in

Using AI to Improve Supply Chains with Cyrus Hadavi from Adexa

Cyrus Hadavi, the CEO of  Adexa, calls supply chains the bloodstream of every business. “It’s how to get the right product at the right time at the right place.” But this is exceedingly complicated when you have thousands of products and possibly hundreds of storage facilities.

The COVID-19 pandemic has brought these issues to the forefront of public consciousness—but they’ve always been there. And Adexa has been helping companies solve supply chain problems since the very beginning of the digital era.

Today they employ a sophisticated, AI-powered solution that didn’t exist at the time of their founding. On this edition of UpTech Report, Cyrus tells us how it all works.

More infromation: https://www.adexa.com/


Dr. Cyrus Hadavi is the founder of Adexa, a leading AI-powered supply chain planning solution provider with hundreds Fortune class clients in five continents. Adexa solutions are based on a unique architecture that enables both S&OP and S&OE in ONE system to digitalize operations.

To this end, Adexa clients can grow to higher stages of supply chain maturity by simply adding more granular data to create a true digital twin. Adexa Genies© are smart agents to automate business processes by continuously responding to events and learning from experience correcting the model and improving the supply chain operations autonomously.

Cyrus’ experience has been instrumental in many global companies, including Black & Decker, Solectron, Northrop-Grumman, Philips, Toshiba, GM, Boeing, Hanes and Seagate. Cyrus is one of the pioneers of applying AI to planning problems. As early as 1990, he created the first-generation of AI planning solutions at Siemens.The result was a seminal paper published in one of the most prestigious publications: The Journal of Artificial Intelligence.

Before founding Adexa, Cyrus was conducting related research at Siemens Research Labs in NJ and Munich. He also taught courses atColumbia University as an Adjunct Professor of Operations Management on the application of computer science and AI to manufacturing. He has performed joint research at Columbia University, the Wharton School of Management, Clemson University, and the Max Planck Institute in Germany. 

DISCLAIMER: Below is an AI generated transcript. There could be a few typos but it should be at least 90% accurate. Watch video or listen to the podcast for the full experience!

Cyrus Hadavi 0:00
You know, we have been working on a distributed environment where you use intelligent sensors, monitor all these behaviors all around the world, whether it’s you know, your supplier in an earthquake region, or whether your supplier next door says, I’m sorry, I’m going to be two days late. Do I need to respond to that? Do I need to change the plan. So that makes the system very flexible, very responsive.

Alexander Ferguson 0:30
Welcome to UpTech Report. This is our applied tech series UpTech Report is sponsored by TeraLeap. Learn how to leverage the power of video at teraleap.io. Today, I’m joined by my guest, Cyrus Hadavi, who’s based in LA California. He’s the CEO at Adexa. Welcome, Cyrus Good to have you on.

Cyrus Hadavi 0:48
Hi, thank you so much. It’s wonderful to be here.

Alexander Ferguson 0:51
Now, Adexa is an intelligent supply chain planning software. So you really focused on helping enterprise manufacturing and suppliers out there, when it comes to planning their their supply chain? Did I get that correct? Yes. So help me understand that you didn’t start? You started, actually, what year did you begin? Oh,

Unknown Speaker 1:12
back in 1994. Adexa was founded. Wow. Am I beginning to date myself?

Alexander Ferguson 1:20
I hope you understand, obviously, that probably the challenges have changed over the years of who you’re serving. Or maybe they haven’t. I’m curious, what is the problem you see right now?

Cyrus Hadavi 1:31
Well, you know, most people, they take supply chain for granted until we had COVID-19. And everybody says, oh my god supply chain. Oh, now I understand. So, you know, supply chain, I always say show me a great company, I’ll show you a great supply chain. It’s just the bloodstream of every business, how to get the right product at the right time at the right place. And that is extremely complicated when you have 1000s, if not 10s of 1000s of different products on how much inventory you keep, where do you keep it? How much do you make? How much you don’t make? Where do you make it? Where do you store it, you know, when you go to the to the grocery store, you don’t just assume everything is granted, you just pick up what you want, until you run out of toilet papers. And with COVID-19 you realize how hard it is. And by the way, toilet papers are produced actually in this country is not even dependent on foreign made products. So that kind of gives you a feel for how critical supply chain is for every business.

