How To Maintain Your Leverage After You Sign An LOI

May 1, 2020 |  

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Ganesh Ramakrishna and Mike Watson built Opex Analytics to 140 employees before they sold it to PE-backed LLamasoft in the fall of last year.

To read a transcript of this episode, click here.

Ganesh Ramakrishna and Mike Watson built Opex Analytics to 140 employees before they sold it to PE-backed LLamasoft in the fall of last year.

Opex is in the business of helping Fortune 500 companies get their products from a manufacturing plant into a customer’s hands. It’s what data geeks call supply chain design, and it’s a big business — especially these days when many people are working from home, and COVID-19 has changed the game for anyone who sells a physical product.

This episode illustrates the definition of a strategic acquisition: LLamasoft wanted to bring more AI to their customer’s decision making, and Opex was a seamless addition. There is lots to learn from listening to Ganesh and Mike, including:

  • How to maintain negotiating leverage (even after signing a Letter of Intent)
  • How to hire highly sought-after employees
  • How to bootstrap your way to 140 employees without raising money
  • Why service companies often fail to build products (and why the inverse is not true)
  • The intricacies of sharing equity with employees
  • Why diligence is like giving birth — painful at the time but worth it in the end

Ganesh and Mike bootstrapped their way to an exit by tightly managing cash. If you’re worried about money these days, we can help find hidden sources of cash in your business when you complete module 10 of The Value Builder System™. Get started free by getting your Value Builder Score.

Our guest

Ganesh is a juggernaut of artificial intelligence ideation. His ability to connect with and work alongside executive leaders, data scientists and development teams alike makes him best suited to bring varied perspectives and solid technical insight into any enterprise problem. Mike is a recognized leader in the enterprise artificial intelligence space. With a PhD in Industrial Engineering and 20+ years of experience leading global business teams at LogicTools, ILOG and IBM, an adjunct professor at two masters programs at Northwestern University and the co-author of two books (Managerial Analytics and Supply Chain Network Design). Together, they founded Opex Analytics in 2013 and grew the company to success in the AI market prior to integrating with LLamasoft, now forming the industry’s premiere AI Powerhouse.

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Transcript

John Warrillow:

This is Built to Sell Radio with your host John Warrillow. So once a year you go to the doctor. They take your blood pressure, maybe they prick your finger and they take a little blood and they give you a sense of your cholesterol level. Maybe if you go to one of those fancy healthcare facilities, they get you to run on a treadmill for a while, see how your heart’s doing. You get a checkup. The same thing should be true of your business. When we look at your business through the value builder score, we’re going to look at it through eight key drivers that acquirers care about. Whether you want to sell your business immediately or in 10, 20 years from now, these are the eight factors that business buyers care about. Knowing them now, will help you maximize the value of your business going forward. Just go to valuebuilder.com and take the questionnaire.

John Warrillow:

So have you ever wondered how to maintain your negotiating leverage when you sign a letter of intent? Letters of intent usually have what’s called a no shop clause, meaning you have to give up negotiations with anybody else and sort of fall into the arms of a potential acquirer. It’s at that point where you can often get ground down in re-trading because the acquirer knows you don’t have a lot of leverage left because you’ve said goodbye to all the other potential suitors. Well, my next guests, Mike and Ganesh from OPEX, found themselves in that situation, but I think did a tremendous job of maintaining leverage, which they’ll explain how they did it in this episode.

John Warrillow:

Lots of good stuff in OPEX is acquisition by LLamasoft. In particular, there’s some interesting information about how they hired really tough to find employees. They were in the AI or artificial intelligence space. So they’ll talk about how they found highly sought after employees, how they bootstrapped themselves to 140 employees without ever raising money. Why service companies often struggle to become product companies, and why the inverse is not always true. And why in Ganesh’s case he refers to due diligence as equivalent to giving birth. Here to tell you the gory details are Ganesh and Mike from OPEX Analytics. Enjoy. Mike and Ganesh, welcome to Built to Sell Radio.

Mike Watson:

Thanks for having us.

Ganesh Ramakrishna:

Thank you.

John Warrillow:

How did you two crazy characters get together? Give me the backstory on how OPEX came to be. Ganesh, why don’t you tell us?

Ganesh Ramakrishna:

Absolutely. John, before we get there, I want to say thank you to you and your show, because we’ve been big fans of your show and we always dreamed of being on the show while we are going through the diligence processing. How would we respond to these questions? Hopefully, we’ll get there one day and if we get there, how will we answer these questions? Thank you very much for what you do here.

