Episode 9

TOC Thinking Process: Going beyond Data In Decision Making (Part 3)

Category :  Thinking Process

Find out how to overcome bias in decision making by using the right thought-ware. Bad decisions can have long standing consequences. So, to avoid bias, managers tend to rely on data. Unfortunately, data does not always help differentiate between truth and perception. For instance, two managers might have two different interpretations of the same data; or two opposing views can have fully reliable data supporting them. Sometimes, there is no data at hand. How can managers go beyond data and use a more systematic and rigorous approach to decision making?

This episode is a continuation of the two previous podcasts on Thinking Processes and explains how to use deductive reasoning to avoid common traps in analysing problems and making decisions.

Shubham Agarwal : Hello, everyone, Welcome to the next episode in this series of thinking process with Satya, we have him here with us. In the last episode, we discussed in detail as to what the thinking processes are, and how do we apply them? How do we use them for defining a problem correctly, which is very important? How do we reach the root causes in the correct sense in the right sense. And we also discussed about the difference between inductive logic and deductive logic or the inductive and deductive way of thinking. And we left it there to discuss more about the deductive thinking, which is quite an interesting way of looking at defining and discussing and analysing problems. So we’re going to go deep into the deductive logic. How does it work? And is it relevant for organisations and managers across the across the companies across the globe, and then see where we go from there. Alright, so let’s welcome Satya. Hi, Satya. Welcome to the TOC podcast again.
Satyashri Mohanty : Hi, Shubham. How are you?
Shubham Agarwal : Great. I’m very well Satya. How are you?
Satyashri Mohanty : All Good. All Good.
Shubham Agarwal : Wonderful. So Satya we discussed about deductive logic in the last episode, in a brief way. And you touched upon the importance of deductive logic, and the difference between inductive and deductive logic. What we’re going to do today is go deeper into it. So I want to start, is there anything that you want to pick up from the last episode before we go ahead?
Satyashri Mohanty : Yeah. So if you see in the first episode, I made a claim that thinking process can be used to explore areas in organisations where data is not clean or data is not available? How do you take objective decisions in such an environment, and I claim that thinking process is a way to take decisions on those areas. So in fact, deductive logic, and deductive logic is a way to do that. Okay. And one of the methods that is used in deductive logic is called the hypothetico deduction method, which in toc they say it’s a predicted effect thinking, right? And, And this, this way of thinking helps you explore areas that is where clean data is not available, and data is missing, or, or you have variables which are not measurable in the first place. Okay. So let me let me give you an example of how
Shubham Agarwal : So let’s, let’s, let’s bring it to, let’s bring it to the managers Satya. And start by asking, why does you know, practising deductive thinking is important for managers. Before we go ahead and see into a into an example on deductive thinking, why does it work for managers? Should they really use it? And why should they?.
Satyashri Mohanty : Yeah, so as I said, even after, you know, last decade of a lot of enterprise solutions, most of the organisations that we come across, still suffer from the problem of inadequate data and clean data, erroneous data, and missing data sets. So I feel we can spend the next one decade but will not be able to eliminate this problem, which means that in absence of data, how do you take decisions, right, and that is going to be a problem. So and that’s why I’m saying that as as managers, when you are faced with a situation where a data set is not available, how do you conclude that, you know, your decision is objective? And it is based on reality, and you don’t have any information and the example that we discussed, if you remember, last time, that if you take a typical consumer goods distribution company, many in India don’t have retail point data. Right? How do you know that? Is there a loss sales happening? Is there a customer coming in and going out without seeing the product available? What are the issues that are facing there right? One of the ways you can say okay, let’s let’s try to wire that environment and and collect the data and then we will decide, but, you know,
Satyashri Mohanty : Ya besides even if you have data at the retail point, you just can’t have data on loss sales, you know, no one writes down how many customers came and went without having or without taking your product? Because I didn’t have it. So yeah, I agree. Yeah.Add – you seem to be a data skeptic !
Satyashri Mohanty : And then data if you see it is always reflects on what has happened, it will never tell you what could happen, right. So that is that is never there. So faced with this situation, how do managers take good decisions, and that is why they need to learn the foundation of thinking process which is the deductive logic. So I’m borrowing heavily from the ways science has evolved by using this hypothetico deduction method to explore areas where we can’t reach out because of our limitations in human senses. Because in science, if you see a lot of topics are around things, which are either too big or too small or too far away from us, or too much into into the past, right, where we have no access, right? How have scientists develop a capability to develop theories? And they’re very sure that those theories are right. Okay. It’s like trying to
Shubham Agarwal : So could we look at an example here, I’m not able to really relate with you here.
Satyashri Mohanty : Yeah. So I’ll give you an example. of a science in terms of an in terms of an analogy, right. And, and so that we can understand how science actually happens using the hypothetico deduction method. So let’s, let’s imagine that there are a few fishes in a bowl, okay, and the fishes are scientists. Okay. It’s a funny example. But we will get to know.Sounds Interesting.

