Money For Somethin'

Data teams after the era of dirt cheap money

“The most important item over time in valuation is obviously interest rates." - Warren Buffett

I recently read some excellent articles on the world after low interest rates. One piece, “What if your entire worldview was just because of near-zero interest rates?” describes the collective addiction to cheap money over the last decade and how this addiction might pervade now that money’s more expensive. Another article from Lauren Balik discusses how the low interest rates created a “human middleware” of nonsensical jobs that will be gutted as times get leaner. Apart from being a data nerd, I’m also a finance nerd, so these articles resonated. It got me thinking about how many data teams¹ formed in a time of cheap money and abundance will have to adjust quickly. What happens now that money isn’t freely available and data teams must operate under constraints and scarcity? What should you do if you’re on one of these data teams?

In case you didn’t get the memo, the days of historically low interest rates - and crazytown tech valuations - are over. In the good old days, companies were raising rounds at crazy valuations, sometimes with nothing more than Github stars and a Slack community. When I’d speak with startup founders about whether they were focused on growing revenues or logos, it was often the latter. VCs wanted to see “traction” through a growing customer list. Whether there were paying customers was often a secondary consideration. The mantra was growth at all costs.

I’d often lament to friends that it all seemed like a crazy and unsustainable hallucination. Companies chased high valuations, sometimes with shaky business models, even in a low interest rate environment, let alone a “normal” business cycle. As Keynes said, “the market can stay irrational longer than you can stay solvent.” The craziness continued until the Fed started raising interest rates for much of 2022. This year, these companies experienced a sudden pivot back to business fundamentals. VCs who previously told their portfolio companies to grow at all costs immediately pivoted to urging their companies to run lean and do strange things like earn money and run net cash flow positive or profitable. As interest rates rise, tech company valuations largely nosedived, and layoffs hit the sector hard. What happens in 2023 is anyone’s guess. The reality of constraints is back.

What do interest rates have to do with data teams? Depending on the type of company, it means a lot. Let’s quickly walk through how interest rates affect the business environment, then tie this back to data teams.

Interest rates inversely affect the value of asset prices (stocks, startups, real estate, etc.)². The higher the rate, the lower the asset price; the lower the rate, the higher the asset price. The last decade featured the lowest interest rates in human history. Because money was dirt cheap, this led to much private equity and startup investment in arguably the biggest asset bubble in history. Nearly every asset class ballooned and ballooned in valuation.

Moving back to data teams. Due to the nature of my work, I work with countless data teams across many industries. During the period of cheap money where “data’s the new oil” and “data science is the sexiest job of the 21st century”, I noticed a lot of FOMO around data. Executives and investors needed to be able to tell a story around what they were doing with data, whether or not something tangible or valuable was delivered (I guess an increase in valuation is a form of “value” to shareholders). Consequently, I saw many data teams created “just because.” You must keep up when competitors are moving fast in a red-hot market. Your goal is to get the next round of VC funding at a high valuation, hopefully before you run out of runway. I’d see teams of data scientists hired, often with little actual work to do. But hey, you’ve got a data team and can show them off to future investors. Since the mandate for these types of companies was growth at all costs, this led data teams to do some things specific to this mandate, such as moving fast and focusing on growth-oriented metrics (DAU, #signups, CAC, etc.), often casting aside traditional things like growing revenue and profit. The data teams were full of intelligent people and operated with good intentions but often lacked direction or support from above (don’t get me wrong, some excellent data teams were providing real value too). With direction elusive, often data teams were quite a bit like performative theater, doing experimental “data stuff” but not contributing to business impact.

Those days are gone. Abundance has a way of distracting people into the hallucination of progress. On the other hand, constraints and scarcity have a way of sharpening the mind. When you have little money, time, and patience from stakeholders, you cut the cruft and focus on what matters. Money is tight, so labor, cloud, and tooling budgets and resulting ROI will be monitored at a very granular level. The value created by data teams is under intense scrutiny. Delivering concrete results that drive the needle is mandatory. Data teams that can’t deliver will be dissolved³. Nowadays, there are two obvious levers to pull that will add value - make money and reduce costs. That’s it. In the good old days, data teams had to figure out how to grow at all costs. These data teams need to figure out how to survive at all costs.

The challenge - if you weren’t delivering business value when you had nearly unlimited resources, what would you change to start delivering value under severe constraints? Time, money, and patience are now the constraints you’re operating under.

If you’re on a data team, what should you do? Let’s first do a quick thought experiment. If your data team was removed, would the business be negatively impacted? If the answer is no, you need to start looking for a new job since you’re probably not the first to ask this question. Otherwise, let’s walk through some things you can do to adjust to the new normal of tight budgets and intense scrutiny on delivering value.

• Make sure expectations are transparent with you and your stakeholders. Be sure these expectations are tied back to something measurable. These expectations should be impactful to the business.

• When used correctly, data should help companies navigate choppy waters and discover areas of opportunity. Remember, downturns are opportunities to pull ahead of competitors and set up your company for success once the economy improves.

• Get your costs under control.

• Remember the two levers - revenue and cost. Focus on ways to help your company make money or reduce costs.

• Level up your team’s knowledge and skills. Best practices and processes allow you to know how to operate more efficiently, saving wasted motion. Invest in tools that help you amplify these efficient processes.

• “No loser talk,” as Wayne Marino, former COO of Under Armour, once remarked to my group. You need to remember that every company exists in the same economy. Outplay the competition, and don’t use the downturn as an excuse. Be smart and merciless.

Strangely, these are things that data teams (and companies in general) should always do. But for quite a few data teams, this will be a sudden and painful adjustment. Is this bad? Quite the opposite, and this is a welcome change. For far too long, I’ve been mystified by how some data teams have seemingly operated in a vacuum, providing questionable value (again, others were stellar!). I’m happy we’re getting back to a focus on fundamentals. The last decade was an anomaly. I hope data teams can adjust quickly and profitably to the new reality.

Money For Nothing

1. For the sake of brevity, this article focuses on data teams formed in companies that raised money in the era of cheap money.

2. To understand the dynamics of asset prices and interest rates, look at how low interest rates affect valuations when you use a standard valuation approach like discounted cash flows. Essentially, low interest rates pull forward the expected value of cash flows from the future to the present. https://en.wikipedia.org/wiki/Discounted_cash_flow

3. I suspect many tooling companies are in the same boat, having raised gobs of money when it was cheap and now have to prove their…generous…valuations in a down market. Expect carnage and consolidation.