Douglas B. Laney, Data & Analytics Strategy Innovation Fellow, West Monroe and Lauren Cascio, Founder, Gulp Data
Gulp Data allows companies to use their data assets as collateral for loans. This data monetization startup emerged from the need to enable SMEs to tap into their data assets as collateral or as leverage for negotiations.
Lauren Cascio, the founder of Gulp Data, set out to prove that data is a liquid asset, and is similar to other assets recognized under GAAP practices (Generally Accepted Accounting Principles).
In this deep dive interview, Cascio speaks with Doug Laney, Data & Analytics Strategy Innovation Fellow at West Monroe, about Gulp’s approach to monetizing data assets, inequities in the market, its business, and its competition.
Q: Let’s start off simply — Gulp Data. Could you give us an elevator pitch?
Gulp Data allows companies to use their data assets as collateral for loans.
Q: What was the genesis of this concept? What were you doing when this idea of data-as-collateral planted in your head, and how did it snowball from there?
I led the data monetization strategy in one of my previous companies. Even after data had become our main source of revenue, it was almost impossible for the finance people like our CFO, the investors, and the board to understand that data should be a balance sheet asset. They would only recognize the revenue it generated and not the actual value of this intangible asset, as you would any other intangible asset, like patents or copyrights. That seemed wild to me.
I stepped away from my operational position in that company almost two years ago. I decided that I wanted to change the way companies were being financed. In particular, I wanted companies in the SME market to be able to tap into their data assets as collateral or as leverage for negotiations. I wanted to prove that this asset is liquid, and that it has the same benefits, if not more, as almost any of the other assets that are currently recognized under GAAP practices.
Q: What challenges do SMEs face when they're looking to properly evaluate or monetize their data?
Leveraging data is nothing new for the big players. There's the famous use case during COVID where multiple airlines pledged their loyalty programs to tap into capital. The problem is, those kinds of financing structures are just not accessible to the SME market.
There are a few barriers at play. First, it’s expensive. To do an intangible asset valuation, a data valuation, or even a standard business valuation — it’s just really costly. You have to go to one of the big guys like KPMG, and it costs a quarter million to half a million dollars just to perform the valuation. It also takes a long time, maybe three or six months, by which point the data is already stale. Additionally, even if you put a value on your data, it’s still not a widely accepted asset by banks and institutions. The result is a disconnect between what is valuable to those financial entities and what is actually valuable in today’s marketplace.
Q: In some ways, data is both the oldest asset and the newest, most modern asset that a business can hold. How does that juxtaposition play out when it comes to evaluating a company's assets?
In my mind, it’s simply a new asset. It’s become kind of a cliche to say data is the new oil, the new gold, the new soil. It's really not any of those, because data as an asset is unique. Data has always been informationally valuable to the business that holds it, but the ways in which we manage and capture it in 2022 has created a completely new sort of asset. The rapid changes in the infrastructure for digital assets — cloud computing, data management, business intelligence, and all the other analytics layers — all of this makes data something that businesses can easily maintain, use, and leverage in a way that just wasn’t possible in the past.
Q: Let’s get back to basics. Why does data hold value in the first place? We can understand how it holds value internally, as businesses can leverage their own data to make better decisions or to generally improve outcomes. But why does data have marketplace value?
So there are two real types of data monetization, direct and indirect. Indirect monetization is what you’re referencing. How does data help the business understand its customers? How can it improve sales? There are myriad opportunities to indirectly monetize data, many of which you share in Infonomics.
Direct monetization is what we focus on at Gulp Data, and we’re not the only ones. For example, if you are an electronic health records company (EHR), you likely already have departments that sell data assets to research institutions and pharmaceutical companies, because that information is clearly valuable to them. That would be considered a private sale, which is one of the three layers of the existing data trade ecosystem. Another layer is the marketplace, where companies can go to buy and sell data. There are a few thousand marketplaces; Snowflake has one, as does AWS. Finally, there are data brokers, such as Experian or Moody’s Analytics, that collect data and sell it as a product. There are more than four thousand data brokers worldwide in a market valued at over $250 billion and growing.
Q: What are the dynamics and potential inequities in today's data marketplace? Is it David vs. Goliath, or survival of the biggest?
It’s funny, because when most people imagine the data marketplace, they think of FAANG trading all of our social media and location data. The reality is most of the data is being generated by the SME market. FAANG are the purchasers, the aggregators that are hoovering up tons of data from smaller companies.
The companies that are responsible for generating the most data are actually in the SME market across all sorts of sectors. The problem is that SMEs don't always have the tools or resources to monetize data or understand its value because they're so focused on creating revenue from their main product. Traditional revenue is what has landed on the balance sheet, that’s what has mattered to investors and boards, so it takes priority over exploring how data could be leveraged.
We are starting to see a shift in which SMEs are realizing, “Hold on, this actually has value.” There’s a desire to turn data into an alternative revenue stream or additional bargaining power at the financing table. The biggest question is how.
