2855: Navigating Uncertainty: The Mu Sigma Way

[00:00:00] Have you ever wondered how the world's biggest companies make decisions in an era where the

[00:00:07] only constant is change?

[00:00:09] Well today we're going to pull back the curtain on the art of science and decision making.

[00:00:16] With today's guest, Dharaj Rajaram, and he's the visionary founder of Mu Sigma, the first

[00:00:21] unicorn startup from India that is revolutionising how Fortune 500 companies solve complex problems.

[00:00:29] And my guest's journey is not just about building a successful company, it's about fostering

[00:00:34] a culture where learning trumps knowing.

[00:00:38] And problem solving is all about understanding the intricate dance of interactions.

[00:00:44] So the big question is, how does a company like Mu Sigma stay ahead in this fast paced world

[00:00:50] of technology and big data?

[00:00:52] And what can we all learn from their approach to navigate in the unknowns of the future?

[00:00:58] Now before I get today's guest on, quick shout out to the sponsors of Tech Talks Daily because

[00:01:03] in today's remote first world, I think settling for outdated managed file transfer solutions

[00:01:08] means ultimately you're risking your sensitive data.

[00:01:12] But if you upgrade to Kiteworks, the gold standard in secure MFT, boasting FedRAMP

[00:01:17] moderate authorisation, Kiteworks isn't just secure, it's a complete transformation

[00:01:23] of how your business handles file transfers and the communications.

[00:01:27] So say goodbye to compromise and hello to unmatched security and efficiency.

[00:01:32] And you can do that by making the switch to kiteworks.com.

[00:01:35] Visit kiteworks.com to begin, that's kiteworks.com to secure your data and empower your business.

[00:01:43] But now let's get today's guest on.

[00:01:46] Well buckle up and hold on tight because no matter where you're listening in the

[00:01:49] world I'm going to beam your ears all the way to India where we're going to

[00:01:53] delve into all these questions and many more as we attempt to uncover the principles and

[00:01:59] practices that drive innovation at the intersection of business and technology.

[00:02:07] So hey Basu, well welcome to the show, Dharaj.

[00:02:10] Can you tell everyone listening a little about who you are and what you do?

[00:02:14] Yeah. Hey, I'm Dheeraj. I'm the founder of Musigma.

[00:02:17] We happen to be a decision sciences company which helps large Fortune 500 companies

[00:02:27] change the way they think about problem solving and use digital technologies,

[00:02:34] anything to do with data, analytics, predictive modeling, AI, all the good stuff

[00:02:41] to change the way they operate. We work with 140 Fortune 500 clients over

[00:02:52] more than 10 different industries. We also happen to be India's first unicorn

[00:02:57] and we've had a good run over the last two decades. More than 15,000 people have been

[00:03:07] trained inside Musigma on data science and what we think of it, we like to call it decision sciences

[00:03:15] because it's about the decision that matters. Well, there were so many reasons I was excited

[00:03:19] to get you on the podcast today. Yes, an Indian unicorn but also the fact that you've

[00:03:24] pioneered the distinctive approach in the analytics industry particularly with the

[00:03:28] art of problem solving. So to set the scene for our conversation today,

[00:03:32] could you just explain the essence of this framework and how it empowers organizations to

[00:03:37] ultimately enhance their decision making processes? See, anything in life starts off as art because

[00:03:46] is a means out of expression. And when it becomes explainable, it becomes science

[00:03:54] and when it becomes to make it scalable, you have to make it engineering. So things

[00:03:58] evolve that way, art to science and science to engineering. We learned through our interactions

[00:04:06] with many of the large Fortune 500 companies is we saw certain patterns. One was these

[00:04:14] organizations were going from a bigger is better world to a faster is better world.

