Episode 47

Understanding the Importance of Deep Causal Thinking in Management

Category :  Thinking Process

In the second episode of this season, Satyashri Mohanty, dubbed "The Coach" at Vector Consulting Group, will be explaining one of the facets of Vector's Thinking Processes - Deep Causal Thinking Satya provides an extremely simple example to first explain the Deep Causal Thinking approach and then describes its significance in conducting diagnostics for business situations. We encourage you to listen in and try to apply these concepts to your own environment.

Shubham Agarwal : Hello and a very warm welcome to the 43rd episode on Counterpoint podcast. I am Shubham and we are going to talk about improvement projects on the podcast today
Shubham Agarwal : Hello, and a very warm welcome to the counterpoint Podcast. I’m Shubham Agarwal. And we are here in the second episode of season two. Now we’re going to talk about deep causal thinking today, and its application in management analysis. But to give you a small example as to what deep causal thinking is, let’s take an example of you having a headache. Whenever we have a headache, we typically take a painkiller. And, you know, the pain goes away. But there’s every possibility that the pain comes back, and back and back again, until we don’t find the real reason why is it happening? So, to solve the pain forever, the headache forever, you will have to ask why, and further why to that and reach the deep root cause as to why the pain is happening. Now, this is very similar to what we do in deep causal thinking in management analysis as well. And that’s what we’re going to discuss today. At Vector Consulting Group, we put a lot of emphasis in causal thinking, and all our consultants undergo months of training to acquire this skill of good causal thinking. This has helped us crack chronic problems of the industry, which have been left unattended for decades together. The podcast today is about giving an appreciation about the need for such a rigour in thinking. And we have none other than Satya, who is the best at thinking processes. He’s also leading the training and an organisation wide adoption of thinking processes at vector. So, let’s welcome him and start the discussion for today. Hi, Satya, a very warm welcome to counterpoint podcast in season two. How are you?
Satyashri Mohanty : Hi, Shubham, it has been a long time between season one and two.
Shubham Agarwal : Yes, it was yes. But it’s good to have you back. And it’s good to start the season again. Because there have been so many listeners who have written back to us asking when are the new episodes coming out? So, it’s really good to start the season two.
Satyashri Mohanty : Okay, so let’s do another take on thinking process.
Shubham Agarwal : Definitely. So, Satya, I want to start with, you know, asking you, what is deep causal thinking? And why is it such a big deal in management analysis?
Satyashri Mohanty : So, Shubham, let’s start with an example. And we will have a causal question in front of us, and let’s see how we are answering it. And based on the type of answers, we will understand this topic of deep causal thinking. Okay, so I have a very simple question for you.
Shubham Agarwal : Okay, yeah, we love examples. Great. Yeah,
Satyashri Mohanty : Yeah, you love examples, i know. So, we start with a very simple question, but promise me that you will not use your prior knowledge.
Shubham Agarwal : Okay, I will, I will do that.
Satyashri Mohanty : Okay, so the question is, why does the sun rise in the east? Okay. Now, if I look at this question, and it’s a very simple question, but as I said, we will assume that we don’t know anything about why it does. So, there are various categories of explanation. So, one explanation, it says that the sun rises in the east because it has been doing so for decades, that’s my experience. Or you can add more weight to it by saying, See, the sun rises in the east, because my grandma also says, based on her deep experience, it is always rising in the east. And hence, that’s how it is rising in the east, you can further add weight by saying, you know, my friend is a cosmologist in a big university. And he says, most of the planets in the solar system, that’s what the sun does, it always rises in the east, and hence the sun rises in the east. I put all these explanations as category one explanation. So, what do you think about it?
Shubham Agarwal : Yeah, if I keep all my knowledge aside, and whatever prior knowledge I have, even then I would say that it is just out of experience of, of, you know, although it is decades of experience, but it’s just out of experience from whatever has happened in the past. I don’t know, the real reason behind it.
Satyashri Mohanty : Yeah. So, you know why you are uncomfortable? Because all my explanations is actually not adding any new information. I’m just generalizing.