Q: Why is data so difficult to properly value, and how does Gulp Data mitigate the challenges?
Traditionally, data valuation has been a manual process. There is no transparency in the markets, so building comps is incredibly difficult. Good luck going to a pharmaceutical company or a lending institution asking, “How much do you pay for your data and where does it come from?” They’re simply not going to tell you. Ok, you want to hire an expert instead — the average consulting firm is likely to build a cost-based model. What did it cost you to acquire the data, maintain it, build the systems around it? What would it cost another institution to replicate what you've already built? Combine that with the amount of revenue produced from this data, subtract what it would cost the company if you lost the data. What this model too often shows to companies and lenders is that their data isn’t enough of a value driver, and might actually just be a cost center. At Gulp Data, we believe this route severely undervalues data.
Of course, we can’t stake loans on a belief, so we’ve built machine learning models that tap into the data markets in real time. This allows us to take an actual market comp for a given data set. That ability doesn’t currently exist elsewhere, to my knowledge. We’ll bring back that market comp to the company and offer loans against that value. We can also make additional recommendations from the models like, how could you increase your value with data enrichment? How should you implement this information strategically? In fact, the most common scenario our customers find themselves in is needing data valuation for leverage in a negotiation, M&A or raising capital.
Q: Let’s talk about raising capital. When you stepped away from your previous job to focus on Gulp Data in 2021, that was in the midst of a record setting year for VC. How does that contrast to where we are in Q4 2022?
Honestly? I thought last year was ridiculous. This shift is great for us, and I think it's healthy for the markets in general. As a founder and as an investor, I’ve always been a big believer in non-dilutive funding when used wisely. The companies that utilize both equity and non-dilutive funding are going to be the leaders coming out of this reset because they are making the most of what's available to them right now. They're optimizing all of their assets, whether that's revenue or research or intangible assets, to help them get through this and continue to grow.
Why is it good for Gulp? Well, we're in the non-dilutive space. As equity financing has pulled back and venture debt has gotten more expensive, we’re a new, somewhat unconventional funding source that businesses can tap into. Odds are they’ve never considered this type of funding before. We’re also a lot more friendly, because we understand the founder’s position so intimately. I’ve personally had bad experiences with venture debt and know that if you have a senior secured position and you default, they will take everything and kill your operations. It’s high stakes money. With Gulp, the worst case scenario for the borrower in default is that we retain a copy of the data to help us satisfy the loan. The borrower still has their original data and will be able to continue operating as usual.
Q: What are some of those common mistakes or pitfalls that founders run into when they're seeking funding, especially in a hyper growth stage?
The core issue is that founders focus on the wrong thing, which is valuation. When you're raising money from private equity firms, raising venture debt from seasoned VCs, they are not focused on valuation. They're focused on what else is in the contract. Do they have ratchet rights? Do they have liquidation preferences? Do they have warrants? These are things that kill a founder’s stake, and they don’t often see them coming. The valuation isn’t the problem — it’s everything in the fine print.
I always tell founders, great, you're raising equity, I hope you’ve found valuable partners. I hope you did your due diligence on whoever you're bringing onto your cap table. But make sure you read what you're signing and understand exactly what you're giving away. Specifically this year, in 2022, it's not just about how high the valuation was. Investors are doing all kinds of things to preserve their position in companies and avoid markdowns. They're going to make sure they can recover the money they're putting into the companies. Competition over deals was fierce last year — the investor is back in control this year, and that means much tougher terms.
Q: Often those PE and VC firms are in the power position at the starting point of financing, too. Can data be the great equalizer and even the playing field for founders?
Yes, for sure. One of the byproducts of being a data lender is the ability to do quick and painless intangible asset valuations for the SME market. It’s not our primary offering, but we do get approached by companies who are going through raises or an M&A and they’re saying, “We have all these users, we’ve acquired all this data, we've done all these analyses. What can I bring to the table with me during this negotiation? How can we convince investors that there’s value here, even if GAAP doesn’t account for it?” That is our hope, to help level the playing field between founders and investors.
Q: Are you feeling tension from the more traditional institutions pushing back on those intangible assets, or are you starting to see a change?
We’re seeing a lot of excitement from lending institutions and VCs. There’s direct buy-in from our partner investment banks that are providing us the capital to lend on data. The LTVs on data are really quite conservative because of its novelty, making it more attractive than almost any other asset-backed lending right now. I think lenders are realizing that data is simply a new asset that they're going to have to understand or get out-competed. The world isn’t getting less digital.
Much of our pipeline is driven from VCs who funnel their portfolio companies to us in hope of understanding their data assets better. They want these companies to continue to grow and survive even if they’re unable to raise additional capital, so they’re looking into new streams of revenue.
