Rethinking How You Make Decisions With AI

[00:00:00] Tessa Burg: Hello, and welcome to another episode of Leader Generation, brought to you by Mod Op. I’m your host, Tessa Burg, and today I’m joined by Dhiraj Rajaram. He is the founder and CEO of Mu Sigma, and we’re gonna be diving into why most AI strategies are failing to deliver on real business impact. This is a common topic on the podcast.

[00:00:25] Tessa Burg: Dhiraj is bringing some real world examples to help you better understand where you need to start and how to use different types of frameworks, not only to determine what you build, but how to fully change the process in which you’re operating to unlock real innovation and real value. Dhiraj, thank you so much for joining us today.

[00:00:46] Dhiraj Rajaram: Tessa, thank you for having me. Uh, it’s an amazing opportunity for me to speak about this topic

[00:00:53] Tessa Burg: So before we jump in, tell us a little bit about yourself and Mu Sigma.

[00:00:58] Dhiraj Rajaram: Uh, Tessa, my name is Dhiraj Rajaram. I am the founder and CEO of Mu Sigma. Uh, I founded this company, uh, about 22 years ago. Um, we were- went on to be India’s– one of India’s first unicorns, and today are, uh, India’s most profitable AI company.

[00:01:20] Dhiraj Rajaram: Um, we typically work with large Fortune 500 companies, uh, helping them– helping prepare them, uh, for, uh, a new world of algorithms. We think of ourself as transformation Sherpas. Um, and, uh, this journey, even though the word AI is, uh, relatively new, uh, we have been working around this topic for quite some time.

[00:01:52] Dhiraj Rajaram: Uh, it used to be called advanced analytics. It used to be called big data. It used to be called machine learning, predictive sciences. So many different words, and, uh, for the, for this perspective that our world can be made very different, uh, by, um, uh, using technology. Um, so, um, uh, so we find, uh, you know, uh, so, so we’ve kind of learnt by working across Fortune 500 companies across more than 11, 12 different industries.

[00:02:28] Dhiraj Rajaram: Uh, and, and, and the learning, uh, is more whole because of the fact of the diversity of customers that we work with. So, so that’s, that’s Mu Sigma and me at a high level. I, um, uh, think of myself, uh, uh, as, uh, uh, uh, uh, both a, a creative person and a programmer. Uh, you know, uh, both are part of, um, you know, me.

[00:03:00] Dhiraj Rajaram: Uh, I do think that programmers can be very creative. So-

[00:03:04] Tessa Burg: I agree.

[00:03:07] Dhiraj Rajaram: Uh, so with that perspective, um, you know, I’ve always felt that there is a need for changing how problem-solving is looked at in the world. So that’s the broad lens, broad perspective from which we built Mu Sigma. Uh, not thinking about it as data or data science, but more as decision sciences.

[00:03:31] Dhiraj Rajaram: Um, and, um, and I sincerely even now believe that even though the new buzzwords like AI are available, I feel the bigger perspective is about decisions. The big D is about decisions How- Yeah … human beings make decisions and, uh, uh, and, and, and why we are gonna get better and better at it because of all of this technology that surrounds us.

[00:03:56] Tessa Burg: Well, you are the perfect person to guide us through this conversation today, since you have actually not only just started helping, as you said, shepherd people through this AI journey, but have seen it be successful. And right now, a lot of people are talking about ROI, but they still aren’t able to get to a place where they go from pilot to scale, and you describe this as the AI value gap.

[00:04:23] Tessa Burg: Can you tell us what exactly is that gap, and why are so many organizations finding themselves stuck there?

[00:04:30] Dhiraj Rajaram: Sure, sure. See, let me start by, you know, claiming where I feel we are. Um, every n- great new technology has created a bubble. Um, and AI is one of the biggest and greatest technologies that human beings have come up with, and therefore is going to create a bubble.

[00:04:53] Dhiraj Rajaram: We are already in that bubble Um, so which means that, uh, you’re gonna see some disappointment. You have to go through this journey of disappointments. Um, but that doesn’t mean that it’s not going to change our world in the long term. Uh, first thing first is that consumer AI got us excited. And, uh, boards got excited, uh, senior managers, senior executives got excited.

