Statistical Problem Solving
Problem solving in any organization is a problem. Nobody wants to own the responsibility for a problem and that is the reason, when a problem shows up fingers may be pointing at others rather than self.
This is a natural human instinctive defense mechanism and hence cannot hold it against any one. However, it is to be realized the problems in industry are real and cannot be wished away, solution must be sought either by hunch or by scientific methods. Only a systematic disciplined approach for defining and solving problems consistently and effectively reveal the real nature of a problem and the best possible solutions.
A Chinese proverb says, “it is cheap to do guesswork for solution, but a wrong guess can be very expensive”. This is to emphasize that although occasional success is possible trough hunches gained through long years of experience in doing the same job, but a lasting solution is possible only through scientific methods.
One of the major scientific method for problem solving is through Statistical Problem Solving (SPS) this method is aimed at not only solving problems but may be used for improvement on existing situation. It involves a team armed with process and product knowledge, having willingness to work together as a team, can undertake selection of some statistical methods, have willingness to adhere to principles of economy and willingness to learn along the way.
Statistical Problem Solving (SPS) could be used for process control or product control. In many situations, the product would be customer dictated, tried, tested and standardized in the facility may involve testing at both internal to facility or external to facility may be complex and may require customer approval for changes which could be time consuming and complex. But if the problem warrants then this should be taken up.
Process controls are lot simpler than product control where SPS may be used effectively for improving profitability of the industry, by reducing costs and possibly eliminating all 7 types of waste through use of Kaizen and lean management techniques.
The following could be used as 7 steps for Statistical Problem Solving (SPS)
- Defining the problem
- Listing variables
- Prioritizing variables
- Evaluating top few variables
- Optimizing variable settings
- Monitor and Measure results
- Reward/Recognize Team members
Defining the problem: Source for defining the problem could be from customer complaints, in-house rejections, observations by team lead or supervisor or QC personnel, levels of waste generated or such similar factors.
Listing and prioritizing variables involves all features associated with the processes. Example temperature, feed and speed of the machine, environmental factors, operator skills etc. It may be difficult to try and find solution for all variables together. Hence most probable variables are to be selected based on collective wisdom and experience of the team attempting to solve the problem.
Collection of data: Most common method in collecting data is the X bar and R charts. Time is used as the variable in most cases and plotted on X axis, and other variables such as dimensions etc. are plotted graphically as shown in example below.
Once data is collected based on probable list of variables, then the data is brought to the attention of the team for brainstorming on what variables are to be controlled and how solution could be obtained. In other words, optimizing variables settings. Based on the brainstorming session process control variables are evaluated using popular techniques like “5 why”, “8D”, “Pareto Analysis”, “Ishikawa diagram”, “Histogram” etc. The techniques are used to limit variables and design the experiments and collect data again. Values of variables are identified from data which shows improvement. This would lead to narrowing down the variables and modify the processes, to achieve improvement continually. The solutions suggested are to be implemented and results are to be recorded. This data is to be measured at varying intervals to see the status of implementation and the progress of improvement is to be monitored till the suggested improvements become normal routine. When results indicate resolution of problem and the rsults are consistent then Team memebres are to be rewarded and recognized to keep up their morale for future projects.
Who Should Pursue SPS
- Statistical Problem Solving can be pursued by a senior leadership group for example group of quality executives meeting weekly to review quality issues, identify opportunities for costs saving and generate ideas for working smarter across the divisions
- Statistical Problem solving can equally be pursued by a staff work group within an institution that possesses a diversity of experience that can gather data on various product features and tabulate them statistically for drawing conclusions
- The staff work group proposes methods for rethinking and reworking models of collaboration and consultation at the facility
- The senior leadership group and staff work group work in partnership with university faculty and staff to identify research communications and solve problems across the organization
Benefits of Statistical Problem Solving
- Long term commitment to organizations and companies to work smarter.
- Reduces costs, enhances services and increases revenues.
- Mitigating the impact of budget reductions while at the same time reducing operational costs.
- Improving operations and processes, resulting in a more efficient, less redundant organization.
- Promotion of entrepreneurship intelligence, risk taking corporations and engagement across interactions with business and community partners.
- A culture change in a way a business or organization collaborates both internally and externally.
- Identification and solving of problems.
- Helps to repetition of problems
- Meets the mandatory requirement for using scientific methods for problem solving
- Savings in revenue by reducing quality costs
- Ultimate improvement in Bottom -Line
- Improvement in teamwork and morale in working
- Improvement in overall problem solving instead of harping on accountability
- Scientific data backed up problem solving techniques puts the business at higher pedestal in the eyes of the customer.
- Eradication of over consulting within businesses and organizations which may become a pitfall especially where it affects speed of information.
- Eradication of blame game
QSE’s Approach to Statistical Problem Solving
By leveraging vast experience, it has, QSE organizes the entire implementation process for Statistical Problem Solving in to Seven simple steps
- Define the Problem
- List Suspect Variables
- Prioritize Selected Variables
- Evaluate Critical Variables
- Optimize Critical Variables
- Monitor and Measure Results
- Reward/Recognize Team Members
- Define the Problem (Vital Few -Trivial Many):
List All the problems which may be hindering Operational Excellence. Place them in a Histogram under as many categories as required.
Select Problems based on a simple principle of Vital Few that is select few problems which contribute to most deficiencies within the facility
QSE advises on how to Use X and R Charts to gather process data.
- List Suspect Variables:
QSE Advises on how to gather data for the suspect variables involving cross functional teams and available past data
- Prioritize Selected Variables Using Cause and Effect Analysis:
QSE helps organizations to come up prioritization of select variables that are creating the problem and the effect that are caused by them. The details of this exercise are to be represented in the Fishbone Diagram or Ishikawa Diagram
- Evaluate Critical Variables:
Use Brain Storming method to use critical variables for collecting process data and Incremental Improvement for each selected critical variable
QSE with its vast experiences guides and conducts brain storming sessions in the facility to identify KAIZEN (Small Incremental projects) to bring in improvements. Create a bench mark to be achieved through the suggested improvement projects
- Optimize Critical Variable Through Implementing the Incremental Improvements:
QSE helps facilities to implement incremental improvements and gather data to see the results of the efforts in improvements
- Monitor and Measure to Collect Data on Consolidated incremental achievements:
Consolidate and make the major change incorporating all incremental improvements and then gather data again to see if the benchmarks have been reached
QSE educates and assists the teams on how these can be done in a scientific manner using lean and six sigma techniques
QSE organizes verification of Data to compare the results from the original results at the start of the projects. Verify if the suggestions incorporated are repeatable for same or better results as planned
Validate the improvement project by multiple repetitions
- Reward and Recognize Team Members:
QSE will provide all kinds of support in identifying the great contributors to the success of the projects and make recommendation to the Management to recognize the efforts in a manner which befits the organization to keep up the morale of the contributors.