John Warrillow:

That’s very generous guys, I really appreciate that and I’m glad you guys found some value. So how did you guys get to know one another?

Ganesh Ramakrishna:

Absolutely. So we go back a long way, Mike and I. So I was a junior consultant in one of the software companies I joined, this was my second job out of school, and Mike was one of the top guys in that company. That is back in 2007. So that company got acquired a couple of times with a company called ILOG, and then ILOG got acquired by IBM. And we worked together through that whole process. So the founding story goes back to 2012. I was deployed in Asia Pacific, and I was in Manila and Mike was visiting me from US, and we were in a traffic jam and traveling from one place to another. Anybody who’s been to Manila can tell you that it’s the city of traffic jam. So we had a lot of time together in these traffic jams. And I’d say I kind of proposed to Mike saying, “Hey, would you ever consider working with me on a business idea?” And he said yes. And as they say, the rest is history. Mike, you want to add to that?

John Warrillow:

What was the idea Mike? What were you guys setting out to do, like what was the original genesis behind OPEX? And what was the idea?

Mike Watson:

Yeah, so the big idea was, we were going to take what we knew about supply chain optimization and combine it with this new field that was emerging called machine learning. So that was the big buzz word at the time.

John Warrillow:

Dumb down that for me? What did you call it? Supply chain.

Mike Watson:

Supply chain modeling, supply chain optimization. It’s basically figuring out-

John Warrillow:

So this is… Go ahead, figure out what?

Mike Watson:

It’s figuring out, you make orange juice, how to get your orange juice from your factories to the warehouse to the shelf so that you can buy it.

John Warrillow:

And what’s the customer… Don’t I just put it on a truck and the truck shows up at the grocery store and Bob’s your uncle? Why is-

Mike Watson:

Think about that, you have to figure out which truck do you put it on? How do you route that truck? Where do you send that truck to? Because it usually goes to a distribution point first. Where should those points be? Which factory should I even make the product in? So all those little decisions that add up to how do you do this efficiently?

John Warrillow:

And so the company was designed to be a consulting company that would help orange juice manufacturer to get their product the most efficiently to a grocery store? Was it consulting, or was it software, or combination of the two?

Mike Watson:

It’s kind of a combination of the two, but to make it easy for our customers, we kind of presented ourselves as consulting. We said, “We’ll come in, we have some people, we’ll solve some particular problems. And what we’ll leave behind, is we’ll leave behind a piece of software that helps you do this stuff more efficiently. And it may even help you predict what the demand is going to be so you can better schedule your workforce and things like that.”

John Warrillow:

Got it. Okay. So I get it, I think conceptually. So take me further. Did you win some clients? Would I know any of the names of customers that you won?

Mike Watson:

Oh, you’d know the names. So we work with basically Fortune 500 companies. We have a video up on our website from a bottler of Coca-Cola that they gave a testimonial about working with us. So the way we started is totally bootstrapped it, and Ganesh and I just went out and started selling our services and once we got some traction, we started hiring some folks. I’m also an adjunct professor at Northwestern and so we had some connections to some programs there, and we started hiring some great people. And it just seemed like the more people we hired, the more blue chip clients that we got, and the happier our clients were.

John Warrillow:

I’ve always wondered what an adjunct professor is, it sounds like an appendage, like you’re not really a professor, you’ve got sort of an arm… What is an adjunct professor?

Mike Watson:

You said it exactly right. If they can pay you under the table, they would pay me under. They would do that. So I show up, I teach my class, the students are happy, and if the students are happy, the program’s happy. But other than that, I have no other connection with Northwestern. I just show up, teach and do my thing.

Ganesh Ramakrishna:

John, another way to think about it is, an adjunct professor is somebody who is just as smart as the other professors but also lives in the real world.

John Warrillow:

Okay. Got it. Got it. Actually he has some experience. I’m looking forward to getting the social media blast about putting down… Okay, so let’s get into it. So Ganesh, take me through… I mean, we don’t have time for the whole story, but from a taxi cab in Manila, you come up with this idea, eventually you got to 140 employees. Fill in the blanks for me, was there an inflection point where things started to really grow beyond just you and Mike?

Ganesh Ramakrishna:

For sure. I think we got a project or two as we were talking to customers, and we got to a point where we could hire four or five people. I can’t name this customer, but we got a chance to kind of code in a way with one of the largest fashion companies in the world. And there we kind of discovered our business model, if you will. We nailed what we are all about, working with that customer for about six to 12 months. And they gave us a lot of business and we grew to a significant seven figure business just working with them. And we have other customers too, but we kind of built our business more working with them. And then we went to market with that message saying, “Hey, we are the core innovation partners, AI is hard, AI for supply chain is a very specialized area, and we’re specialists at this and we’re going to learn with you and we’re going to build software for answering a whole range of questions for you.” And that started clicking with the market.