[00:05:22] Dhiraj Rajaram: They could play with it. They could download Claude. They could download ChatGPT. They could play with it, do maybe a few things that they never thought they could do. And quickly they went to the middle management and their own teams and said, “Why can’t we change our world based on all of this?” And, uh, when that happened, uh, it seemed quite logical that, oh, the, the world is going to shift tremendously.

[00:05:47] Dhiraj Rajaram: But what we didn’t anticipate as much is the unaddressed complexity in many large organizations. As these organizations have become more and more successful, they have been adopting layers and layers of unaddressed complexity. Uh, the, I call it the spaghettification of the organization. Um, this s- uh, spaghettification means that the organization is more connected than it can fathom.

[00:06:29] Dhiraj Rajaram: Um, it, while it believes that, its people believe that they want to be independent, and they really love their independence, they are now more interconnected and interdependent than ever.

[00:06:44] Tessa Burg: Mm.

[00:06:45] Dhiraj Rajaram: So they’d like to work from home, but they can’t work from home. They can’t make things happen when they do that. Um, there’s, the spaghettification, uh, came out of very valid reasons.

[00:07:02] Dhiraj Rajaram: It came from past success, uh, because when you have success, you have a new market, a new product, a new type of customer. Every time something new comes on, on to, on the old.

[00:07:16] Tessa Burg: Mm-hmm.

[00:07:16] Dhiraj Rajaram: Uh, now that has meant there’s, that there’s a lack of transparency of data- There’s a lack of persistence in conversations between human beings.

[00:07:30] Dhiraj Rajaram: There’s a lack of cumulativeness of the compute environment. People land up doing projects to projects, not programs. All of this has meant that for this new technology to land into this spaghettified world, it makes it very, very hard. And, uh, the old world in which they were thinking about problem- so problem-solving worked out very well for them, but it’s not gonna work out in the future for, for, for the very same reasons.

[00:08:03] Tessa Burg: Mm-hmm.

[00:08:04] Dhiraj Rajaram: So we’re kind of learning why it won’t work and what the new world ought to be in which you can live, uh, up to the promise of enterprise AI. But as of now, we are going through the trough of dis- disillusionment, I would say, disappointment. Uh, but, but that’s suppo- that’s, that’s something we have to experience, and we have to experience that to go through the, uh, the, the good parts of what it could do for us.

[00:08:34] Dhiraj Rajaram: But we need to change our mind, uh, in many ways of how we think about problem-solving.

[00:08:41] Tessa Burg: Yeah, I think that’s a really strong call-out, because you started by highlighting that there have been other technological bubbles, but this one is different in that we can’t treat it, how we go to market with it, how we use it to serve our customers as just a tool on top of what we’re doing.

[00:09:05] Tessa Burg: We have to change how we’re doing what we’re doing.

[00:09:09] Dhiraj Rajaram: Mm-hmm.

[00:09:10] Tessa Burg: And I think it was a really powerful statement that you said people want to be more independent, but they don’t fully realize how connected they are. And I, I hear this a lot when we start with really where to get started with AI, and we look at an existing process, and you start to learn about the different steps, and we ask about the points of friction.

[00:09:33] Tessa Burg: But the way people look even at those points of friction is almost why they’re necessary or where they came from, and they do couch it in past successes, not realizing that that could be the thing that’s actually holding them back. And it’s, it’s sort of hard to be like, “Okay, we can learn from what we did in the past, but we can’t exactly…”

[00:09:58] Tessa Burg: And to make decisions the same way, and I’d really love to dive a little bit deeper into that, ’cause you’re proposing to make decisions differently, not going above and beyond just working differently.

[00:10:12] Dhiraj Rajaram: Yeah, yeah, yeah. Uh, first of all, I would say that every bubble, every new technology bubble has said, “This time it’s very different.”

[00:10:22] Tessa Burg: Yeah. Yes.

[00:10:24] Dhiraj Rajaram: So I think it’s, uh, you know… But the… And the reality is every new technology is built on previous technologies and therefore has to be bigger.

[00:10:35] Tessa Burg: Mm-hmm.

[00:10:36] Dhiraj Rajaram: Uh, so, so the, it’s the, so there’s a natural inflation in the bubbles, in the nature of bubbles. It’s a natural inflation. I’m saying, uh, it won’t be a, it won’t be called a bubble if it was the same bubble as the last one.

