To view the original post, please click here. For Eric Benhamou’s interview for U First Capital’s Enterprise Summit, please continue below.
Introduction
Ahead of the U First Enterprise Summit & Startup Pitch Session, we had the opportunity to sit down with Eric Benhamou, ex-CEO of 3Com & Palm, and Founder & General Partner of BGV. Benhamou gave us an overview of BGV’s investment strategy for 2020, and highlighted the firm’s focus on the emerging Enterprise 4.0 space. He describes how the first three phases of Enterprise IT laid down the infrastructure required to generate massive amounts of new data, on a scale inconceivable just a few years ago. Startups that can extract tangible insights from this data, and offer businesses complete, full-stack solutions, are poised to lead a sweeping digital transformation, he argues. Enterprise 4.0 is upon us, Benhamou posits, and it will fundamentally alter the way businesses, and entire lines of industry, behave and generate value.
See the full interview below.
Thank you, Eric, for taking the time to sit with us. Before we dive-in to Enterprise 4.0, and BGV’s domain focus, please share with us what expertise, values or characteristics set BGV apart from other funds in the space. How would you characterize BGV’s investment approach?
The partners at BGV, unlike at most firms, are all entrepreneurs and operators with deep, direct experience launching and scaling businesses. We have a visceral sense of what it’s like to get a company started and boot-strapped. So our investment style is very active, and we expect to have a close day-to-day working relationship with our founders. Our portfolio is more concentrated, because we can’t afford to adopt this approach with a very large portfolio, but we can do it with a portfolio of around 15-20 companies. We have nine members on our investment team, so this is a load that is manageable for us.
Company building is a skill that is borne out of direct experience. For us, it’s not a theoretical skill that we’ve modeled or studied, it’s a practical skill that we’ve lived. So we understand, intimately, that early stage investing is a risky endeavor. Most companies, even the ones that become very successful, go through very difficult patches, and many face the prospects of death. This is something that is an integral part of the startup experience. Therefore, it pays to have investors who understand the process, and understand the cycles. They don’t panic when there are challenges; instead they draw upon the processes that have proven to work, to overcome these challenges. Not every investor likes to do this, and not every investor has the skill set to do this, but this is very much built into the cultural DNA of our firm at BGV.
At U First Capital, we’re very active in working with corporate funds, and later stage funds, as well as bridging the gaps with earlier funds, like yours. Where does BGV overlap, and where does it differ, from corporate funds? And how do you work together?
Many funds operate downstream from BGV. They’re typically growth funds that need to have access to companies that we’ve nurtured and grown at the early stage. These are funds that typically invest in companies that have achieved product market fit, and some measure of repeatability in the sales motion. We welcome the opportunity to work with those funds. They add a different kind of value — mostly capital and operational processes downstream — they don’t necessarily offer value in strategy, or in product market fit; but they help scale the company to a point of exit, or profitability or IPO.
Early-stage company building expertise is very different from late-stage asset deployment expertise. I would say that less than 10% of venture firms in the US have the sort of approach and skill-set that BGV has. Not only is it valuable when you capture ownership in companies at the early stage — you end up riding the value creation curve for much longer, and capturing the value created along the way. In our case, we happen to enjoy the intensity of the experience that’s required for these partnerships with our founders. At later stages a different kind of evaluation and decision-making is required. So, naturally, each stage investor brings a different perspective to the innovation landscape. But it’s very much a symbiotic relationship.
Let’s talk Enterprise. Please tell me a bit about the cultural roots of your fund? What space does BGV play in, and what domain experience do you bring?
BGV is an enterprise-focused early-stage fund. The entire team has deep roots in Enterprise IT, and this dates back to the very first phase of Enterprise IT deployments, to the time of mainframes and terminals, when the only places that had computers were universities and government agencies. This was the very first phase of Enterprise IT. This was even before the Internet was known to the world. It existed as a government project called the ARPA-net. This is where our careers began, for the partners of BGV.
Can you give us some background of how we’ve progressed from Enterprise 1.0 up until what you call Enterprise 4.0?
Enterprise 1.0 is the phase I just described, with mainframes and terminals, before the World Wide Web had emerged. This was the birth of Silicon Valley. We moved from Enterprise 1.0 to 2.0 when laptops and PC’s arrived on the scene, and they became connected to servers. Enterprise applications started to get distributed across client-server computing structures. This was the phase that put 3Com on the map. We laid down this connectivity infrastructure and drove that Enterprise 2.0 phase. We connected all these computers, and these servers. We helped power client-server computing in the 80s and 90s, and we stood at the forefront of that wave.
In the mid-90s, the Internet became well known to the public thanks to the invention of the browser, and thanks to a company called Netscape, that popularized the Netscape browser, and made it possible for retailers to offer web stores. Broadly known as the dot.com boom, e-commerce businesses emerged across the US. This is what put Amazon on the map in the late 90s, and fueled disruptions in the retail industry that we’re still very much feeling today.
