In this inaugural edition of our interview series focused on digital transformation within the debt world, we speak with Eric Ball, Founder and General Partner of Impact Venture Capital, a venture firm based in Silicon Valley. Impact Venture Capital invests in early-stage AI startups, often coinvesting with the venture arms of major tech corporates. Some of those investments are in fintech, including a few aiming to transform the capital markets, including CapConnect+, BondCliq, and 280first. Prior to starting Impact Venture Capital, Eric served in senior roles in corporate finance, including as SVP and Treasurer at Oracle, where he spearheaded the issuance of more than $50 billion in bonds. He holds a PhD in finance from the Drucker-Ito School of Management and has taught at four universities. Eric has also authored books on management aimed at a general audience. He currently serves on the boards of voice AI unicorn SoundHound, several private portfolio company boards, and on two nonprofit boards (the National Association for Urban Debate Leagues and the Lucas Medical Foundation). In this interview, we discuss transformation within both the CFO suite and the debt markets, as well as his efforts to bridge the worlds of academia and finance. We also touch upon the emergence of generative artificial intelligence and recent research he has conducted into implicit bias in venture funding.

Bridging the worlds of academia and business

Good afternoon, Eric - and thank you for joining us.

You’ve written two books. The first is a non-fiction work: Unlocking the Ivory Tower - How Management Research Can Transform Your Business.

The second - Silicon Galaxy - a novel published last year – folds a primer on business management into the narrative.

Can you tell us how these books came to be?

Thank you. Well, I started my career as an academic. I did all the course work toward a PhD in economics at the University of Rochester and then left for the corporate world. However, I felt I had unfinished business, and many years later I found a part-time PhD program studying under Peter Drucker and completed a PhD in management.

During this time, I had one foot in the academic world and another slowly climbing the corporate ladder at big corporates. And I realized that although academic economists and researchers produce a lot of material that isn't relevant to the day-to-day work of business executives, there's a significant subset that is relevant and that sometimes gets lost in the noise.

For the first book, I applied a filter to all the literature I’d been exposed to as an academic and tried to identify the 10% that would be most useful to business people, including those who may think that the ivory tower doesn't understand the nitty-gritty of their day-to-day work demands.

I wanted to uncover and highlight answers to questions like, what motivates employees? What makes effective leaders? Just core questions that have to be addressed in any organizational context.

That first book distilled the work of important thinkers down to a few brief pages each. In one volume, the reader can absorb the conclusions from dozens of essential books and articles on business management.

Although the book was well-reviewed, it didn't sell particularly well. And what my co-author and I took away from that was that by just giving the conclusions, we had perhaps stripped out the interesting parts. People remember things in context; when they're fleshed-out and embedded in a narrative. There's a reason that some of these authors took 300 pages to make a point that could otherwise be summarized in a page. At the time, I didn't know if I would write another book, but I resolved that if I did, I would try to make it more engaging.

That first book was published in 2012. Fast forward to COVID and we're all in lockdown. I decided I wanted something productive to come out of my quarantine. And I said, what if I took some of that same material that I had summarized - management research on how to be an entrepreneur and how to run a business - and embedded in it in a more entertaining context?

And so I came up with the most ridiculous scenario I could, which is that aliens from outer space land on Sand Hill Road in Silicon Valley and kidnap a young venture capitalist. The aliens offer up all these advanced technologies to humanity, including a cure for cancer, flying cars, and other great stuff. But they say: “We're not going to give it to you - we're going to sell it to you. And so you need to help us figure out how to form startup companies that are going to bring humanity these advanced technologies.”

It's kind of a silly premise, but it was a way that I could teach readers about entrepreneurship through a hopefully entertaining story involving a VC that teaches a band of aliens the very same lessons.

The aliens in Silicon Galaxy choose to launch their companies in the Bay Area for a number of good reasons outlined in the narrative. I don’t feel it would be incorrect to assume you maintain a broad belief in Silicon Valley’s ability to shepherd through innovation. At the same time, the book is not without a few critiques of the tech ecosystem there.

Well, that reflects that there is much to praise and criticize in the Valley. I live here and I love being near a bunch of bright people with ambition. On the other hand, sometimes Silicon Valley may need to get over itself; the pretension and bias and herd behavior can make it an easy place to mock. Still, I love it here and don't plan to live anywhere else.