Alexander Ferguson 2:45
And take me on this journey. then going back to 1994. When you when you began at AXA like what what did it start the the initial challenge that you saw, you’re like, I’m gonna solve this, did you immediately see the issues with supply chain and you want to just jump in?

Unknown Speaker 2:59
Well, I go even before that, which is gonna tell you how old I am. You know what I did my PhD thesis in, in artificial intelligence as far as the 80s. And what people think AI is a new thing. So and then I also did some industrial management courses and degrees while I was studying in England. So I started my career at Siemens research labs, where I worked on problems of planning and scheduling. And then I realized that, you know, for decades, people have been applying operations research techniques, to planning problems. And, you know, it’s nice as a theory, but in most cases, it’s not it wasn’t working back then. So I said, How about taking a AI strategy and techniques, so this complex problem, and that’s why I started working, combining AI techniques, manufacturing, to supply chain issues and problems. And we were very successful with a number of divisions within Siemens. And then, you know, I was there for about 10 years, I left. And I started with a very small startup company in the same area. I was there for a couple of years, just for two years, I said, You know, I can do this better. So I left and I started up Adexa. I started as a consulting company, I worked with a number of great companies for a year or so designed the software. And then, you know, the rest is history. And you know, we were growing for the first three years, we were growing like 300%, the year after that 3,000% and so on and so forth. So, you know, it’s been a wonderful experience.

Alexander Ferguson 4:48
Doing your PhD on AI artificial intelligence, he said in the 80s. How has AI stayed the same and changed since then

Cyrus Hadavi 4:59
you No AI actually was invented back in the 50s. But the kind of requirements and processing that is needed for artificial intelligence, machine learning require the law of memory. And it required incredibly powerful computing power. Back then, within habit, we had the algorithms, we had the search algorithms, you know, we had the pattern recognition, algorithms, and so on. But the speed of computing wasn’t there. And now with only big data, and the reason why Big Data is important is because there’s so much data coming at you. And the question is, hey, what is the relevance of, you know, weather in Africa to my production in Europe. That’s why you get so much data coming at you. And there’s so much every consumer behavior, every product, design, all of these are interrelated. So you want to keep them in a big place, and then look at them and process them as they are. So you know, when this happens, this is going to happen. So you can predict the future by learning the patterns that are going on in the universe.

Alexander Ferguson 6:14
When you were working at Siemens, and a bit later, were you actually like, writing in developing the actual algorithms themselves, like trying to decide are we use this year and this year?

Cyrus Hadavi 6:23
Oh, absolutely, absolutely. We had to develop algorithms, you have patterns on for the first time in supply chain planning algorithms. There, it’s a very interesting, dynamic complex, and it’s getting more and more complex. Look at the number of disruptions we have been facing recently, you know, from COVID-19 is kind of an exception, but not really, because companies are losing hundreds of millions of dollars. And I you know, I have backup with this statement every year because of disruptions. I give you a couple of examples. Texas freeze, tornadoes, and East Coast stores blockage because of this duck, who I mean, it happens all the time. Now, these are the ones that we hear about. But disruptions also happened when all of a sudden, people say, wow, I like red shirts, more than green shirts, and all of a sudden demand goes up or red shirts. What do you do? You know, all of a sudden toilet papers are scared. What do you do? How do you respond to it? So the companies are relying now on systems, so called digitalization, in order to see if something happens, what are my choices? How do I respond? But even more importantly, they use the system to predict what can happen, because you know, what, my supplier in the month of December is always two weeks late. That’s an underlying current US supply chain, that machine learning can tell you so you can account for it. So that level of disruption, complexity, consumer demands, I wanted the same day, Mr. Amazon, you know, if you are out as a when you keep Where do you keep it? How many of these items do you keep? And these have to do with prediction, and understanding consumer behavior and making sure that you have the right back in the right place at the right time.