John Warrillow:

Got it. So the fashion company that you worked with, you were kind of, in your own words, kind of co-innovating.

Ganesh Ramakrishna:

That’s right.

John Warrillow:

Were you specific with them about who owned the IP?

Ganesh Ramakrishna:

In that case they owned the IP. The kind of stuff that we did for them, they owned the IP and we didn’t care.

John Warrillow:

Is that part of your scope of work and part of your contract, it was stated clearly that they own the IP?

Ganesh Ramakrishna:

That’s right.

John Warrillow:

So how did you go from them owning the IP to reusing the IP? You know what I mean?

Ganesh Ramakrishna:

Yeah. We didn’t have to reuse that IP. So when you go from a fashion company to a CPG company, from a CPG company to a transportation company, the problem statement changes. It’s a different set of IP that you create. So we were getting good at that stuff. As we were getting good at that stuff, we also realized that, hey, there’re unique blocks that all these customers need and no one has commissioned us to work on that piece. For example, we have a platform for deploying apps. Nobody commissioned us for building that. We, by that time when we were up to about 15 to 20 people, we had enough funds in the company to say, hey, we’re going to start a software unit inside the business, that’s going to build software that we think all customers would need. So about the 20 people mark, we kind of had two parts of business. One where we are coordinating with customers, as Mike said, that’s the service angle. On the back end, we’re creating IP that’s independent of the work that we are doing with customers.

John Warrillow:

And Mike, how are you guys financing this growth when you went from project based consulting, if you will, and a few handful of bodies to building a piece of software that you could reuse? Did that require outside investment or how did you guys finance that?

Mike Watson:

So we financed everything with cashflow from our projects. So the whole thing was 100% bootstrapped. And as we started building some of the product, we did it probably slower than we would have if we would have brought in capital, but I think we made a decision that we were going to just build the business based on the revenue, and basically based on the profits that we were making.

John Warrillow:

And so did you guys take a haircut on your market rate salaries during this time? Ganesh is laughing. I mean, can you think about what you would have commanded in the marketplace as an AI specialist? Were you paying yourself 100% of that salary? 50%, 200%? Give me a sense.

Ganesh Ramakrishna:

I was thinking what salary cut? What is that?

John Warrillow:

It’s what you live on. Come on, were you not paying yourself anything?

Mike Watson:

So the first couple of years we didn’t pay ourselves anything or very little. And then towards the end we did take home a salary, but I don’t think it was what’s the market salary.

John Warrillow:

Would it have been 50% of what you were worth in the market?

Mike Watson:

Yeah, probably 50% of what we would have, somewhere around there.

John Warrillow:

So you’re investing personally in this business all along the way. So it really is, you’re all in, it’s not outside.

Ganesh Ramakrishna:

And John, what will help the listener understand is, we came from a product company background, so this idea of doing services, core innovation on the front, and doing software on the backend, they usually say this idea is not a great idea, but the thing is, the core innovation was a new thing that we were doing. Services was a new thing, and we were finding traction. Marketing was accepting that. But in the back end, the software side, we came from that DNA. We were software people who were doing this new business model.

John Warrillow:

So when you say it’s not usual most services companies dream of having a software product that never works, but the other way around, adding some service onto a software DNA that usually has got a better traction or better life.

Ganesh Ramakrishna:

In retrospect, that’s why it worked out for us.

John Warrillow:

Can I ask, what is it about having a product DNA first and adding services as a layer that you think gave you an upper hand?

Ganesh Ramakrishna:

Because product is, I mean, at least in retrospect, my personal experience is that software is really much harder than services, to scale and to build. Here’s another way to think about it, it takes many iterations to build the right software. And the more experience you have, the stronger your DNA competent in that, the fewer iterations it takes. So we didn’t have the funding to fail three times and get it right the fourth time. We had the funding to try once and get it right the first time. And the DNA kind of helps us to go in with the confidence that what we’re building is what the customer needs and what the market needs. And having the services front end, you get the validation very quickly because our people are data scientists were consuming our software. And we had a huge base by that time, 50, 60, 80, users in Delhi, who were consuming our software and we get the validation. Because the product enhancement did not require a paying customer for the software. Our folks are validating that what we’re building is the right thing.

John Warrillow:

So you’re eating your own dog food, is that the expression?