Shubham Agarwal : Yeah, exactly
Satyashri Mohanty : From many observations or I’m depending on authority, right? So, let’s try to move deeper into category two explanation, right. So in a category two explanation, there will be independent variable X leading to Y. So, I’ll give you an explanation where, you know, X leads to Y. So, the explanation goes like this. You see, I every time I’ve seen a rooster crowing. I’ve seen the sun rising in the east. So, my explanation is the crowing of the rooster leads the sun to rise from the east.
Shubham Agarwal : I’m sorry, I couldn’t stop myself. But it’s really funny. Yeah.
Satyashri Mohanty : Yeah. But as I said, you know, you’re finding it funny because you know the real answer, right?
Shubham Agarwal : Exactly. Yeah.
Satyashri Mohanty : So that part aside but look at the second explanation is far better than the first one. Okay, why because it is adding some new information it is telling that, hey, there is a variable called the crowing of the rooster and that is causing the sun to rise from the east. Right?
Shubham Agarwal : Yeah, yeah.
Satyashri Mohanty : Now what is what is other than, you know, being funny? What do you think is a problem here?
Shubham Agarwal : So okay, so let me let me say one more thing before we go to the explanation. If this was, if this would have been the real reason, no, I would have called upon that rooster, and probably gave him a sleeping pill on Monday morning, that solves the problem forever.
Satyashri Mohanty : Yeah, you’d have slept longer.
Shubham Agarwal : Yeah, I know. Right. So yeah, there is some explanation as in there is some reason why the sun is rising in this explanation. But still, there are a lot of questions again, one rooster causing it. What if the rooster does not crow? And the sun would still rise? All those sort of questions would start arising in my mind.
Satyashri Mohanty : Yeah. So, I will put it this way, we will look into the other reservations little later. I know you have you have created a lot of reservations we will reach to it later. But at this stage, I would say what this lack is a causal mechanism. When I say causal mechanism, that means it lacks a mediating variable that an X is causing Y. I don’t know how X leads to that Y, how the crowing of the rooster what does it lead to eventually that the sun rises from the east. So, the detailed mechanism is missing? So let me add a category three explanation, which has some kind of a mechanism. So, this could be even more funny. but please bear with me.
Shubham Agarwal : Yeah, yeah, sure.
Satyashri Mohanty : So, the explanation goes like this. So, when the rooster starts crowing, the pitch of the sound is so irritating. Yeah, the Sun God wakes up. And he does. So, from the east side. So now what I have given you is a mechanism as well, I’ve given you an independent variable, I’ve given you a detailed mechanism. Right? What do you think about this?
Shubham Agarwal : Yeah, there is some detail. But once again, the explanation or the mechanism is slightly not so believable. Because again, I think that is because of my prior knowledge. But
Satyashri Mohanty : Yes, Shubham, I know. Yeah, I know the struggle you are going through. But, you know, sounding funny or sounding weird is not a good criteria. If that was the criteria, we would reject many of our theories in physics.
Shubham Agarwal : Yeah, true.
Satyashri Mohanty : In modern physics, if you look at some of the explanations of, you know, quantum phenomenon happening around it sounds very weird, it sounds funny to people, right? So, so being funny, being weird is not the way to reject an explanation. Right. So to understand what is lacking here, we need to really verbalize it very well. So, for that, let’s go to the category four explanation, which we all know about.
Shubham Agarwal : Sure.
Satyashri Mohanty : Right? So, the category four explanation, which is the real one, which is the deep causal explanation for why the sun is rising from the east, we know that the rotation of the Earth from the west side to the east side in front of the sun gives us that apparent vision of sun rising from the east, right. So, what I told you is also has a cause and effect and a mechanism, all those characteristics are there. But now let’s understand what is the difference between the category three explanation which by the way, right, you know, X and a Y and a mechanism and a category four, which also had a X and a Y and a mechanism, right? So, what is the difference? Right. Now, let’s understand, if you love the explanation of rooster crowing, for some reason, let’s understand that there is there is somebody who loves this theory so much that this kind of, you know, believes in that theory. Now, there is a good chance that this theory can be potentially variable. Now, let me understand, what do we mean by potentially variable now, for example, when I’m saying that the crowing of the rooster you know, causes irritates the sun god and then he wakes up, you might ask a few counter questions, right, a few attempts to refute my arguments and the your refutation would be, I don’t I don’t know why, you know, the roosters pitch why that sound would be so irritating because, there are so many other sounds that are happening in nature and some of them would also be equivalent to the pitch of the rooster and sun good should wake up at random times, right.