Alexander Ferguson 8:28
If you could go back to yourself, you know, 20 years ago, and share something that you know, now being the leader of the 27 years, but taking the knowledge you have now Is there anything you would go back and say to yourself, I’m

Cyrus Hadavi 8:43
as this scientist as well, as a business owner, and so on, you all respond to the demands of the market, the demands of the market back then was very different to the demands of the market. Now, what happened was that, you know, in the 40s, and 50s, or people concentrated on worker efficiency, machine efficiency, and then, you know, people came along and said, it’s not equipment efficiency, it’s factory efficiency. And then they said, Yeah, that makes sense. Because when equipment is isolated, what matters is the throughput. And then people can use it and not really know is the whole enterprise efficiency, you know, how do we work? And and, and then later on in the supply chain comes along, there’s no, it’s the end to end supply chain. That’s what the efficiency is. So that’s how we’ve been responding to the market, understanding the needs and the way we view the problem and address

Alexander Ferguson 9:45
issues, emphasizing so that the very fundamentals of what you’re tracking or the other KPIs is changed over the years.

Cyrus Hadavi 9:54
And, you know, it makes sense to look at the end to end efficiency, you know, people talk About read, impact of green supply chains. And then you say, yeah, I’m going to go on buy a nice electric vehicle. But then if you look at the end to end cycle these batteries, how were they made? Where are they gonna end up? Because their life is kind of limited and short. And then overall impact on the planet and the climate? Everything else that goes with it, then the question is, am I really contributing to improving climate change, and so on? Maybe you are, maybe you’re not I don’t know. But that’s what matters to look at the end. When we look at, for example, companies are struggling with planning cycle times, it takes them two weeks, three weeks for production, when we come in and say, well, from end to end, you can do it within hours, why would you spend three or four weeks to do that, you know, you can respond and make changes to the plan. But now we go even further than that we’re doing continuous planning. Like as the events take place, we revise, read, repair, and improve the plan as they happen. So it’s kind of looking at the problem holistically, and trying to make sure that you’re really addressing the issues, the underlying currents and everything that goes with it.

Alexander Ferguson 11:37
I’m curious, as you mentioned just a little bit ago about being a scientist and a business leader, do you feel that you’ve built your company differently than maybe another type of founder or leader? And if so, how? How have you approached it from a scientist background and building this company?

Cyrus Hadavi 11:59
You know, that’s a great question. And, you know, we are all, so proud of technology that we have built. And you know, if anything, I would say, we’ve put so much more emphasis on the technology and engineering than we should have put in sales and marketing. And maybe the question you asked earlier, what would you have done differently? Maybe we should have put a lot of emphasis on sales and marketing, and what we didn’t, and and, you know, people that we have, you know, on average, for example, in r&d are team players are average of 1718 years with us, and they’re so passionate about what they have built what they have made. And it’s very interesting, because we have been moving in time, with what matters, you know, if you look at supply chain technology today, people are so focused on this big, centralized local sales and operation planning system fmlp. I mean, these systems are good, they’re great. People are using it, people are buying them today. But is it going to handle all the real time events that are coming at you, you know, weather changes, hurricanes, suppliers, late customers, for more this big concepts of, you know, software is not reactive, it’s not responsive enough to do that. So we you know, we have been working on a distributed environment, where you use intelligent sensors, monitor all these behaviors all around the world, whether it’s, you know, your supplier in an earthquake region, or whether your supplier next door says, I’m sorry, I’m going to be two days late. Do I need to respond to that? Do I need to change the plan? So that makes the system very flexible, very responsive.

Alexander Ferguson 13:58
was a business leader who’s who’s built and run a company for 20 coming out 30 years? What would you say is your biggest lesson learned? If you had to speak to another business leader, another founder, and share a word of wisdom, a tactic that worked? Well, they’ve gotten to where you are today, what comes to mind?

Cyrus Hadavi 14:22
Where every function in the company gets somebody who can do it better than you. You know, check the ego. Because, you know, if I’m looking for a developer, system architect, they have to know what you’re doing better than you better than anybody else. In fact, a salesperson, a marketing person, because if we don’t do that, we are shrinking. We need to kind of rolling and the way, growth is not just by the number of employees, it’s just by the quality of people that we get. And you know, it’s a cliche that you know, people You know, they asked me? Oh, of course they are. I mean, what would you do? It’s, it’s incredibly important to spend the time. And I learned this lesson back in year 2000, you remember not because, you know that there was this bubble that was growing, and we were growing like, so fast. And we were hiring people left, right and center. And, and you know, we had a hard time finding good people, right people, etc. But, and then we realize that, you know, this is going to stop with Canvas, go out and hire anybody we just need, I was really looking for quantity, you know, whilst he was telling us, hey, you know, how big are you? How many people do you have? How many salespeople do you have? And you know, that that’s something which really, every company even today, you know, he takes you take a lot of time to get very high quality individuals.