Ganesh Ramakrishna:

Pretty much.

John Warrillow:

And the 140 people, give me a sense of how they broke out. Are most of them software developers? Are they consultants? I’m sure you had all those, but where’s the… There’s a lot of people.

Mike Watson:

In the 140 we probably had 30 to 40 people who were developers, and we did our development in India. So we actually grew a development team in India, which also allows the self-fund too. So that was another trick that we use to say, let’s build a team. We found a leader over there who we could really trust, and he helped grow that team. And so that let us do that from a cashflow point of view. And then probably the remainder of the people, we had a handful of people doing the marketing and admin kind of stuff and keeping things going. But the vast majority were the hot data scientist consultants. It was like that commodity of folks that were doing the trendy field, doing data science.

John Warrillow:

And Ganesh, how did you guys go about recruiting? Because data scientists, I mean, the only people I can think of that would be harder to recruit for will be AI specialist. And you’re matching them together. Like, we want data scientists who could do AI, that’s got to be the hard… I mean, everybody wants those people. How did you find them?

Ganesh Ramakrishna:

Good. I think we got very, very lucky there, because I think when you hire a data scientist, that could be a podcast by itself, but we understood what they were looking for. They were looking for good work, a good culture and good coaching. I think those are the three things they were looking for. And good coaching is something we could solve easily because of Mike’s professorial background. And the original seeding of the company was with the kind of people that they would all want to work with. Good work is because we were working with multiple companies in different industries, there was always a platform for, and the terminology we were using with our client, was core innovation. These are not one of the middle consulting work.

Ganesh Ramakrishna:

So the diversity of work existed, and the depth of work existed. And finally the culture is something we have to work very hard on. And we were very first principles on that. Everything that we had to do, we were like, what’s the right way to do it? Instead of coming up with the bias of background thing, here’s how things should be done. We were lucky enough to recognize that this is a new kind of business, and what will work here has to be thought through instead of just saying, “Hey, here’s how I did things in this big software company or this big consulting company,” because it’s neither of those. So we were able to be first principles on a lot of the cultural stuff.

John Warrillow:

What triggered to sell this company?

Mike Watson:

So we weren’t actively searching to sell it. We were approached by the buyer who is Llamasoft, and at the time we’d grown to 140 people. We had ambitions to take what we’d done and turn it into software. And basically at this point in our history, the only thing backing us up financially is the mortgage on our two houses. That was it. We were sort of past that point where our mortgages would even made a dent in things if things had taken a dip. And so it was sort of the right time. The business was going well, the cashflow was good, the projects were good, things were fine, but it was just knowing in the background that, hey, we approached by this company LLamasoft, we knew them from before.

Mike Watson:

Ganesh told the story of the cab in Manila, at that time we were competing with LLamasoft so we kind of knew them there. And then as OPEX Analytics, we didn’t compete with them but we’d run into them on occasion on different accounts. So we knew them, knew their culture, and we felt like it was a great fit and they were going to be a big platform for us to sort of take our group to the next level too.

John Warrillow:

What was the strategic connection Ganesh? I don’t know LLamasoft, I don’t know their products. What is it that they saw in you and what did you see in them?

Ganesh Ramakrishna:

So a little bit about LLamasoft. I mean, when you think about, Mike talked about solving supply chain problems, so there’s a specific area in supply chain problem solving called supply chain design. This is how you structure your supply chain so that it can run efficiently. So they build the software for that kind of work. So pretty much every Fortune 500 company that has a supply chain, not the insurance companies, but that has a supply chain, Llamasoft is a vendor to them in supply chain design.

John Warrillow:

Got it. And so it sounds like they were a competitor, a competitor of yours.

Ganesh Ramakrishna:

So I can understand why you say that. So they were in the standard software for supply chain design. And what we worked on was, how do you bring this new space of AI to solve all kinds of other problems in the supply chain? So it’s puzzle solving, I mean, if you think about it, but puzzle solving as a structured problem, the original design of a supply chain. But we came in with core innovation.

John Warrillow:

So what kind of problem would OPEX solve that LLamasoft out of the box software would not have solved. Can you give me like a real life example? Let’s go back to the orange juice guy with the orange juice plan.

Mike Watson:

So the orange juice guy has to figure out where should they make the product, which warehouses should they use? That’s what LLamasoft traditionally doing that. And then what we would come in is, help them predict which truckers aren’t going to show up today, or what’s the price you’re going to pay for a truck tomorrow. And so we were playing in the white space that they weren’t playing in. I think that was the fit, we were right next to them, but solving different problems. So it was a nice compliment.

