Why You Need to Data the Sh*t out of Your Business in a Downturn By Brett Hurt
The post Why You Need to Data the Sh*t out of Your Business in a Downturn appeared first on data.world.
In the now iconic line of the 2015 movie The Martian, marooned astronaut Mark Watney (played by Matt Damon) gave us a new verb to sum up his only possible exit from his Red Planet dilemma: “I’m going to have to science the sh*t out of this.”
For many businesses, our own version of a Martian dust storm has already been likened to an economic hurricane by no less than JPMorgan CEO Jamie Dimon. So amid these howling headwinds of inflation, the likes of which we’ve not seen in decades, I’ll create my own new verb as well – every business leader should be ready to roll up their sleeves and data the sh*t out of their entire operation.
To bring the metaphor home, just as Watney had to locate, tally, and optimize every gram of protein, every molecule of oxygen, and the energy from every available isotope, companies must now not just collect but analyze to the Nth decimal point the complex relational web of data that defines the 21st century business – with 21st century tools.
Now of course, as the CEO of a leading data catalog company that creates the tools I’m talking about, I’ve got a proverbial dog in the fight. Fair enough, bias disclosed. But I also have some exposure to turbulent economic times, having founded and led two companies, Coremetrics and Bazaarvoice, through the dot-com bust of 2000 (followed by the horror of 9/11) and the Great Recession of 2008 and 2009. If anything led to my motivation to co-found my sixth company in 2016, data.world, it was the imperative of data mastery – the biggest lesson after surviving those two economic traumas. Now my team and I are at the frontier of the unfolding, data-driven economy. So the case that the coming economic challenges will be the first we can meet with a seriously augmented playbook, one that scarcely existed a decade or so ago, is a proposition I do not make lightly.
Data Runs in My Blood
Data and mathematics runs in my blood, with my grandfather having worked his entire career at the University of Texas at Austin as an advanced mathematics professor. He would always grill me on math way above my grade level, and I realized later on in life that he was doing me a big favor. I grew up really monitoring analog data in my parent’s stores. Ground truth was essential, and we would constantly ask customers how they found us and whether they were finding what they were there to shop for. When I attended The Wharton School to earn my MBA, I chose Sam Walton as the leadership icon I would study in my leadership class. I read his book Sam Walton: Made in America, which was all about seeking ground truth in his retail stores. He wrote the book to inspire his children and teach them how important it was to stay humble and be very customer focused.
It was at Wharton where I co-founded my retail business, an e-commerce company named BodyMatrix, which my wife, Debra, helped start. It seemed natural that we would want to be like my parents and Sam Walton, to seek ground truth in this new virtual medium. As a shopper, you couldn’t touch or feel any of the products online. As a retailer, you couldn’t see how your customers found you or where they were getting frustrated when unable to find what they were shopping for. And you couldn’t interact with them in real-time online, only via email after the fact. This spurred me to create my own analytics and personalization system on top of the e-commerce platform that I had built. It was a eureka moment to say the least once I was done with the initial version – it gave me a “bigger brain” than my parents ever had in their physical retail stores. I could monitor exactly what customers were doing by capturing all of their clickstream behavior, leveraging cookies as unique customer identifiers, and storing it in a large data warehouse with a smaller data mart running on top. Seeking to make my own data and analytics system better, I met my Wharton friends that worked at both Amazon and CDNow to learn of the tools they used and just how that had done this. To my surprise, they urged me to start a company to provide this for online retailers like them (one of them was Matt Laessig, who is one of my co-founders and our COO here at data.world). When I was about to graduate in 1999, I founded Coremetrics, which was named after the core metrics that retailers desperately needed to run their online businesses. Dot-coms were flying blind back then, and they absolutely loved the visibility we gave them. They went from basic metrics that really didn’t matter, like pageviews and unique visitors, to much more robust metrics powered by Coremetrics. Our tools of insight enabled look-to-book ratios on each product, browser-to-buyer conversion ratios, advertising-clickthru-to-sales ratios, individual prospect and customer profiles of clickstream behavior that could be used for targeting email campaigns and personalized offers, and much more. We founded Coremetrics too late though – the dot-com bust that started in 2000 was right around the corner and 97 of our 100 customers ultimately went out of business after the bubble bust. But then we won Walmart and built Coremetrics by helping traditional retailers that were launching online, providing them with far better metrics to run their e-commerce business than any of the dot-coms had before. Coremetrics made me fall in love with data as the most powerful resource to create culture change, sustainability, and resilience through the toughest of economic times.