Alexander Ferguson 16:02
What do you look for in your own hires?

Cyrus Hadavi 16:06
Well, you know, most of the resumes that come to us, they already qualified. You know, they come from great universities, they’ve had the foot track record. All of that is right there. The question really is, what kind of emotional intelligence they have, what kind of mentality they have, in terms of teamwork, in terms of growth in terms of passion, because, you know, most people get fired up, because they don’t know if a job is because of the attitude. I mean, let’s face it, it’s just, they don’t get along with others, they don’t want to do what they are supposed to be doing. Whether they’re young to know it is just that kind of cultural fit is critical. People who have you know, high integrity, people who are team players, people who are honest with each other, it doesn’t mean that you don’t challenge the company challenged the system. No, quite the contrary, if everybody agrees we’re in the wrong place. No, absolutely. So we need to have honest people, people who care, and people who want to work with each other to grow the game. You know, as far as I’m concerned, everybody’s absolutely important. But more importantly, the company, which means all the individuals in the company are more important, because that, you know, if I hired great players here and a mediocre player here, if he’s not carrying or she’s okay, here note, you know, all these others are going to leave. So that’s basically, you know, focus on the quality of people that you have, and their cultural relevance to the company.

Alexander Ferguson 18:00
For you starting as a, if I understand correctly, more of a consulting company to start with, and then building out software, where today you are now, are you considered a software assassin? model?

Cyrus Hadavi 18:13
The way you approach it? Yes, well, software for a long time, was so called on premise. So we have a lot of customers who use our software on premise. Now, for many reasons, big companies, as well as small companies, they like Software as a Service, because it removes a lot of work internally within the company, or you put it all in on out somewhere. And then we take care of administration, we take care of everything for you, you just run it get results, and everybody’s happy. And Wall Street likes it because it’s you know, you don’t own the software. You have to pay every year every month to be able to use it. So is this recurring predictive revenue? Obviously, it’s very important. So yeah, we offer ourselves for now as as, as a service,

Alexander Ferguson 19:05
what that evolution from consulting into software, and now SAS, what would you say is the biggest lesson learned of that process?

Cyrus Hadavi 19:17
Well, you know, consulting helps, because you understand the nature of the problems and challenges that the companies are going through. So working with them, helping them and obviously, as a consultant, what I was doing, was helping them to, to understand, for me to understand the challenges and to help them to design business processes that, you know, they can use in order to be more efficient and better. Now, technology comes into it, because it increases the velocity of street. Same process. You know, you can add but you have a cap Later, you can add a lot faster. So business process, you can forecast with demand a lot faster, you can add your supplier that fast that you can send signals to your supplier a lot sooner. So, a system essentially improves your cash to cash cycle, it improves your commitment dates to your customer, it reduces the you know, Operation cost because you can identify the problems or keep the right level of inventory very quickly. So all of these are essentially business process as well as technology. And then of course, people put together that’s really the secret sauce.

Alexander Ferguson 20:45
I’m curious as a as a business leader is like, you’ve obviously seen the ups and downs that they come with, with with running the business, what would you say, was one of the most challenging times that you were able to make it through and and continue to grow from there, but that that challenge mode, maybe was a plateau? Or a difficult time? Can you can you think of one and share one?

Cyrus Hadavi 21:08
Ah, you know, given the history of our company, I can think of many but, you know, the challenging times are things that happened, for example, in 2008, what happened in 911, what happened in you know, the bubble burst in 2000. You know, those are the kinds of, and, and the problem is that, you know, you hire great people, you work with them. And things happen, which are out of your control. And, you know, if you don’t take the right action, the ship is gonna sink. So having to downsize the right size, is certain instances, which is the nature of every business, it’s probably was probably hard to sign for me.

