STARTUP DNA AT CORPORATE SCALE
Effective Engagement with the Innovation Ecosystem
ABOUT THE WEBINAR
96% of corporate innovation initiatives fail. Another form of innovation, startups, actually fare worse with less than 1% succeeding. Yet over the last 80 years, the startup/venture capital industry has consistently generated outsized returns from investments in innovation. This session will provide an overview of the battle-tested startup and VC-inspired tools and techniques corporations need to leverage to drive operational excellence at innovation, cultural transformation, and reliable returns from innovation spending.
- How corporations can excel at innovation
- What tools a company needs to build an innovative culture
- How to avoid disruption in a fast-changing business environment
ABOUT OUR GUEST
Mike Sigal is Co-Founder of Upside Partners, a Silicon Valley-based consultancy that helps corporations and institutions develop operational excellence in innovation through the application of startup and venture investor best practices. Mike also serves as a General Partner at 500 Startups Fintech Fund, the world’s most active investor in early-stage fintech startups. Previously, Mike was a 7-time entrepreneur (3 exits, 1 IPO).
Hello everyone and welcome to Silicon Valley Innovation Center. My name is Rahim Rahemtulla. I’m SVIC’s Brand Ambassador. Here at SVIC, we connect the world’s executives to the Silicon Valley ecosystem. And so today as part of that mission, we are bringing you a webinar with Mike Sigal. Mike is a co-founder at Upside Partners. Today, he’s going to be leading us in a discussion on corporate innovation, so please send Mike your questions at any time via the webinar console. We’re going to have a Q&A following his presentation, but equally, he’s happy to take questions anytime throughout his talk, so don’t be shy and do send them our way. And I think that’s enough from me. Mike, I’d like to hand over to you now. You ready to go?
So, when we usually begin our discussion with large corporations, particularly in the financial services space, we point out that, ultimately, digital technology is disrupting everything. So, if you’re looking through some of these brands that I have up on screen, what you’ll note – aside from being relatively new entrants – is that none of them operate on the traditional business models that they reflect in their industries. The good news for existing incumbents is that it’s been seen, generation after generation, that digital disruption happens in a predictable fashion where new technology emerges, you get innovative startups that being to exploit that new technology, that the new digital models begin to proliferate, then some advanced incumbents begin to adapt, mainstream customer shift and then, ultimately, you have a new normal where you have incumbents that have transformed themselves and some new entrants who now own the new marketspace and you see that incumbents that haven’t shifted end up going the way of the dodo.
The other thing that we often have to note, particularly with boards – some of our large clients – is that disruption doesn’t seem like it’s happening until it does. And over the last couple of market cycles, we’ve seen a predictable time for this to happen on the order of about six years. And there’s example after example of this kind of behavior.
So when you know that disruption is going to hit your industry at some point and you can make some judgment about when that is likely to happen, then if you are indeed a senior manager at an institution, what you need to recognize is that disruption or being disrupted is a choice and you have to decide for your shareholders whether you’ll continue to reap current profits or reinvest them in beginning to transform yourself.
When I bring this slide up, what I want you to note is that in each column you’ve got the top six revenue earners globally in 2016 in each of these market segments. And you’ll note there that there is a mix of companies that started off relatively recently and companies that have been around for quite a while. The thing to note is that these companies that I’ve circled in green are one that spent many years, once they saw that something in digital was happening, investing in their capabilities, platforms and in their people to insure that they would end up as one of the “new normal” instead of one of the disrupted. And, naturally, this landscape is changing continuously, thus the need for reinvesting.
Now, if I look at our own specialty industry – financial services – I often point to Goldman Sachs, the investment bank. The first time I ever met a venture capitalist from Goldman Sachs who was doing early-stage investments in the technology companies was in 2007. So even back then, they recognized that something was going on to change the shape of their market. The returns on those early-stage investments really are pronounced in 2016-2017, where Goldman Sachs launched a consumer lending brand called Marcus which does consumer loans of about $15,000 to $35,000 dollars. So Goldman is a financial services firm, but they are an investment bank, not a consumer lender. Between 2016 and 2017, Marcus originated $2 billion in loans, which is just an astonishing growth rate, dwarfing many of the online lenders combined. So that’s the kind of time it takes of investing and learning new ways of doing things to be able to reap the rewards when the time for the organization is right.
So what I want to share with you next is a high-level playbook and then a couple of tactical approaches to getting ready for disruption or making sure that you’re not one of the disrupted. And it comes down to, really, four relatively simple things: the first one being the Cloud, the second one being data, the third one being working with startups and the fourth, and clearly the easiest, is changing your company’s DNA.
Now, I’m sure all of you have heard lots of arguments for moving to the Cloud, so I’m not going to belabor this other than to say that, basically, the potential disruptors for your business out there have brought down their costs of delivering new products and services by virtue of using the most modern technologies. If you are continuing to have to patch your legacy technology, you’re never going to be as agile and you will always have a larger cost base than competitors who are using more modern technologies.
By way of example, in our own industry, in financial services, there’s $480 billion a years spent by financial services firms on maintaining their legacy systems and operating them, and that’s a huge overhang when you consider the need to invest in newer technologies. That extends not just to the computing systems that you’re using, but also your data.
If, in fact, you don’t have control of your data in a modern sense, in the way that an Amazon or Google does, you have a very hard time securing that data, you’ve a very hard time developing a overall view of your customers that can help you decide which new products and services to bring to them on a regular basis. When I look, again, in our own industry, in financial services, a lot of the data end systems are siloed around particular products or services: a lending product, a credit card product, a savings product, a home loan product. When you can’t look across all of those systems efficiently, you’re not going to know when to cross-sell, you’re not going to know when there is an opportunity to introduce a new service that you otherwise might not come up with.