[00:04:21] They are going from a world of economies of competing on economies of scale to competing

[00:04:26] on economies of speed. They are going from building products and services to building

[00:04:32] experiences. So all these things meant for them to see the real look at the way they were viewing

[00:04:43] problem solving. The big insight we had was that problem solving in the past was

[00:04:54] governed by the foundational principle was very engineering oriented, very linear thinking

[00:05:05] oriented in a world which was far more certain than today. The problem solving in the future

[00:05:15] which is now I would say in a world filled with uncertainty is extremely nonlinear and you have

[00:05:25] to think of problem solving as interactions a lot more. Your world if you are a large Fortune

[00:05:32] 500 company is not one or two big problems but many, many small problems that are constantly

[00:05:37] interacting with each other. So the ability to see your work as network becomes extremely

[00:05:45] important all work is network and the ability to you know mine the interactions for example

[00:05:54] if you are hydrogen and I am oxygen the interaction between us could create water

[00:06:00] and that's wonderful if it creates water but it could also create hydrogen peroxide

[00:06:04] that's extremely poisonous. So the quality of interactions become more important than the individual

[00:06:11] entity in today's world and imagine a world where technology is making everything more and more

[00:06:19] and more connected, more and more and more complex so you'll have to figure out a way

[00:06:27] to see problem solving as interactions as quickly as possible so that's what we do.

[00:06:33] And also I think the pace of technological change at the moment means scaling decision-making

[00:06:38] capabilities is crucial for every organization in every sector especially when they're aiming to

[00:06:45] to stay agile in this fast-paced environment. So just to bring to life what we're talking

[00:06:49] about here how does the art of problem solving how does that facilitate that scalability and

[00:06:54] speed and decision-making within or maybe some of those organizations that you're working with?

[00:07:00] Sure see what we find is technology quotient of an organization

[00:07:12] can only become lower and lower and lower that's a natural law.

[00:07:18] What do I mean by technology quotient? The technology that you understand

[00:07:22] divided by the total technology in a world where your denominator is exponentially

[00:07:28] increasing relative to your numerator the ratio is only getting lower and lower and lower.

[00:07:35] So you have to prepare for a world which is going to

[00:07:45] where your ability to learn new technologies is what is going to help you do well.

[00:07:52] How quickly, how much of what's the not it's not what your knowledge quotient is

[00:07:56] but what your learning quotient is. So learning is going to become far more important than knowing

[00:08:04] and in such a world you cannot wait for for every technology you cannot wait for that expert

[00:08:10] in that technology inside your organization you have to try to experiment and become the expert

[00:08:16] or semi-expert as quickly as possible and keep moving you know I call it you know dynamic

[00:08:23] stable structures what do I mean by that if you're a if you're cycling you are more stable

[00:08:30] when you're dynamic the if your cycle is still it's hard to balance it you know so that's the

[00:08:37] perspective that I would keep and in such a world interaction property is going to become far

[00:08:42] far more important than anything else. So you know what I see in large organizations

[00:08:50] is that on one hand their business complexity is increasing on the other hand

[00:08:58] their ability to learn new technologies is decreasing and the up first case the

[00:09:07] up first case of everything inside the organization the speckled classification

[00:09:11] of the organization happens because of unaddressed complexity.

[00:09:15] So if you're an organization you are supposed to operationalize and make ideas real that's your

[00:09:25] business that's what you're supposed to do. Yeah how do you what does that mean well that means

[00:09:31] there's a journey of a concept it goes from an idea in somebody's head as content to

[00:09:38] conversations between people to go it going into the compute environment and from there

[00:09:46] it being consumed by business and then it commercialized. So that's the journey now the first thing

[00:09:52] that happens because of unaddressed complexity is that there's a lack of transparency of all of

[00:09:57] the content. The second thing is that there's a lack of persistence in conversations you have

[00:10:04] the first conversation then in the second conversation one of the important people are missing.

[00:10:10] Third conversation the right data is not there so something or the other makes them

[00:10:19] you know and delay the process and because of all of this the cumulativeness of the work

[00:10:28] is missing and they land up doing anecdotal project to project work and not programmatic

[00:10:35] in their approach to work. In effect what the how they feel is if you pardon my French

[00:10:40] their get shit done go shit this low right this is what we are trying to address. How do you have

[00:10:46] a better get shit done go shit and you know and how do you see the world of problems

[00:10:55] as connected and how do you maintain the persistence of the work and the cumulativeness of that work

[00:11:05] and for that to happen you need better structure and that structure or design I like the word design

[00:11:13] better than structure that design you know you have to bring the machine and the machine has two

[00:11:20] parts it has a design and an information flow you know the design must you know enable you to

[00:11:30] A do things do more things with less people B do more things faster C do more things in a sustainable

[00:11:41] manner and D do things that you have not been asked. In other words you have to be a little

[00:11:50] innovative you cannot be waiting for the solution consumers or the business to tell you what they