Alexander Ferguson 21:59
How do you handle that? as a, as the one who’s having to make those decisions? How did it make you feel? How do you personally motivate yourself through it or keep going and having the right mindset,

Cyrus Hadavi 22:11
you know, the only thing I can keep telling me, if I don’t do this, everybody else is going to sink. So your choices are very clear. And in business, you need to have a clear mind. You know, you need to have a warm heart and a clear head. But it’s when when choices are that clear to you, you have no other choice, besides the board is out there to say, Hey, man, what are you doing about this? So what do you tell? You put the blame on them, right?

Alexander Ferguson 22:42
The board’s got Toby got to do I this this constant of ebb and flow or constant moving forward, what drives you like what keeps you excited, both about this space about the run the company and just moving forward.

Cyrus Hadavi 22:57
You know, what keeps you excited is when I see our customers, they way they use the software and the way they benefit from it. I really mean that because, you know, some of our customers, when when they went through COVID, they switch their supply chain one of them we change a major apparel manufacturer change from ozeri, to face masks, practically, you know, virtually overnight, another customer, they change the configuration of their supply chain, because of terrorists from China, who make sure that they are optimizing the, the past that their products, and they did that overnight. You know, when you see that, and when you realize that, you know, as you know, a relatively small company, you know, we’re not Procter and Gamble, you know, we are contributing to the economy. I mean, I can honestly say, we have saved companies, billions and billions of dollars, because of the amount of inventory you’re saving, because of gaining market share. And, you know, we work with companies, not just in the US, also in Japan, in Taiwan, you know, one of our customers provides 70% of semiconductor chips in the world. Any imagine I’m thinking about man, you’re actually using a technology, how critical the semiconductor is, especially today, when yet you’re using our software to commit to their customers and ensure that you’re producing it at the lowest possible cost. I mean, this to me if this doesn’t make you feel,

Alexander Ferguson 24:50
yeah, it’s like you’re you’re you can see your impact on the entire global economy. How does that make you feel?

Cyrus Hadavi 25:01
I hope you can see the excitement in that you’re doing. And, you know, it is important because it’s not just me, everybody else, people in our family, they’re sitting back there at home now, you know, they’re more productive than before, and, you know, typing away and producing this incredible technology. And when they see that, they feel that they have enabled these companies, they feel that they have been part of the, this global economy. You know, on top of that, it’s good that, you know, we are contributing to the economy, we are hiring people, you know, we are exporting our software to, you know, Europe, Middle East, South Africa, you know, and Asia and so on. So, you know, these are an, you know, as a, as a, as a young person, young student at the university, I never imagined that I could be able to contribute this way, and create this environment, not just for myself, but also for the whole team, and then contributing to the economy and being part of the global economy.

Alexander Ferguson 26:16
Having from being getting your PhD and artificial intelligence in the 80s, and then working in Siemens, and then being able to start run your own business focused on supply chain planning. What do you see is the future then looking ahead of where supply chain management and supply chain planning for for, for manufacturers, suppliers everywhere? What do you see?

Cyrus Hadavi 26:40
You know, there’s no question that the systems they are getting more intelligent, they got to get a lot more intelligent. And this has been going on for a long time, you know, I think, from what I remember, 40% of jobs lost is not because companies went and started manufacturing, or young, in Vietnam, or China or whatever it was, because of automation. Now, what we are doing, we’re bringing automation, to the kind of jobs that white collar workers are engaged. And this level of intelligence requires people who are doing this kind of job right now, they can train themselves to go even higher levels of function that they have for the company, for example, the planners, in companies, they do a very critical job in every company, we help them to make that decision. Over time, we can help them to augment their decisions and recommend decisions to them, etc, etc. So the level of the level of help that the system offers, the user is going to increase more and more and more the extent that now they can think more strategically, they become data engineers, they become people who can say, yeah, you know, in the long run, this is how we need to redesign the supply chain, in the long run, this is how we need to renegotiate with our suppliers. So that, you know, instead of allocating this job to the equipment, or calling the supplier says, Can you send it solar? Yeah, you know, this is good. I mean, it’s critical. But now the system can take care of that, you know, now we are we are creating intelligent robotic processes that interacts with your suppliers, and when they are late, or when they don’t respond, they serve, you know, what’s going on. And then if they respond and say, we’re going to be two days late, you know, remember that information. Now, another agent, say, hey, they’re going to be two days late pre plan, and, and that takes care of everything automatically. And then later on, after six months, they come and say to the management, hey, this particular supplier keeps delivering late, late late, you might as well change the delivery time from two weeks to three weeks. So then you create a much more accurate plans, and all you find another supplier. So, you know, these undercurrents in the supply chain, there’s so much that we don’t see, but the systems can detect that. And they can bring it to the surface. If somebody for example goes to L’Oreal’s website keeps looking at a particular brand of lipstick or whatever the case might be. That is an indication that there might be much higher demand for this product in the next three months. So monitoring the activities on the web. All of these requires, you know these machine learning and intelligence and this is what I meant by all this data, and all these events coming at you, and how you deal with it. And that’s really what what I see moving on to the future. The other thing is that companies now, you know, we have drones delivering same day, perhaps, I mean, it’s already here. So as a manufacturer, how do you respond to this digital marketplaces and say, I’ll give you a give you what you need? How do you do that? How do you respond to that? How do you plan for that? And, you know, a simple racing bicycle has 11,000 different configurations. Can you keep them in inventory? No. But you can respond to it, and build them very fast. So that level of responsiveness, automation, is next day delivery from FedEx, who would have thought of that same day delivery from Amazon, who would have thought of that, you know, one hour glass, you know, making or just the time is shrinking, and you need to increase the velocity of doing business. And that’s what the challenges of it needs to