John Warrillow:

That makes sense. I want to go back to something you said earlier, Mike, I think it was, you said the only thing backing you guys up was your mortgage. And had things gone south, even the mortgage probably would. So what I’m interpreting you to say is, okay, so 140 people, I’m imagining that those are not inexpensive people. So your payroll is millions of dollars a month, I think.

Mike Watson:

Absolutely.

John Warrillow:

Certainly a million if not multiple millions of dollars a month. So that’s a big nut, and you both got homes. Are you just joking to say that you had mortgaged them or you literally your bank line was guaranteed by your homes?

Mike Watson:

It’s more of a joke, we never had to tap into it, but we had a tiny line of credit at the bank. But we literally had nothing, no financial backing if things had gone south. Well, we would have had to tap into my mortgage to sort of put a bigger mortgage on the house, then use that money to keep the business going. We never got to that, but it was that level of… We had cash in the bank, but that was it.

John Warrillow:

And did you have any sense of what you thought the company was worth? I’m guessing you guys had those conversations between you. Did you have, if you can’t share the number that’s okay. I’d be curious to know sort of how you arrived at number, did you think it was a multiple of revenue or EBITDA? How did you think about valuation?

Ganesh Ramakrishna:

Go ahead.

Mike Watson:

So as we sort of thought about it, we were personally consulting and we knew that that had one set of figures, and then we were partially software. And we kind of felt like our valuation would sort of fit in with those numbers. And then to be honest, we talked about what we thought the value was, and the AI companies were kind of a hot space in 2019 for sure, and probably even now. So we sort of had some sense of what we thought the company was worth.

John Warrillow:

What multiple of revenue? Give me a range Ganesh. Would you have said the software revenue was worth, and what do you think the services revenue. I mean, just the broad range of whatever multiple.

Ganesh Ramakrishna:

So I think if we had come in as a pure services company, you’d be in the 2X to 3X kind of range.

John Warrillow:

A 2X of revenue or EBITDA?

Ganesh Ramakrishna:

It’s revenue. I mean, this is a hot space, so the metrics is usually not EBITDA, it’s just straight up revenue. And there were some hot shot software startups, big time startups who were founded in 2017, ’18 kind of timeframe. By that time AI had become a standard playbook on how to start a new AI firm. And what we heard was, they were raising funds at the 10X kind of valuation, if not more.

John Warrillow:

So you were thinking somewhere in that range of revenue multiple, and so is this a bit… I mean, I know you’ve been successful in other businesses and you’ve gone through other exits, but I’m guessing your shares of OPEX were at that time, even if you’re using the lower end of that valuation range, a fairly significant part of your net worth. Would that be fair to say?

Ganesh Ramakrishna:

Pretty much, yeah. It’s a very easy fair statement to make.

John Warrillow:

And same for you Mike?

Mike Watson:

Same thing. And the other thing we did with the equity too, the equity in OPEX Analytics was spread widely throughout our employee base. So it was really spread out very widely across the employee base. I mean, we definitely had advisors who were going through due diligence who were sort of shocked at how widely it was spread.

John Warrillow:

Okay. Tell me more about that.

Mike Watson:

Early on when we were getting people to join, we offered equity in the company. And I think a lot of people appreciated the fact that they would have a stake in the outcome. Of course, we could never promise anyone anything for this equity, because probably most likely it would have ended up valuing zero, if you just looked at probability in general. But we were, I think fairly as part of our principles that we wanted to be able to offer lots of people equity in the company, so they all had a stake in this thing.

Ganesh Ramakrishna:

So John actually, significant equity. When you’re thinking about, hey, how do you recruit and retain data scientist, part of the secret sauce was, you own a significant part of this business. I mean, they knew on the first day what percentage of the business they own. It’s not just throwing some numbers at them and saying X thousand options, they don’t mean anything. Again, being first principles we were like, you own X percentage of the company as of today.

John Warrillow:

So I know a lot of people listening to this will have gone through machinations in their mind about how do I share equity? Is it options, is it phantom equity, is it real equity? Maybe talk me through how you guys landed on your program. And my follow up question in case you want to answer it as part of that is sort of, if you had to do over again, how might you structure it differently, hindsight being 2020?

Mike Watson:

I don’t think we were so strategic in how we set it up. We set ourselves up as an LLC just based on some advice we had from our lawyer, and then we basically had stock options that we issued off of that. And again, we just had our lawyer set up a stock option plan so that people would get options in the company. And I think that served us very well. Every year or so we’d go back to our lawyer and he would issue a certain X number of new options that we could then distribute to the new employees as they joined. So it was fairly simple, we didn’t think through it too much. What we would have done differently, would we have set up a C Corp? I don’t know, maybe we would have thought about a C Corp if we’d known that this was going to happen, but the LLC gave us a lot of tax advantages as we were kind of growing and gave us some flexibility there that I don’t think we would have had with a C Corp.

