ICYMI: Andreessen Horowitz – Data Is Not A “Magic Wand” To Fend Off Competition
Martin Casado and Peter Lauten of the well-respected venture capital firm Andreessen Horowitz recently made the case that simply collecting data is not a sustainable approach to staying ahead in the tech sector, an analysis echoed by other experts who highlight that data does not have inherent value. Rather, experts argue, it’s the effective utilization of data that creates value.
More from Martin and Peter, as well as other experts, is below.
Data, by itself, does not protect companies from competition.
Casado and Lauten note that even with scale effects, data is rarely a strong enough moat. “Yet even with scale effects, our observation is that data is rarely a strong enough moat. Unlike traditional economies of scale, where the economics of fixed, upfront investment can get increasingly favorable with scale over time, the exact opposite dynamic often plays out with data scale effects: The cost of adding unique data to your corpus may actually go up, while the value of incremental data goes down!”
Data is not a “magic wand” to fend off competition, they continue. “Data is fundamental to many software companies’ product strategies, and there are ways it can contribute to defensibility — but don’t rely on it as a magic wand. Most of the narrative around data network effects is really around data scale effects, and as we’ve outlined in this post, those sometimes have the opposite effect if not planned correctly. But don’t even assume you have a data network effect (you likely don’t), or that the data scale effect will last in perpetuity (it almost certainly won’t).”
There generally isn’t an inherent network effect that comes from merely having more data, the authors add. “Systems with network effects generally have the property of direct interactions between the nodes over a defined interface or protocol. Joining the network requires conforming to some standard, which increases direct interaction for all nodes and makes those interactions increasingly stickier. But when it comes to the popular narrative around data network effects, we don’t often see the same sticky, direct interaction play out.”
The ability to draw proprietary insights from data decreases as data becomes stale or is collected by competitors, they conclude. “This point may seem obvious but can’t be emphasized enough: In many real-world use cases, data goes stale over time… it is no longer relevant. Streets change, temperatures change, attitudes change, and so on. Not just that, but any proprietary insight many data startups have initially weakens over time because the value of data decreases as more people collect it: Your prediction edge erodes as competitors chase you in the same domains. And the amount of work required just to keep an existing corpus fresh over time — let alone ahead of the pack — increases with scale.”
Data on its own has little value, it’s the talent and processes that interact with the data that make it valuable.
American Action Forum’s Will Rinehart highlights that “data is ubiquitous” and that it is tech talent that makes the data valuable. “Data isn’t the most important asset in the digital economy, but the talent needed to make that data useful is crucial. Herein lies the flaw with the “new oil” analogy. Saudi Arabia has a tremendously valuable asset in the volume of its oil because the ability to process oil is well known and relatively simple. Not so with data, however: Data is ubiquitous, but what isn’t widespread is understanding what kind of information you might have and doing something useful with it.”
CCIA’s Jakob Kucharczyk notes that “data can be used over and over again.” “Unlike oil, which is used once, then burns up in combustion, data is regenerative, meaning it can be used over and over again. It lives on and gains new life each time it is shared or used in a way that adds value to someone. It builds knowledge, meaning, and value the more it is interlaced with other data. However, data is only valuable if one can derive meaningful insights from it. Large amounts of data is useless if nothing meaningful can be derived from it. That contrasts sharply with oil.”
Economists Anja Lambrecht and Catherine Tucker highlight that substitutes to data exist and that insight into consumer needs is critical for success. “Our analysis suggests that big data is not inimitable or rare, that substitutes exist, and that by itself big data is unlikely to be valuable. There are many alternative sources of data available to firms, reflecting the extent to which customers leave multiple digital footprints on the internet. In order to extract value from big data, firms need to have the right managerial toolkit. The history of the digital economy offers many examples, like Airbnb, Uber and Tinder, where a simple insight into customer needs allowed entry into markets where incumbents already had access to big data. Therefore, to build sustainable competitive advantage in the new data-rich environment, rather than simply amassing big data, firms need to focus on developing both the tools and organizational competence to allow them to use big data to provide value to consumers in previously impossible ways.”
Georgetown University Fellow and Adjunct Professor Mark MacCarthy points out that unlike oil, valuable data sets are “widely available” and easily accessed. “Moreover, oil and information differ in the ease with which it can be fenced off and controlled. The tangible physical nature of oil means it is very easy to establish control over it and exclude other people from using it. But information is not like that. Many valuable data sets are widely available. For instance, the public can easily access prices charged by online merchants and that information can be used by anyone seeking to devise a pricing algorithm.”