ModuleQ | David Brunner

 

About David Brunner

In 2011 David Brunner founded ModuleQ, a SAS based company to prevent knowledge workers from being overloaded with information. Before founding ModuleQ, David received a PhD from Harvard University in Information, Technology & Management, a joint program integrating business and computer science. Upon Graduating from Harvard, he worked with the CIO of Shinsei Bank to study their highly innovative IT systems. When the CIO retired, his successor engaged David to consult on the design of the bank’s next generation of workflow systems. Before entering Harvard, David was an associate in the Tokyo and San Francisco offices of The Boston Consulting Group. He holds a BS in Computer Science from Stanford University, where he was a Terman Award recipient. David is also coauthor with Stanford Professor Emeritus Edward Feigenbaum of The Japanese Entrepreneur: Making the Desert Bloom, a book describing the challenges faced by entrepreneurs in Japan.

 

Interview Transcript of: ModuleQ | David Brunner

 

Alan
Welcome back. I’m here today with David Brunner. He is a CEO of a Silicon Valley startup called model Q. Welcome to today’s show.

David
Thank you. It’s a pleasure to be here.

Alan
So David, give me the background of what brought you to where you are today, maybe starting to some educational and then prior experience and, you know, kind of what the, what the direction of ModelQ is,

David
I was born and raised in Silicon Valley fell in love with computers at a young age. And I went to school in my backyard at Stanford, to study computer science and AI. And while I was there, my I connected with my mentor who, Edward Feigenbaum, a professor who was one of the founding fathers of the field of artificial intelligence and developed some of the early what were called expert systems that were used in both business but also government and intelligence settings, to solve problems that normally would require a human. And I was inspired by the potential for applying some of those tools in business settings to help knowledge workers be more effective. And so I after I graduated, much to the disappointment of my mentor, who wanted me to go get a PhD, I went went off to learn business at the Boston Consulting Group. And along the way, I had become fascinated with Japan. So I went to the Tokyo office of the Boston Consulting Group initially, and then San Francisco, and then succumb to the nudging from my mentor and went off to get a PhD. So I went to the Harvard Business School and Harvard University to a joint program of computer science, and business called Information Technology and Management, where I could put together my interests in on the one hand AI and computer science and on the other hand, business and management. And I did a PhD thesis that focused on how organizations change how businesses change, as you integrate computer software and AI more and more deeply into the fabric of the enterprise. So that was my focus. And after I graduated, I decided I wanted to commercialize that research, because there was a particular problem that I wanted to solve. And that was the problem of information overload. Because in in business, and just about every professional has experienced this, we’re bombarded by ever more information. And we spend more and more time, just dealing with the overhead of trying to keep track of what’s going on filter stuff, find the stuff we need, stay organized, stay on top of it, that stuff that intelligent systems should be able to help us with. And but we don’t have those systems, your email client doesn’t know anything about the people you’re corresponding with or why you’re corresponding with them, or what your priorities are. So I wanted to build systems that can really partner with us in doing our work and augment us and make us as professionals more effective. And so that’s what led me ultimately to found module Q to build those systems. And so module Q is an AI company developing AI that we call personal data fusion, to address the problems of high value knowledge workers.

Alan
The market, first of all, understands the need anybody who has an email box, it’s just overloaded with things they don’t need. But as you as you move out and scale this, right now, you’re relatively new. But But But how big do you feel? How big do you see the vision model Q becoming?

David
This is enormous. The total cost of information overload to the knowledge economy, there are varying estimates, but they’re all over a trillion dollars a year globally. So the problem is enormous if you can unlock a trillion dollars of value a year that has macro economic impact. So we are starting with a very narrow niche, because one of the things I learned from my mentor at Stanford is that to solve a lot of these problems, you need domain specific focus. So if our systems are going to partner with you to help you do your work, if you’re a lawyer, they need to understand how lawyers work. If you are a sales professional, our systems need to understand how sales professionals work, and so on. And so we’re building a general platform in the cloud to support personal data fusion. But on top of it, we’re building applications that are targeted very specifically to particular kinds of professionals. And the first of those is actually for enterprise sales professionals. But over time, we’ll add tools for other kinds of professionals to ultimately cover as much of knowledge work as we can. So this could be in the sales alone. The addressable market for us is $10 billion. Going beyond sales, it’s almost certainly in excess of 100 billion. It’s enormous.

Alan
Now, there’s an article that you recently wrote, and how the US will become an entrepreneurial desert. Can you tell me about that?