If much of academic research isn’t terribly practical, can you describe the types of research you find most helpful or illuminating?

Well, let me use an example to try and answer that. There's a whole literature around leadership that gets circulated in business schools and I'm critical of some of that research because you could tell stories about one leader and stories about another leader - and derive opposing conclusions from each set of stories. And then you’re left with the question of which principles to apply in which context.

I try to describe some academic work where instead of theorizing about what makes a great leader, researchers actually sat down and observed leaders. For instance, there was some research done in the 1970s where a researcher sat in CEO offices with a stopwatch and determined that the a CEO went an average of a few minutes between interruptions. And yet the CEO is responsible for strategic planning. Now, how do you think strategically when you can't go five minutes without an interruption? That kind of research can be illuminating and yet I don’t think many managers appreciate it.

Digital transformation of the CFO suite

Relative to other parts of the enterprise, finance has historically been underequipped with custom technology tools. However, that’s starting to change with more targeted solutions for the CFO suite now coming to market. With better technology at their disposal, how do you see the role of the CFO - or the CFO suite more generally, including the treasurer and controller – evolving in the coming years?

I'd say at the core - finance organizations can spend less time collecting data and more time interpreting it. At the start of my career, I worked in five mega-sized corporations in finance and a lot of my time was spent in Treasury. And in Treasury, a lot of the labor hours were devoted to just trying to figure out what the exposures and risks were.

At one point I managed foreign exchange hedging. It's actually quite simple to hedge a foreign exchange exposure. What's hard is figuring out what your exposure is - and most people in that job spent over 90% percent of their time on that. There are many jobs like that that are somewhat clerical in nature. But if technology can collect data then your labor force can do more actual thinking and analysis.

With some of these technologies, you can simultaneously reduce headcount and make your organization more effective.

Can you point to a few of these tools?

Well, there's been an explosion of tools, actually.

There have been a couple of tools to automate the financial planning and analysis function. This used to consist of employees populating spreadsheets with backwards-looking data, and then go to each business unit to collaborate on projecting future metrics, and then work to synthesize these projections into a unified total. The result would be a budget and series of stretch goals internally and more achievable guidance for investors externally. It was labor-intensive and time-consuming but thankfully there are a lot of tools now that have made the numbers assembly part of that easier. One such firm is Adaptive Insights (which was acquired by Workday), another is Anaplan, as well as offerings from some of the big tech ERP providers.

I was at Oracle, which created ERP software that automated a lot of elements of the accounting function. There are also several newer startups that are automating the internal audit function.

In the past couple of years, I’ve seen a high number of startups whose customers are treasurers within the finance organization. I appreciate the chance to look at companies where my own experience may provide useful context.  I'm tracking at least ten treasury-oriented startups right now.

And so the whole office of the CFO is in the middle of an automation revolution that's using machine learning, big data, and AI. I think that's going to continue, and I think it's going to allow the percentage of revenue accounted for by general and administrative expenses to go down while the impact of the finance function goes up. It's an exciting time for finance.

When you see this impact going up, to the extent that power or responsibility is a zero-sum game, do you see other parts of the enterprise experiencing an attrition in those areas relative to finance?

It's hard to generalize because different job functions become relatively more powerful at different times and in different sectors. I think that in the 1950s and 1960s, there was a lot of manufacturing innovation and so the physical engineers had a clear path to power in a company. And then in the 1980s, there was a lot of financial engineering and leveraged buyouts, where the finance function became a bit more relevant. And I’ve seen in industries facing regulatory and legal issues where the general counsel has become CEO.

I think that in the tech sector over the last few decades, software engineering has been a good skill to have to rise to the top of the corporate hierarchy. However, I think that the new tools we just discussed are helping finance reclaim some of that ground. You now more frequently see CEOs who were previously CFOs as opposed to some other function. So CFOs appear to be a bit ascendant in terms of their relative power. In tech, I think engineering and product are still important but not as dominant as in the past.

Reforming credit markets

As SVP for Finance and Treasurer at Oracle, you raised over $52 billion in bonds to fund over a hundred acquisitions. Can you tell us how bond issuance evolved at Oracle and the tech industry overall?