[00:10:50] Tessa Burg: Mm-hmm.

[00:10:50] Dhiraj Rajaram: Because we would have got used to it.

[00:10:52] Tessa Burg: Yeah.

[00:10:52] Dhiraj Rajaram: You know? A bubble is something that creates an am- an amount of expectation that it does not meet for a long time, uh, and that is when that disappo- the feeling of that disappointment is all of those things that makes it a bubble, right?

[00:11:11] Tessa Burg: Yeah.

[00:11:11] Dhiraj Rajaram: So the, by the very nature of it, it has to be bigger.

[00:11:14] Tessa Burg: Mm-hmm.

[00:11:15] Dhiraj Rajaram: Uh, so, so I would start with that. Um, the second thing I would say is that everything that we have done, uh, has come from a very much more deterministic world than today. Um, so, so what do I mean by that? Well, what I mean by that is that, uh, the, the, the, the world that we live in, as we continue to do better and better, uh, if you are a large company, a large retailer, or a large pharma company, the market gives you permission to exist on an everyday basis, and you’re winning that per- permission from the market.

[00:12:01] Dhiraj Rajaram: Each time you win that permission, you’re kind of… The, the very nature of you proving, uh, proving to the market that you deserve to exist means that you are, you’re absorbing more and more complexity in your world Now, what that means, uh, is that y- you are no more competing on just economies of scale, a bigger is better world.

[00:12:30] Dhiraj Rajaram: You are now have to compete on economies of speed-

[00:12:33] Tessa Burg: Mm-hmm …

[00:12:34] Dhiraj Rajaram: uh, which is a faster is better world. Uh, you know, the bigger is better becomes like a standard now, and then what is a differentiator becomes faster is better. You’re no more competing on just products and services. That has become standard. You’re competing more on building experiences, which

[00:12:52] Dhiraj Rajaram: has become the differentiator. Now, uh, y- y- to- as we, uh, you know, enter, uh, such a world, the, the deterministic way, deterministic environment around which we learned problem-solving is challenging the n- challenging us because we have entered a non-deterministic uncertain world. Now, let’s understand the source of uncertainty a bit.

[00:13:19] Dhiraj Rajaram: First thing is that your organization has more and more internally, it has what is internal to the organization. Think of the organization as what is internal to it and what it gets affected from outside in. So what is internal to it is the unaddressed complexity. Then the market volatility is impacting it from outside.

[00:13:42] Dhiraj Rajaram: The problem ambiguity is impacting it a little bit from outside, a little bit, uh, from, uh, inside because problems can exist both inside and outside your world. So when you have problem ambiguity, market volatility, and unaddressed internal complexity interacting with each other, that produces a certain amount of uncertainty.

[00:14:03] Dhiraj Rajaram: That uncertainty, to deal with that uncertainty, you need a very probabilistic way of thinking about problem-solving. Every one current state does not have one future state. It could have many, many future states. So how do you, uh, think of problem-solving in that world? You’ll have to, uh, you change your ways of problem-solving.

[00:14:25] Dhiraj Rajaram: So that’s what I’m, uh, uh, uh, you know, uh, learning as I interact with all these organizations.

[00:14:33] Tessa Burg: Yeah. So let’s focus on what you’ve observed and what you’ve learned from working with many different organizations. Do you have a couple of examples of companies that are doing this really well, or that maybe-

[00:14:46] Dhiraj Rajaram: No

[00:14:47] Tessa Burg: they’ve gone through the, the wave of disappointment and they’ve come out on the other end?

[00:14:51] Dhiraj Rajaram: Yeah, yeah, yeah. So, uh, so we’re working with, uh, you know, uh, a large, uh, you know, home improvement retailer, and w- what we, uh, saw that they, they… Any organization is in the business of, uh, uh, you know, persuadability.

[00:15:14] Dhiraj Rajaram: So, like, if the people in the organization cannot persuade the organization to do something, it’s not a good organization. Mm-hmm. So you have to be able to persuade the organization. It’s like a machine, right? So, uh, you can have, like, various types of machines. You can have an alarm clock, which you persuade to ring at a particular point of time by setting the alarm clock, and that’s a very…

[00:15:36] Dhiraj Rajaram: It’s a small memory it has, and it- in that it captures that, hey, 5:00 AM I have to ring. Then you have a thermostat where the memory is a little bit a richer memory because you are constantly real-time checking temperature and changing things. And then you have maybe a nice pet, uh, which has emotional memory.