Yeah, so the fish in a bowl analogy, right. So there is there is a bowl in a room. And there are, let’s say, a few fishes there. And remember, they are in a bowl, they can’t move around, their worldview is limited to what they can see this, so they see a room and it so happens that it’s a room of a teenager, so they get to see the teenager, right. And being, you know, scientists they are role is not limited to just eating and sleeping, they are also interested to develop theories to understand what’s happening around them. So one of the scientist fish observes the teenager and finds out that there is a pattern in which he or she is waking up, you know, having his food going to the washroom, and, and he sees that there is a pattern in the daily chores, okay. And so he develops an equation, let’s call it the daily chores equation, right? And the other fishes validate this daily chores equation and and find out it’s correct, it’s, it’s able to predict all the behaviour of this teenager. Now, meanwhile, there is another fish out there who looks at the room and sees a particular strange phenomenon happening. Right, and that’s near the door. Remember, it’s the bowl, they can move around, they can see what’s happening in the room, they don’t know what is beyond that room. their worldview is limited to what they can see.

Their universe, is that room.

Yeah, that’s, that’s their universe, right? And, but they are like scientists, so they are not happy with what they are seeing. So they are developing theories and trying to understand what’s happening around them. So one of these fish looks at the door and sees that as human beings who pop in and pop out, they just come in and vanish.

Add – ok like the parents who don’t stay in the room – they come in and go out of the door.

Okay. Now, so he says, This is pretty strange, but he also develops an equation, let’s call it the pop in and pop out equation. Okay. And it is, he looks into that equation, but and that works pretty well. And the daily chores equation works pretty well till the another fish says boss there is I see a problem in these two equations. Now, if you look at the daily chores, equation that you have developed, why is that in the room itself? Right, when the person is moving around? Why does he not pop in and pop out? There’s something strange it assumes that only at the door You know, you see a pop in pop out happening, why is that in the daily chores equation, you find out that it makes an assumption that no such pop in and pop out will happen in the room? Okay, now comes a contradiction. Here are two theories, which is now contradicting itself, because there is something strange about this human being that next to the door, pop in pop out happens but inside the door the daily chores equation works with a with the assumption that there is a continuity of the human being, he does not vanish, right? So so that that’s a paradox, right? So, so what happens is people spend the not people the fish here and spend a lot of time trying to solve this paradox. And then somebody says, you know, what, there must be another room beyond this room. Okay? And this solves the paradox, how it solves a paradox, it is not that the human beings, you know, can vanish and reappear on their own, it’s just that they go outside to another room and come back here okay. So, with this, the continuity requirement of the first equation is met with the continuity requirement of the second equation. So there is no vanishing happens. So everybody’s happy Well, this is a this is a conjecture, by the way, this is a conjecture No, they have no where with all to check whether this is really a room out there or not. This is a now a conjecture which is solving the paradox. The paradox of a human being vanishing and not vanishing in some situation not vanishing in some situation vanishing and reappearing. So, the the explanation that there must be room outside solves this and says that there is no vanishing act out here. It just that Like the teenager is staying here, the parents are staying in some other room, they just come through the door and go away. Right there is no vanishing, which is happening. Now, this is a fantastic discovery, maybe the fish will get a Nobel Prize for it for finding out that there is a room outside, but it’s still not get a Nobel Prize. You know Why? Because now what they have to do is predict some more effects from the multiroom theory. But how do they know it could be? It could be a wild guess that because nobody is aware seen a room? No fish has ever seen a room beyond this one. So how do we know there is a room existing? So what do they do? Right? It’s similar to environment, no data exists, right?