[00:11:56] want you have to be ahead of the curve and that's when you're innovative right. So these four things

[00:12:01] your design has to deliver you know for for the organization and for that you need

[00:12:10] you need two things you need a quick way to build what I would call signal engines

[00:12:16] where you take all of this data remove the noise come up with signals and give answers now it can be

[00:12:23] as simple as a dashboard or a report or it can be asked you know sophisticated as a

[00:12:28] predictive model and an AI engine but whatever it is it is about a signal engine that's one

[00:12:34] part of it the second part of it is how do you ask good questions good prompts you know

[00:12:40] and that's the inquiry engine so what we do in our a OPS out of problem solving system

[00:12:49] is build a combination of build a structure that creates a kitchen which has good signal engines

[00:12:57] and inquiry engines build that machine inside everybody is interested about making new kinds

[00:13:04] of food what we believe is that they need to build a new kind of kitchen before they can make

[00:13:09] new kind of food so we're trying to build that kitchen for them so which can be sustainable for

[00:13:14] them in making all these new kinds of food that they want I love how you're able to just cut through

[00:13:20] the BS there as you said it's all about getting shit done sometimes and another thing that attracted

[00:13:25] me to you or wanted to get you on here is you also place a very strong emphasis on analyzing

[00:13:30] the problem space by considering both the internal and external data sources and I love that it

[00:13:36] seems a great move away from binary thinking so can you just discuss the importance of taking that

[00:13:42] holistic view and also again when it comes to getting stuff done how it aids organizations in crafting

[00:13:49] more effective solutions because that's the destination they need to get to right yeah I think

[00:13:54] the reality of the world that we live in today is that no one organization has the monopoly

[00:14:02] and so to make a good decision you need to get to the highest version of the truth that you can

[00:14:12] in the lowest possible amount of time right now it and that's an optimization at some point

[00:14:19] between the big P of truth and the small d of time now when you see that way

[00:14:25] uh what we are gonna what we want to see is that these large you know organizations they have to

[00:14:36] look at sources of truth being of three kinds data that they have inside the organization data

[00:14:43] that they could get from outside the organization and last but not the least data that they can

[00:14:47] create data that doesn't even exist today so your ability to come up with you know

[00:14:54] the truth from all these three types of data is going to become very very important but for that

[00:14:59] you need a machine that is ready for taking all of that you know if your machine is not ready for

[00:15:05] taking all of that if your kitchen is not built for that then you can't make you can't

[00:15:10] you can't have the results that you want and the tech industry often witnesses that development

[00:15:16] of solutions and before but they do that before a thorough understanding of the underlying

[00:15:21] problems and we've seen a lot of that with the obsession with AI at the moment with so many

[00:15:27] just wanting to be part of the AI narrative without understanding what problem they want to solve so

[00:15:32] in your experience what are the pitfalls of that approach and how do you move

[00:15:36] signal with your methodology how do you address these issues by by getting back to focusing

[00:15:41] on the problem I don't think there's a deep state in technology which is creating a

[00:15:46] conspiracy or anything like that but yeah but I but I signed it funny that every three years

[00:15:55] we have a new word for the word technology yeah so initially we called it you know software as

[00:16:05] servers then we called it analytics and advanced analytics and then big data and machine learning

[00:16:11] and now AI yeah right so we seem to there's always a you know a new actor in town who's

[00:16:19] who's the most important thing so you we find that quite you know we had we've been through many

[00:16:24] of those things right now so I'm I mean I'm not I'm not undermining you know the advancements

[00:16:33] in technology here but what I find is that the I think what we have is a lot of technology in

[00:16:43] search of use cases there is there is scarcity in use cases and abundance of technology so

[00:16:53] so you have a lot of hammers who are looking at everything and saying that's a male that's a

[00:16:58] male that's what I say and and business is not sure about what they want to do but they're very

[00:17:09] sure that they have to have the word AI in it so that's a very dangerous situation to be in if I

[00:17:16] were a CIO or a CTO you know I would I would I would make sure that there is a systematic

[00:17:26] process to emphasize on the use case because he or she is hearing a lot from these technology

[00:17:37] companies operate with amazing marketing budgets and amazing P ratios where they can invest so much

[00:17:48] into filling your ears with buzzwords yeah so your ability to create you know a noise

[00:17:58] canceling filter which has an orientation towards use cases is going to become very very important