David
I was citing some some concerning trends that have been some data trends in the data that have been released recently. I actually haven’t commented on the latest update. The Kauffman Foundation pointed out but that there has been an uptake in the last year or so. So we’ll hope that things are turning around. But if you look over the span of the last few decades, there’s actually been a decline in the startup rate. And back in the late 90s, I was researching, actually, with Professor Feigenbaum, the low level of entrepreneurship in Japan, Japan is actually now experiencing a little bit of an uptick in entrepreneurship. But the trends that we’ve been seeing in the US data over the last decade are true to look like the trends that we were looking at in Japan that were concerning us. So I think there is there is cause for concern as to why it is that entrepreneurial activity in the US is, is depressed and has been falling over the last couple of decades. And there’s great research showing that that’s not just in the sort of across the economy, but it’s also in sort of the High Risk High Return startups that drive the economy forward. So cause for concern, a little bit encouraging recent uptick in the data. But I think we need to do more to promote entrepreneurship.

Alan
David, I need to take a quick break. I’m visiting here today with David Bruner. He says CEO and founder of module here, and we’ll be right back after these messages.

Alan
Welcome back and visit here today with David Brunner. He is the CEO and founder of module que and is focused on personal data fusion, artificial intelligence and really exciting to hear, you know that the founding of this come because I think ultimately it will change the way that we live in life. But I want to I want to circle back. From a business model, it sounds really good, conceptually, because I know, every one of us who are in technology, we’re feeling a lot of information overload. How does mono cue those set out to solve that issue for us to decreasing our information that we have to sift through every day.

David
We’re building artificial intelligence technology that we call personal data fusion, and almost everyone has actually already experienced personal data fusion, this is an emerging AI mega trend that all of the industry majors are already on Microsoft, Google, Apple, if you’ve ever looked at your phone, and it’s told you leave now for your meeting, because traffic is heavy. That’s personal data fusion, the system behind the scenes is collecting information from your GPS sensor on your location, from your calendar on where you might need to go next, information on traffic information on routes to your destination, it’s fusing all that together, and extracting from it a single high level insight to help keep you on track, which is oops, you’d better run out the door right now. So that’s personal data fusion as it’s currently emerging. But that’s just the beginning. Because there’s so much information coming at us, we need systems that can fuse it together, and turn it into a higher level more coherent, understandable, useful dashboard of what’s going on in our life. We’re focused on doing that for your professional life. So whereas Microsoft, Google Apple, they’re doing it horizontally to solve everyone’s problems. And that’s great. We’re doing something that complements that which is to focus in on particular kinds of work, and augment that with personal data fusion. And so our first target market is actually enterprise sales professionals, because they have an extremely demanding job with getting more demanding every day with enormous information overload. And if we can help them be a little bit more responsive, by giving them that kind of cues, helping them see the important deal related information right away so that it gets their immediate attention. And they can manage it effectively and orchestrate their team more effectively. We can help them sell more, we can increase the speed of their deals, and we can increase their win rates.

Alan
When you’re setting out to do this and build the database. I read today an article with about how Google is mind mapping every search that every individual does, how much time we spend on a website. When our interests are in there. There seems to be a lot of concern, at least when I read that, that there’s privacy issues there.

David
That’s exactly right. And this is a huge issue for the industry to deal with. And it’s something that we have a very clear philosophy about and I actually posted recently on me dem and an article that I co authored with one of our board members, Professor Ethan Bernstein of the Harvard Business School that we titled Big Brother versus personal data fusion, because there’s really two directions that this technology can go. One Direction is Big Brother, we observe everything. We feed it all into these massive AI systems. And we figure out what everybody is doing. And we observe them all the time, and we try to manipulate them. The problem there that has lots of problems, but the problem in a business setting, just focusing on what’s the return on investment, right, if we just put a hard heads our business analysis angle on it, is that it’s actually disruptive, because there’s very robust research that shows and actually Professor Bernstein did some of this research that shows that when you over observe professionals, they begin to focus their time on making sure that they look good to the people observing them. So they start wasting their energy, their productivity goes down. And not only that, they decide not to innovate or experiment, because they don’t want to be second guessed. So it turns out, it’s destructive for your organization to roll out those kinds of tools, it’s actually important that you have technology that we call personal data fusion, which gives people personal space. So this information is being analyzed and correlated for you. And nobody else has access to those insights unless you share them.

Alan
David, I, I want to get more into this personal data fusion because this is huge. But I do need to take a quick break and visit here today with David Bruner. He’s the CEO and founder of modelQ We’ll be right back after these messages.

Alan
Welcome back and be busy here today with David Bruner. He’s the CEO and the founder of module Q, which is an artificial intelligence company focusing on deep personal data fusion and big trend for the future here. I want to jump back into Big Brother versus privacy. We talked about Google’s mapping, and I’m sure Google is not the only one to map the way that we make decisions and websites visit. But how do you balance this in terms of making sure that the people that are observing are not influencing the change in natural behavior?