What’s funny is we’ve done no marketing whatsoever. Instead, we’ve had hundreds of applicants come through the door in the last six months driven by so-called traditional institutions. We’ve had incredibly positive reactions to our lending product, and I think it's because the timing is right. Of course, we do get called crazy occasionally, which tells me we’re on to something here.
Q: What are some of the concerns that an SME might have when it comes to monetizing their data?
Privacy is paramount. As a data company, privacy is at the core of our entire business. We will not work with companies that don't have the proper infrastructure to protect themselves, because it's a risk not only to us but to our clients, our borrowers, and their customers. Even still, we’ll have companies who stop the process because they don’t feel comfortable with the optics of using their data like this, which we completely understand.
There’s a specter in the collective imagination about data trading — that it’s mostly personal data, and it’s only used for advertising things we don’t need or manipulating elections. That’s really a small percentage of what happens in the data market. The reality is that data, when properly used by the small private market, is typically used for good.
Regulators might mean well, but GDPR was an example of how too much regulation over data can have negative consequences, because they have really chilled innovation in the EU. Take the EHR we spoke of earlier — let’s say they have all this data on a chronic disease that, when aggregated and anonymized, can provide invaluable insights to researchers looking to cure or treat that disease. When too much regulation on the exchange of that data is enacted by institutions that don’t understand it, that conversation and that innovation stops. The fear of arbitrarily enforced fines is just too much.
There are some state-level privacy laws coming into place in the United States that are geared towards FAANG and other big companies with hundreds of millions of dollars in revenue. Those regulations aim to cut down on black box or black market data trade. That’s not where we function, and that’s not even the majority of the data trade. The vast majority of data is traded in a private, secure way where everything is anonymized. It is abiding by all of the compliance standards, even in healthcare and financial services.
The reality is that companies are using data anyway. What you want to ensure is that they're using it responsibly. Leveraging it as an asset to improve your services is one way of doing that. Partnering with a trusted company that secures data assets and monetizes them responsibly is another.
Q: So what should companies do to prepare themselves to responsibly leverage their data? What are some of the things that companies overlook when it comes to building that appropriate infrastructure?
We do a lot of this vetting in our application process before we ever move into a data sampling process or a loan offer. A company needs to have the basics down. They need to have to have some infrastructure, they have to have a technical lead, and they need a cybersecurity strategy. They should have performed vulnerability tests, penetration tests, all the things that any organization with data should be doing anyway.
When we initially launched, we were targeting very early stage companies, pre-series A companies — and they weren't mature enough. They didn't have enough infrastructure and they didn't have enough data, typically, unless it was a deep tech company, like a biotech company, or a rocket company. In most cases they simply didn’t have enough data to actually obtain a sizable loan. In that stage, they need to be putting infrastructure in place. The awareness around data management is rising, though, even for these early stage companies. A core focus on almost any executive team is having a Data Officer, having an Information Officer, or building strong technical departments that are ready to manage data assets.
Q: Why do you think now is the right time for a company like Gulp Data to seize the marketplace?
Serendipitously, we founded Gulp Data last October, right before all hell broke loose in the equity markets. When we started operating this year, it ended up being a perfect time because of what was happening at a macro level. Not only were companies now looking for non-dilutive sources of revenue, but lenders and investors wanted to bring due diligence back in a big way. Due diligence is Gulp Data’s bread and butter. We help directly with valuations and data intelligence in a matter of hours, something that could take internal teams at VCs or portfolio companies days or weeks. That’s a part of this great timing.
The other thing is I think that the market is ready to recognize data as an asset. I’ve been working in data for a decade, and in 2013 people thought I was crazy when I was talking about AWS and the possibilities and scale of cloud computing. I could see how all this data was going to start leading most organizations, and I think that's finally coming to fruition. There's a lot more chatter about it. The cloud computing markets are exploding, valued at $484 billion this year and expected to exceed $1.5 trillion by 2030. This is the right time to get traditional finance people on board with this, because they can start to see that if they don’t, the fintechs are going to beat them.
Q: It does seem like your interactions with those traditional institutions are confirming your theory. They’re hungry for this.
The conversations have been great. Honestly, I expected a lot more pushback, but that has not been our experience. I think the market is ready to take a fresh look at the restrictions of GAAP in a digital world and take data as an asset seriously. Hopefully we can revisit this conversation in a year and we’ll have multiple data lenders on the market.
About the Author
Doug Laney is the Data & Analytics Strategy Innovation Fellow at West Monroe where he consults with business, data, and analytics leaders on conceiving and implementing new data-driven value streams. He originated the field of infonomics and authored the best-selling book, “Infonomics,” and the recent follow-up, “Data Juice: 101 Real-World Stories of How Organizations Are Squeezing Value From Available Data Assets.” Laney is a three-time Gartner annual thought leadership award recipient, a World Economic Forum advisor, a Forbes contributing author, and he co-chairs the annual MIT Chief Data Officer Symposium. He also is a visiting professor at the University of Illinois and Carnegie Mellon business schools, and sits on various high-tech company advisory boards.