The third element of being ready not to be disrupted is figuring out how to work with startups. This is not to say that you need to invest in them or use them as vendors or acquire them, but you do need to make a concerted disciplined effort to figure out what they have to teach you. Startups have a lot of advantages, they have some disadvantages, but they have a lot of advantages that incumbents simply can’t easily address. That includes being built on the most modern technology, which is designed with customer experiences for faster adoption. They almost always can deliver services at a lower cost base. They are able to, often, unbundle the services that larger organizations like yours might offer and, thereby, either break through resistances that customers have to feel like they are having to buy too much from large organizations or that the products and services are not targeted. And in financial services, they’ve found a way to use that unbundling often to navigate through, in early days at least, sticky regulatory environments. And then, finally, they’ll often be able to target customers that your cost base or your traditional marketing channels are not able to target.
And I’ll give you a specific example from our own portfolio that maps to each of these. Again, this is going to be a financial services example. So a company that we invested in a while ago that provides what’s called titled loans. So these are often thought of as payday loans where the borrower is using their automobile as the collateral. The traditional industry, which is about $5-6 billion industry and has interest rates approaching 360% APR is definitely a payday lending business. One of the ways this industry works is that all of the loans are originated at retail storefronts. The average storefront generates about 300 loans a year. That requires the customer to go into the store, to provide the title to their car, where the loan is completed. And the typical customer for something like this might be construction or plumbing or landscaping, where the car is a material part of delivery of the service. One of the tricks that the existing industry uses is to require that the borrower come back to the same retail storefront during business hours in order to make payments on those loans. You can imagine those kinds of borrowers, they’re supposed to be on jobsites earning revenue, not going and paying off loans.
So what this particular company that we invested in did first of all was to develop a system to acquire the titles of cars directly from Department of Motor Vehicles in the states where this kind of lending is allowed. That means origination for the loans takes minutes and can be done online instead of during the middle of a working day.
Then, they went and struck deals with folks like Wal-Mart and 7-Eleven to allow the borrowers to be able to go during their opening hours to repay loans. So, in fact, what they’ve done is they’ve low-disrupted the cost of both delivering and servicing the loans and dramatically improving the customer experience to the point that, as a lender, they get letters from customers saying, “Wow, this is terrific.” Amazing NPA scores for this company. Because you’re able to repay the loans whenever is convenient to you, the average cost of a loan is about 70% less than the traditional industry and, as this company is able to access less and less expensive warehouse capital, they’ll be able to drive the cost even further. Going on to the point about nontraditional customers, the borrowers, which represent about 22 million Americans, these are underserviced or unserved customers by the traditional financial industry. They’re simply not profitable enough for traditional banks to serve. With the kinds of NPA scores, the satisfaction that this organization is driving, they are in an amazing position to be able to, over time, deliver additional financial services, to become a complete service provider for these underserved Americans. Things like savings plans, college savings plans, health savings plans, credit cards, insurance.
So these are things that startups are able to do where often the existing business model of incumbents simply aren’t flexible to accommodate this. These are the kinds of things that we find our clients are able to learn by engaging with the startup ecosystem. The ways that we see corporates engaging with the startup ecosystem is across a very large range of engagements. Everything from providing technical support, investing in or running accelerator programs and startup competitions all the way through corporate venture capital, where the companies set up their own funds to either make investments in other venture capital funds or directly into the startups. In fact, in the financial services industry, we see about 30% of the venture capital that has been deployed into Fitch startups coming from corporations. And to give you a sense of scale, as of Q2 this year, over the last 8 years we’ve seen over $80 billion of venture capital going into FinTech startups. So the resources that the corporate that would like to be leaders, as industries transform, put to work is very substantial.
So then there is the easy trick, and this is what we try and help our corporate clients with, which is transforming their talent. This, we find, is the single most important thing that a corporation can do to be ready for the future. The reason I’ve got this image of the McLaren pit crew up is this pit crew in particular studies with the UK’s Royal Ballet. They study choreography and dance. And why do they do that? Because if you think about a pit crew, this is a dance to get the car out of the pit as quickly as possible. And the point I want to make about that is that they’ve gone to an uncommon place to learn the skills that they need to outperform. So I want to talk a little bit more about that.
Now, inside corporations there is an amazing hit rate of radical innovation coming to market, a whole 4%. Now, if you think that is low, I want you to consider for a moment that in the startup world less than 1% of all companies that receive initial funding generate some kind of meaningful returns, just by way of comparison. And the reason that corporations have such a difficult time with generating returns out of innovation spent comes down to soft skills.
To skills, to their culture and to the incentives that management puts in place to put behind innovation as opposed to behind day-to-day delivery of quarterly results. The nice thing is that all of these are learnable; it’s a question of where you go to learn them.
So the skills that we see corporates need to embrace in order to succeed are the following: that they have to understand what’s important to the startup ecosystem; that they have to learn something that we refer to as “entrepreneurial reasoning”; that probably, most importantly, they have to learn to learn efficiently. I’m sure many of you have been told that the key to innovation is learning to fail fast. Well, I think we can all agree that failing is no way to get your next promotion. But learning to experiment cheap – that’s a way to build a corporate capability. Learning to create business challenges around near-term challenges that your line of business owners have is another important skill. And then, finally, ultimately, as a large institution, your job is to deploy your resources against new products and new services that are going to generate a return. And if you look at how the ecosystem does this, it’s with a portfolio approach. So I’m going to go into each one of these in detail and this in particular is where I’d encourage any of you that have questions to go ahead and surface those to me.
