Douglas B. Laney, Data and Analytics Strategy Innovation Fellow | West Monroe
In the wake of the Silicon Valley Bank implosion, many companies feel pressured to pursue new sources of capital. Venture capital and private equity funding have already cooled since the record-setting pace of 2021 and are poised to dry up even more as fallout from SVB ripples through the tech sector. While some experts predict an uptick in mergers, buyouts, and IPOs on the heels of the banking collapse, companies that cannot or do not want to pursue these paths might consider a newly emerging alternative: collateralizing their data assets to access lending capital.
To say that data is valuable is far from a controversial claim. There is enormous demand for quality data across industries and categories, as evidenced by a data brokerage market that spans more than 5,000 firms worldwide and is projected to reach $462B by the end of the decade. Businesses also know that their data has obvious worth, even if it never lands on a balance sheet, because it helps them refine their operations and offerings. They may even realize that their data could be valuable to interested parties outside their business but balk at selling it outright. Data marketplaces are too opaque, too complex, too far from the core business, and the risk of potentially compromising trust and competitive advantage might stop organizations from ever exploring monetizing data.
Data monetization doesn’t start and stop with selling, though. There are many ways to squeeze value from data assets, and leveraging data as collateral is particularly attractive in today’s environment. One increasingly popular arrangement from neolenders is to offer loans backed by a copy of an organization’s data. These loans are non-dilutive, preserving equity for founders, and the original data never leaves the borrower’s possession. A particularly founder-friendly aspect of these loans is that in the case of default, the borrower does not lose their original assets and can continue operations as normal; the lender simply retains the copy of the data so they may satisfy the loan terms.
There are a few hoops to jump through to access these kinds of capital arrangements. First, you must find the right lender, as many traditional banks still refuse to acknowledge the financial worth of intangible assets. Second, the borrower and lender need to agree on the value of the data set in question. This can seem daunting, as valuation models for data are still maturing and have historically taken too much time and resources for SMBs to comfortably access. Fortunately, there are emerging players in data-as-collateral that use machine learning and AI trained on thousands of transactions in the data marketplace to incorporate market comps for data sets and speed data valuation timeframes to hours, not months.
Chief Data Officers are uniquely positioned to lead the charge in pursuing this new capital stream, and most report they’re already making progress in deriving value from their organization’s data assets. In the most recent NewVantage Data And Analytics Global Leadership (DAGL) Survey, nearly every CDO surveyed responded that they deliver some measurable value with their data (up from only around 50% five years ago). Moreover, 90% say their organizations are increasing data investments during 2023, even with rising economic instability.
These are heartening responses, but consider that 60% of those same CDOs reported that their data is still not managed as a business asset, leaving substantial gaps in organizational understanding of data’s actual and potential value. CDOs must meet the mandate to manage and monetize data, but many are operating within murky understandings of where that value truly lies. Demystifying that value through data valuation is a critical first step toward actualizing the potential of organizational data assets. Even if a loan is not ultimately pursued, the mere exercise of managing, measuring, and reporting the value of data assets can have a profound effect on organizational alignment and C-suite buy-in for further data investments. As the headwinds of venture capital and traditional financing grow rougher, data assets may be the buffer that makes the difference between capsizing and smooth sailing.
About the Author
Doug Laney is the Data & Analytics Strategy Innovation Fellow at West Monroe. He consults with business, data, and analytics leaders on conceiving and implementing new data-driven value streams. Laney 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.” He is a three-time Gartner annual Thought Leadership Award recipient, a World Economic Forum advisor, and a Forbes contributing author. Laney co-chairs the annual MIT Chief Data Officer Symposium, is a visiting professor at the University of Illinois and Carnegie Mellon business schools, and sits on various high-tech company advisory boards.