Methodologies for “Problem Solving”

Recently we came across the article titled: “How to master the seven-step problem solving process: Structured problem solving can be used to address almost any complex challenge in business or public policy” from Mckinsey & Co.  This article makes a very useful and interesting reading material. Below is a table that shows the alignment of the STIMS Strategy for System Thinking and Transformational Skills as well the as the differences.

STIMS strategy emphasizes knowledge integration across the disciplines of Science, Engineering and Management, skills which are dependent on collective core capabilities of human resources involved in the project and problem solving. STIMS Strategy also requires treating every problem as a “System” and handling the solution at three levels: Awareness, Analysis and Synthesis.

The referenced article also makes reference to the “Design Thinking” methodology. The table below provides a comparison between this methodology and the STIMS methodology for System Thinking and Transformational Skills.

Figure 1
Figure 2.
McKinsey: seven-step process https://cdn.ksrinc.com/mckinseysurvey/How-to-master-the-seven-step-problem-solving-process.pdfSTIMS Institute: System Thinking and Transformational Skills. https://stimsinstitute.com/2018/01/24/stims-strategy-for-life-long-learning-for-intrepreneurship/
1.Problem definitionDevelop a Common Language:  Define the “problem” as Input / Transformation / Output system. (See Figure 1)
2. Use logic trees to disaggregate the problem. (e.g.): “How can we save Pacific salmon?”Decompose the outputs between the “What?” – the deliverables (TECHNICAL Outputs) – and the “Why?”- value /benefit for the user (SYSTEM Outputs). This is the STRATEGY behind the solution. Transformation = The “SCIENCE”, the causal  connection between the inputs and the outputs;
ENGINEERING is the application of the “Science” to achieve the deliverables Problem and its solution = Knowledge Integration (Across relevant Science, Engineering and Management (Strategy) relevant to that problem.
3. Rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?Decompose the “inputs” in four categories: Investment / Expenses / Need / Constraints  or Platform (Hardware) / Tooling (Software) / Need / Specifications
Machine / Tools (Supplies) / Component / Parameters.
Develop tools and methods to validate the “Science” and the “Strategy”
4. Work plan: Depending on what you’ve prioritized: It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level one answer, there’s a level-two answer, there’s a level-three answer.  One can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.Complete the STIMS Diagram. Identify the gaps and find the data and resources to fill the gaps: This step leads to a natural formation of inter-disciplinary Team (Eco-system) across relevant resources inside the company, across companies and other players. Develop a “Hypothesis” – science based model – based on real life data. Demonstrate the hypothesis and its modifications: Using a controlled “testing” or “incubator” unit. More rigorous the understanding of relevant Science and Engineering more accurate and reliable is the testing and validation. At this stage the TECHNICAL Outputs and how to achieve them (in a scaled down version) are well established. Scale up the testing unit to achieve the desired outcomes – the SYSTEM Outputs.
Some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative.System Thinking involves three levels:
AWARENESS (of the problem as a whole) – Steps 1and 2 above.
ANALYSIS (of the problem in terms of relevant Science, Engineering and Strategy) – Steps 2, 3 and 4 (See Figure 2).).
SYNTHESIS (Knowledge integration and delivery of SYSTEM outputs) – Step 4
It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process.Bias is an outcome of subjective (task oriented) approach for problem solving; System Thinking (and related knowledge Integration) is non-personal and hence distances human bias from the solution process. However caution must be exercised with respect to bias due to lack of relevant knowledge (Science, Engineering and Management (Strategy / operations) – core capabilities) behind the problem and its solution.
5. AnalysisSee Step 4
6. and 7.
Synthesize the pieces that came out of the analysis and begin to weave those into a story; That helps people answer the question “What should I do?” Motivating people to action
Synthesize the solution at three levels or scales:  
Feasibility demonstration (Bench Scale) where the Science is validated.
Scale up where the Engineering (and its constraints) are established.
Full scale implementation where the SYSTEM outputs (from Item 2 above) are validated.
  
“Design Thinking”:
Start with an incredible amount of empathy for the user and use that to define the problem; go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.
System thinking and Transformational Skills (Seven steps):
1. Develop a common language: Define the problem as Input / Transformation / Output system
2. Decompose the “problem” into relevant Science / Engg. / Mgt.
3. Distinguish between “deliverables” and “Value/benefits” – end user experience (Technical Vs. System Outputs).
4. Emphasize on Science and Strategy;
Rely on diagnostic tools, in-process (real life) data and analysis.
5. Eco – system Development (Every solution requires many partners both inside the company as well as outside).All partners in the eco-system are connected through the common Science, Engineering and Strategy (System Outputs).
6. End to End Innovation (Awareness to Analysis to SYNTHESIS)
7. Emotional Intelligence (for innovation and problem solving) https://stimsinstitute.com/20151207books/

STIMS Strategy for life long learning for intrepreneurship

Professionals in every field must constantly equip themselves with the latest skills to achieve new solutions for process problems.