Satyashri Mohanty : So how do they know they’re sure so they start predicting more effects than if there are multiple rooms in this house, then there must be some sound that gets created in the other room. Right should reach to us. Okay, so then they set up experiments, a mechanism of sound, yes, you know what, there is a sound coming in, right. So this is how they will set up multiple experiment a sound around smell, but still, they don’t know, you know, the room. But through multiple predicted effects, which is deduced from the hypothesis of multi room theory, they start checking each one of them and each one of them gets validated, then they say boss, there is a very high chance that there are multiple rooms in this in this, you know house.Universe.

Yeah, so this is how science progresses. This is just a funny example to tell you that how will

I love the example.

Yeah, we live in a limited environment of the earth, and we can see as much but how do we know? You know, crazy theories about what happened 14 billion years ago, and all that it is all through this way of hypothetico detection method. Okay. So if you can borrow this method, what what science has done is, science has solved the problem of how do you do science when data is not available? How do you do science when you can’t sense things directly? Right. So they have found out this method, and this method is all about a conjecture, a hypothesis and deduce from hypothesis all kinds of predicted effects, right, multi room theory means this should happen. Multi room theory means, you know, you should get the smell, you should get those sounds. So each one, you check each one of them. And if it stands corrected, then you can say your multi room theory is valid. But if one of them is proven wrong, then you have a serious doubt about your theory you have to throw it away. Okay.

Shubham Agarwal : Right that’s what my concern is Satya here that this could take a long while to develop theories. And this could take a long while to deduce effects as well, and predict effects which have not yet happened. Don’t you think? So? Well, when we have data, we simply look at a pattern and use that for making future predictions.
Satyashri Mohanty : Yeah. So that, that I know, it’s a easier job, because see the data and then you can predict theories so a lot of science, as I said, is developed that way, in particular, the science of the observable world, which is the way the cars move, or the you know, Apple falling down all this is our observable world, and we can develop theories by looking at at the data and identifying a pattern, but when it goes beyond that, there is this is the only method that we know, as of now, that we conjecture, we predict, okay, and then we run experiments to see whether those predictions have come right or not. And if it has come right, then, you know, we accept that this is this theory is correct. And that is how we move, but does it require it requires a thinking capability, but it also requires your ability to develop those working theories from which you have to predict like, for example, in this case, the fish is able to develop a theory of multiroom, which is, which is the act of creativity in a way, because he’s able to visualise that, you know, this is my theory, and from there I will I will predict, right. So, it is to that extent, it is creative, right. So, we we will talk about how to reach to that hypothesis first. Right? And and that’s, I think, is your question, then how do you reach to that hypothesis, and from there you can predict, and then you run the test to see whether those are happening or not, but i will tell you in case of management, and it looks so difficult in the example of fish. But in case of management, you can do it on a day to day basis, and you’ll be much better off. Let me give you an example of how deductive thinking.So let us look at an example in the business context. Yeah,

In the business context. So you know, we you know, we do a lot of work in the space of operations and supply chain, right. And one of the areas that we do lot of consulting work is around improving the delivery performance of organisations, right, and you commit something to the customer, are you really delivering things on time as per the desired lead time? So that’s one area that we work right. And you won’t believe, you know, we get requests from clients calling us saying that can you have a look into organisation. And so in one case, we got a request coming in from the CEO that I think something’s not right. Can you? Can you come in, right? So we came in, we met the supply chain head. And I’m going to tell you how deductive thinking is being used in our conversation, right? So we walked into the supply chain head, and he said that, you know, we are such and such guys, you would have seen the CEOs letter we are talking about on time performance. So can we get more information about that? Right. He said, boss what we don’t have on time delivery problem. Okay, so you don’t have on time delivery problem? No, not at all our if you look into our data or delivery performances, is is in the high 90s. Right. Now, just imagine now what what should we be running in our mind as a consultant you are coming there? Right? What should be running in your mind? It’s because this guy saying I actually got I have a data. Okay. And, and and that data he is saying that boss I have I have a very good on time performance. And the CEO has called us.