[00:15:55] Dhiraj Rajaram: It really cares about you. It cares about your feelings. And then you have human beings who kind of have very complex memories. They remember more things than you would like them to remember. You know, and that’s a very different way of interact. So as the memory, quality of memory increases, you know, your persuadability increases.

[00:16:15] Tessa Burg: Mm-hmm.

[00:16:16] Dhiraj Rajaram: So your organization is an organism. It’s also a machine. It’s al- it’s also an organism, and it has its own memory, but the quality of memory is something we have to ask, what is the quality of memory? Now today, there is a reality representation gap. What that means is, in an IT system, if you are a home improvement retailer, inside the IT system, I have a pretty good understanding of the number of door frames that were sold in store number 32.

[00:16:46] Dhiraj Rajaram: But what I don’t have is all the decisions that were taken to make that number happen. I don’t have the discounts given. I don’t have the relationships with the vendor. I, uh, what the contractual obligations were. I don’t have the shrink inside the org- uh, inside that store. I don’t have the weather outside the store that affects that.

[00:17:07] Dhiraj Rajaram: So I ha- I don’t have all of this information, but I have just this one information stored in rows and columns which says, so many door frames were sold. So what you have is an action trace. You don’t have a perception trace and a decision trace. Human beings go through perceptions first, then decisions, and then actions.

[00:17:27] Dhiraj Rajaram: But all you are capturing in IT systems is actions.

[00:17:30] Tessa Burg: Mm-hmm.

[00:17:30] Dhiraj Rajaram: So you have a low-quality memory because it is only a memory of data coming from an action trace. You don’t have a memory of process coming from the decision trace, and a memory of purpose coming from the perception trace. So you have very low-quality memory.

[00:17:50] Dhiraj Rajaram: So unless you change that quality of memory inside the organization, first thing, and second thing is you have to stop thinking about problem-solving in parts. Mm. So we got very good at so- problem-solving in parts. We like to do this, marketing. We like to do pricing. We like to do forecasting. We like to do replenishment.

[00:18:10] Dhiraj Rajaram: We like to do supply chain. So we became very good at doing things in parts, but we gotta start seeing things as a whole because experiences are made as a whole.

[00:18:22] Tessa Burg: Mm-hmm.

[00:18:22] Dhiraj Rajaram: The customer sees the whole. He doesn’t see just marketing. He doesn’t see just forecasting. He sees the whole. So, so how do you get a customer who sees the whole?

[00:18:33] Dhiraj Rajaram: If you want to produce experiences that see the whole, you have to do problem-solving as a whole. So you have to stop doing problem-solving as entities or in parts. You have to start solving for problems as interactions as a whole. So this new perspective to seeing problem-solving as interactions Needs not a world of rows and columns, which is databases, but it needs a field of context-

[00:19:01] Tessa Burg: Mm-hmm

[00:19:02] Dhiraj Rajaram: which has a perception trace, a decision trace, and an action trace. So what we are helping large organizations do is before you jump into AI, build a field of context. Understand the field of context. See, what AI is doing is it is easily exciting people to be builders.

[00:19:23] Tessa Burg: Mm-hmm.

[00:19:24] Dhiraj Rajaram: So everybody has a higher builder mindset now.

[00:19:26] Dhiraj Rajaram: “Oh, I can do this with Claude. I can do this with, uh, Open, uh, Chat-GPT, all of this. I can do, do this with new technology.” Everybody has the… is excited to have a higher builder mindset, but it is not purely a builder mindset that helps you solve a problem, it’s also the user mindset. So the builder mindset and the user mindset have to improve the interactions between each other.

[00:19:50] Dhiraj Rajaram: They have to harmonize that interaction. A very heavy builder mindset with a very poor user mindset is worse off than a medium builder mindset and a me- medium user mindset. So the… So what we are saying is, how do you b- bring empathy into the problem space?

[00:20:10] Tessa Burg: Mm-hmm.

[00:20:11] Dhiraj Rajaram: To bring that empathy into the problem space, Tessa, we have to build fields of context, and see the problem space as a whole, and bring more design thinking into the problem-solving space.