So, often when a corporation realizes it wants to do something in digital transformation, it wants to do something in innovation, they’ll come to Silicon Valley, they’ll try and study what the large successful companies have done or, perhaps, they’ll send managers to innovation or entrepreneurship programs at universities. And what we contend is that those are not the right places to learn, nor are the traditional consulting firms, the McKinseys or the Boston Consulting Groups or the Accentures because they don’t have the key skills and methodologies that you need to use. When you look at the venture capital industry, which has been around for about 80 years, and you look at the ecosystem around venture capital and startups, what you’ll see is that it is an industry, in fact, that manages to generate outsized returns despite that less-than-1% success rate for any given startup. They, over 80 years, about 8 generations of the venture capital industry, have come up with disciplined practices that can be implemented by a corporation that can be perfected in order to generate those same outsized returns from innovation efforts.
So the first key thing to know – and this refers back to understanding the startup ecosystem – is that in a venture, funding always follows risk elimination. Now, many of you will now in the color bar in the middle here, you may have heard of these ideas of angel investing and pre-seed investing and seed investing in order to fund startups. What often – unless you are in the industry, unless you’re a startup or unless you’re a venture capitalist – you don’t recognize is that each phase of this investment comes with a different risk reward horizon and that each investor who operates in one of these segments has a business which is specialized to invest in that particular risk rewards horizon. Now, the bar above that talks about the way that startups are built from formation to validation to growth, one of the other things that folks don’t often recognize is that at each of these stages there are key performance indicators that help investors understand whether a startup is ready to go on to the next phase of investment.
As an example, when we, at 500, startups make investments at the pre-seed and seed stage, often the companies are pre-revenue, which means you don’t really know what their unit economics are but there are certain indicators about whether they’re ready for a seed round or not. We look at things like how frequently is the startup able to generate code, to add new features or refine features, based on customer feedback. If they only launch code once a month or once a quarter, the likelihood is that that startup will not be able to succeed relative to its competitors. If they’re launching multiple times a week in response to early user feedback, then whether or not they have it right the first time, the likelihood is they’re going to figure it out and they won’t burn through all their capital before doing so.
When you’re getting ready for a seed round, you might look to what we would call unit economics, so what’s the cost of acquiring a customer and then how much is it going to take, or how long will it take, to get a payback on that customer, and do you have statistical significance in that data. If I know that I can acquire a customer and get a return on that customer in only a couple of weeks, then as a venture capitalist, I’m willing to invest in that company because they stand a real chance of growing their user base and their revenue. If it takes 6 months for them to get a payback on a customer acquisition, then the likelihood is that they’ll die before they get any real revenue and, as a result, I’m not interested in investing.
Now, the other thing to note here – and this is going to come up for us later – is that in startups, each one of these phases often is about 12 to 18 months. If you think about your own internal procurement processes, often they’ll take more than 12 to 18 months, which means by the time you engage with a startup to learn from, they’re dead. Now, this is important because if you actually engage in learning from startups and you don’t create some way to engage with them faster than your traditional engagement process, you’ll never learn anything from them, you’ll kill them with kindness. So this is the other reason why it’s important to understand how the startup ecosystem works. If you are not able as a large institution to create, if you will, a gear shift between the operating speed of your own institution and startups, then you stand almost no change of being able to engage with great startups. And your competitors, who are able to create a fast track for engaging with startups, will get the benefit of learning from those companies. Any questions to this point? Any arguments? Nothing yet. Okay.
Nothing at the moment, Mike. I’m sure we’ll have some on the way, though.
I’ll come in with them. Yeah.
All right. The next skill is learning to promote entrepreneurial reasoning about the future in your managers, in your executives. Now, there is a woman professor at the University of Virginia, Darden School of Business who did some research in the 90s into what makes entrepreneurs entrepreneurial. Her name is Saras Sarasvathy. And what she found was that the key thing that makes the difference between an entrepreneur and a manager is how they think about the future.
Now, if you went to business school, if you’ve succeeded as a manager in a large organization, generally you engage in something that’s referred to as causal reasoning.
And you can sum that up in saying, “To the extent that we, as an organization, can predict the future, we can control it.” Now, the way that often plays out is some part of your organization will be responsible for doing market research to try and understand what customers are going to want in the future. And you’ll assemble some research or you’ll hire a firm to do it for you, you’ll drop that on the boardroom table or the executive table, they’ll be some discussion in debate and then they’ll be some budgeting and then you’ll go out and execute. The problem is that, in general, by the time you decide to go execute and have the budget to do it, the market’s already passed you by. You have to remember that the world will never change as slowly as it will at this very moment. And then at this very moment. And then at this very moment. So this way of trying to predict the future and then building an organization to go after that often will leave you behind.
Entrepreneurs, as a rule, think about the future a little bit differently. They say that, to the extent that they can control the future, they have no need to predict it. And I can sum this up for you by talking about Elon Musk, who runs Tesla and the boring company SpaceX and others. So you might not have ever thought of them this way, but ultimately Elon Musk is a real estate investor. He’s a real estate investor who doesn’t care about the price of real estate on Earth because he’s designed his businesses basically to help them own all the real estate on Mars. And even if he fails to get to Mars, he’ll still get to the Moon. So here’s someone who is controlling his future and has no need to predict it. And over and over again you can see that the best-performing entrepreneurs act in the same way.