[00:18:08] so I feel you know that's something I think the really smart CIOs and CTOs will figure out

[00:18:15] a way to cut through the noise and and and put more of an emphasis on use cases and realize that

[00:18:25] impact happens at the use case which means the business problem interacts with the technology

[00:18:34] solution and it's at the point of interaction the music is made at the point of that interaction

[00:18:41] the clap happens you know at the point of interaction and if that if those two hands don't

[00:18:48] meet well you don't have that clap it's an emergent feature so that's going to be the differentiating

[00:18:55] factor of for success of the CIOs of the future and the CTOs of the future who are going to be

[00:19:01] prepared for a world of algorithms now you're talking my language I absolutely love that

[00:19:06] and that's one of the reasons another reason I was excited to get you on here is because

[00:19:10] you've been instrumental in building real AI solutions across various sectors that solve real

[00:19:16] problems so can you share a few standout examples where your team has been able to leverage AI

[00:19:22] to solve some of them complex business challenges because we've all heard the word AI everywhere

[00:19:28] we look but a lot of businesses are like yeah but what we're solving here what we're making

[00:19:32] better so do you have any examples you could share just to bring this to light many examples

[00:19:37] and you know we're working with large pharma companies on their you know r&d ecosystem

[00:19:46] on their drug development ecosystem we're working with cpg and retail companies on revenue management

[00:19:52] until you know in their sales and marketing area yes all of these one common theme among all

[00:20:00] of these problem spaces across pharma cpg technology media and telecom industrial you know

[00:20:10] oil and gas companies all of these things is the fact that these are complex environments

[00:20:17] where many many things are happening inside the organization and no one part of the organization

[00:20:24] is seeing the whole picture so the so so so that's that's the common theme among all of these companies

[00:20:34] you know and what we what what we do I mean I can give you multiple examples you know but I have to be

[00:20:41] you know I cannot name those customers but yeah having said that I could look for large oil and

[00:20:47] gas company wants to improve its ability to to it's improve its effectiveness in how they are

[00:20:57] how their wells work now that's a very complex problem and that has to be thought of as an entire

[00:21:04] program in anti-health them with that a large financial services company is looking to put

[00:21:15] an anomaly detection platform to understand how quickly they can respond

[00:21:21] to back things that can happen in their request you know a retailer wants to be able to real time

[00:21:32] look at videos inside a store and make decisions around you know story out and see

[00:21:43] how they can learn from video data of how people are behaving inside the stores rather than you know

[00:21:51] you know most just transaction data that comes in you know as sales and marketing and all of sales

[00:21:58] and so on and so forth so I think the the the ability to make all of these decisions

[00:22:07] needs a level of sophistication that needs to be built and technology is going from building

[00:22:16] execution systems to exploration systems execution systems were about making things happen okay I have

[00:22:24] a process in place I want to make things happen exploration systems are hey I have a

[00:22:29] process in place but is there a different process that could help you know help me do things better

[00:22:35] so I'm asking very different set of questions and I'm far more inquisitive in exploration systems

[00:22:42] related to execution systems for example SAP enables CENERP software that enables execution

[00:22:49] well large extent inside an organization but the kind of things we do in large fortune-finered

[00:22:55] companies is hey you know being their business research lab in thinking about hey what are the

[00:23:04] various possibilities where they could take their business and how should they be asking questions

[00:23:10] and to some extent one measure of what we do for large companies is improving their curiosity

[00:23:17] question in other words can we reduce cost per question in the organization can they ask more

[00:23:23] questions at lesser cost and cost meaning not just the money but also the time you know can

[00:23:29] they do it faster so that perspective is how we think about it and we are pretty much helping you

[00:23:35] know uh business and technology improve their interactions that they can have with each other

[00:23:41] to make all of this happen as you said a few moments ago we've all been on somewhat of a journey

[00:23:46] seemed like every few years as a different share of flint town the next big thing remember the

[00:23:51] metaverse a few years ago if you remember that which seems to have fallen out of favor now

[00:23:56] given your background in management consulting and the establishment of move sigma as a category

[00:24:02] defaulting firm you've seen a lot of things you've seen a lot of changes but what key lessons have

[00:24:07] you learned about driving innovation driving value through data analytics has that much change

[00:24:13] when you are doing those things or do you still keep to those core principles what have you learned

[00:24:18] the core values with which we operate uh you know we've been able to uh