Shubham Agarwal : Yeah.
Satyashri Mohanty : Now listening to that refutation. If I start changing my explanations, right, adding newer elements to it. For example, I might say, you know what, it is the relationship of the rooster and the sun god it’s so bad that you know the crowing sound irritates him he just wakes up right
Shubham Agarwal : So, once I started poking holes, you’re started adding new variables, new explanations onto that.
Satyashri Mohanty : I added new variable now you might ask that okay, I take your point, I take your point that this is rooster sound is irritating, but why should always he wake up from the east side? What is East got to do with irritation? Now I might say, okay, East has a energy field, which is a little negative. And, and so when somebody is feeling negative, he wakes from the east side. So what I’m doing here is I’m adding elements, right, to my explanation, and but I’m retaining the original direction of those causal
Shubham Agarwal : Somehow, yeah, somehow retaining,
Satyashri Mohanty : Yeah, retaining it the direction of the causal arrow which saying, okay, the rooster crowing leads to the sun rising the East. Now, what I’m doing here is I am giving you what is known as a variable explanation. Okay, I’m giving you a variable explanation and when I start giving you a variable explanation, that is what is known as a bad explanation.
Shubham Agarwal : Yeah, so, if we compare the two like the third, the category three and category four explanation,
Satyashri Mohanty : So, look at this if you try to refute category four explanation, right.
Shubham Agarwal : Right, yeah. Let me try to refute it. Suppose I argue that there are planets in solar system which have different direction of motion and yet the sun rises in east in all of them. I am just making a counter claim.
Satyashri Mohanty : So, when you offer me that reasoning, right along with maybe some proof, I have nowhere to hide, I must give up my theory. Yeah. Now, can you see the feature, one of the biggest features of the category four explanation is, it is refutable, it is falsifiable, I cannot add elements to it, it is non variable, right. So, so that is it is vulnerable in that sense that you can refute it. And I have no place to hide, and I have to give up. Right.
Shubham Agarwal : Right, right.
Satyashri Mohanty : Now let’s look at some more differences.
Satyashri Mohanty : Let’s look at the language. You see the language that I was using when I was using some kind of a variable explanation. I was depending on more and more vague language, I started using language like, energy field. Right, I started. And if you had asked more question to it, I would have maybe invented more vague language. And, and so look at the language that I’m using in category four explanation is very precise. Right,
Shubham Agarwal : Right. It is very short. It’s very precise. I’m not giving jargons and sort. Yeah,.
Satyashri Mohanty : There’s no jargon, right? So again, a good criterion is your language has to be very precise when you are depending on causal explanations, right? Now let’s look at let’s look at another difference.
Shubham Agarwal : So Satya, again, I’ll keep summarizing as an when we move to the next one. So one is that falsifiability The second is that the language should not be vague,
Satyashri Mohanty : Correct, absolutely.
Shubham Agarwal : And what else?
Satyashri Mohanty : Yeah, so let’s look at another you know, difference. So, in category four explanation, when I started talking about the rotation of the Earth, in front of sun, right and you know, the how the shadows are getting created, and hence the day and night happens and ends, you feel the rising of the sun, by the way, it is dependent on another theory, can you guess which, which one is that? It is dependent on another theory of physics, which is the optical theory of light, how light behaves? Right.
Shubham Agarwal : Ahh, okay, right.
Satyashri Mohanty : So, while I’m developing an explanation, I actually indirectly connect to another established theory, which is well proven. So in this case, I while you know, giving this explanation I reached to the optical theory of light, which is well established well experimented. Right. And so,
Shubham Agarwal : I won’t contend that theory.
Satyashri Mohanty : Yeah, but look at look at the explanation of rooster crowing leading to the sun rising in the east.
Subham Agarwal : Yes, it was not linked to any established theory. Infact you were adding new theories like feeling of irritation due to particular pitch of sound or why east has so called negative field. These were all new theories created just to support the original hypothesis.
Shubham Agarwal : that’s probably the third feature that you know, I have, I have linkages to other theories which are established, well established. And those are not vague, you know, out of thin air.