So the point here is not that you need to change the way that you run a large organization because, ultimately, you do need to manage an organization. However, when it comes to looking at what your organization can do, what new businesses it can go into, what new capabilities it can build, you need to cultivate this effectual reasoning throughout the organization. And when you’re working on something in the future or for the future, you leverage effectual reasoning. Once you figure out where things are going, once you’ve proven a business case, then you want to manage that more closely to scale it.
Mike, can I interrupt you for a second? I’m with a question.
This, I think, speaks a little bit to your previous slide, the one previous to this one, on engagement with startups. Can you determine a budget for corporate VC financing? How do you do that? Is there a golden ration of some kind that organizations should look to? And then, once they do make that investment, what are the KPIs they need to be tracking to get the most out of that engagement with startups?
Yeah. So we’re going to come to this a little bit later, but I’ll give you, because it’ll probably take a little time to absorb.
That golden ration. MTI and others, I think there’s a good Harvard Business case study about this, basically say that any given corporation needs to invest somewhere between 10% and 20% of annual revenue in what is sometimes referred to as an innovation fund. That’s a lot of money, but when you’re trying to safeguard shareholder value in the future, you need to make sure you’re around in the future. Now, not all that money goes into venture investing. That is an overall spend on gearing yourself for a future that’s running faster and faster. That could be modernizing your old systems, get them to the Cloud and getting control of the data. It could be investing in proof of concepts. It could be investing in improving the skills and capabilities of your talent. And, of course, it can be direct investments in startups.
But overall a large organization needs to spend somewhere between 10% and 20% of their annual revenue in making sure that they’re ready for the future.
In terms of KPIs, it’s going to be a little different depending on how you distribute that capital, but often in early days of a large institution’s journey towards what we would sometimes call “innovation maturity”, you’re going to need kind of orthogonal measures. As an example, we often look for engagement by lines of business in innovation projects. The traditional line of business-owner, when you walk in their door and you say, “Look, I’ve got this great startup company and I think we can transform the way you do your business,” they’re going to say, “Yeah, not so interesting. I have to worry about my quarterly numbers.” If you’ve gotten good as an organization – and we’re going to go into this more in a minute – in beginning your path towards innovation maturity, then you will see that line of business-owners come to the folks that have innovative ideas and say, “Look, I could use help improving the way my business currently works.” If those requests from lines of business are beginning to scale, that’s a great indicator that everyone is looking not how to be forced into innovation but are attracted to the gains that innovation can bring to their existing business. So that’s a good one.
And that’s about taking a proactive approach, in that case.
Exactly, exactly. We could dive into others. If I take it up a level, the chart I used before, here is, at each stage, I said, that you use different metrics to determine whether you’ve hit statistical significance of taking a risk or a set of risks off the table. The same thing goes with the evolution of your organization. As you get better and better at innovation, you’re going to change the things that you measure. Now, that’s usually a very difficult thing for a large organization to wrap their arms around. Ultimately, the board wants to know that you’re hitting certain profitability or margin or growth metrics and that’s it. The problem is that innovative projects and innovative endeavors can’t be held to the same measures that you would use at a steady operational state. And so one of the biggest tricks for organizations is getting comfortable with the idea of, “For innovative stuff we’re going to change measures as those innovative projects mature. And then, once they get to a steady state, we’re able to use our traditional metrics.” There are metrics that can be used along the entire lifecycle, but they are going to change from, often, quarter to quarter. Did that address your question?
For sure. I think that’s a very good answer. We have one more question but perhaps, do you want to carry on and I’ll save it for a little bit later?
If it’s germane to the content that I just shared, you can go ahead and ask it now.
Well, it’s a venture capital question and, I think, on sort of measuring the quality of the engagement and the success. I suppose what you were saying about how the traditional measures don’t apply, that is true and even more true, I suppose, if a corporate is performing venture capital outside of its existing business.
So corporates as venture capitalists are kind of an interesting animal and they have to be very cautious in how they set up. And the reason why is that if you take the average corporation who, let’s say, sets up a $50 million fund to invest in startups, for a large organization $50 million is a commitment but it’s really not that big. Then, when you consider the liquidity path for startups, essentially that investment, even if it is wildly successful, a $3 million out of a $50 million fund invested into an early stage startup for maybe 10% of the company, that investment usually won’t get liquid for somewhere between 7 and 10 years.
And if it’s an awesome outcome, the $3 million might turn into $30 million. Not a bad return, but relative to the overall size of the organization, $30 million is not going to move the needle. And so often, when corporates set up their funds, they set them up not for the financial return but for the insights that they can gain by being involved in the startup ecosystem. And that’s fine. But given what startups, great startups, need in order to follow their path, often corporates – who are looking for strategic return more than financial return – are not playing by the same rules when they go to invest in the company, and that will often create what we call “adverse selection”. A startup who is given the option of taking money from a corporate or taking money from one of the top-tier VCs in the Valley will almost always select the VC. And it will be the startup that isn’t really that great, that isn’t going for world domination if you will, that would take money from the corporate. The empathy that the corporate can show to what the startup needs to do in order to get to scale is really what’s going to determine whether they’re able to participate in that deal or not.
So forgive me all for flipping around but if a corporate is interested in investing at this later series A, series B growth stage, then if the corporate cannot deliver a customer contract or some kind of distribution deal, some kind of commercial benefit in addition to the investment, then they’re just not that attractive relative to traditional venture capital funds. So the corporates need to learn to leverage their assets in ways that will make them attractive as part of the group that comes together to invest in the companies round after round. Does that address your question?
Yes. Yes, thank you, Mike.