This brings us to Enterprise 3.0. The introduction of smartphones changed the game. With Palm, we were also very involved in driving the early stages of that wave. The Internet, the browsing, the mobility, and eventually, the cloud, all constituted key components of Enterprise 3.0, which saw innovation move from desktop applications to mobile and cloud-based applications. The focus on Data & APIs opened up Enterprise IT to a much broader cross section of industries: financial services, in particular, saw incredible changes; education was transformed thanks to the Web; and obviously the retail industry, which has seen total disruption.
But it’s not until Enterprise 4.0 that the digital transformation became totally pervasive across all sectors. This last transition from 3.0 to 4.0 is very recent, and has become the central focus of the firm.
So how is Enterprise 4.0 different? Can you highlight a few key differentiators or key attributes?
In recent years we’ve been able to deploy sensors — very low cost sensors — everywhere: on our bodies, on vehicles, inside vehicles, in our homes, in factories, and really across the planet. We use these sensors to monitor temperature, humidity, chemical composition, movements, and so on and so forth. This has given us access to immense amounts of data — data which did not exist as recently as five years ago.
In combination with this we’ve made incredible progress in the development of Artificial Intelligence through the development of Machine Learning algorithms. This combination of machine learning algorithms and these vast amounts of new data, has made it possible for relatively small companies to extract insights from this data, to create value from these insights, and to transform lines of business and entire industries. This general description is what we mean by Enterprise 4.0.
These young companies create complete solutions, as opposed to horizontal layers of technology, and these solutions can be sold to lines of business, as opposed to a central IT organization. As a result, the deployment of these solutions is faster, and more decentralized, and costs less to evangelize, sell and deploy than previous generations of IT. That’s a very good fit for what Venture Capitalists like to fund.
Enterprise 4.0 is the central focus of BGV today, certainly for this fund, but probably for the next several funds to come. We think this is the beginning of a broad sweeping wave of transformation that will affect every single industry.
What do these companies look like in the wild? Are there any portfolio companies you can give us that showcase the attributes of the Enterprise 4.0 startup you’ve described? And which industries are these companies seeking to disrupt?
I’ll give you three examples. Two are portfolio companies, and the third is one we looked at closely, but did not end up investing in.
Drishti was born as a spinoff of the Stanford Research Institute (SRI), one of the top research institutes in the world. They are using advanced machine vision techniques and AI to watch manufacturing lines and interpret what each station and sub-station does. From this analysis, they can then extrapolate meaningful insights for the manufacturing line, for efficiency, and for quality management.
To appreciate the significance, you have to understand how manufacturing works. Most people today believe manufacturing is completely automated and that things are built primarily by robots. The reality is quite different. Certainly, there are robots, but 90% of the tasks remain manual. So manufacturing lines are primarily populated with people, not robots. Whenever you have people making gestures to manufacture things — to assemble things, to put components on boards, to move boards around, etc — you’re following manual processes which are subject to variations, like everything manual. Machine vision technology has been introduced to observe and decode these processes, and Drishti can then generate a baseline of what a well functioning manufacturing line looks like. By observing every single widget being built, they can see any deviation at any point, at any station, or sub-station, and that deviation is recorded so the plant manager, the line manager, or the supervisor, can see if there are variations to the process that could lead to yield issues or quality issues. This is done in a very detailed and analytical way, to the point where every single widget — be it a smart phone, an appliance for a kitchen, anything that’s being manufactured — can come with a full compilation of gestures required to build that widget. Then, to the extent to which you have underlying issues with the building of that widget, it can be traced to a specific step missing, or to a step not being done according to specification.
This kind of company would not have been possible to create five years ago, as there would not have been enough cameras, or smart cameras, available to decode these steps. And Machine Learning technology was just not advanced enough to be able to learn from all of these steps and this accumulation of data. So Drishti is an example of an Enterprise 4.0 company that is transforming the science and analytics of manufacturing.
For the second example, we just recently made an investment in a waste management company, Everest, that is transforming the waste management industry. The way waste is being processed today is the same as it was done 50 years ago. Big trucks haul large garbage bins collected from cities and factories. They bring these bins to a recycling center. The bins are emptied on a big rolling belt where it is sorted and separated by human operators. So picture a very large belt — like a gigantic treadmill rolling at 30 feet per second — and alongside this belt are three or four manual operators, each wearing a mask and gloves, and each one of them picks up the pieces of waste that appear on the belt that can be recycled. It could be a smashed coke can, a plastic bottle, or a piece of cardboard. The human operators then turn and dump these items into recycling bins next to them, all while more items are coming at them. This is not only mind-numbing work, it is dangerous work. It is very hard for an operator to be concentrated for eight hours a day doing this task. But that’s the state of waste management today.