[00:20:23] Dhiraj Rajaram: There are only two personalities in, in an organization, and I said not two people, but two personalities. The two per- And I could take on that pers- any personality, but the two personalities I could take on are being a problem solver or being a solution consumer. So the interaction between problem solvers and solution consumers must work really, really well, and that’s what we are facilitating using a field of context.

[00:20:50] Tessa Burg: That was an amazing answer, and I think one of the most powerful things that you said was around the context. And for those who are sitting in a seat and they’re like, “Well, my organization hasn’t allowed me to get access to the tools to build. I know that I can build. At home I might be using these tools to build things.

[00:21:10] Tessa Burg: I’m feeling like I might be behind.” And the organization themselves is like, “We gotta start with this strategy first. We have to start with, uh, maybe a specific app or tool first, and then we’ll decide who gets what.” When I hear that type of process that a lot of organiz- and, and this is, you know, many different organizations doing this, but especially in businesses like banks and hospital systems where they feel they have more regulation, I feel like what they’re mi- missing is exactly what you said, which is start with the context first.

[00:21:46] Tessa Burg: And every business, not just those industries, have created their own complexities that have kept them separate, and I don’t think they’ve brought that to the front yet. They’re not… There’s not enough… They have to have A time where they’re bringing, like you said, more empathy for why there are gaps and blockers and separation, and not so much of following the same processes they used to follow where it’s like, “Well, we’re gonna try it over here, and this department owns this, and that department owns that.”

[00:22:23] Tessa Burg: Like, where, where is a- where’s that field of context? I just love that phrase. Yeah. For what are the things that we need to decide on together.

[00:22:32] Dhiraj Rajaram: Yeah. You know, it, they also deserve empathy because, uh, those organizations have not had a need for that till today. Yeah. True. So the need for that is arising from the sudden increase in possibilities and the sudden increase in the builder mindset.

[00:22:49] Tessa Burg: Mm-hmm.

[00:22:50] Dhiraj Rajaram: So while technology companies from the West Coast of United States have done, um, a lot to increase the builder mindset in the world, they’ve not done enough to increase the user mindset, you know? So, and that has to be done by the users themselves. So that happens in, uh, Atlanta and Bentonville and Chicago, where these technologies have to land, in Idaho, um, in, uh, uh, you know, in, in, in places where companies that make stuff happen, make stuff that we-

[00:23:28] Tessa Burg: Mm-hmm

[00:23:28] Dhiraj Rajaram: use, we eat, we,

[00:23:32] Dhiraj Rajaram: uh, you know, uh, we consume, you know? Uh, so, so enterprise AI is about helping enterprises that make things that we consume, you know? Uh, so, so, so it’s, it’s different from, uh, uh, you know, uh, uh, uh, yeah, you, you can, you, you can do cool things, uh, uh, uh, in the consumer world because it has not yet… It does not have as, as much unaddressed complexity.

[00:24:02] Tessa Burg: Mm-hmm.

[00:24:02] Dhiraj Rajaram: Uh, a consumer is still a single, a single-person organization. Think of a, what is a consumer? A single-person organization. You know? So when you see the world as a, you have only two types of organization, a single person organization and a multi-person organization. And then you have a mult- when you have large number of people, uh, the num- amount of interactions between them has created so many, so much complexity, uh, and that, then that, that’s, that gets, uh, uh, you know, compounded with, uh, geographic distance, market distance, uh, product distance, segment distance, technology distance.

[00:24:40] Dhiraj Rajaram: So all these distances start creeping in to, uh, just the number of people issue. So, so, so, so what worked in the consumer world, n- it not working in the enterprise world, we should not be so surprised by it, but seems like we are surprised by it. But that’s a natural bubble that gets created. The, the, y- make something work cool in an int- consumer world, create a big bubble, create a big valuation, consume a lot of money from that valuation, make sure you can use that money to make other things work.

[00:25:12] Tessa Burg: Mm-hmm.

[00:25:13] Dhiraj Rajaram: So this is a typical pattern. So w- we get fooled again and again the same way, uh, through an interaction between a technology guy and an investment banker coming together and doing this again and again to us, and we kind of like are sheep, uh, you know.

[00:25:29] Tessa Burg: Yeah.