Sure. Okay, so let’s get back to it. So this next thing that I want to address is about learning to learn efficiently. What you’re looking at right now is what we see as the traditional way that a corporation will go into the process of building a proof of concept to teach them something about how their organization works or whether they can generate a return. So let’s take artificial intelligence as an example. Someone inside the company says, “Hey, this artificial intelligence stuff, it’s going to take the way that our business works. We should investigate it.” And some manager then says, “Okay, you go off and you write us a plan for using artificial intelligence.” So that’s signified by the little gray dot, there’s in an investment – in this case, the resources – decision to go down this route. Then there’s a process of, “Well, how much money do we need? What kind of budget do you need in order to fully investigate this idea? Okay, now let’s go off and create an RFP to go get some vendors who will provide solutions that will let us investigate this AI stuff.” Then the company will go through a technology-purchasing process. Once that’s complete, they’ll finally engage in a POC. And then if, in fact, the POC proves interesting, an investment will be made to look at deploying that new capability. Now, in the average organization, this process takes 12 to 18 months an there are relatively few times where you make an investment decision. And, as a result, you’ll end up deploying, for argument’s sake, $3 million and 18 months before you know if the technology can add any value for you. Highly capital inefficient way. It’s a bureaucratically efficient way, but a highly capital inefficient way of testing new theories.
So what we often advise is that, good, when you’re talking about learning to learn, becoming a learning organization, it looks like this, where you start off by defining a business challenge or set of business challenges. You syndicate that opportunity out to the startup ecosystem and/or your own current vendors or internal resources in order to propose potential experiments to run that will prove or disprove whether the technology can impact the business challenge. And then you run an experiment and you run it in a particularly disciplined way. So rather than taking millions of dollars and many quarters to get to an answer, you’re generating many more answers in a much shorter period of time for much less money per experiment. And I’m going to take you through this process in detail. But, at a high level, what you’re ultimately trying to achieve is the ability to generate a lot more about your idea or how you think a technology can help you in a much shorter period of time for much less capital invested. This is the essence of how you become an effective learning organization.
So what I’m going to walk you through now is the model that we use at Upside Partners with our corporate clients for actualizing or for instrumenting the methodology that I just shared with you. The first piece is to describe your business challenge, and in a minute I’m going to take you through what that actually looks like. From a business challenge, you can write up what we refer to as an “innovation brief”, which usually is about half a page that can be syndicated out to the startup ecosystem to say, “We have this business challenge. We have $X in order to run an experiment around the business challenge. Propose to us what kind of process we can run, what kind of experiment we can run to prove whether or not your technology is useful for impacting our business challenge.”
The next step, once you have that innovation brief, is to go ahead and push it out to the startup ecosystem to drive interest amongst startups to help you solve your challenge. You’ll go through a selection process that really gives you an opportunity not to be, I’ll call it, an “innovation tourist” with the startups, but rather engage in a collaborative conversation about how their technology can impact your specific business challenge. When you go out and you want to mine startup’s brains about what they’re doing, you are not demonstrating what we would call startup empathy. They don’t want to talk to you. You’re a waste of they’re time. On the other hand, if you come in their door with a defined business challenge and a budget and a timeline, then you, at least, look like a qualified customer who is willing to discuss the framework of the challenge that you have and, thereby, provide some insight for that startup about what their product – whether it’s now or in the future – needs to do to solve not just your problem but others. So you avoid the problem of adverse selection.
Once you’re able to find some startups that may have some solutions for you, you run a PoC, a proof of concept, cycle in a particular disciplined way and between, or by doing that, what you are generating ahead of time is the business case for using that specific technology. And then you’re able to make the decision based on the data that you’ve generated of, “Should we become a customer of this company? Should we invest in this company? Should we acquire this company? Or do we just not have enough information yet and we want to go run some more experiments before we decide to scale it out?”
So let me dive into these in detail. This is what a properly formed business challenge works like or looks like. Now, we’ve had any number of clients – and I’m sure some of you have had this experience – where some senior executive walks through the door and says, “Hey, I’d like some of that AI stuff. We’ve got to get some of that AI stuff because our competitors are doing it and we don’t want to be left behind.” Typically, when I make that statement when I’m doing a live speaking event with this kind of stuff, I see lots of heads nodding. The problem is, when you frame the interest in artificial intelligence in that fashion, you are already at the beginning of that 18-month, very expensive cycle. You also run into the problem that if you walk in the door of some – in this example – Chief Lending Officer and you say, “Hey, we’ve got this AI stuff and it can make a big difference in your business,” that’s when you run into that problem where that Lending Officer says, “You know what? I don’t have time to think about that. I’ve got to hit my quarterly numbers.”
So what we advice is that you turn it on its head. You go out and you find the line of business-owner – in this case, a Chief Lending Officer – who has or is willing to discuss a challenge that they have that will impact, ideally, something in their next bonus period. So in this case, the problem is that the Chief Lending Officer wants to increase their lending volume and they’re able to say that, “Success would look like growing my loan production by a specific amount year over year without changing my underwriting standards.” It implies a timeline; in this case, year over year. So what you’ve done by framing a challenge in this way is, first of all, you’ve engaged the line of business-owner. And second of all, basically set up what an experiment with a startup would look like. “Can a startup impact my loan production without changing underwriting standards in a certain period of time? Now I have a small contained test with actual success criteria associated with it.”
What that allows you to do for any given business challenge is then create a key driver’s based view of the solutions that are out there in the market. So no longer are you beholden to a company that says, “We’re just AI or we’re lending solutions,” where you have to spend days or even weeks of trying to understand what that company does before you know if it can be useful. And instead, in a relatively short period of time, you can decide, “Well, if I’m trying to drive lending, is this going to help me with acquiring new customers? With cross-selling my existing customers? Or, in some fashion, approving a higher percentage of the loan request that I get?” You’re able to, essentially, create a market map of the startups that are out there and how you believe they can impact your business. And for any given startup, you can have a conversation in a very short period of time – and I’m going to talk through that in a moment – where you say, “All right. You’ve got that interesting technology. How will you impact my business? What experiment will we run to impact my business?”