This journey continued with my next business, Bazaarvoice. We pioneered customer reviews for retailers and brands online all over the world. There were only three retailers in the U.S. with customer reviews online when we started, but Bazaarvoice quickly became ubiquitous, operating across more than 40 international languages. Bazaarvoice taught retailers exactly what customers thought about their products. Four-star reviews often included descriptions from customers like, “I would have rated it five stars if only it had this or that feature.” Product returns are very costly for retailers in an already low-margin business. Bazaarvoice taught retailers and brands exactly why products were being returned. I’ll never forget when Walmart, again one of our early customers at Bazaarvoice, told their suppliers that they would return low-rated products not just from their online division but from all of their physical stores as well. It made their supply chain far more customer-centric. Brands like Samsung started to pay an incredible amount of attention to Walmart’s customer reviews, powered by a direct data feed from Bazaarvoice. Like Coremetrics, we hosted customer summits and it was incredible to hear both brands and retailers talk about how much they were diving into the data of customer reviews, and how much more efficient it was making their sales, returns, and partnerships with their suppliers. Sam Walton would have been proud.
Mastering the Universe of Data
Just a few days ago we had fun discussing these learnings and my background in the 90th episode of Catalog & Cocktails, our podcast at data.world, with colleagues Tim Gasper and Juan Sequeda. When I reflect on these hard-earned lessons today, the biggest insight to keep in mind is that data are simply facts about your business or organization – and we’ve never had them in such abundance, even as we often fail to use them. Because the much-evolved utility of data, its governance, and this new and expanded business playbook are really about these relationships of facts. In sum, they add up to what at data.world we call agile data governance and the emerging concept of data meshes, which I wrote about on this blog in March.
Every CEO, COO, CFO, and management team operates at the nexus of these connections of facts. This is the ecosystem of suppliers and customers and all the facts they generate and animate. It’s the cosmos of inbound facts on sales and prospects, outbound facts such as marketing or promotion, and accumulated facts such as records of operations to date. This web includes capital: physical, financial, reputational, and human. This commercial sphere includes capacities: the skill and intellect of the team, the productivity of machines and software, and the scope of digital infrastructure. The hard facts of the environment – interest rates, unemployment rates, supply chain efficiency, government policies, competitive pressures, and commodity prices – are the frame around this ecosystem. To some degree, a version of this organizational choreography has been the lot of the business leader since the dawn of commerce, much like it was for Sam Walton and the techniques he pioneered. Every decision is made at the intersection of some subsection of this array of elements. But now, all wired together, the sum of the interactions among all of these elements – these facts – are logged and charted as data, in ways unimaginable just a few years ago. It’s worth reminding ourselves that the estimated 100 zettabytes of data stored in “the cloud” – enough to fill the standard hard drives on about 40 billion Mac laptops – resides in a technology launched just in 2006 with the advent of Amazon’s first cloud servers at AWS.
What this means is that we can optimize our businesses as never before. With $11 trillion erased from global stock markets in the first five months of the year, the NASDAQ off 26.5 percent as of last Friday, Elon Musk musing about his “bad feeling,” and Dimon predicting a hurricane – either a “minor one or Superstorm Sandy” – now would be an awfully good time. Except that, as I wrote in February, outside of the FANGs and a few other tech behemoths that have truly mastered their universe of data, very few companies have effectively done so.
Instead, executives remain in the dark. IT departments rush between data silos to the point of exhaustion, as thousands of data engineers rush to the door amid the Great Resignation. As detailed in one of our favorite books, Winning with Data by Frank Bien and Tomasz Tunguz, teams literally brawl over decision-making in the absence of accessible and verifiable data. This will only accelerate if we panic. Kevin Kelly, the towering thinker and author whose books include The Inevitable, on the emergence of this new data-based economy and society, has described us as being captured by a “counterforce,” as we reflexively “hoard data like gold” rather than use it.
In many ways these failings were masked, or worse even ignored, during the successive rounds of stimulus during the pandemic. As we effectively hit the dimmer switch on the economy the interventions, including the $1.9 trillion CARES Act, filled a demand hole that averted the likes of a 1930s-style Great Depression. This era of virtually free capital was also an accelerant to the businesses of the future, e-commerce, communications technology, biochemistry, meme stocks, cryptocurrency values, and more. Since the beginning of the pandemic, real estate values skyrocketed in the emerging new technology hubs like the one in which I was born and now live, Austin. With all the numbers up and to the right in so many P&Ls, everyone could play genius as we minted unicorns by the hundreds.
But first, we saw this bounty of liquidity squeezing supply chains as demand overwhelmed supply. Inflation began creeping up. Then came lockdowns in China, a grinding war in Ukraine with no end in sight, and soaring energy and commodity prices. There are few better illustrations of the ensuing dynamics than of yet another noun-turned-verb, Zoom. The company’s share price on NASDAQ was $67.28 on the first day of trading in 2020. On October 18 of that year, it had zoomed to $559. As of Friday, it was in the neighborhood of $109. If you’ve been patting yourself on the back for buying property in Austin, Miami, Denver or other digitally friendly destinations, consider today’s reality of new mortgage rates. A house bought today on a 30-year mortgage – any house – is effectively 67 percent more costly than it was in January.