[00:25:29] Dhiraj Rajaram: Uh, so, but that’s okay. But that’s, uh, but that’s, this is not a new pattern.

[00:25:33] Dhiraj Rajaram: This is an old pattern.

[00:25:35] Tessa Burg: Yeah. No, that’s true. It, it is. I just chuckle because, um, this pattern is actually part of the show Silicon Valley, which was made, like, a really long time ago.

[00:25:47] Dhiraj Rajaram: Yeah, yeah.

[00:25:47] Tessa Burg: But they talk about that cycle in a, in a funny and amusing way. It’s, like, one of my favorite-

[00:25:52] Dhiraj Rajaram: Yeah, yeah. It is …

[00:25:52] Tessa Burg: TV shows.

[00:25:54] Tessa Burg: Um-

[00:25:54] Dhiraj Rajaram: We, we are, human beings are quite amusing.

[00:25:57] Tessa Burg: Yes. Yes, they are. Like several sheep. And they, I think they even use that same phrase, which- Yeah … that sort of just, like, cracks me up.

[00:26:05] Dhiraj Rajaram: Yeah.

[00:26:05] Tessa Burg: Um, so if we look at, I wanna make this more, help make it more tangible, uh, f- for listeners, and you, you cite a couple of examples.

[00:26:15] Tessa Burg: They are CPG companies that have done this well, and I believe it’s Starbucks and Pizza Hut. Tell us a little bit about what have you seen in the way that they’ve changed the way they make decisions that then does impact the experience and impact, uh, their customers?

[00:26:33] Dhiraj Rajaram: Sure. I could even show you, uh, a small example from, in a video.

[00:26:38] Dhiraj Rajaram: I don’t know if I’m allowed to share that here.

[00:26:41] Tessa Burg: We, well, we can- But- … definitely put the link to the video on the podcast page on the website. So- Yeah, yeah … yeah, we can take a look at it, and you can voiceover it, and

[00:26:49] Dhiraj Rajaram: we’ll make it a- Yeah, yeah. So I can, let me start by saying, you know, the patterns f- and then I’ll show, I’ll play the video for you, and then you can, you can keep it as part of the recording.

[00:26:57] Dhiraj Rajaram: Um, but, uh, and then you can decide. But here is the thing, right? First thing is, uh, appreciate the fact that- Your old world of problem-solving came from a world which was one current state has one future state. Now you have one current state has many possible future states. So in your old world, you could use ROI as a governing principle.

[00:27:23] Dhiraj Rajaram: You can’t use ROI anymore as a governing principle. You have to use ROO, return on options. So you have to only answer to uncertainty is optionality The old world was linear, where you could t- go from current- one current state to one future state. The new world, you can’t be linear. You have to be a little nonlinear in your thinking.

[00:27:45] Dhiraj Rajaram: The old world was purely intelligence based and logic based and ITs based and Waterfall model. The new world is no more just logic based. It is, uh, an intelligence based. It is intuition based. It’s design based. It’s observation based. So you have to take that design perspective and combine it with the intelli- the intelligence and the intuition have to combine together to create a new way of thinking about problem solving, um, where clarity emerges through action.

[00:28:21] Tessa Burg: Mm.

[00:28:22] Dhiraj Rajaram: Uh, a- in the old world, uh, you know, action emerged because of clarity, and you got all your clarity, and then you decided to act. Now you don’t have all the… We are living in a world I call Jack knows jack shit. So in that Jack knows jack shit world, you have to, you have to, uh, you have to keep, uh, un- uh, being hum- be humble about the fact that we don’t know the, what will happen in the future, but we kind of have a sense that we have to make, we have to make progress.

[00:28:56] Dhiraj Rajaram: Uh, and through that progress, we learn more and more, and then we kind of, uh, you know, live with that humility on a constant basis. You kind of literally have to live with humility a lot more in the way you think about problem solving. So which means that you cannot be solving problems as parts. You have to be problem solving as whole.

[00:29:16] Dhiraj Rajaram: You have to be problem solving using interactions. You cannot be… Your source of truth cannot be databases. Right. Your source of truth has to be field of contexts. So preparing your organization for solving specific problems will also include that you will prepare your organization for a better art of problem solving.

[00:29:36] Dhiraj Rajaram: You will develop better capability.