Alexander Ferguson 31:12
be you see, in that last piece of just painting a picture, the shrinking of the quantity of supply needed, will the system be smart enough so that the actual manufacturing of set items will be more on demand? And less just build a whole bunch and then wait until we sell it?

Cyrus Hadavi 31:32
To some extent, yes. But you know, certain products like semiconductor chips, they take months to be built, and they’re getting more complex and the length of Bill. So yes, you can make things very, a lot more responsive factories, manufacturing, what you really need to be able to predict. You see, what is my demand going to be like, in such and such months of the year? Why is the case, figure out what the causes are? And what’s causing those demand pages? You can figure out in month of September, I’m getting hurricanes in East Coast of the United States in these areas. I have two suppliers there. What if they get hit by a hurricane? What are my choices? What are my options to have I designed my supply chain to be resilient. So systems that you know we’re creating helps the team to predict that and to be able to know about it

Alexander Ferguson 32:34
isn’t writing, the way it works right now? Would it be just prompting you and saying By the way, this weather thing is going to be coming up next year, you should probably consider something is that happening right now? Is

Cyrus Hadavi 32:46
that apps? Absolutely. It’s first, you know, this supplier in the month of June is going to be their lead time is longer. seven pieces of equipment. Now we have what we call probabilistic or stochastic planning, which means that the capacity of your equipment or your subcontractor is not always a constant, it changes depending on the season, delivery performance in Ohio in winter is different from, you know, Ohio in summer. All of this information is available, we learn from it. And then we build it into the plan, as well as making recommendations to the management and saying that performance of the supplier performance of subcontractor or equipment, etc.

Alexander Ferguson 33:32
You said a bit earlier also how the this is truly automating the knowledge worker in many ways now, or the the blue collar worker, those who are Manning this, but it’s not displacing them. Rather, it’s it’s lifting them up to that to play more of an advisor or strategic role. If you were to speak to someone in this type of role. What are you going to? What would you encourage them that they need to be focusing on?

Cyrus Hadavi 34:03
Oh, it’s like everything else, you need to constantly educate yourself, you know, things are changing. I’ve been educating myself as to you know, what is changing? What do I need to know? What do I need to know, you know, every day we have newer techniques, better algorithms, and so on and so forth. So, you know, are obviously, this is not my primary job, but I need to understand what is happening to manufacturing, what is happening to companies, what is happening to your current political economy, all of these is just matter of educating myself so that I can get better at what I’m doing. And, you know, not with our users with everyone, I think, unless we constantly go through this education process, at some point, obviously, I would become redundant. So it’s a matter of time.