Everest has deployed a complete solution that puts smart cameras above the belts — similar to the cameras that monitor freeways to evaluate traffic patterns and congestion. You have a bridge, equipped with cameras, running over the treadmill with the waste, that is watching all the objects passing through. The Everest software analyzes these objects, and after a few hours of training it knows how to identify a coke can, a piece of cardboard or a plastic bottle. Alongside the belt, instead of having human operators, imagine two or three robots on each side with grippers or suction arms. These robots receive instructions from the cameras that have identified the objects, and they know where to pick up the objects and where to dump them in a bin for recycling.
This solution is far more efficient, more cost effective and more yield-effective. Robots don’t miss objects. They don’t get tired. They can work 24 hours a day. They don’t go on strike. So, clearly, a transformative impact on the waste management industry. And it makes even more sense today when you think about how much more waste we generate as a society compared to 10 or 20 years ago, and how much more environmentally aware we are today compared to a generation ago. This is a company that goes along with the macro-trends that drive the economy and society as a whole and takes advantage of the technologies that were not even available five years ago. It’s a typical Enterprise 4.0 company.
The third example, is cardiologss, a French company (the other two were Indian cross-border companies). We didn’t invest in cardiologs, in the end, but we took a very close look, and we were very impressed. cardiologs focuses on heart patients who had a heart incident. Usually when you have a heart incident you call an ambulance. You call 9-11 and medical technicians are dispatched to your home, or wherever you’ve had the accident, and they use a device called a halter device to help with the diagnosis. Halter devices have probes that are put around your chest to pickup heart signals. These signals are complex to read, and it takes a trained technician 15-20 minutes to completely read and decode a halter signal pack. What cardiologs does is replace the human interpretation with a computer interpretation of the signal with an immediate diagnosis. So, not only does it save cost — the cost of having a trained technician dispatched on site — but it reduces the time it takes to get an accurate diagnosis, and increases the chances for the patient to get the immediate treatment they need to survive the incident. So, this is likely going to be a much more popular approach when you think about how these signals will become readily available from the wearables we have. It doesn’t take a halter device to capture these signals. Within a few years there’ll be tens if not hundreds of millions of people around the planet who will wear biosensors, perhaps embedded in their watch, or otherwise. They’ll pick up these signals and send them, probably, to a cloud service. So, that technology that cardiologs invented will be usable at scale, to basically interpret signals across a very large population and provide preventive diagnosis of impending heart incidents. This is yet another industry that is being disrupted by an enterprise 4.0 company.
All of the examples you’ve given are companies that launched abroad. Is BGV focused on startups in foreign markets by happenstance, or does this fit into a deliberate investment thesis?
That’s a good point, and that’s something that’s really quite special to BGV. We are, above all, focused on cross-border opportunities. Although we are primarily anchored in Silicon Valley, we don’t believe this is an appropriate place to start businesses today because it is too expensive, too congested, and too competitive. Yet, at the same time, Silicon Valley is not a place you can avoid if you’re serious about building an Enterprise 4.0 company. The only way to square this circle is to grow this new generation of companies in places where you have access to talent, and, simultaneously, to establish early roots in Silicon Valley, so you can develop a cross-border company along the way.
One thing we’ve observed over the last few years is that company creation has become a lot more democratized, and a lot more decentralized. In markets outside of Silicon Valley there’s simply less competition for the kind of talent these companies require.
This creates an ideal combination of cross-border funds, like BGV, with cross-border companies, like the ones I discussed. These companies typically have a talent advantage by virtue of where the founders come from, and their own relationships — they could, for example, come from Israel, India, France, or elsewhere in the world, where they have access to computer scientists, data scientists, even hardware engineers or semi-conductor engineers, who can build products at a fraction of the cost, and who exhibit much higher degrees of loyalty to their employer, than the ones you recruit in Silicon Valley.
At the same time, having a foothold, and being immersed in the Silicon Valley ecosystem is essential, because this is where business relationships get forged, where business development activities must focus, and this is where all the big actors in the industry are concentrated.
The art, and difficulty, is to create these cross-border structures while keeping the companies as single companies. In other words, it’s one thing for a large company to have offices in different parts of the world. It’s much more challenging for a small, tight, nimble team to operate as a single company if its key talent and resources are spread out around the world. Thankfully, today, it’s possible to do that because of the ease of communication, the ease of travel, the exchange of data and team building across long distances. So those are the kinds of companies we like to focus on, and to fund. Close to three quarters of our deal flow fits the model I just described, and most likely, three quarters of our portfolio will mirror that as well.
Hopefully we’ll have some companies at our pitch session that fit this profile. That’s all the time we have for now, but we’ll look forward to continuing the discussion at our Enterprise Summit, and we hope to glean further insights from you there. Thank you again for your time.