Satyashri Mohanty : Right for on time delivery. Improving on time delivery. Yes.
Shubham Agarwal : Now, how do you react to this situation?
Satyashri Mohanty : You first find out who’s saying the right thing?
Satyashri Mohanty : Yeah. So but that maybe maybe both are right. Right. One of the things thatAnd How is that?

Like, for example, that’s that’s how you start looking at things that look, if the on time delivery was good? There is no way the CEO would have called you. Okay, this is this is the first I’m trying to deduce if the on time delivery was good. There was no way the CEO can call us. But this guy is saying

Satyashri Mohanty : Yeah he doesn’t want to spend his money for no reason.Yeah, he’s calling you right. He has called you and, and and it’s not that you know, him. That’s why he’s called you he called, you know, for help by looking at our work. Yeah, as a professional. And you know, that. And here is a guy saying boss on time is is perfectly fine. Right? And the data source, it’s fine. Now, tell me in your mind, what should you start thinking? I’m saying can you use deep what could be wrong in this environment? There is a person who is saying that the the on time is good. And there is a person who is saying on time is bad.
Satyashri Mohanty : defining how is the on time defined.Perfect. So you’re started now started now, instead of falling into a trap of these inching costs? Yes. That’s the next question. See boss tell me how are you measuring this on time delivery? Okay, that’s that’s the and remember, this is by by a hypothetico reduction method. You arrived at this question that please tell me how are you measuring this on time? Because I feel that if this guy is right, and this guy is right, then the only ways that the formula could be at a problem that he’s saying that as the formula, I’m right, and that guy must be saying, as per intuition. I’m right. Okay. So we discover more and we say, Okay, great. He says, I, you know, I, how do you calculate and, and we found out after discussion that he’s using a lot of ways of calculation, which are internally focused, like, for example, he’s revising the dates. It is as per the latest revise dates, he’s taking a liberty of, of, you know, plus minus one week of delays considers on time so you look at all those loopholes. And yeah, and and he said, this is the way we are calculating instead, okay, this is not the way to calculate but your customer is very sensitive about, you know, a single day delay, that’s the environment you are in. So, could you calculate these numbers? Can you find me the numbers if, you know, if, if you take a single date, and and you deliver in full on that day, if you miss a single quantity or a single item, or and you miss a day, it should be disqualified from the on time calculations as you can, you know, can you do these collections again. Now, he might say, Oh, no, no, I it will take a lot of time for me. Okay. And we can say, boss can you tell me intuitively, what is your on time performance? as per this new calculation? He might, he might say, Oh, well, I don’t know. Right. Now, what should be a conversation next? Right? The very important fact is, he is claiming that his on time delivery is very good. Okay. Now, let us predict few more effects that we can that we expect to see in a very high on time delivery performance. Now, I don’t want this meeting that I’m having right now to get into some kind of data crunching analysis. Show me the data, I just found out that data, the formula is wrong, I still don’t want to get out of that room and seek for data. I want to still use the hypothetico deduction method to find out whether reality is as good as this saying, Can I make a conclusion in that meeting? So let’s, let’s apply this so I’m saying your company which has got a very high on time delivery performance, right. What should not happen in that company?
Satyashri Mohanty : There should be no stress or no exigencies. No. What do you say changing priorities, and last minute changes into the, you know, the deliveries or the structure or the ways of sending your material out.
Satyashri Mohanty : Yeah. So, you know, a lot of people do all that and still make on time happen, right? So yes, I mean, a good on time performance companies should not have these kind of change of priority. But people might say, you know what, that those are the special efforts I put in to get on time delivery performance, right? So my end customer is happy is the claim, let’s say, Okay, now you know that now you know that you are in a situation where you seriously doubt it. And I don’t want to depend on data, I don’t want to say please collect the data, and let’s evaluate and then God knows what data he will collect, I want to be in this meeting and conclude that there is a problem without opening a single data out there, right? Just using hypothetico deduction method, right. So let’s understand if the on time delivery is very good, how should customers be feeling about this organisation
Satyashri Mohanty : They should be feeling great about it,
Satyashri Mohanty : At least no delivery complain. So which means what should be happening, that there must not be any phone calls coming in, which is like people shouting expediting customer calls would be very, very negligible. Okay. So then you can ask the question that, do you get often customer complaints about deliveries? You know, almost shouting at you do this? Do you get these kind of calls? Does your planner get this kind of calls? The answer if this is yes, in this case, it was Yes. By the way, yes yes we keep on getting these calls, right. Okay. So, you know, one particular defect got ticked. Okay. So I parked it, I have to make another predictive defect, another deduction, right, from the theory that the on time delivery is very good, right? repeat customers? Yes. Yeah, repeat business that is on one side is about the customer, right? customer being happy or unhappy, right? I want to make another another side, just just let’s not expand on that. Because if we expand on that there are this case of repeat. And repeat business also depends on how the industry is performing. By the way, if everybody’s lousy on on time, they won’t have a problem. But I want to now look at another predictor effect little outside this domain that we just covered, which is the impact on customers, right? There’s another one that we can make, right? For example, okay. We can make one assumption here, which is a valid assumption that the customers required date should be spread all across the month. There need by date, it should be spread out, or it should be random across the month. Correct? Yeah, it should be random should be random. There should not be any pattern right. Now, I asked them the question. Do you have a delivery skew at the end of the month? Right. And, and, and in this case, I got an answer. You know, what, our 60% of our deliveries happens in the last week. Okay, now, I say boss if 60% of the deliveries are happening the last week, right? Are you telling me that 60% of your customers want delivery in the last week? This is how they’re requested for business, what is the business that they are doing that they are requesting everything by the month end now then is like oh, I never thought of it like that, then you say boss you are getting continuous customer complaints. You are also having a skewed delivery. You think that you are there is a there is a problem of on time it is it may not be you know, it may not
Satyashri Mohanty : be bad. But But there is a huge problem around this deliveries. Yes, I suspect. Okay, now let’s look into the data. Now let’s, let’s validate what we are said by looking into the data. But by this time, he is also convinced that there is a problem. Okay. So what did I do here? In this method? What I did is I went in, and I started saying that, okay, if your theory is right, okay, my hypothetico deduction, I deduce from this theory, multiple predicted effects across different areas around customer satisfaction around the way deliveries happen, right? And I tried to check which one of them is, is right now, if all of them are right, then there’s a good chance that theory is right. But if one of them is wrong, all it’s all of them are wrong. Definitely what you’re saying is wrong, right. So now look at this, how much data is needed to to arrive at a conclusion that there is a problem. And there is a you you suspect it very strongly that there is a problem? Right? And that is enough for us to look into data. I’m not saying don’t look into data, and this next step is justYeah i get what you are saying