Being adept at ‘Transformational skills’ and ‘system thinking’ constitutes a lifelong learning strategy required to develop a stream of New Solutions, a must to survive and succeed in the 21st century economy

MMI Cover story image

Who exactly are ‘intrepreneurs’?
We hear a constant drum beat for professionals to be entrepreneurial, capable of handling a variety of jobs and problems. This is in total contrast to the standardized
and de-skilled task-oriented replication activities. There are many opportunities to integrate knowledge from various sources – from other workers, knowledge available across departments, with the suppliers as well as with the customers or end-users. The advent of smart phones, Facebook, Google and other search engines also augment this ability to aggregate information from across the globe and convert them into new knowledge. The result is a “new solution” of high added value. They are heralded as “entrepreneurial”. The new term used for such entrepreneur working inside a company – as opposed to a startup operation – is “Intrepreneur”.

Life Long Learning Strategy:

Modern Manufacturing India, a Publication of the Indian Machine Tool Manufactusers  Association (IMTMA) carries the cover page article authored by STIMS Institute. This article provides a strategy for life long learning for entrepreneurs and intrepreneurs.

STIMS Cover story MMI Jan. 2018 issue

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The MMI magazine January issue can be accessed at: http://www.mmindia.co.in/flipbook/jan2018/

Developing a frame work for Effective Collaboration between Academic Research and Industrial Outcome.

We were invited to present a Key Note lecture on August 5, 2017 at the Chinese Conference on Abrasives Technology at Harbin Institute of Technology, Harbin, China. Inserted below are main points, some images and a link to the full presentation.

Key Note lecture final

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Acknowledgements

  • Thanks to Prof. Zhang at HIT, to the organizers of CCAT and Harbin Institute of Technology
  • Thanks to Dr. Jinsheng Wang, GM, Intelligent Grinding   Technology (Shenzhen) Co., Ltd., my friend and host for this visit
  • Thanks to many friends and colleagues across the globe in the industry as well as in the academia.
  • This talk is a summary of many years of experience  and successful collaboration between Academic researchers and Professionals in the industry across the globe.

Outline

  • 21st Century economy requires New Solutions with deliberate focus on Academic Research; That Integrates knowledge from all sources
  • New Solutions require three types of Knowledge:
    • Academic learning
    • Hands on Experience
    • Transformational Skills.
  • New Solutions in Grinding Processes are the result of collaboration between Academic Research and Industrial Applications enabled by Transformational Skills.
  • Transformational Skills are necessary for industry /   university collaboration
  • Examples and Case Studies.

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SUMMARY

  • 21st Century Research has to be targeted to deliver New Solutions
  • This requires integrating knowledge from all sources.
  • Knowledge Integration is enabled by System Thinking:
  • Every solution is integration of Science, Engg. And Mgt.
  • Focus on the big picture, not merely the dots.
  • Three sources of Knowledge are simultaneously required today:
    • Academic Education
    • Hands on Training
    • Transformational Skills.
  • During this talk we have described the “System Thinking” and “TS”.
  • We have also shown examples of how these are useful for promoting effective industry/university collaboration.

 

Developing a framework for Industry – Academia collaboration : A case study

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Education & Training NGPG EM Mar 2017

To address the limited capability among Indian machine tool manufacturers to produce high precision machines, a model on Next Generation Precision Grinder (NGPG) has been developed. This project also illustrates the development of a collaboration frame work to integrate the expertise available with the Indian machine tool manufacturers, academic resources, etc with the knowledge available from across the globe.

Key lessons learned:

  1. Cooperative R&D is entirely possible between industry and academic/R&D institutions in India as long as everyone is focused on the same common goal (i.e.) advancement of academic knowledge that supports commercially viable end results.
  2. Such an approach is most appropriate for medium to long term R&D projects (3-5 years), not those requiring immediate development.
  3. At higher reaches of technology, the scientific inputs can only be brought by academia, since industry – especially the SMEs – mostly does not have the needed resources.
  4. There are tools and resources available from Govt. funded agencies that could be deployed by students and industry professionals. Developing such eco-system enhances efficiency and reduces the total cost and investments needed in such projects.
  5. A structured project with system thinking leading to clearly laid down quantified objectives stands a good chance of success.
  6. There must be a driver each from industry and academia, who make it their personal mission to complete the project successfully.
  7. 7. It is essential for the industry and academic institution to continuously interact and jointly work on the project at every stage. Such collaboration also benefits from engagement of organizations, such as IMTMA and international experts in knowledge integration.
  8. A free exchange of information and data is essential, without being worried about Intellectual Property (IP) confidentiality at every stage. This can be secured through a mutual Non-Disclosure Agreement (NDA) at the start.
  9. If properly reviewed and managed periodically (as by the PRMC), it is possible to complete such projects within the time and budget allotted.