Now, there’s a lot of ways to go out and find startups; I’m not going to get into all of them. By the way, this whole deck will be available to you after the call, so you can come back and look at these. Suffice it to say, you have a lot of options for how to engage the startup ecosystem. One really important thing, down there at the button, hackathons do not work for attracting interesting startups. They’re pretty good for getting your own internal people to think creatively about how to solve problems, but no startup worth its salt will come to your environment and do a bunch of work for you on spec unless there is some meaningful carrot there. And that usually means a business problem with a timeline and a budget that they can materially impact.
Now, generally speaking, you have to look pretty far and wide when you want to find startups to solve your problem. This is what a typical funnel looks like when we engage with our clients to find solutions. By syndicating out, if you will, that business challenge, you should get some stream of startups that are interested in helping you solve that problem. You’re going to have to have a conversation with about 30 of them where you’re indicating, “Here’s the problem that we have and here’s our timeline and yes, we are approaching this differently that many other corporations do.” Some number of the startups that you talk to will essentially apply to work with you on solving your problem and that is function of figuring out what do they have to bring to the table that other startups don’t. You’ll then shortlist the companies that really seem to have something useful. You’ll do interviews – and I’m going to describe how those are done in a moment – with several of them. And then, and only then, when you’ve whittled down the list to a couple of companies that you want to work with, you’ll engage in in-person meetings with those companies.
So the traditional process we see in corporates is you’ll often send out the equivalent of a scout who will take an hour meeting with a startup and then, if they think it’s interesting, they’ll bring that startup in for another hour meeting with several other people. You’ll then go back and you’ll think about it for a while and then maybe you’ll engage again and begin to frame what a proof of concept might look like or what an engagement with a startup might look like. So in that traditional process, you’ve spent anywhere between an hour and, call it, 10 hours of your management staff’s time getting to know a startup. You’ve obviously burnt a lot of your time and energy and, even worse, you’ve burned a lot of time and energy of the startup without them anything out of it. No learning, nothing but “Hey, we’re a big corporate and we’re interested in working with a startup.”
This process that I’ve lined out on screen, if you’re doing it properly, to get to the point of those 5 to 7 remote interviews, you’ve used basically only one person’s time to manage this funnel and then you’re able to execute those 5 to 7 interview in a single day. If you’ve done this correctly, for the startup, before they have that interview, before they have an opportunity to talk to real-decision makers about what they can do, they’ve spent less than half an hour. With that dynamic, you’re both saving yourself a lot of time and money and you’re presenting the startup with a value proposition of engaging with you that is much different and much more attractive than a lot of your competitors.
Now, when it comes time to have that interview, there’s a way to address it that is not typical for the way that a corporate buys, but is very typical for the way that venture capitalists invest. The framework that you see on screen – Team, Traction, Tech, Trends and Terms – is the way that most investors, they may not use this specific framework, but these are the principles that they look for in a company when they decide whether they want to invest the time and energy on due diligence to potentially make an investment in that company. And these change a little bit depending on the stage of the venture capitalist but, as you can imagine, I want to know that there’s a good team there, that it is appropriate for the time in the company’s life, that there are the right skills and experiences. That the company, given the stage I invest, has the right – term of art – “traction”, which means they have the metrics, whether it’s revenue metrics or cost of customer acquisition metrics that make them right time for our kind of investment. That they have some interesting technology or approach to the market. That they are following the investment trends or the market trends that I, as an investor, want to invest in. And can I make the investment at terms where I will potentially be able to get my return? As an example of terms, when we at 500 invest, our average investment is about $150 grand for about 6% of the company.
Now, if we have found that that same company previously raised about $150 grand for, call it, 50% of the company, then we know if we make our investment. First of all, we won’t get the price we want. And second of all, the cap table of that company will be so polluted that they’ll never be able to raise another round.
Okay, so when it comes time to talk to a startup, there is also a framework that a corporation can use to make the same kind of assessment in a very short period of time, typically 20 to 30 minutes. And what you are looking for is not, “Are we ready to deploy this company’s technology internally?” but rather, “Would this company be a good partner in running a short, focused experiment? Will we learn from them? Is it aligned with what we’re trying to learn? Can we scope the way that this technology would be implemented to be something small by its size? Can we agree on what hypothesis we might test? Have they done tests like these with other institutions before? Is the way that the technology works, is the way that the company works, does it map to the rest of our organization, the people that need to be around the table? And, frankly, do we like the team? Do we want to work with them? It’s going to be a short intensive experience and, basically, if we really don’t like these people, there’s probably another startup that we can work with where we do like the people and we will learn more from.”
Now, one client that we worked with, we ran them through this whole process, we brought them 7 companies to interview, to solve their problem – in this case, it was a fraud management problem – and we did these 20 minute interviews with the startups, our team facilitated them. And at the end of that, we asked those corporate executives, “What did you think? Who are your top 3?” Or, more accurately, we asked them, “Which of the 4 do you not want to work with?” And they said, “Well, here’s our favorites, but we need much more information. We need more data about how their technology works and what their investment looks like” and all of these things that you would need to know when you’re going through a purchasing process but you don’t necessarily need to find an experimental partner. And so we asked them what kind of information they wanted and then we went out and got it and then we reviewed it with them. And then we asked them again, “Which top three do you have?” And it turned out that it was the same top three. So what our corporate client learned was that you can, in fact, collapse the time and money spent on trying to find interesting partners to work with.