Before you start saying that I want to search a specific data. You are already mentally very sure that there is there is an area of reasonable doubt.

Shubham Agarwal : Okay, this is wonderful. I really love the example. Yeah,
Satyashri Mohanty : Yeah. And and there are funny things that happens in meetings, right. For example, I attended a meeting of one of these companies, which is into selling packaged food, okay, now, so it was a sales meeting and in meetings, what happens is people throw hypothesis. And the hypothesis as a statement of this is happening because of that, right? a cause and effect statement, explanation, explanation, which somebody, you know, pulls out of the hat in a meeting and presents it right. And there are people who doubt it, right? Like, for example, in this case, the sales were going a little flat. And the CEO was asking guys what’s happening, why the sales is going flat? Right? Remember, everybody is eager to give up a cause in a business meeting, everybody says that boss I know the answer, right? So you ask the sales guys What is happening? And by the way, every different people have a different because to it, that’s a different topic altogether, but you ask the sales head and the sales head says in this case, what he said you know, the customer’s taste in our product category is just going away people are no longer liking our product, okay. And that is how the sales are down. Now, it could be correct also, it could be correct also, now, now there is this production guy, right, who felt threatened in this meeting and saying boss that means you are pointing out to our r&d and all those the quality of pointing out to a quality or something or other. So he is become defensive. So he does not like this hypothesis, right? So his immediate reaction was, how do you know that the customer taste is coming down? Okay, it
Shubham Agarwal : Which is a very valid question i think.Right. And, and, and the CEO said, Okay, guys, we need to do a survey.