Satyashri Mohanty : Absolutely and they are they are established, they are experimented. They have been validated by you know, a lot of other scientists out there. Okay. So, I’m just borrowing from there while giving explanation for something that you asked me to explain. Right. So now let’s look at another difference. So the story is not over. There is one more difference, right.
Shubham Agarwal : Wow, okay.
Satyashri Mohanty : Now, because of this linkage, suppose if I ask you, if you go to some of these exoplanets, the planets, which are outside the solar system, which have their own star system, there are funny cases where the planet does not rotate. Okay, it is still, now in that planet, if you land up, what do you expect to see? There’s no rotation?
Satyashri Mohanty : Yeah. So, here, if you see, suppose if I tell you another thing that mercury rotates very, very slowly. Okay, as compared to Earth. Okay, what do you expect to see? If you go to Mercury, what do you expect to see
Satyashri Mohanty : A lot of time, something like, you know, it takes 100 I think 150 Odd Earth days for a sun to rise in mercury. So, so look at this, what is happening here is we started off by trying to ask the question, why does the sun rise in the east? While developing the explanation, we ended up explaining some other phenomena that we never wanted to explain in the first place.
Shubham Agarwal : Right, right. Yeah.
Satyashri Mohanty : So that’s the power of a goof causal explanation, yeah, there are the unintended outcomes, you asked me a question I answered. And suddenly that answer is explaining some other phenomenon that we never had in our discussion point. Right. So this is a good causal explanation, not just explains the phenomenon under discussion, but also many other in different domains.
Shubham Agarwal : Yeah, that is really powerful, I think, although the first three feature were powerful as well, but this is this highly powerful because now I can go beyond I’m going beyond whatever I was discussing with you probably the domain that I was talking to you with. And I go beyond that and make predictions, which is so powerful.
Satyashri Mohanty : Actually, you know, the fourth one is a property and you rightly identified the fourth one is not just a property it’s the very power of a causal thinking okay.
Shubham Agarwal : Right.
Satyashri Mohanty : Now, let us understand, let’s not totally give away the category 1, 2, 3 explanations right let’s not just throw it away to the dustbin Okay, and let’s understand that you know, particularly category one where we are trying to collect a lot of data, we can actually build a model right. And in fact, if you build a model, where you have data of rooster crowing and you have you know, high level of prediction other than maybe the cloudy days, mostly, you know, that model will work to a large extent, predicting the, you know, the sunrise to a large extent, it will always rise in the east. You will always see that in most of the cases the rooster is crowing. And you know that that has some prediction power, even though it is not having, let’s say a deep causal thinking, but it has some prediction power. So let’s give it the credit. Yeah, it deserves, right?
Shubham Agarwal : Yeah.
Satyashri Mohanty : So, what is a big difference between the prediction power of the category 1, 2, 3 explanations versus the category four explanation? Right? The category four explanation is it has got what I call a domain shifting predictability power. Right? It’s a, it’s a jargon that I’ve used, when I say domain shifting predictability power it is that.
Satyashri Mohanty : I have experience of the earth because I stay in the in the earth. Right. And, and I’ve seen the sun rising, and so I’ve built that prediction model, but I have never been to Venus right. But if I told you that Venus has a retrograde motion, which is opposing motion, you can easily predict where the sun will rise in Venus right, and I can go to a star system, and if you understand how the star system is, and what is happening to that planet, if I tell you a planet is still, without going to those planets, those exoplanets, way away from our solar system, you are able to easily predict what is going to happen. So, you know, or or for that matter, you know, we are talking about Earth and Sun at such a mega scale, but if I tell you, you know, I give you a globe, which represents the earth I give you a torch light, right? And I start moving, can you tell me what is going to happen? You will be you will be able to tell me what will happen, right? So the power of category four explanation is you, you can traverse beyond your domain of experience into newer domains. And using that causal theory, you can predict what is going to happen elsewhere where you have never been before. Okay,
Shubham Agarwal : Which I think is a real advantage. I think from you know, whatever discussion we’ve had till now, I think this is the real power of deep causal thinking that I can go beyond my domain and predict something so precisely, yeah.
Satyashri Mohanty : Yeah. And let’s look at another big advantage. So, Shubham if I ask you, how many experiments would you need, you know, to validate what I’m saying, how many experiments?