Once you select your top three, in our example, partners, you then want to frame an experiment to run together and you want to do it in a particular way that economizes on the time and energy that your organization has to put in to running the test. And this is where, if any of you have heard the term “lean startup” or “designed thinking”, this is where this comes in. Generally speaking, the right way to run a PoC is to first try and ascertain whether the target customers or end users are interested in what you have. This might be done through things like paper mockups, it might be done through what we call a “smoke-test website”, which is not a real working product but is indicative of the value propositions that the new product would offer, and you run these tests. Often, it’s difficult for corporates who are concerned about exposing their brand for a product that is not working yet or may never come to market.
Well, there’s an interesting way to partner with a startup where you can use the startup’s brand or set up an independent brand simply for the purpose of running the test. These tests might last anywhere from a couple of days to a month. When you finish those tests, what you need to look at is whether the customers cared. If they didn’t care, then kill the project. If they did care, move on to the next phase. Now, that idea of killing a project quickly sometimes is, again, very hard for the way that large organizations work but in this kind of disciplined framework, if you know what you’re trying to achieve is a certain experimental threshold and if you don’t achieve it you’re going to go do another experiment, all of a sudden, you have a disciplined methodology for returning the capital that you would have otherwise used to the next experiment.
In the next phase of one of these experiments, you’re going to essentially do the business modeling. You are going to figure out, “If we were to deploy this technology, what would we have to do to our systems? What new operational policies would we need or procedures would we need? And how much would all of that cost?” As an example, we had another client where we went through a customer validation process. Everyone liked the results, but when we looked at what would it take to deploy that solution, we realized that it would require hiring hundreds of new customer-call center people. Well, the economics of that just didn’t work out, so we killed the project and went on and looked for the next solution.
In the final phase, if you’re able to determine that end users would like this solution, whatever it is, if you can determine that there is a potential business model there, then and only then do you go and engage IT to help you understand what it would take to roll out. In most organizations, IT is the mot impacted organization. They’ve got the longest to-do list of anyone else in the organization, particularly when it comes to deploying new technology, obviously. So you don’t ever want to go take their time and energy for something when there’s no business case. When you know that there’s a business case and you can go to them and say, “Look! There’s this great business case. What would it take to roll this out?” then that’s a really great use of their time.
Once you finish this entire process, you can imagine that for an experiment that’s gone all the way through, just by the way that you’ve gone after it you’ve built all the elements that you need for a business case. When you are able to run these experiments at some scale, your organization ends up looking a little bit like this. Rather than running a few tests a year for a lot of money for each test, you’re able to run many tests a year for a little money per test and generate a whole lot more data about what you’re doing. When you’re investing in innovation capability to get your organization to the point of being able to do this, that’s when you can make significant investments in order to reduce the cost and time per test that you might execute with. So that could be, “We’re going to create a sandbox that has APIs of our technology.” “We’re going to get our people trained in product management techniques or in lean startup techniques.” “We might invest in getting our complaints and our legal teams to create a fast track for being able to get deals done with experimental partners in hours, not months.” These are basically the capabilities you want to build in order to do that. When it comes time to think about that big innovation fund that we talked about previously, this is what you’re deploying that against.
Now, finally, I want to talk about how you distribute that innovation fund against various projects. And there’s a theory of innovation that maybe some of you have heard that’s sometimes referred to as “the horizons of innovation”. It’s also referred to as “core, adjacent and transformational”. Core innovation is when you’re improving the operating metrics of an existing business or an existing product line, which is sold to an existing customer base. If I can bring down the cost of generating loans for prime home customers, then that improvement is going to essentially drop directly to my bottom line. An adjacent or horizon to innovation is about changing either the business model or the customer base, but not both. And then finally, a transformational innovation is where you are essentially changing both.
Now, to be judicious, it’s advised that you distribute your innovation fund against core, adjacent and transformational in the proportions about 70% for core, 20% for adjacent and 10% for transformational.
The reason you want to go after core is imagine when you go to those lines of business-owners to try and generate their challenges, to try and get them to engage in this process. If you are bringing them either adjacent or transformational, you’re not helping them with their day-to-day job. If you’re bringing them the opportunity to make improvements in the business that they have today, you’re helping them to get their bonus, you’re helping them to understand why innovation has to be part of their day-to-day job. And it’s in that context that you’re able to begin to spread the culture of innovation throughout your company: when innovation isn’t just some project done on the side, but rather done day-to-day around metrics that you have to hit next quarter or next year. As the organization begins to learn, it becomes more and more capable of doing projects in either the adjacent or the transformational realm. So you’re able to generate those internally as opposed to being stuck in a position where, for example, Wal-Mart needs to buy Jet.com for $3 billion, something we call an “unicorn hedge”, in order to get themselves into the future.
So I want to leave you with this thought that you don’t have to engage in getting your organization ready for the coming disruption, but your competitors are. And if you don’t do it, that’s where you’re going to be end up squashed. Okay. That’s all I’ve got. I’m happy to take questions.
Thank you, Mike. You say that’s all you’ve got but that was more than enough, I think, plenty to digest there. And we’ve gone a little bit over time. I haven’t seen any new questions come in but if I had to sum up, Mike – which is a tricky thing to do because you covered a lot of ground there – it seems like the methodology you are suggesting suggests that we need to move with speed for sure, but not just speed for speed’s sake, not in a reckless fashion but in a very surgical, highly – I supposed you could say – disciplined way. Is that a fair assessment?