Oracle was the first major tech company to issue a significant amount of debt, which we executed as a $6 billion bond issuance in early 2006. The accepted wisdom before that had been that tech is inherently risky and so you need a more conservative financial profile to compensate for a riskier business profile. I give a lot of credit to the senior team at Oracle for realizing that this was an artificial distinction relative to non-tech businesses, that tech could use debt as a tool as well.

The tax structure of the time made it hard to repatriate cash earned overseas. Oracle had tens of billions of dollars stuck overseas where it could be brought back into the US, but only at a punitive tax rate. It was more efficient to leave it overseas. And by issuing debt you could borrow in the US in a way that you'd still be net cash positive.

We were the first big bond issuance in tech, and immediately thereafter, Cisco followed suit, and then others, it became a new trend. And now it's the norm, and gotten much bigger. There was a brief moment where a banker said I had participated in raising more capital than anyone in tech. But that record was quickly broken as other firms had mega issuances and so it is no longer remotely true, even at Oracle, which has raised more debt since I left than when I was there.

Can you tell us about some of the specific pain points you experienced during the process of issuing debt at Oracle? And have things improved since then?

I think a surprising element of the bond issuance process then and even now is that it hasn't changed a lot in the past few decades. You have a debt capital markets desk consisting of bankers who work the phones and call institutional bond buyers and ask them for their orders, and then inevitably the books get oversubscribed. They then cut back the orders.

It's historically been a very manual process. And it is a lucrative business, with bankers historically charging a shared set rate, perhaps ⅓ of a percent to ¾ of a percent depending on the term of the bonds. So a $10 billion bond issuance might generate $50 million in bank fees. Some larger corporates have been successful at negotiating lower fees, but it remains a high margin business.

More importantly, the bond issuance process has not historically generated the true price discovery of an auction. On average, bond spreads tighten after issuance, which suggests that corporates end up paying a higher interest rate (that is, a wider spread over the treasury rate) than they have to.

Jeff Bezos famously remarked “Your margin is my opportunity”. I don’t believe Amazon has tried to disrupt the capital markets yet. Have others tried?

Well, as a venture investor - instead of simply reacting to entrepreneurs who come to me and say, “Please invest in my business”, the team at Impact Venture Capital (including my business partner Jack Crawford) and I engaged in an exercise where we said: “What business should exist, but doesn't?”

And a true auction platform for debt issuance was one answer that we came up with.

So I played a role as a co-founder of a startup - CapConnect+ - that does exactly that. The management team there - led by Suresh Perera - partners with bond issuers and banks to make the bond issuance process more efficient. The goal is for the corporate to be more of the customer and less of the product in a way that can save issuers on debt expense and provide a fairer and more transparent allocation to institutional bond investors.

In addition to issuance, bonds have also been somewhat laggard when it comes to trading mechanics. Trading for stocks, options, and futures have evolved at a rapid rate in the direction of transparency and speed over the last 30 years. Has there been any movement here for bonds?

Well, another one of our portfolio companies is BondCliQ, which was founded by some Goldman Sachs alumni, led by CEO Chris White. He and his co-founders had the observation that bond pricing for secondary trading in bonds is intentionally inefficient.

If you want to buy a share of IBM stock, you can go on Yahoo and see in almost real-time what a share traded for five seconds ago, right? But if you want to buy an IBM bond - you have to go to a broker who gives you a bid-ask spread and it's based on yesterday's data. If you buy a bond, you don't know if you got a good price or a bad price. And this is how stocks were traded too until 1968.

Stocks have since moved towards a more transparent system. But that hasn’t occurred yet with bonds. So BondCliQ is trying to bring pricing transparency to secondary trading in corporate bonds and eliminate another source of friction in a market that's measured in the trillions.

Investment approach at the Impact Venture Capital

Impact Venture Capital is noted for the way you work with established companies on co-investments. I’d like to talk a bit about that. Money is fungible – so why does it matter that the money is coming from an established tech company – and not, let’s say - Abe Froman, Sausage King of Chicago? What do the start-ups gain that they might not obtain from other investors? And on the other side of the table, how do the established companies benefit?

I love the Ferris Bueller reference. That's a classic film.

We're trying to invest in young companies that have either already caught the attention of a major corporate or that we think would catch the attention of a major corporate once we point it out.

Having the corporates as a co-investor validates that it does overlap with the technology interests of the big corporates. Critically, these are the same big corporates that often act as acquirers. So, as a start-up, when you’re looking for an exit, it gives you a leg up.