John Warrillow:

Ganesh what would you add to that?

Mike Watson:

No, in retrospect I think there are some tax optimization strategies you can take. I mean, there’s something called QSQV, I think something like that. There are tax advantages to setting it up as a C Corp. If you’re a founder thinking about setting up option pools, I would say talk to a startup attorney. And that would be what I would have done if I’m doing it again. Talk to the startup attorney who specializes in stock options. What we did served us well, I’m not regretting what we did, but I think there are other tax optimized solutions out there.

John Warrillow:

And rather than getting into all the minutia and the details of that, because we’ve got people listening to this from different tax jurisdictions, parts of the world where it’s really differently. So I think you’re right Ganesh, I would recommend anybody talk to an attorney or a lawyer who really specializes in this. Also talk to an accountant who specializes in this stuff, because it gets way past my pay grade very quickly. And it also varies by geography. But I think you’re right that, doing it up front often allows you to either save a lot of money or potentially make different decisions if you have that luxury. Back to my original question. So yes, you shared some equity with key employees and employees along the way, but I’m still hearing, and just I want to validate this, that your shares in OPEX, the ones you personally held were still a significant part of your personal financial situation. Is that fair to say?

Mike Watson:

Yeah, there were definitely a big part of it. I mean, the company was going well, and I have to say that if we didn’t sell and there wasn’t an exit, I wouldn’t have been crying or my family wouldn’t have been suffering or anything like that. So we were in a good position in that sense too. We’ve been professional, we’ve been working at the good careers up until we started this company, OPEX was shedding good cash and making good money. So we were doing all right. I don’t want to paint the picture, like we were just starving to death waiting for these options to exercise. I mean, nice part of our total net worth in some sense, but if it hadn’t happened, there’d be no difference between how Ganesha and I we’re living today versus then.

John Warrillow:

And I guess part of me is wondering about the followup question, which is like, so why sell? If the big win is not going to make much of a difference to you personally, you’re already doing well, why bother selling?

Mike Watson:

I think it goes back to the risk. Still 150 people, that’s a big nut every month, and if something had turned one month or the other that would have hurt and we could have got in trouble quickly in that sense. So there was always that aspect of it that we had to worry about. And the other one was that, LLamasoft approached us. They are backed by a private equity firm themselves. And so in some sense it was continuing what we were doing in, again, another startup, a munch bigger startup, a much well funded startup, a startup with a huge infrastructure and a huge client base. But certainly one that if you know anything about the PE, private equity business, they’re set up to eventually do something. Like private equity does IPOs, they sell, et cetera. So it kind of felt like a continuation of what we’re doing with a bigger backer behind us to take our ideas to the next level.

John Warrillow:

That’s helpful.

Ganesh Ramakrishna:

I think… Sorry, forgot my point.

John Warrillow:

Did you lose your mind Ganesh?

Ganesh Ramakrishna:

No, I got my point back. Okay. So we were struggling with this, in trying to think about how to think about this because Mike and I, we knew that even in the worst case scenario if something bad happens, we would be just fine. We’d gotten to the point where financially we’d be okay. One trick we used is, hey, let’s think about employee number three, employee number four, employee number five, what about those people? How would it play out for them in one scenario versus the other. And that kind of made it easier for us to make the decisions that we made.

John Warrillow:

Got it. Got it. That’s helpful. And so take us through… I mean, you’ve listened to a few of these episodes before, you know my question is going to be, so how did you kind of go about shopping the company? I mean, LLamasoft’s great, you got an offer, did you go and hire a banker and sort of turn it up to sell and get some competitive offers?

Mike Watson:

We didn’t. So what we ended up doing was, LLamasoft approached us and we weren’t in a position to shop the company around. We did not have a banker. We were sort of talking to some bankers, but we hadn’t signed anything. It didn’t have anything firmly in place. And LLamasoft came with an offer, and I think we went back and forth a couple of times and kind of came up with with a price that was agreeable to both sides. And then sort of from there, we kind of started the process. So we never felt like we were in a position to shop it around competitively or go out and look, and we felt like the offer and everything else that LLamasoft brought, like the culture and their future prospects felt like the right package. And we knew that if we’d walked away, that offer might’ve gone away and there might not have been a better one down the road and it would have been a lot of effort to get to a better one. So Ganesh and I had to go back and forth on that. It was a tough decision. Did we know we were making the right one, right decision? No this, but this is how this one played out.