Alexander Ferguson 34:56
This the better time of where you’re putting to educate yourself. Let me ask Get a more pragmatic or very just a tactical question. How are you educating yourself right now? Like, maybe in the past, we’d open the newspaper and look at it, or we would go to take a class at a school. But in today’s era, where are you personally, not a system, but personally as a human getting your sources of data into information and keeping yourself educated,

Cyrus Hadavi 35:20
there are plenty of publications such as reports from, let’s say, McKinsey and Company there, you know, reports in obligations like economist, Wall Street Journal, New York Times, you know, there are a lot of relevant and then you look at them, you read them, and then they reference other complications as you go through in order to get a better understanding as to what’s going on, it’s a matter of finding the right pump, you know, there are a lot of applications in the industry that we look at. And then on top of that, you look at what the market needs, what the customers are asking. And, you know, you put the whole thing, a lot of things, by the way that we are coming out with customers never asked us is really is like, what, what’s that about? You know, what do you say was about? I forget is about, get more horses, if you want to go faster, as opposed to get in your car. So nobody knew about cars. Part of our job is to bring in I mean, who knew about a cell phone, being able to do all of this, nobody asked for it. There’s a lot of innovation is the kind of distributed agents that they just talked about. Nobody asked for that. But we have created that in order to be able to respond, this huge amount of data coming in. So it’s, it’s more of a research, development, and understanding the future, educating ourselves, you know, bringing all of this and then you know, on top of that, creating that environment where people can innovate, can change, and have the freedom to do what they need to do in order to address some of these interesting, exciting times that are ahead of us.

Alexander Ferguson 37:13
I love it. I love it. Let me ask just the kind of a fun question I’d like to ask. And is there any favorite software or technology as a consumer, cheap, cheap software that or technology that you like and use in the past a little while.

Cyrus Hadavi 37:30
I think there are a lot of them around. But the best form of software, and technology, high tech type of software that you get is one that is intuitive. You don’t need user manuals, you take it, you start using it right away, you don’t know all the different complexities and our and capabilities of it, but you can use it right away. And it solves the problem for you or improves what you’re doing in performance. Apple is a good example. You know, it’s, I get the phone, I start using it. I hit a couple of buttons here and there. And then I know what’s going on that consistency in terms of painting the user as they use the software and leading them to the right place. You know, a bad example is when you do a search on on a search engine, you get 20,000 20 million responses. I don’t want that I don’t need that. You know, and then people, you know, start paying in order to get to that. That’s not a good example of software when you’re not getting the answer you’re looking for. Or you’re getting so many that the real answer gets lost.

Alexander Ferguson 38:53
When I say that the definition of a good software versus bad software, you paint the picture of particularly consumer world that gray software is so easy. It’s just you there’s no user manual needed. It just makes sense. And it works. Do you in the in the b2c world? Definitely. Do you see the same in the b2b environment?

Cyrus Hadavi 39:12
Oh, absolutely. Because now in b2b, it’s not so much about just optimizing the supply chain. It’s also collaboration and more recently about negotiation. So when I’m working myself on my hand, for example, as a planner, all of a sudden I may want to ask my manager question or ask a supplier question. I would like to see a little window on the corner of my you know, laptop or whatever, and dial him in and ask him Hey, can you deliver two days from now one day from now? And then you know, they respond or you ask a manager, which one of these products have higher priority because you know, we have a conflict in capacity, that level of collaboration and negotiation with sales because sales people says no, don’t do this. You’re going to lose the customer. So, optimization is one thing. Usability is another collaboration, negotiation. All of these need to be combined in that what we call the user experience, because that’s really what matters user experience. What what is it that experience when they sit behind their desk and use your application.

Alexander Ferguson 40:25
So your journey that you’ve been on personally and this business professionally, I can only imagine the the ups and the downs this way that way, but if anything, it’s always moving forward for this worldwide supply chain be able to help the economy. I appreciate your also your excitement when you can see your hand in development of the economy itself. Thank you so much for sharing your insights and the journey that you’ve been on. For those that want to learn more about Adexa you can go to Adexa.com that’s adexa.com. And thanks again, Cyrus for for joining us.

Cyrus Hadavi 41:00
It’s been a wonderful experience. Thank you so much.

Alexander Ferguson 41:04
We’ll see you all on the next episode of UpTech Report. Have you seen a company using AI and machine learning or other technology to transform the way we live, work and do business? Go to UpTech report.com. And let us know

SUBSCRIBE

YouTube | LinkedIn | TwitterPodcast

Managing Construction Data with Raffi Holzer from Avvir

Better Weather Data with Buck Lyons from WeatherFlow