This, I think, is a is a very pathetic approach to deal with this problem. Why? Because look, look, look, here, you’re sitting in a meeting data is not,

Satyashri Mohanty : That’s quite a strong claim.Yeah, you’re sitting in a meeting, you have an area on which data is not available, right. Now, instead of using a method which I said our hypothetico detection method, you started saying, Please give me the data. So please do a survey and get me the data, then only I will decide. This is the problem that I am saying that every time you face an area of unknown, people say, people say I need I need data. Right? Everytime you face an unknown area, in management, people say, I need data, I’m helpless. I’m trying to say you’re not helpless. Now, in this case, let’s take this example. Now, you will appoint a market research agency God knows he will do a survey what sample size he will collect, how he will define taste, a lot of these things will be done and God knows when that report will come out right now, I’m I’m making a challenge that in that meeting, can you make a few predicted effects right to check the validity of this of this claim? Okay, can we can we do this? Can we make some kind of a predicted effect right. So it based of the of the product category, the customer is not liking the taste, right? If that is the case, in the entire product category what must happen? Can you can you can you predict ?

The other the other similar product or similar tasting products would also not be selling?

In fact, what is what should also happen is that the competition sales should also be you know, going down.

Correct exactly correct.

So, one of the important questions that can be asked in that meeting is what’s what’s happening to the company is this right? Or for that matter what’s happening? So, if you say my competition sale is going up, right, then you say boss, hi, now doubt this entire hypothesis right. So, this is this is the thinking approach that is required to deal with subjects where where data is not available. In fact, the you know,