We talk a lot to corporates to try to understand what technologies they're seeking access to and to help make them aware of young startups that are bringing those technologies to market.

Corporates used to look for innovation from internal R&D and through M&A. And they finally figured out that there's a third leg in that stool, which is investing in startups, which is way more capital efficient. The corporate does not have to buy all of the company to get access to the technology. If you can buy say 10% of the company at a low valuation early, you can earn a large financial return and also engage with a much higher number of startups with new technologies.

Diversity, equality and inclusion in venture funding

You conceived and helped co-author a report on diversity, equity, and inclusion, or DEI. Can you describe the findings of your research?

I was basically revisiting my former life as an academic. And I was looking at this data that suggests that 40% of entrepreneurs are women. But over the last several decades women have received considerably less than 10% of venture-backed funding - depending on the study, it's anywhere from 2 to 8 percent. So women represent 4 out of 10 entrepreneurs, but they're getting a single digit fraction of the investment dollars - and that's a mismatch.

At the same time, older entrepreneurs are experiencing a similar dynamic where a lot of the venture capital has gone disproportionately to younger entrepreneurs, despite the fact that the median age of founding CEOs has been going up dramatically. And there's some research that shows that you actually learn things over time. You don't just get tired and old; you may have actually learned something useful to help a startup succeed.

So I wanted to look at the data in terms of the performance of CEOs of different gender, age, and race and ask: “Is there a difference in performance? Could there conceivably be some rational reason for this bias? Are young, white male, twenty-something dropouts really better?” I don't think so, but let's look at the data and see. So we looked at the data and we essentially found no real difference between men and women or between younger and older entrepreneurs, except that women CEOs on average tend to have shorter times to exit than male CEOs. So on that parameter, women seem to be - not just as good - but perhaps better than men.

Interestingly, we tried to look at race. But there are so few entrepreneurs of color receiving funding that we couldn't even generate a data set - which tells you maybe all you need to know about that bias. The rest of the researchers are now trying to gather a bigger data set to capture more entrepreneurs of color. But this particular project had to set that aside and focus on gender and age.

Going through your portfolio companies, I saw the founder of one of your companies who appears to be past a typical retirement age and it struck me how rare that is.

And he heads up Cornami - our single best performing company. The founder there has CEO experience since 1981. And we invested in him and the company in 2016 when it was young. Last year SoftBank led an investment round there with a valuation several times higher, so we are expecting a pretty good return on that.

Generative AI and wrap-up

Through Impact Venture Capital's investments, your board appointments, and other activities, you have to stay on top of developments in AI, the mechanics of bond issuance, FAA regulations on personal aircraft, academic management research, blockchains, and quantum cryptography, among other topics. What’s a new field or topic that you’re currently trying to get up to speed on?

I would like to learn more about a topic that’s top of mind for a lot of people: Generative AI.

The AI up to now has been really good at predictive AI. To take one example, you might put sensors on physical structures and use AI to do predictive maintenance after the AI has been trained using images and past data on imperfections. So, instead of inspecting a building once a year, you put sensors all over a plant and inspect first the ones that show troubling data rather than the ones coming up on the one-year mark. So predictive AI has made progress.

But lately we have this explosion in generative AI. This AI tends to draw upon a much broader, more disparate array of sources. So a management tool wouldn’t just grab information out of the accounting system, but maybe also from the R&D team’s work notes as well as emails between the CEO and the head of marketing. In short, it would canvass a larger space to gather data and come up with insights that may not be based on numerical indicators or regressions, but also on other associations. It doesn’t appear infallible, it just reflects the information available, so if the tool canvasses discussions with inaccuracies, it can repeat those inaccuracies. But it can also be a tremendous time-saving tool.

I am not an expert in generative AI and I would like to learn more quickly.

Generative AI.

You invest in some bleeding-edge, space age technologies. You also have two adolescent/young adult children. Do you ever go to them for tech help – or does your household completely invert the traditional age-ascending direction of tech assistance rendering?

Not at all! I invest in tech; I don’t always have experience in using it. I have a sophomore majoring in honors computer science at the University of Wisconsin, and he’s been my tech support since I became self-employed. I call frequently with requests that are some variation of “Please tell me how this gadget or app works”. So we are certainly a bit inverted in terms of the younger educating the older generation.