This Is the “Crucible Moment”
As I was finishing this essay, the World Bank issued its sobering assessment of all that is hammering the global economy. What grabbed the attention of most headline writers was its forecast of 2.9 percent growth this year – down from 5.7 percent last year. What might have been given more attention was the bank’s prediction that “subdued growth” is likely for the remainder of this decade and we may be looking at a repeat of 1970s “stagflation” (i.e, paltry growth and high inflation). Some heavyweight economists challenge the comparison with the 1970s as overwrought for reasons like the fact that interest rates remain far below inflation levels globally, giving policymakers tools they lacked four decades ago. There’s also encouraging evidence of oil price turmoil boosting investment in renewable technologies of solar, wind, and geothermal. This year, for example, we’re on track to add a record 320 gigawatts of green power generation, according to the International Energy Agency, an amount roughly equal to the entire electricity demand of Germany.
Indeed, we may get lucky, although the inflation print of 8.6% on Friday was not an encouraging sign. And blowing on your dice and hoping your fortune will change is a ritual best saved for Las Vegas (coincidentally, where we are right now for the Snowflake Summit). What is indisputable is that we are suddenly in what investors like Bill Gurley call a “risk-off” environment. This is a planetary reassessment of how business models will fare and it means safe bets only for the foreseeable future. Practically, this means businesses everywhere are turning to the conventional, three-part inflation times playbook: cut costs, trim margins, and – if you can – raise prices.
Now I don’t mean to diminish the importance of the conventional playbook, which we are going to need. One of the best roadmaps in my realm of venture investment, “Adapting to Endure,” was just produced by Sequoia Capital. And while I can’t share it, as it’s “confidential”, it’s been reported upon numerous times and CNBC did a very effective summary. In this “crucible moment” as Sequoia calls it, companies will be forced to accept lower valuations based on revenue multiples, scrap projects and R&D for tactics that can generate cash, get real clear and honest with their stakeholding investors and employees, and focus on identifying immediate opportunities such as extended terms for the strongest customers.
I salute all of this, particularly on clarity and honesty. But the playbook needs a new chapter. Among its authors is Brian Chesky, founder and CEO of Airbnb. His company saw its value halved by the pandemic, saw revenues fall 80 percent overnight early in 2020 and yet pivoted to a better business model that enabled him to conclude the year’s biggest IPO of more than $100 billion just months later.
Chesky is what I call a “knowledge superhero”. His company is as much a data company as it is a lodging company. Like Warby in eyewear, Oscar in health care, or Spotify in music, data science is at the heart of every decision. Airbnb’s fifth employee was a data scientist and they built their own data catalog in-house (before data.world existed), as former engineering leader Jeff Feng discussed in the 28th episode of Catalog & Cocktails. But the broader point of this essay is that we must all become “knowledge superheroes” in the crucible moment. The tools of data catalogs and knowledge graphs, the brains and nervous systems of the 21st century enterprise, are here. Knowledge graphs are the most sophisticated means of reasoning and used by Meta, Google, Amazon, and other tech behemoths. But now, every manager, every executive, can and should be equipped with the tools that make the “facts” of the business visible and transparent as never before to manage their businesses in precise, mission-specific ways. Enterprises that are truly data-driven – or fact-driven to be more precise – no longer have to guess at their weaknesses, strengths, and the opportunities that exist in our troubled times. And they can execute with insights a hundred times more detailed, in ways a 1,000 times faster, than we could two decades ago, even with the powerful new technology of Coremetrics at the beginning of my journey into the incredible promise of data.
To return to our mythical hero on Mars, Watney had what he needed to survive – hydrogen captured in jet fuel, carbon dioxide in the Martian atmosphere, heat energy from a salvaged radioisotope thermal generator, nutrients from abandoned potatoes, and of course nitrogen fertilizer harvested from his own bodily functions. And he could waste none of it. But he had to know the facts: where it was in the post-storm wreckage, how to innovate and combine it, and how to operate at the nexus of this ecosystem held together by knowledge.
Which is how we should think about our challenges today. Except it’s not science fiction. It’s not imaginary and it’s not on a distant planet. These earthly tools of insight are our reality right here amidst our own version of a dust storm with no end yet in sight. “Chance only favors the mind which is prepared,” said the superhero of chemistry Louis Pasteur. We remember the remark as a clever phrase, but in fact it was a statement of principle he made studying business failures. He was right then, and still is nearly two centuries later. Today our chancy times will only favor the business prepared with knowledge, the facts, and the insights of the brains and nervous systems of data.
Featured image credit: Team of Professional Computer Data Science Engineers. Gorodenkoff. https://www.istockphoto.com/portfolio/www.gorodenkoff.com
The post Why You Need to Data the Sh*t out of Your Business in a Downturn appeared first on data.world.