How to effectively apply Loop learning in social sciences and MBA courses


Loop learning is a fairly simple concept to understand. It involves a good deal of attention to detail. It also involves inference of data collected and it also involves a certain amount of group study and also continuity of learning at any point in time. Some nuances of this type of learning is sought to be explained in this article.

Introduction

Certain concepts are not found in any textbook. It just gets evolved over a period of time, based on learning experiences and in different contexts. Loop learning is one such. At the world-famous Loyola College, Chennai, it used to be mentioned by one or two teachers who were so serious about it. Even in those days, in the early eighties, when there was no internet, we had this method of learning.

For example, we were asked to collect data about slums in Chennai city. We were asked to go to the field. This task was given to five of us and the subject was Sociology in India. We had to collect data on all the slums in 1981. We had no references. We were guided by one brilliant professor. He would work so hard to infuse confidence in us. We went to the Chennai Corporation and got some data. We were then asked to go two slums to find out the socio-economic conditions of the people. We collected data on income. We had data on the spending patterns. We had data about all informal jobs that the people did. We were forced to get all the data, organize that in the form of graphs, and other statistical forms of presentation, and get the same typed as a project report. The presentation to the entire group and then later comments from students of the Madras School of Social Work, helped us to understand various strands of the socio-economic conditions in two relatively big slums at Saidapet and Tambaram areas of Chennai city.

This project work served as useful study material for the next batch of MSW students at Loyola College. This is what the professor called loop learning. Even in those days, when computers were just becoming famous, we learned that the loop in the aforesaid task referred to the various dimensions of each of the socio-economic data that we collected. Furthermore, we were sent by the learned professor to interact with two professors at the University of Madras. These two professors of Economics had already done some research on slums in Bangalore City. The loop kept on expanding. All five of us were kept in the loop. There was not a single task that was restricted to just the MSW syllabus was Loyola College was already an autonomous institution even then.

It thus turns out that, effective use of the loop learning concept is to a) Understand what is loop learning b) Collecting relevant data c) Analysis of data collected d) Identity all relevant loops for learning and e) Keep the loop learning alive forever.

Understand what is loop learning

As already explained in the aforesaid example, loop learning is very comprehensive learning related to any subject or concept through real-world data collection, learning through all loops related to what is being studied, and through a process of group study, come out with different perspectives in any given situation about the subject under study. Of course, loop learning is possible only in social sciences and in the BBA/MBA courses.

To take a simple example of loop learning, let us take the example of organized retail in Chennai city. The MBA student of a leading B school is charged with the mandate of identifying pockets where the reach can be expanded. This would entail taking at least two or three formats of organized retail and studying them in-depth, for various leads. For example, in a post-COVID situation, the Kirana shop keepers would be keen on involving a large number of Kirana traders as partners in the strengthening of the supply chain competencies of Amazon, in say, a suburb like Guduvancheri in South Chennai. The competition will be fierce. The key will be innovation.

The aforesaid insight would be the first loop. Further learning of the loop would even lead to other insights. For example, in a village near Gudvancheri, the insight will lead to another fact. There is one big wholesaler, who acts as the main source of supply for sixty shops in the nearby six villages. The loop will expand to this question: how can Amazon make this wholesaler a part of the supply chain at minimum cost? Loop learning thus has no limits. One loop leads to another. The learning is so dynamic. There are too many variables and the whole is made up of so many parts. In marketing, the scope of such loop learning is a never-ending process.

Collecting relevant data

This is step two. This has already been explained in the above example. However, the data is never complete. The MBA student will do well to collect all strands of data about every single loop that keeps coming up for consideration. For example, a particular piece of information might pertain to the presence of a good number of high net worth individuals, most of whom work in the nearby Mahindra World city, India's first Special Economic Zone.(SEZ).

The loop would expand to exploring ways to bring an entire lot of these customers into the Amazon ecosystem by and through tie-ups with the nearby good Kirana shops. This might lead to a win-win situation for both the Kirana traders and for Amazon. This is exactly how the MBA student needs to keep on expanding the loops at any point in time and then collect the data.

Analysis of data collected

Let us come back to the same example. When the MBA student analyzes the spending patterns of the IT professionals, the learning would be that they all tend to buy in bulk from only one big retailer, who has a good reputation for honesty and integrity. Analysis of data would also throw light on how the trader could also stock some items that the people normally order through Amazon. Can the chain be broken, so that the door deliveries are reduced by Amazon and the free deliveries already made by the retailer are now expanded? That is, can it lead to the cutting costs for Amazon? This is exactly how the data collection should lead to fresh loop learning. Obviously, the loop keeps on expanding every single day.

Identity all relevant loops for learning

This has been partially explained above. However, for the MBA student, loop learning will also cover the secondary sources of data. The loops will mean expanding the scope of his learning to any fresh insight made possible through similar research. Years ago, loop learning restricted to study of two fairly normal mini-supermarkets, with a big focus of customer tastes in a small town, Cheyyar, near Kanchipuram in Tamil Nadu, revealed that many customers wanted the imported Malaysian chocolates for their children. Somehow or the other, the salesgirl did not give this proper feedback to the shopowners.

When the MBA students also found that a good number of bachelors wanted the ready-to-cook stuff to be stocked by the two mini-supermarkets, the sales zoomed. Of course, the scope of loop learning was rather restricted, as the college where the MBA studied was not a well-known college and the student had to be handheld by me at every stage. Of course, continuous goading then enabled the student to learn far bigger insights from so many loops into so many aspects never taught in his classroom.

Keep the loop learning alive forever

Let us take the example of the famous historian and sociologist, Dr. Ramachandra Guha. He has now researched Mahatma Gandhi's life and messages like no other scholar have ever done. The result is that he is able to bring in fresh insights into Mahatma Gandhi's life and his messages that were never even thought of. He has sound data and evidence to back his arguments and even his critics find him so challenging. They would rather keep quiet than providing him food for further thought, that are, of course, further loops for his learning and research. Today, he has expanded the scope of his loop learning to interpret, with due respect, dangers to Indian federalism, and then connect them to the thoughts of the Mahatma.

In so doing, he is able to weave a web of several thoughts that would obviously flow out of new loops, as it were. This is exactly the scope of the loop learning that am trying to emphasize. Quite obviously, the loops will keep on coming. Let us take another big issue crying for national attention now -- the issue of migrant labor. In the weeks to come, there will be several scholars who will open up new loops. This will provide fresh insights and the debates will become all the more interesting.

Conclusion

Given the scope of loop learning, based on my own experience and background, I have explained the concept with the help of some examples. Obviously, the social sciences and business administration courses are fertile grounds for loop learning in so many ways. This is mainly because there are too many variables to be studied and every situation is always dynamic. The situations also keep evolving over a period of time. Loop learning is a good concept to study and implement at any point in time.


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