[00:24:26] that they have remained constant for us and which is learning is more than knowing experimentation

[00:24:32] is more important than experts don't keep any secrets interaction properties are more important

[00:24:37] than intellectual property share share share be generous right because the economic rent associated

[00:24:46] with any idea the time you have to make to have to to make money out of the idea is becoming smaller

[00:24:53] and smaller and smaller there's no way you can keep secrets in a super connected hyper connected

[00:24:58] world so it's better to accept that reality and and and constantly be making uh making things happen

[00:25:07] for for for uh all stakeholders and so on so that's the core philosophy that's not changed

[00:25:13] but having said that because learning is more important than knowing that on a day-to-day basis

[00:25:21] you know the tools that you would be use are changing faster and faster and faster the uh

[00:25:28] you know the the methods that we are doing things are also changing faster the number of

[00:25:33] new things that are new actors who are coming in initially it used to be about just technology

[00:25:39] and business then math came in then behavioral uh finance and behavioral economics came in and

[00:25:46] then design thinking came in so now you have uh concepts from other industries coming in so the

[00:25:53] the number of players number of who come in into the game is increasing uh which means that you

[00:26:01] have to accommodate newer ways of thinking uh and be a little bit more flexible than before

[00:26:08] and and most organizations you know get stuck in their ways uh very very quickly and the the

[00:26:17] the ability to get unstuck is is hard and especially if you're bigger it's the problem is exacerbated

[00:26:24] even more I'm glad you mentioned there uh some of the companies getting stuck in their ways

[00:26:29] because when i was doing a little research on movesink you know one of one of the things

[00:26:33] that really really stood out for me is how you're renowned for having a vibrant youthful

[00:26:38] workforce with a significant portion of your employees being trained through the movesigma

[00:26:43] university so can you tell me more about this and how this unique educational approach ultimately

[00:26:49] contributes to your company's success and innovation capacity it feels incredibly refreshing

[00:26:56] sure sure see um you know be made to you that uh you know the wisdom of an age has to be

[00:27:05] complimented complimented uh with a lot of energy that young people bring to the table

[00:27:12] um you know that's that's that's how we we make something good happen um but we also understood

[00:27:19] the fact that the kind of talent we need in this new world you know the the preparatory

[00:27:26] environments in the world the colleges are not making those kind of peak um we realized

[00:27:34] therefore then building talent was going to be important for the category not just the company

[00:27:40] but for the category so um so we kind of had to take that as natural responsibility as the

[00:27:47] category building company to build talent um and uh so the first thing that we did was

[00:27:55] we kind of saw this as an opportunity to lead the way and uh we basically had a

[00:28:05] solid recruiting program in place where we checked for both left brain and right brain

[00:28:12] thinking so we would have an aptitude test and then we would put them through a group discussion

[00:28:18] where they are uh encouraged to take opposite points of views and dialogue and debate and all

[00:28:24] of those things we then get them to do a video synthesis test which is they look at a video

[00:28:30] of seven to ten minutes and they have to write down uh the synthesis of it in a small piece

[00:28:37] of paper which is a little bit bigger than your business card and last but not the least

[00:28:41] a fit interview which checks mostly for growth mindset and curiosity once we recruit these kind of people

[00:28:50] uh we put them through a training ecosystem which starts with the basics of structured thinking

[00:28:57] and design thinking and storyboarding and communication with clarity uh through uh the

[00:29:04] core of hard skills be it programming applied math uh statistics econometrics operations research

[00:29:12] you know uh ai all of those kind of things and the last thing we do is how do you land the plane

[00:29:20] you know on uh on the ship because it's it's it's not like you're landing the plane on an

[00:29:28] infinite you know runway you have a ship and you have to be able to land the plane on a

[00:29:32] business use case so the ability to be practical uh and not get carried away by just the passion

[00:29:41] for technology is going to be important so that that means the purpose you know has to interact

[00:29:47] with the passion the passion of the practitioner has to interact with the purpose of a person who

[00:29:55] wants outcomes and business thinking so those two things have to you have to have an harmony

[00:30:02] operator between the passion and purpose and getting that put in place you know as a culture

[00:30:09] means that you have to build systems in place that uh allow the input to output journey to interact

[00:30:16] well with the output to outcome journey so this this ability to have good harmony between these

[00:30:23] two journeys is going to become very very important and so we build systems in place

