Harry was interviewing candidates for a role which required fast problem solving. Harry was frustrated that even people with sound academic background were getting rejected just because they were not able to solve simple hypothetical problems (which closely relate to actual situations). He contemplated that candidates were trying to apply the past frameworks to solve future / unknown problems and were getting stuck.
The situation above is just coincidental but can manifest in a variety of situations. Can Models / frameworks be counter productive ? I have squared this thought in my mind for a considerable time now. What I conclude is that – Models necessarily doesn’t make us dumb, but yes they have the potential to make us dumb. However, If used carefully, they also have the potential to make us smart, very smart and perfect.
Model / framework is a piece of concise information on steps one should take in order to solve a problem efficiently. For e.g. “Lean” is a model that claims to eliminate or reduce wastes . There are numerous models that claim to magically solve problem in every industry.
Let me explain 6 possible ways how models can make us dumb !
Not choosing the right model
Each problem is different & there is most likely a perfect model for that kind of problem. In my area of work for e.g. there are different models e.g. Lean, Six Sigma, TBEM, BPR or knowledge Management for different kind of problem. Not choosing appropriate model may lead to lot of wasted effort / time and frustration. You can detect such situations by asking “why” questions e.g. Why do we have to look at this data at all, what do we do further based on this data.
Not customizing the model
May be the model is correct but it needs customization to the industry or company culture. Just In Time for e.g. is a great model but it has certain prerequisites e.g. Integration with suppliers & vendors. Ignoring such facts will lead to wasted effort. “Lean” for e.g. need to integrate customer processes in the value stream map unlike in manufacturing.
Not considering the science and assumptions of the model
Some models require expertise in underlying science but the science is ignored. For e.g. Six Sigma requires basic understanding of statistics however we see various applications without understanding statistics.
Not considering the situation as it is
Many times we try to solve the simplistic version of the problem however the problem actually is much more complex. Not considering them as complex as it is can be disastrous. I myself had this experience when the I proposed solutions that didn’t consider the intricacies of industry and teams culture.
Applying a model to a “Just Do it” situation.
All of us know that there are situations where we know what to do i.e. Solution is clear for e.g. Situation will improve by implementing the correct steps”, and no further analysis is required. This is not a use cases for application of a model or framework. Applying frameworks in such situations can be stupidity.
Trying to solve the problem, when measurement will solve
Peter Drucker said – ““That which is measured, improves”. It applies to not all situations but there are many such situations where measurement itself will solve the problem. We can apply a model / framework and get good results too but it may not be the most optimal utilization of resources. Applying a framework in such situations will be micro-management.
Consultancy companies like BCG, McKinsey just do great work of applying frameworks correctly and makes big money.
In a nutshell, if we start with good assessment of the situation (existing solutions, solutions tried in past & teams culture and understanding), prudently choose a framework, it can make us smart.
Using models can help us reach optimal solution without reinventing the wheel. It helps to see a situation from 360 degrees, not missing on any aspect. If business / industry context is applied well, it will reduce chances of failure and reaching the desired state quickly.