David
I think it’s a great question. And as I mentioned in earlier, Professor Ethan Bernstein at the Harvard Business School, and I recently published a post that we called Big Brother versus personal data fusion, because the risk of all these big data technologies is that you can end up with too much surveillance, and you can risk the loss of privacy. And we’re focused on business uses of these technologies. And so it turns out that in business settings, there are actually real costs to doing too much surveillance. And they come in two flavors. One is you get people saying, Hey, I’m not gonna use your system anymore. And so for example, we focus on on enterprise sales professionals as our first audience. They use paper notebooks, they are not going to be micromanaged and continuously monitored. Because they expect to be able to exercise their professional judgment and have some personal space. It’s kind of like you don’t expect your manager walking into your office and riffling through your filing cabinet. It’s the same thing. And so it turns out that when people are observed too much, their productivity goes down, they stop innovating. And so senior management needs to understand that they should not want to have excessive surveillance. And so they will need to invest in tools, if they’re going to increase the productivity of their knowledge workers that give them personal data fusion, that provides personal space and privacy for those professionals rather than trying to observe every single action they take. And that’s going to be a new direction and especially in sales. There has been a tradition of saying well all the data ought to be in our customer relationship management system. It never has been and never will be, it doesn’t actually need to be and having it all there would actually decrease the performance of the organization.

Alan
When we look at the future here at in you have a big influence in Japan, some your investors and and board members, but when Japan seems to have a lead on the industry, with robotics and and also this artificial intelligence, do you see that the wave of the future is See the robots actually replacing the humans in terms of the jobs, job placement, like, for example, fast food and she they talk about McDonald’s robots and how much are we going to see that.

David
We are absolutely going to see some replacement of humans by technology. For example, if you drive a truck or a taxi, you know, that job is not gonna be around forever. So you better start looking for other options. That said, there are a lot of jobs that require empathy require the ability to build relationships, all professionals do almost all professional jobs, there is a component of convincing others of the validity of your perspective, those are the kinds of things that systems won’t replace. And so when we look at enterprise sales, for example, the enterprise sales professionals are actually more in demand than ever, and demand is forecast to rise, because their job is actually to sell change to customer organizations, they need to go into organizations and convince them that they should change what they do, and buy this product or this service. That’s a very difficult job. And it’s something that you really can’t replace with a robot or with artificial intelligence, what you can do is you can augment it. And so recently, people have started talking about augmented intelligence. And I think that’s a great term to describe the partnership between humans and computers. But certainly when you look at the really routine tasks, those are going to be automated out of existence. But that’s probably a bad thing, because not a bad thing, because most people don’t really want to be doing those things. And so the key is to make sure that we’re creating opportunities for people to do more meaningful work. That’s a few levels up the cognitive ladder.

Alan
When you’re looking into this area of you know, with ModelQ, what is the business model? Are you software as a service or what it has? Who will your clients be?

David
So this is software as a service. And we’re going to market with the same model that, that, for example, WebEx used to go to market, which was going out initially to the frontline teams that actually use and benefit from the product. And it turns out that frontline sales teams have more discretionary budget than just about any other frontline folks in the organization. So they can make the decision to adopt this. Ultimately, once the need for this becomes clearer, you know, this is a disruptive solution. So we’ve got to go directly to the people that benefit from it initially, ultimately, it will become clear that GE our salespeople sell more when they have technology that enables them to be more responsive to their customers. And so we expect to make enterprise sales in subsequently, but initially, it’s about going out to those frontline folks, and it is software as a service.

Alan
Yeah, technology is changing so fast. How do you keep up with this as you continue to do research and work on disruptive models? You know, your company’s since 2011? How much? How large are you right now.

David
So we’re 12 full time, people.

Alan
But it doesn’t require a lot of people with the big data and artificial intelligence into the future.

David
This is one of those things that as you begin to dig deeper into the problems, the complexity goes up exponentially. And so we’re still at the proof of concept stage. As we grow, we will need a lot of people to look into all those things, because the the artificial intelligence, the knowledge, engineering, the algorithms, that’s going to require an enormous amount of investment to build out. So we will need that. But at this point, it’s really about hiring people who are cutting edge and who have their pulse on their finger on the pulse of, of the technology. And so, our CTO had a career at Oracle was in a Ph. D. program at Columbia where he was studying AI. Of course, we have an advisory board that is cutting edge on on technology.

Alan
So David, if a person wants to learn more about magic key, where would they go?

David
To learn more about module Q, you can go to our website, module q.com, that’s mo de uleq.com. Or if you’re interested in our products, specifically for b2b sales professionals. That product is called a realm of like, rev your engine or revenue. And so go to rev for sales.com.

Alan
I’ve been visiting here today with David Brunner, he says CEO and founder of ModeDavid, thanks for being on today’s show. Thanks so much for having me.

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This transcript was generated by software and may not accurately reflect exactly what was said.

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