Absolutely. That innovation isn’t magic; it’s skills that can be learned and perfected. And that comes through discipline.
Yeah. And I suppose that’s the key, isn’t it? It’s developing that discipline. What’s the reaction you get when you present this methodology to corporates? Because it really, I feel, does challenge the way they tend to engage with startups, the way they think about it. It seem to me that it’s about trying to get them to think of startups in a way which is a more equal partnership where the corporates don’t necessarily feel that they can just turn up and throw some money at a problem, but they really need to engage and really offer the startup something as well.
So generally speaking, the reception, I think, is positive. We often run into organizations that know they have to innovate. Maybe they’ve taken trips to the Valley, that kind of thing, and they end up saying, “Well, we know why we need to innovate, but we don’t know how to it. We don’t know how to bring these capabilities into our organization.” So when we demonstrate or we articulate this framework and that it can be something that is managed and perfected and improves the capabilities of their people, depending on the maturity level of the company, they really love this. If an organization is just getting started in innovation and they want to learn from the lessons of those that have come before them, they love this. If they have been investing for a few years and they are not seeing the results that they want, the returns that they want, and they don’t quite know why, they love this.
If they have just embarked on, they budgeted for spending some money on partnering with accelerator programs or they’ve made the investment to create some kind of lab environment or something like that, then they tend to be resistant to this idea because they’re so excited and they didn’t sell, internally, making that investment that they’ve just made on methodology like this.
So those folks are not good clients for us. The folks either who are at the beginning of their journey or who have been at it for a while and realize that they can improved their returns by trying something different, they love this.
And so, do you see that sometimes? Do you have to say sometimes to corporates that you wouldn’t–? They may not approach you, in the first place, if they already have their own innovation labs or R&D in place they’ve spent a lot of money on, they may think they know they have their own path to go for and therefore they won’t necessarily approach you, I suppose.
That or they approach us for something different, where they’ll want our help in scouting for startups using their old way of doing things. We – I’m wearing my 500 Startup hat – because we are most active FinTech investor in the world, we literally have a dozen banks or insurance firms from around the world approach us every week and say, “Can you introduce us to your startups?” And the answer first is, “Well, tell us about the problem that you want to solve and the budget that you’ve got associated with it’” And they say, “Well, we’re just investigating artificial intelligence in this field.” And we turn them away. We will not introduce them to our startups because, ultimately, they waste our startups time and probably even worse, they dilute their own brand in the startup ecosystem. So if we can’t make a match between a startup and a corporate, we won’t do it. And similarly, companies we’ll come to us and they’ll say, “Can you help us find startups?” And we say, “We don’t do that; we teach you how to be an effective partner to startups and how to build your own channel or approach to the market so you can find them efficiently.”
Sure. And so then, I suppose, the ultimate goal over time, then, is for these corporate entities to be able to work with you to learn the methodology, to become disciplined and, eventually, they can go out on their own and they’ll be able to do this regularly.”
Yes. And I will bring up the one self-serving sale fly, which also at the bottom has the link for the slides. That is exactly what we do. We advise, we have a programmatic way of training the companies how to implement this methodology. We provide support to them and coaching to them. And then we can help them, once they demonstrate that they have this capability, we can help them reach the startups that they want, we can help them setup their own corporate innovation, corporate funding programs for startups and things like that.
And, presumably, from the startup side, Mike, you’ve worked in startups yourself, obviously you have a lot of experience there and, presumably, part of this methodology is developed through having spoken to them and seeing what their needs are and sort of feeding that back to the corporate world.
Absolutely. And I think that’s what gives us the credibility to deliver a different way of thinking about this to corporates, that we are practitioners both on the startup side and on the venture investing side.
How big is the gap between the startups and the corporates? Do they understand each other at all? How big is this?
It varies. It varies widely, from comparing apples not to oranges but to the blenders or something like that through in cases where you have a company that has made some investments in their innovation disciplined. They’ve already ran through or ran into a lot of the problems that we see, whether it’s engaging lines of business or, “Why can’t we get startups to talk to us? Or, why do we get edged out of deals?” In that case, often, some folks inside of the corporate have, again, we referred to it as “startup empathy”, but they need a way to convince the rest of the organization as well.
And for a corporate that wants to gain some of that startup empathy, is it answer, for example, trying to recruit people who have worked in startups?
Certainly that’s part of it. It’s not always the easiest thing to do, to get the great entrepreneurs to come and work for you, but that is one strategy that you should use. Overall, we believe that the corporates themselves need to transform their culture. They need to build these capabilities. Certainly, their higher indiscipline is part and parcel of that.
Indeed. Well, thanks so much, Mike. I think it’s been really educational and, as viewers can see there, we’ve got your contact details and how they can access the slides. If they want to carry on this conversation, then there are ways to do that. But I think for today that’s probably where we’ll wrap things up. So, Mike, thanks again very much for joining us today.
My pleasure. And thank you to all the viewers for sharing part of their day with us.
Indeed. It’s been a pleasure. I’ve been Rahim Rahemtulla here at SVIC. We’ve been joined today by Mike Sigal. And I want to say, if you did enjoy Mike’s talk, if you are interested in the ideas that he talked about today, if you’d like to take it further, he’s got his contact details there. And I’d also encourage you to have a look at our page, Silicon Valley Innovation Center. We run a program called Navigating FinTech Disruption that touches many of the ideas that Mike has raised today as well. So our next program is in November 5th to 9th and you can find the details on our website siliconvalley.center. And I think that’s where we’ll wrap up, so thanks all again for joining us. From me and from my guest today, Mike Sigal, until next time. Goodbye.