Shubham Agarwal : I think just one would be enough as well. I mean, even if I get one. Yeah.
Satyashri Mohanty : One experiment. And if you doubt that experiment, maybe you repeat it, but 1, 2, 3 data points, and you have established a theory and look at category one explanation.
Shubham Agarwal : Wow, yeah.
Satyashri Mohanty : It needs a lot of data points, to validate or invalidate the theory, look at category four explanation, it requires very less data point. Now, this has got a huge ramification in the speed of knowledge development. So, if you have a category four explanations, right, you actually generate knowledge at a much faster pace.
Satyashri Mohanty : Correct, Yeah, no, that that power, again, is very huge, because I just need one or two or three at best, or one experiment and validating that or invalidating that could give me that the theory, you know, stays or not.
Satyashri Mohanty : Yeah. And just to give you an example of, you know, the category one category 1, 2, 3 versus four, I remember, you know, I joined a steel plant as one of the maintenance managers. And I was in charge of a rolling mill. And one of the problems that we all grapple with in a rolling mill.
Shubham Agarwal : It’s very good to hear from you Satya about your experience beyond vector before vector because we’ve never really heard that so yeah, please.
Satyashri Mohanty : Okay. Yeah, so, I was always as a maintenance engineer, I was always fascinated with that one operator, who could always predict a coil breakage and coil breakage is a big nightmare in a rolling mill, it takes a huge setup time to setup, right. So, whenever that operator used to come in, we would have very less coil breakage because that guy knew and, and also to warn us what we have to do to manage it, and there’ll be very few coil breakages when that operator was in right. Every time we asked him to explain, you know, why, what is he doing what does he understand he would go mumbo jumbo, he’ll ramble, and we would never get a clear answer. Right.
Shubham Agarwal : Okay.
Satyashri Mohanty : And that guy, it’s not that he was hiding his knowledge or anything, but he was not able to verbalize, you know, what is what is working out there. He had some kind of rooster crowing model in his head. And he knew something right, the same guy.
Shubham Agarwal : So, he had seen that process so many times over and over, that he could somehow predict that,
Satyashri Mohanty : Yeah, looking at his musician like performance, we asked him to move to another rolling mill, which had a bigger coil breakage problem, that guy couldn’t do anything. And this is where, because you had a category one, two or three explanations in his head, not a deep causal explanation. When we shifted his domain. He was not able to do anything. His power to predict was not there. So, so this is what I wanted to highlight the, you know, the point of domain shifting predictability, which is, which is a very big one, when you do deep causal thinking,
Shubham Agarwal : And that’s, that’s, that’s a great explanation or there, that’s a great example. Because, you know, often we find that happening in organizations around us. They have some explanation to it, which is not so strong, but they’ve seen that process over and over. So, they have some, some vague predictive power, but that’s not very, you know, strong or entirely, like the properties that we discussed. It was It is not falsifiable and all of those.
Satyashri Mohanty : Yeah. So, for example, you know, this guy is very good in sales, we don’t know, why is he good? What is he doing? Even that guy does not know. Yeah, right. And we have some kind of vague thing that is that we cannot, you know, transfer from one person to another person, even to transfer one person, the knowledge of why we need that deep causal explanation so that we can abstract that knowledge and shift it to another person. Right? If you don’t have that, if you don’t know that causal mechanism, you become dependent on people, you know, when that guy was there, he kind of, you know, does something he is like, and many organisations depend on, you know, people like that, right? Because they never ask the deep causal question of why certain things are happening, or certain things not happening, right.
Shubham Agarwal : So, Satya, clearly, the deep causal thinking has great power. And, you know, if we were to use it in management sciences, it will enhance our results much, much, much more. Are you saying that we don’t use this deep causal thinking as much in our day to day management sciences, because all the examples that you’ve taken hint towards that?
Satyashri Mohanty : Yeah, the claim might sound preposterous, you know, my problem is, we are at a stage in management, where we don’t even appreciate the need of deep causal explanation. And by the way, you know, the points that I’m making is nothing but philosophy. Philosophy covers the topic of how you think and how we explain all of that, it’s never taught, philosophy is never taught in MBA schools. Right?