[00:29:39] Tessa Burg: Mm-hmm.

[00:29:39] Dhiraj Rajaram: You cannot just make good food. You have to build a better kitchen, too. Yeah. So organizations, if they say that, “Ah, I, I, I, this AI thing is exciting. I’m gonna make better food with it,” they’re gonna f- fail. They have to understand that, oh, sh- this AI thing is a new kind of cooking.

[00:29:57] Dhiraj Rajaram: I’m not gonna be able to make this new kind of cooking till I upgrade my kitchen for Italian food. I need a, I need a pasta maker. I need a cheese grater. I need a better oven. I need this. I need that. You can’t suddenly go from Indian cooking to Italian cooking without having all these other- uh, aspects.

[00:30:17] Dhiraj Rajaram: Uh, most of cooking in the West has been assembling. They call it cooking. They just assemble stuff, you know? The East has, uh, given you a different perspective for cooking. Cooking is much more than just assembling, you know?

[00:30:30] Tessa Burg: Mm-hmm.

[00:30:31] Dhiraj Rajaram: So, but, uh, now I think organizations are going from an assembling world to a real cooking world, so a lot of things have to happen.

[00:30:38] Dhiraj Rajaram: They have to build a better kitchen. They have to like… Their world is now complex enough. So there’s no difference between Western world and Eastern world other than the amount of complexity and history involved in it, you know? So the same thing is happening to organization. We just are taking in more and more complexity now

[00:30:56] Tessa Burg: I love that analogy to build a better kitchen.

[00:31:00] Tessa Burg: Yeah. I mean, that- it’s so easy to relate to because that breaks down the walls in the organization. It invites, you know, different perspectives, different ingredients, different flavors to all come together in a shared space. And-

[00:31:14] Dhiraj Rajaram: Yeah, I could actually… You know what? I could play this video for you and maybe pause and show you what a field of context looks like, just to make-

[00:31:22] Tessa Burg: Sure

[00:31:22] Dhiraj Rajaram: you and the audience, uh, look. So this is, this is what a field of context looks like, right? This one is not just about the, the data that you have, but also the, all the purpose of that data, the process of that data, how it flows-

[00:31:38] Tessa Burg: Mm-hmm

[00:31:38] Dhiraj Rajaram: … what questions are you asking, how are they connected to each other, and seeing all of that in that way.

[00:31:44] Dhiraj Rajaram: So, so that’s gives you… makes it real for you.

[00:31:48] Tessa Burg: One thing I will say about that visual that I… for people who are just listening, is it looks a lot like a mind map. And can you tell me a little bit about the clusters on that- Yeah … mind map?

[00:32:01] Dhiraj Rajaram: Yeah, yeah, it is. It’s… That’s the word I get a lot. Um, it’s a, it’s a mind map, you know.

[00:32:08] Dhiraj Rajaram: Um, and that’s a good word, uh, to start off with. But now I say it’s not just a mind map, it’s a field of consciousness, you know?

[00:32:18] Tessa Burg: Mm-hmm.

[00:32:18] Dhiraj Rajaram: So, uh, a field of context is a field of consciousness a lot more than just mind. Mind is when the thinking happens, you know. Mm-hmm. But there is a lot of things that happen, you know.

[00:32:29] Dhiraj Rajaram: When, when I ask you, Tessa, about the most important decisions of your life, it’s, uh, nothing to do with your mind. How you fell in love with somebody, you know. Uh, you know, uh, yeah, sometimes we regret, “How the hell did I fall in love with this person?” But, you know. Yeah. But jokes apart- Yeah … the, the most important things in our life have not come from mind.

[00:32:52] Dhiraj Rajaram: It has come pre-mind.

[00:32:54] Tessa Burg: Mm-hmm.

[00:32:54] Dhiraj Rajaram: Uh, and post-mind, right? So this, uh, mind is still the where the thinking happens, the decision happens, the explainability can happen, and you can, uh, you feel good about it. But it’s much more than that. There’s the things that are happening in the perception world, you know?

[00:33:11] Tessa Burg: Mm-hmm.

[00:33:12] Dhiraj Rajaram: Uh, and, uh, so, and things that are happening in the action world, so there’s perception, decision, and action, right? So the mind map only ca- captures the, the, the, the, the, the, the thinking part, the decision part of it. But this is much more than the thinking part also. Uh, and that’s why I feel of it as a field of context is a, a, a f- a field of consciousness which kind of allows you to have very different interactions.