John Warrillow:

Often deal people would say, maybe you gave up a little bit in negotiating leverage because you kind of fell in a bed with one. Did you ever feel a little vulnerable on that score where you didn’t have that competing offer to keep everybody honest? Ganesh, do you know what I’m kind of getting at?

Ganesh Ramakrishna:

Yeah. And so I think our biggest leverage we had was the fact that we were okay not doing this transaction. We could live with that outcome where the transaction did not happen, at least for the first 175 days. The last five days we probably got pretty keen to get it done because so much energy was poured into the process. But without that I think we’d have been in a very difficult situation, because as you know the due diligence process, there’s lots of ups and downs and it’s a pretty stressful process for everybody. But I would say the biggest leverage we had was the willingness and the ability because of our customers, and the love that they had for us, and the revenue base that we could just say, okay, it’s not working out, that’s fine.

John Warrillow:

Yeah. Yeah. That makes sense. What was the most difficult part of diligence?

Mike Watson:

I think that the most difficult part was just the time commitment. As the way we were set up, Ganesh and I were very involved in all the day to day operations of the company, so trying to keep the company running and then trying to do the due diligence, and as a much smaller company, we were pretty lean. We didn’t have other departments to lean on, so all the questions came through Ganesh and I basically. And so the hardest part was just the time and just all the details about all these different business functions that we didn’t have people that we could rely on to answer those questions.

John Warrillow:

And because you guys are so integral, I’m assuming that a fairly big part of your deal was an earnout, where you were asked to stay on. Is that fair to say?

Ganesh Ramakrishna:

Absolutely.

Mike Watson:

So we were definitely asked to stay on, we’re a people business, so the buyer, LLamasoft definitely wanted the people to stay and lawyers are pretty smart. I’m pretty sure if I read the fine print, I probably signed away my kids somewhere if I leave this place. And we went into this deal not looking to exit, get out of this business, but to continue it in the sort of this phase two here.

John Warrillow:

So did you carry some equity into the new enterprise?

Mike Watson:

We did, yeah. So without getting into the details, but there’s definitely some of that too where we carried some of the equity into the next phase here.

John Warrillow:

So I’m assuming there’s some cash upfront, there’s a bit of an equity carry where you held some equity in the new, and an earnout where if you hit certain milestones in the future, there’s an extra payment of some sort.

Mike Watson:

Actually it turned out there was no earnout, because our businesses were similar enough, it just felt like it would be difficult to add that in there. And so as we kind of went through the negotiation, it’s like we had talked about that and decided it was just too difficult to put that in. So there’s other ways that they structured the deal to sort of get the same spirit of those incentives.

Ganesh Ramakrishna:

So John, also going back to your original question, what are the hard things, one thing for me, I was a little bit surprised by the long tail of duties and activities. I mean, there’s always the core things that happen. Everybody talks about it, everybody knows about it. But there’s a long tail of requirements, and each one of these things is like a five hour, four hour, 10 hour activity. But there are just five, six, seven dozen of these small, small things that kind of profess why I surprised.

John Warrillow:

Give me an example of something that surprised you personally, that was so detailed, so into the weeds that you were like, really, you want to know that? I’d love for you to share an example because I want people listening to know what level of obscurity they might have to go to, or what level of detail that would be asked. Can you think of an example where you had to devote five hours to getting a piece of data?

Ganesh Ramakrishna:

Yeah. I mean, it’d be something like, there’ll be obscure questions in a questionnaire, where they’ll be like, it’s pretty open ended, let’s say, hey, did somebody say something to… Obviously on things like, let’s say, potential lawsuits. What kind of HR activities happened in the last three years in your company? And something could be around harassment, let’s say. You don’t have any harassment issues in your company, you can’t say no, but they’ve asked some questions in such a way that you’ve got to detail something that happened to you. It has nothing to do with harassment, but the way they phrase the question makes me want to say, hey, this person said something to this person about this event. And you say that, the questionnaire goes to the attorney, the attorney has a two hour call with you about it. And there’s nothing really in it. Everybody knows there’s nothing in it, but that opens up another questionnaire and you’re going to answer those questions in the questionnaire, and everybody fully knowing that there’s nothing here.