Shubham Agarwal : Yeah, sadly, not.
Satyashri Mohanty : Yeah, so the point is, if I have a bad explanation, I can get away with it. You know, the proof of it. You know, management is a field where people get away with jargons. People get away with vague explanations. And I would, I would put the blame on consulting industry.
Shubham Agarwal : I agree, Consulting industry is notorious for talking in jargons and making communication deliberately difficult to understand. The cartoonist Scott Adams makes fun about the practice of consulting industry.
Satyashri Mohanty : So, you know, people, people, people use vague language a lot. And that’s the first sign where we don’t even have a problem with that. So, you know, we should reach stage, for example, you know, in management, there is one unwritten rule that if you’re saying something without data, people won’t accept it. Right? But if you give a bad explanation, you will get away with it. Right? So my claim is, you know, in management, we’re happy with 1, 2, 3 level of explanation, we usually don’t bother.
Shubham Agarwal : So, your point is, the fact that the key professional community gets away with vague language is itself a proof that there is not even an appreciation about the need for deep causal explanation. Ok Satya give our listeners an example of good and bad explanation in context of a business problem.
Satyashri Mohanty : Look at some of the problem statement, let’s say, you know, you go to a company and say inventory is high and the question is why the inventory is high. The first thing is the default explanation, across is you know, the industry benchmark is like this, you are above the industry benchmark and that is why the inventory is high. Now, what do you call this, this is nothing but pure category one explanation, this is high because of authorities. So called that company where you know, it is much lower hence this is high or somebody is saying so, right. It is all category one explanation. Right. Or for that matter,
Shubham Agarwal : Yeah. And we love benchmarking, I mean, for that matter, you know, companies typically work with benchmarking, yeah.
Satyashri Mohanty : And the ugly truth of benchmarking is everybody knows that we are comparing apples with oranges. The product mix is different. The routings are different, the touch times are different, the market conditions are different. The lead times that you are exposed to are different, there are so many factors, right. But still, we use it as a reference to declare something as good or bad? Right. For example, if you say my sales productivity is low, okay, do you say so? Well, you know, industry benchmark is so much of turnover per employee you are having, you know, much less than that. Hence, this is what I call as a bad explanation. Right. Another explanation, you know people use a lot is they see that the problem is because I don’t have a solution. For example, you know, this is used by many, many vendors, IT vendors who would come in and say, hey, guys, if you’re if you have a delivery problem, you because you don’t have a very good software, which could do the skit.
Shubham Agarwal : Yeah. And that’s very typical.
Satyashri Mohanty : Yeah. So, you know, I’m not against it. But the point is, you have not bothered to develop a causal explanation of why things are wrong in your own organisation. Right. And, and you’re depending on what’s happening outside. So, when you say what’s happening outside is the reason what is happening in my organisation, people know, this is not the right way to look at things. I have a headache is a problem statement. I do not have a paracetamol, or a painkiller is not a problem statement. Right? Because when Yeah, when you when you try to look at a problem through the eyes of a solution, you don’t see the problem in its true gravity and you don’t understand much and this is one of the reasons you will find out there are a lot of fads, which get developed in management, suddenly something very popular withing few years, it just vanishes, why, because primary thinking is what’s happening elsewhere. So, let’s let me do it. Okay.
Shubham Agarwal : Can you now take the example of inventory getting high and give us a category 4 or a deep causal explanation.
Satyashri Mohanty : Yeah. So, just to take the example of why the inventory is high, and we try to develop a deep causal thinking right. In Vector, we would say you got to do it by staying in the client’s environment, you got to tell me what the client is doing with the assets that they already have with the IT assets, whatever they already have, what mistakes they are doing, that is causing the inventory to be high, right? And, and the explanation can go like this, hey, guys, the inventory is high, because the lead time is already very high. And because the lead time is high, I must forecast for a longer period, forecast for longer periods are erroneous, and hence the inventory is high. And, while the inventory is high. Also, there is cases where inventory is stocked out. So, what you’re seeing as a high inventory is also pinpointing to situations of low inventory.
Shubham Agarwal : I can connect to one feature of deep causal explanation, that you highlighted before. It not just explains the topic under discussion but another existing phenomenon or a topic that was not part of original discussion.
