suicide. Continue reading →

The simple setting of goals and tracking metrics variances to these goals does not make improvement occur. Traditional charts such as a table of numbers, pie charts, stacked bar charts, and red-yellow-green scorecards can lead to much firefighting. In addition, using these charts to run a business is not unlike driving a car by only looking at its rear view mirror. What is needed is a no-nonsense predictive performance measurement system. Continue reading →

In this second part of a 2-part series (i.e., follows Part 1), the Define phase problem statement and project charter of the Lean Six Sigma Define Measure Analyze Improve Control (DMAIC) roadmap is further elaborated on, where there is a true integration of Lean and Six Sigma tools in the roadmap.

- Goals for the project should be targeted and measurable. When appropriate, it is beneficial to express goals in Cost of Doing Nothing Differently (CODND) units. CODND has advantages over a traditional Cost of Poor Quality [COPQ] approach since a specification is not required for this type of financial reporting.
Example: Reduce the median call wait time to 40 seconds or less, yielding an estimated $250,000 per year benefit at the ABC office. Continue reading →

Lean Six Sigma project success depends upon communication so that there are no misunderstandings. The project charter communicates the objective of the project and its scope, while periodic report-outs provide an ongoing means for effective project-status communications.

The define phase of a Lean Six Sigma Define Measure Analyze Improve Control (DMAIC) roadmap’s execution provides a project chart and problem statement, where the referenced DMAIC roadmap has a true integration of Lean and Six Sigma tools: Continue reading →