[00:33:40] Dhiraj Rajaram: Today, there are three kinds of interactions between problem solvers and solution consumer personalities. The first kind of interaction is the poorest kind of interaction, which is debates. Mm-hmm. And debates are fact-based, you know? “Oh, my fact is different from your fact, and therefore I am right and you are wrong,” you know?

[00:33:59] Dhiraj Rajaram: So that’s a, that’s a very poor kind of interaction. The second kind of interaction is discussion. Discussion is less fa- is maybe fact-based, but it is, it is allowing for other facts also. So all the facts get into a bucket, and then you make like this stew, you know? You make a big stew out of it. It’s not really great cooking, but it’s just a big stew, you know?

[00:34:21] Dhiraj Rajaram: So, uh, and then you have the third kind of interaction, which is the best kind, which is dialogue. You know, one entity makes the other entity better. One condiment makes the other condiment better. The food really is enhanced by the various things interacting with each other, you know?

[00:34:40] Tessa Burg: Mm-hmm.

[00:34:41] Dhiraj Rajaram: For dialogue to happen, facts cannot be the only way you think about it.

[00:34:44] Dhiraj Rajaram: You need frameworks.

[00:34:45] Tessa Burg: Mm-hmm.

[00:34:46] Dhiraj Rajaram: A dialogue works better with frameworks, right? So ontologies, fr- frameworks are, are built on ontologies, you know, ways of thinking about problem spaces and how they interact, and then they have memory of purpose, memory of process, memory of data, all of them interacting with each other.

[00:35:03] Dhiraj Rajaram: That’s the field of context. That’s the field of consciousness, much more than a mind map, I would say.

[00:35:09] Tessa Burg: Yeah, and I like in the video it showed there’s a combination of people observation and then leveraging technology to pull out more actions- Absolutely … and more interactions that we as people don’t always, can’t see.

[00:35:24] Dhiraj Rajaram: Ab- we can’t see, because we have to… It just f- you know, before you serve a great experience to somebody, you have to serve them humility.

[00:35:33] Tessa Burg: Mm-hmm.

[00:35:34] Dhiraj Rajaram: Uh, and, uh, the problem space shifting is a s- is serving them humility. “Oh, I thought I was solving this problem. I’m actually solving something different.” You know?

[00:35:43] Dhiraj Rajaram: And you have three kinds of data, right? The data that you have, you work on it, data that you don’t have but you can get from outside, and then data that you have to create, right? So the more and more you appreciate the problem space, the more and more you will orient yourself towards getting all three kinds of data.

[00:36:01] Dhiraj Rajaram: And then you’re, you’re more and more contextual to the reality. Uh, a- a- and there’s lesser of a reality representation gap. So, in a world of agents and agentic AI, uh, you know, building field of context is going to become essential.

[00:36:19] Tessa Burg: Yeah, I agree. Well, we are at time. That flew by. This has been an amazing conversation, and I think all the listeners should check out the podcast page.

[00:36:30] Tessa Burg: We’ll have a link to the video there. They can get the full transcript, really start to reflect on what does it mean to build a field of context, and how can you start to pair those human observations with technology to get those different types of data, and that will be the fuel to making decisions differently.

[00:36:51] Tessa Burg: Um, really appreciate your time today. It was great having you on the podcast. If listeners wanna find you after they hear this episode, where can they find you?

[00:37:00] Dhiraj Rajaram: Uh, they can find me at, uh, www.mu-sigma.com. Uh, the dash in between mu and sigma is very important. Don’t forget it. Uh, it stands for how mu and sigma interact with each other.

[00:37:15] Tessa Burg: Oh, okay. Nice. And then we’ll also have a link to Mu Sigma on the podcast page. If you want to hear more episodes of Leader Generation, you can find them at modop.com. That’s M-O-D-O-P.com, or just search Leader Generation wherever you listen to podcasts. And until next time, thanks again for coming, and I hope you have a great rest of the summer.

[00:37:38] Tessa Burg: I hope it’s not too hot.

[00:37:39] Dhiraj Rajaram: Thank you. Thank you. Thank you for the opportunity.