Satyashri Mohanty : You might further ask me why the lead time is high. Yeah, and you are not happy with that you will say why the lead time is high, I still have to explain in your environment, not go to and tell you what’s happening with your neighbour, I have to go and tell you, okay, the lead time is high, because maybe the rate at which you’re releasing material into the shop floor is much faster than your constrained resource. Because of which your WIP is piling up. Higher WIP means higher waiting time, higher waiting time is adding to the total lead time and hence, you got to forecast for a longer period and the complete explanation, now look at this way of explanation is not depending on what’s happening elsewhere. It is explaining staying there and telling what’s the real issue.
Shubham Agarwal : Right, I think Satya for that matter, this example of high inventory and taking the normal explanations that are being given in the industry and taking an explanation, which you just gave us, clearly shows us the difference and once again, establishes that why deep causal thinking is so powerful and so important. And yeah, it is a strong claim. But I think it makes a lot of sense that typically in organizations, we do not even appreciate the use of deep causal thinking, forget using it in day-to-day management analysis.
Satyashri Mohanty : Yeah, we got to reach a stage when, you know, in meetings when arguments are happening, people who point out saying that, hey, you violated the grammar of deep causal thinking now, that never happens.
Shubham Agarwal : I want to ask for an example, where, you know, Vector has used deep causal thinking and solved a problem. Could you give an example for that?
Satyashri Mohanty : Yeah. So, in fact, I would urge the listeners to go back to the previous podcast, and I think that was done by Malik. So yeah, and this was a company, which asked us that they had developed an app for order taking, right, they wanted their customers to place orders directly on the app. And, and, and it was part of their digital strategy. So, they spend lots of money doing that, but end of the day, people were not entering the order into that app. Now, they asked us, you know, we gave incentives, our app is so nice, it is, you know, you can just click and get your things done, why are people not using this app? And that was a question that was given to us. So, I will not reveal the answer. What I would expect is people go to that podcast, listen it again now, right, while listening check for these properties of good deep causal explanation. The first one, it has a cause and effect. That’s the first one. The second one, it has an mechanism, it has a detailed mechanism explaining how from the cause till the effect for the mediating variable, third one, it is non variable, right, which means it is falsifiable, right it is it is it has got a property where I can refute it, and the proponent would have no place to hide that is what I call falsifiable or non-variable, then it is stable, you can set up a test. Okay. Next one, it should always explain a phenomenon that we never intended to explain in the first place. So, while developing that explanation, we touched upon another topic, that the organization had never thought that we kind of answered another question that the organization never asked us to answer. Right. So, it had that property. And, and the, the last one was, that while developing this explanation, it should touch upon another established theory, like, you know, in the case of sun rising from the east, we touched upon the optical theory, right. So right, I asked people to, you know, look into this. Six I said.
Shubham Agarwal : Sure, yeah. So, the episode that Satya is referring to is the 46th episode, which is how to ensure a successful product launch, it will be great for all you listeners to go. And, you know, check all these properties, all these six properties that they have just mentioned, yeah Satya.
Satyashri Mohanty : And they can write back to us, it will be a good exercise for them to appreciate deep causal thinking.
Shubham Agarwal : Definitely. So, it’ll be great if you if you guys can guys can write back to us. If you find some loopholes, or if you if there’s any advice, comment, suggestion, question, whatever. So, it’ll be great to hear from you once you have listened to both the episodes. I think it was a great discussion that we had. And it was good to understand such a deep topic. Now what it also asks is for another episode to explain how to use it in our day-to-day life.
Shubham Agarwal : So thanks a lot Satya for your time. And once again, it was great having you on the on the podcast, as always.
Satyashri Mohanty : Thank you, thank you Shubham.
Shubham Agarwal : Thank you, and for all the listeners. You know what to do, please listen to episode 46. Write back to us. And we’ll keep coming back with more episodes, at least one on how to use deep causal thinking for sure.

The thinking process methodology followed by Vector, has been developed using the body of work from philosophers like Aristotle, Karl Popper, Sir Francis Bacon, Physicist David Deutsche and management guru Eli Goldratt. We call the process the Scientific and Systems Thinking Process

Thank you. This is Shubham signing off. Bye bye.


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