[00:30:27] the machine that we build was an interaction between people rossesies and platforms so we

[00:30:33] built a lot of software for our people think of it as an iron man suit you know so we didn't say oh

[00:30:40] I need this special person we said yeah yeah we need good people but we'll also give you an iron

[00:30:45] man suit and so you you you know and if you just have the iron man suit it's just a piece of

[00:30:52] metal and if you just have a you know a good-licking guy with a french beard he's just Tony Stark he's

[00:30:58] not an iron man yet so you want the interaction to actually happen so that's what we did and that

[00:31:04] enabled us um to pretty much put about 15 000 people through this um uh learning process

[00:31:14] another insight we had was that people do their best work when they are in their learning curve

[00:31:20] they feel sense of adrenaline at a very very different level they have a lot of gratitude for

[00:31:26] the problem space when they are learning um you know uh what happens post learning is that they

[00:31:32] become full of themselves and they don't have as much of a gratitude for the problem space and

[00:31:36] that comes in the way of doing doing things uh you know as good as you can and you will see this

[00:31:44] in many of the artists the best work they would have done the best songs they would have

[00:31:49] written would have been in their initial years um and there's a reason for that I think I believe

[00:31:54] it comes from the growth mindset perspective and having gratitude for the opportunity at hand so

[00:32:01] we kind of put all of these things together and built a business model uh with you know training

[00:32:10] and as a core part of it many of our customers now encourage us to build decision decision

[00:32:17] scientists in their environments and we've become uh you know we've taken our learning ecosystems into

[00:32:24] their uh into their into their world also and we are finding that to be a you know a big differentiator

[00:32:33] I'll give you one data point there are about 15 000 people who have gone through this program

[00:32:38] um and you know there are 10 consumer internet unicorns in India and the head of analytics

[00:32:44] and decision sciences and AI for all of them you know is is an ex view segment uh so the so you

[00:32:51] will find that um the the the alumni ecosystem of view sigma is very very strong uh and and that

[00:33:01] that makes a big difference for us he really does it's absolutely inspirational to hear and then

[00:33:07] your passion for this too also comes across and obviously as we look towards the future it gets

[00:33:13] harder and harder to predict what the future will look like because it seems to be moving a

[00:33:19] break next speed right now the pace of technological change but i'm curious from your vantage point

[00:33:24] here how do you see the landscape of business intelligence and decision sciences how do you

[00:33:30] see them evolving and what role do you see you guys playing shaping that future and are there any

[00:33:35] emerging trends or technologies that you're particularly excited about maybe it's the next

[00:33:40] hour if it's going to be coming into town in the future but is there anything that excites you at the

[00:33:44] moment i i've taken a very philosophical perspective towards this yeah and you know my philosophy

[00:33:51] is that jack knows jack shit i think the the world of unknown uh you know the world of unknown

[00:33:58] is only going to get increased that's a law of physics yeah you know and it's um and having

[00:34:06] a realistic perspective towards that will we're encouraged need to not be so

[00:34:12] say that this is the landscape that's going to be there uh i had ability to my intention

[00:34:20] is not to predict and uh be surrender to the fact that the world is going to be unpredictable

[00:34:30] uh and i surrender to that kind of i'm at peace with the systems that you can put in place

[00:34:38] to to the to the perspective that there's going to be a multiplicity of technologies

[00:34:43] there's a multiplicity of business models a multi multiplicity of algorithms uh you know

[00:34:52] and in that world you have to quickly figure out ways to uh curate uh you know things very quickly

[00:35:04] and combine things very quickly to achieve business outcomes for business stakeholders

[00:35:13] and that's a very practical perspective and probably more i see more authentic

[00:35:19] than uh saying that uh ai is the next best thing and i'm going to do everything about it's going

[00:35:25] to be about ai and uh you know i feel it's uh that's uh you know so many of our many of the

[00:35:32] companies have started calling themselves ai companies you know they change their last

[00:35:36] names every time that's yeah i very bad to change your last name every time somebody becomes

[00:35:43] popular you know it's you should be very proud of who you are and and you know i'm a little bit of a

[00:35:52] you know perspective towards the fact that all of these are just tunes they are they'll come

[00:35:58] and they will go um um you know and they should go uh because uh i i think i'd rather be

[00:36:07] uh a good carpenter rather than get excited about the latest hammer um so that's how i would see this