John Warrillow:

Did you eventually have to pull up and say, “Okay guys, enough is enough.” Did you have to have that…

Ganesh Ramakrishna:

I mean, not for the whole deal, it’s like, these topics we’re done here. We were very lucky that by that time we had built a very good rapport with the CEO of LLamasoft, where we could go back and say, there’s the attorney to attorney conversation, there’s also the business people, we were able to have open conversations say, “Hey look. You got to stop your attorney from doing this.” Or he could come back and tell us, “Hey, we need more information here. The deal is a no go if you don’t get that information, I will manage my people in these four areas.” We could have that kind of open conversations amongst the business people because the lawyers do their thing and they’re very good at doing their thing, but it really helped us having that business relationship built out, all the six months which we were engaged.

John Warrillow:

I know employees were a big part of this piece for you guys. You had options for a lot of your employees. How did those options pay out when the transaction happened? Were they 100% paid in cash? Or did they have to carry? I’ve always wondered how that works with options when you as founders are asked to carry some equity. How did they get paid out?

Mike Watson:

So some of our employees had exercised their options, so Ganesh and I were not the only holders of shares when it happened, but basically everyone, option holders and shareholders had basically the same thing, a mix of some cash up front and some equity on the backside. So it was kind of equitable in that way. It was legally complicated to do that, but that’s how it ended up looking.

John Warrillow:

What made it legally complicated?

Mike Watson:

There was a combination of vesting on the backside options and then actual stockholders versus option holders, there were some different legal transactions there. And then the vesting part on the backside made it a little more complicated than normal. That’s an example of some of the detail that you get into. We never knew that this would be that complicated, but it turned out it was not easy to make sure that that could all work out in a right and equitable way for everyone.

John Warrillow:

Ganesh, what’s your favorite story of sharing the news with one of your employees?

Ganesh Ramakrishna:

I can’t remember any. Mike do you remember any stories? It’s all the haze. Seriously it’s like, when I talked to my wife about giving birth to our two kids and I was like, “Hey, do you remember how painful it was?” “I don’t remember anything.” I was in the room, it was painful. It is a little bit like that, I feel like I was the pregnant woman in this case.

Mike Watson:

The stories I remember are like the longterm employees who had been there a long time, they took some equity, they kind of trusted the company. And it was just the joy on their face that like, “Hey, this is pretty exciting, Mike. This piece of paper I had is actually worth a little bit more money, I didn’t think it was worth anything.” That was pretty good. And since we spread the equity wide, and since we had employees in India and things like that, the amount of money that we were able to provide in this exit was nice money for lots of people in the organization. And that made us feel pretty good.

Ganesh Ramakrishna:

That is very satisfying for sure.

John Warrillow:

I’d imagine it would be. Did you buy yourselves a trophy? Was there any Teslas… The Tesla seems to be the go to trophy for people who sell their company. Did you buy a Tesla?

Mike Watson:

No, I didn’t buy. Maybe took my wife out to a nice dinner and that was about it.

John Warrillow:

Ganesh?

Ganesh Ramakrishna:

Dinner, and I updated my speakers, that’s it.

John Warrillow:

Boys, do you want to stay married? Let me give you a tip. When you sell your company, you got to do better than dinner. All right. Just a little tip. Take it for what it is. I’m just teasing. I think this is a great story. I really love the way you described the strategic fit between you and LLamasoft. There’s clearly an adjacency but also a tremendous strategic fit. So I think it’s an awesome story. If people wanted to learn or reach out, I know you guys are busy with your day jobs, but is there… I mean, do you accept LinkedIn connections or what’s the best way for folks to stay in touch?

Ganesh Ramakrishna:

Absolutely.

Mike Watson:

Yeah, LinkedIn’s probably the best way. It’s pretty easy. If you go to LLamasoft I think you can find our profiles and our email addresses there too. So it’s relatively easy to reach out to us.

John Warrillow:

To track you guys down. And we’ll put the spelling of your first and last names, both of you, in the show notes so people can search you up on LLamasoft’s website. This was a real joy. I wish you guys all the best in this next chapter, and I’m so thrilled that you took the time to do this.

Ganesh Ramakrishna:

Thank you very much.

Mike Watson:

Yeah, thank you John. We appreciate it.

John Warrillow:

Thanks for listening to Built to Sell Radio with your host John Warrillow. For complete show notes with links to additional resources, visit builttosell.com/blog. John is the founder of The Value Builder System. To find out how to improve the value of your business by 71%, visit valuebuildersystem.com. John is also the author of Built to Sell, creating a business that can thrive without you, and the automatic customer creating a subscription business in any industry. Connect with John at facebook.com/builttosell or on Twitter at John Warrillow, W-A-R-R-I-L-L-O-W. Thanks for listening.

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