Having driven several Lean Six Sigma projects as a consultant, the intention of this channel is to share the knowledge and experience gathered over the years.
1. when you present to ceo and sr management information need to simple and to the point.
2. Executive needs sharp and short information than a lengthy presentation .
3. This vlog deals with Pyramid Principle with few examples.
4. For further reading please refer book written by Barbara Minto - " The pyramid principle"
This Vlog series cover Management Consulting Principles and create useful tips to apply in project coaching and so on.
Process Capability and Organization Maturity Levels!
Business capability maturity model. Level 1 to Level 5 with descriptive explanations.
Every organization tries to improve but not everyone achieves the level in terms of Organizational Maturity. There are only handful of industries in general and companies in specific achieved and stayed at the highest maturity level not by accident but consciously & constantly driving the organization.
What is meant Process?
This vlog series is to give a meaning / definition of various phrases we use in the world of QUALITY AND EXCELLENCE from my perspective.
QC tools revolutionized the process analysis and leading to process improvement.
In this vlog the following tools are covered.
1. Histogram: The most commonly used graph for showing frequency distributions, or how often each different value in a set of data occurs.
2. Pareto chart: A bar graph that shows which factors are more significant.
3. Cause-and-effect diagram (also called Ishikawa or fishbone diagrams): Identifies many possible causes for an effect or problem and sorts ideas into useful categories.
4. Control chart: Graph used to study how a process changes over time. Comparing current data to historical control limits leads to conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation).
QC tools revolutionized the process analysis and leading to process improvement.
In this vlog the following tools are covered.
1. Histogram: The most commonly used graph for showing frequency distributions, or how often each different value in a set of data occurs.
2. Pareto chart: A bar graph that shows which factors are more significant.
3. Cause-and-effect diagram (also called Ishikawa or fishbone diagrams): Identifies many possible causes for an effect or problem and sorts ideas into useful categories.
4. Control chart: Graph used to study how a process changes over time. Comparing current data to historical control limits leads to conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation).
I have covered Project Charter - in my previous post Knowledge Nuggets - part 3.
The next step during the Measure phase is the data collection. I want to share some of the interesting and critical points during data collection. Data filtering or screening:
Important step before you work on the data analysis is to do the data screening to check the validity of the data. May be data entry error, intentional data tweaking, lack of understanding of data definition. Hence start with operational definition of the data.
If the data is not accurate and you will draw wrong / erroneous conclusions about the process behavior.
Data needs to representative of the process. what is representative? Sample data set need to capture all the factors contributing to variations in the process. This is important to study the process behavior accurately.
For example, if you collect data to study the height of Indian population you can’t select data only from south or north. Since the height of the population varies significantly from North to Southern part of India.
Data segmentation:
Segmentation is important to study the process behavior. You can’t mix two different things in one data set. This will hide the process behavior.
For example,
Shift operations
Regions
Machines
Raw material
Vendors and so on.
Practical aspects of Measure Phase data collection to consider:
Few challenges one may face during the Measure Phase especially in the case of Service Industry:
Existing measures may not be available
No data capturing system in place
People don’t want to capture as in the case of “error” between the maker and checker. They rectify the error and never track to find out why and what kind of errors are occurring.
This will delay the project progress to proceed further within the time plan if above things are not addressed.
The end in mind for Measure phase is to establish Baseline Process Capability.
For service industry the best method for establishing process capability is to adopt simple DPMO method according to me.
As service processes, in many cases, not fitting in any of the known Statistical Distribution properly.
No need to get stuck to find what distribution your process fits in, which is unnecessary according to me. More specifically it will never fit in the principles of normal distribution.
Aim is to improve the process not to get stuck Statistics.
When there is no reasonable data available?
Worst case you will not have enough data to establish process capability. The team should not get stuck at this stage and invest time to establish base line. Since you have enough sense of the problem please move on to the next phase. Nothing wrong.
Simple saying, we have no data we can’t use DMAIC is not an excuse. This way you will get away with not resolving the problem.
Also, as part of the measure phase, it is a good chance to define, test, validate and establish the new data collection system.
Let me conclude the post with the following comments given by Mr. Mikel Harry on my blog " DMAIC" some time back. Well-articulated about the data collection.
I will cover in my next post on the following topics Normal distribution, Process Capability and 6 & Sigma explanation.
Would you drive a car without a dashboard? Absolutely not right?
Before I get in to the details of Performance Management System. Let me take an example of a car to drive home the point.
Car is a good example of having indicators / warnings both lead and lag indicators. Rather car has lot of lead indicators.
Visual and audible warnings when fuel is low
Warning indicators covering all directions
Service due indicator
Speed limit indicator and lot more..
All the above said and unsaid indicators are critical for driving car safely.
When we have so many indicators for a car, can anyone imagine running an organization without any indicator. Disaster isn’t it?
As a Six Sigma practitioner I can’t think of any process where you don’t have a measure. Afterall what gets measured gets improved.
Performance management using Key Performance Indicators is critical for any organization not only to move forward but also in the right direction. The following are the reasons for the above scenario:
Poorly understood kpis
Isolated / islands of departments and their priorities
No strategic direction
Improper drill down of organizational strategy
Lack of communication of organizational strategy
Lack of top management involvement in setting the organizational strategy and drill down
I will cover the following in my next post:
What is meant by KPI
Lead and Lag indicators
Pitfalls of Goal / KPIs setting
Few industries specific example of Goal deployment – a case study