Shubham Agarwal : So satya you’re claiming that in the same meeting without going outside that room, we can actually come to the real problem and the root cause for this or we can have at least few theories, which we can
Satyashri Mohanty : We can become falsify, we can see we can be sure of one thing we can falsify, we can take away theories which are should be taken out within a What stays back see what stays back has to be checked with proper data and all right has to be checked because as I said, in the, in the example of the on time performance that we discussed, we still had to look at the data at the end, okay. So that you know, but we are reasonably sure So, what happens is you throw away bad theories out, okay, so you have a method of, of filtering out bad theories. And what the good one stays is either you run an experiment, or you do a data check again, so that you are sure of things. Okay.
Shubham Agarwal : So, like you said, in this example, and I love both the examples, deductive thinking, the way you have presented it until now is not perfectly decisive. Right. We still have to go to data to acknowledge and validate the hypothesis that we have. Right? And not a cause and effect hypothesis, just the hypothesis itself. Right. So there is uncertainty and variability in the environment as well. And we cannot be really sure of our conclusions, just by thinking is what you are saying?
Satyashri Mohanty : Yes, you are right. And we can’t be sure about thinking because reality has a lot of things hidden out there, right. So, what this hypothetico deduction method does is it is a very, I would say a non empirical way of filtering out bad thinking or bad theories, okay. The good ones stay now, when the good ones stay, you got to run an experiment, okay, to check whether this is really happening or not. And that experimentation will tell us okay, is this cause and effect happen now, if it is a case of innovation, that you have not done anything before, then you do an experiment, which is forward looking, right, I make some changes and see, well, this is happening or not. Now, if it is a analysis of a diagnosis of event that has happened, you do a data crunching of the of the past to see whether you know that thinking that we have done is is reflecting in the data or not. Okay, so it’s whether you are trying to innovate something right, then hypothetico deduction method first, helps you bring out good ideas on the table and weeds out the bad ideas, right? And then you can run an experiment, and you can be reasonably sure that this experiment would fructify right? And the experiment might surprise you a little, but then you modify after that.
Shubham Agarwal : Okay, so Satya the example is great. I think I love the example and how you describe it. It’s very powerful. But again, this is you’ve been doing this for years, the operations is your field sales is your field, why don’t we look at an area, which you’ve not had really experience with, you’ve not had any clients in? And still, we could apply directive thinking, because, you know, you are an experienced one at deductive thinking, what about someone who is new to it? So I want to see how do we do in a new environment?
Satyashri Mohanty : Okay, so, I will take an example of, so I Okay, let me first agree that you have a fair point that with what what happens is, with a lot of experience, you have a lot of these hypothesis theories that you have in your in your armoury, and you can do predicted effect from there. Right? That’s, that’s one way, right. But you can also do it in an environment where you don’t have, let’s say, much experience, right? And I’m talking about a company, which called us and said that, can you do something in our marketing? Okay. And, and at that point of time, we didn’t do a lot of work in marketing. So when, when it was marketing, it was all about, how do I position my product, right. And at that point of time, now, we started doing a lot of work in marketing, but at that point of time, we were new to that area of marketing, this topics of how do we position our product? Those are topics which are new to us, we were more in Okay, you know, can you fix something that is broken, right? This is about creating a new value perception in the in the mind of the customer. So, one of the typical ways, right, what people do, when they are given such a job is to go and do a survey, a market survey, and then you go and ask the customers, and they start bitching and moaning, and you list down a list and you say that, you know, 20% of the customers complained about delivery, another 30% complained about prices being too high. Other 20% said, boss you your call centre is not responsive. So you have got a huge list of bitching and moaning and then you look at Okay, what all I can do about it, maybe you said I can’t, I don’t have resources and time to deal with everything. So let me pick up the top one and two, that’s a typical way, you know, people approach to this, right. And if you see, you know, one of the giants in the field of innovation, which is Steve Jobs is, is very much against against market surveys. And he says that customer doesn’t know what they need, right? And because they have not experienced the new things that the brand is about to present, so if you ask them, they’ll always complain in context of what they have already experienced. So he said that it is a responsibility for us to actually think through the next innovation. So when we use this word think through, and I suspect that he talked about deductive logic of how do you think through and identify because we see thinking is is a very wild game. Anybody can think anything, right? So how do you converge and say that this is the right thing to do? experiment that this is the right thing to you know, plan your r&d around, right? So we said okay, let’s apply the the deduction logic, with the limited knowledge that we have, you need some basic starting point, right? And instead boss let’s find out what is the the unmet need of the customer? What is the real big pain point that even the customer will not be able to verbalise? Right? So let’s understand it from the first principles of thinking. And and so we said, okay, what’s your environment is boss? This is genset and who’s your customers in big construction? builders. They take our genset. So, so what do then, you know, subsequent question What, what all they had this list of, you know, the market survey, which talked about a lot of problems
Satyashri Mohanty : Yeah. No, they had this survey results, which said that 20% complaint about deliveries, okay. 30% talked about cost being very high. We said, Okay, let’s Park this. Everything aside, and let’s look at real issue that is happening, right. And then let’s think through this before we go and do data crunching right. So the one of the things that is for sure, is that most of the construction projects are delayed, right. you’d agree. Most of the construction projects in this country Yeah every

Yeah, we can be reasonably sure that’s that’s one hypothesis that is there. Now let’s imagine that if all the if most of the construction projects are delayed, and there is a planner, right, who has to place an order for genset about three to four months before his real requirement at that, because that’s the lead time of getting a genset. So three to four months before his requirement, he has to place the order. Now, looking at the fact that the projects are delayed, okay. What do you think is the big dilemma of the planner, who’s going to place the order went

When to order

When to order, right, because you know, what, not only projects are delayed, but we also know that projects are also unpredictable, unpredictable, in the sense that, I think it will be on time and it got delayed, nobody knows what is going to happen four months before. Right? things can go wrong things can so if you have a very ambitious planner, he might say Boss, I can get things done, it will happen in a very short period of time, if you have very pessimistic plan saying boss things will be delayed. So the problem of the procurement guy is, should I place the order now? Okay, now let’s look at this. If he places an order, there could be two problems that should come up, right. And remember, all this I’m doing is through a hypothetico deduction method. I have taken what what is information I have I have information that projects are delayed projects are unpredictable. The lead time of delivery of a genset is about four months. And I’m saying Hence, I conclude, I deduce from this fact that any plan any planner on that project would face a big dilemma while placing an order Should I place today or should I wait a little more right, because if if the order is placed today and the project is gets delayed, that means the genset will arrive much ahead of time, which means that his money you’re losing your working capital is blocked plus pilferage and all those things right. On the other hand, if he if the genset ordering is too late, right and and reaches the site late then the project is delayed where you’re losing crores. So in this environment, and just let’s take facts together and try to deduce what is the customer’s real need, which he may not even verbalise in the survey, right? So, here is the customer, which is the guy who’s placing the order right, he has a big dilemma, should I place the order now or should I place the order little later? Okay, now, he faces this dilemma. So, it is not about on time, in fact, he has a problem of early delivery also. Okay, if you if your genset is ready and say boss I don’t want it and then you are over his neck and saying boss you take it otherwise, you know, this order gets diverted? So he knows this kind of a problem right? Now tell me what is his real name? Is it really on time delivery? What is his real lead?

