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Double Loop Learning - an Example

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DOUBLE LOOP LEARNING – AN EXPERIENCE
This example is a bit too technical, but as I believe that this is a good example from my experience about double loop learning (we used to call this as “Thinking outside the Box”), thought of putting it the least technical form as possible.
I was working as a software architect in a particular client’s team. That software system was pretty old and matured (the system was in existence for the past 20 years) and hence we used to treat the existing guidelines in use as the best available. As the system consisted of several hundred independent software programs (also known as modules), each of those has to pass a huge amount of data (names, addresses, other program related data etc.) between them during the operation. As a standard and also to ensure conformity, they used to employ a pre-defined structure to pass data (which will have a fixed size limit with each field having specific starting and ending locations. for e.g.: For address, the first name will be there in the first 30 characters of that structure and middle name will be coming in the next 30 and then comes the last name, followed by address line 1 and 2, each of which is 35 characters in length etc.). The flip side of this is that, even though you are introducing a new field in this predefined structure only for a couple of modules in this 700+ modules system, you will have to modify all the 700+ components to be able to maintain the same structure across, as else, the data positions will get messed up between the changed and unchanged modules. This was such a headache for every software project happening. So, they have put a rule that, anyone introducing a single change to the structure of data will have to change every program, so as to avoid issues. This caused even a simple software project, which was supposed to do a very small modification, also to change all these. This caused a lot of effort wastage and time wastage. But as the easier process is to have measures to best manage the issue (which is a single loop learning), people use to follow the above rule, and keep on increasing the bureaucratic process around this more and more, with a lot of reviews about it, checklists etc. A few of us who were fed up with this as this was unnecessary wastage of human time and effort. We have started to think about ways to improve this situation. So, we discussed among ourselves for several months about the reason why this is happening, and how similar situation is handled in other systems. We found out that the issue exists in other places as well, and they were either following the same process of avoiding this by not having a uniform data structure (which will cause a lot of issues, due to nonstandard formats between different programs, and can cause business issues like address being distorted, cut-off etc.). Finally, I was able to think through this and found out that the basic issue is not the uniform structure, but the lack of space allocation for future expansion. So I came up with a new idea to have free space to be provided inside the structure nearer to each group – i.e. 150 characters after the name fields, 200 characters after the address etc. – so as to handle any future expansion needs. This we proposed and got all of the convinced about its potential time and effort saves, and finally implemented. For the past 3-4 years, they never faced the old issues and the projects are able to complete their changes almost 1-2 months prior to their previous timelines, simply because of this change. The above one, I believe is an example of double loop learning. Instead of patching the affected area (which was the old process of changing everything every time), we found out the root cause of the problem, and modified the system to avoid that root cause (Double Loop Learning). This saved huge amount of time and money for everyone involved.

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