[00:36:15] uh but uh you know but having said that you cannot ignore you know these technologies you

[00:36:21] have to you have to engage with them you have to play with them but not get uh you know obsessed

[00:36:27] about the tool um but i would rather get obsessed about the interaction of the tool with the business

[00:36:35] you're skills so um you know it's just a it's just the point of obsession is it is focused

[00:36:42] on a different place uh so that that's how i would put it yeah i would completely agree with you as

[00:36:49] well i think it was six seven years ago that so many businesses were changing their that last

[00:36:54] part of their name to a blockchain company and this share price was going through the roof and

[00:36:59] they're probably the same companies and ai companies and a lot of cases so i kind

[00:37:04] of don't thank you enough for coming on and sharing your insights but before i let you go

[00:37:08] i want you to leave one final gift to everyone listening and that is either a song that we can

[00:37:13] add to our Spotify playlist or a book that you would recommend that we can add to our amazon

[00:37:18] wish list but what would you like to leave everyone listening with uh you know the book

[00:37:22] i would suggest is anti-fragile by nascin talib uh it's uh it gives you a fun nice

[00:37:29] fundamental framework for thriving in a world of change uh and you know appreciating the fact that

[00:37:43] you know it's uh you know you you what does it mean to deal with the stress factors associated

[00:37:55] with the change and not just look for resilience but look to look to do more than resilience so you

[00:38:04] have to be you have to try uh rather than just you know the goal cannot be to not not break

[00:38:11] because of change but all has to become the goal has to be to be better because of change and that's

[00:38:16] what anti-fragile actually talks about it's a great book and i think the fundamental principles

[00:38:21] from that actually apply very very well to a world of changing technologies uh and uh you know

[00:38:31] thriving despite the inner world in a world of changing technologies

[00:38:37] lovely i'll get that added straight to our amazon wish list for people to check out and for

[00:38:42] anyone listening wanting to find out more information about music but we've covered so much in a

[00:38:47] short amount of time but anyone that wants to find out more contact you or your team find out more

[00:38:51] about that university and the great work you're doing there where would you like to point everyone

[00:38:55] listening i think uh you know it's www.mue-sigma.com awesome i'll get that link added to the show

[00:39:07] notes so people can find that and even contact your team nicely easily too and as i said we

[00:39:13] covered so much there from analyzing the problem space the problems with building technology before

[00:39:18] you fully understand the problem that the tech aims to solve we could talk about this stuff for hours

[00:39:23] but just a big thank you for taking the time out of your day to sit down and share your story

[00:39:28] and your insights thank you so much thanks neat for having me i think in my conversation with

[00:39:34] diraj today we've entered into the heart of problem solving exploring how mue-sigma's unique

[00:39:39] perspective on interactions rather than isolated entities is actually paving the way for breakthroughs

[00:39:46] and decision sciences from the importance of adapting to new technologies without getting lost in

[00:39:52] trends to fostering a culture of learning and curiosity diraj was able to share his insights

[00:40:00] that challenged the conventional wisdom of the business world and as we reflect on the role

[00:40:04] of ai in solving real world challenges and the future of decision making for me it becomes clear

[00:40:10] that the path forward is both complex and exhilarating and i could have chatted to him for

[00:40:16] another hour we were talking about so many different things outside of technology and

[00:40:21] business from politics to global politics and beyond and from this moment on i'm going to

[00:40:27] call him my spirit animal i'm convinced that we are all connected no matter where

[00:40:32] you're listening in the world there is a spiritual side of me that just believes that we're all

[00:40:36] connected so a big thank you to diraj for being a real breath of fresh air today but over to you

[00:40:44] what are your thoughts on integrating these approaches into your own problem solving practices

[00:40:49] how can we apply the lessons from mue-sigma to navigate the complexities of our own

[00:40:55] increasingly interconnected business life and world this is where i ask you to share

[00:41:01] your thoughts with me let's continue this conversation on leveraging technology

[00:41:05] to make better decisions in both business and life so email me now tech blog writer outlook.com

[00:41:12] twitter linkedin instagram just at neil cqs i'd love to hear your thoughts on everything we

[00:41:17] discussed today but that is it for today's episode i'll be back again tomorrow with

[00:41:22] another conversation on a different topic hopefully you'll join me again then but until next time

[00:41:28] don't be a stranger