Satyashri Mohanty : It is when he wants it It should it should come when he wants it and not when he has ordered for it.
Shubham Agarwal : Which means what? Okay, the best thing that can happen in this environmentSo the inventory should be available.
Satyashri Mohanty : Yeah, he should see the best thing is Can he order as late as possible? Yes, that’s the real need, he can he order as late as possible? Because if he’s very close to the event, right? If he’s very close to the event, then his forecast accuracy is far better.Wonderful.

Which means what if the lead time of the genset is let’s say seven days, right? If the lead time of genset is seven days then this dilemma is solved. Okay, yeah.

Satyashri Mohanty : So its a huge customer problem that the company is solving
Satyashri Mohanty : Right. now. So when we went around asking Okay, I want to on time delivery, okay, in four months, I want on time delivery performance, that is not his real problem. His real problem is is this dilemma should I place an order early or should I place order late because at times, I will end up in a working capital problem. At times I have a delayed construction project because of a genset, right. So now we said you know what, we will build a supply chain, which will guarantee seven days delivery. Okay? And and we call up our customers and say, Please place orders as late as possible. Now just imagine this, this is now a thinking hypothesis.This is epic

This is a thinking hypothesis that is put on the table we are not sure you know we had to experiment it and so we went around did the experiment and and it clicked in the market. Okay? And it clicked only in the builder segment. Yeah it it didn’t click in some segments but in the builder segment it clicked big time. Okay so this is how i said that you know you can you can think okay and and try to come out with a solution without depending on the data. You actually think of a reality valid it into a thinking process and then you do the experiment and collect the data. So i suspect the you know when giants like Steve Jobs said i don’t need market survey i need my guys to think through this. I suspect that he talked about this process the the process of using the hypothetico deduction method to to look at what is there in the unknown. So this is then you know the customer said oh wow this is what we wanted we never thought this is possible so if you ask me i can never imagine someone giving me a genset in seven days. I can’t imagine that. So i can never you know give that response in a survey.

You are changing the way the industries define its a made to order industry you are making it a make to supply.

Yeah its called for different stocking model and all that there was a lot of intermediate stocking but that’s secondary. I am saying that the marketing strategy was developed using a thinking process without you know the survey came later we just went out and said that would you like something like this and they said wow.

This is great Satya so i i totally understand the power of deductive thinking i think i am interrupting you in a way because we are short much over time like always because its lovely to have a conversation with you but what we will do in the next episode is set the ground rules for good and constructive deductive thinking and then look at some of the tools if we can as to how we can you know how can someone who is very new at it start developing these start using these. Right. Is there anything that you would like to end with?

No Sure so i think the rigour of thinking is very important and that is underestimated in this world that thinking requires a rigour right ? and we have a rigour in Maths and English, every every subject needs a rigour. Thinking is left alone thinking also has its own grammar and we should have a rigour around that. So we will talk more about.

Wonderful. We will probably. Great. Thanks a lot Satya and thankyou to all the listeners for giving your time. I am sure you are loving the podcast. Do share your feedback on the social media handles that we have. The links are in the details and you can also visit our website for many more articles on similar topics and much. Thankyou this is Shubham signing off. Bye bye.


Your Comment

Your email address will not be published.

Get in touch

Registered Office:
Vector Management Consulting Pvt. Ltd.
10th floor, Thane One, DIL Complex,
Ghodbunder Road, Majiwada,
Thane (West), Maharashtra - 400610, India.
022 6230 8800, 022 6230 8801

Corporate Identity Number:
For any queries, contact:
Mr. Hemal Bhuptani
[email protected]