When Data Creates Competitive Advantage
Many executives assume that customer data can give you an unbeatable edge. The more customers you have, the more data you can gather, and that data, when analyzed, allows you to offer a better product that attracts more customers. You can then collect even more data, repeating the cycle until you eventually marginalize your competitors. But this thinking is usually wrong. Though the virtuous cycles of data-enabled learning may look similar to those of network effects—wherein an offering increases in value to users as more people adopt it and ultimately garners a critical mass of users that shuts out competitors—they are not as powerful or as enduring.
Nevertheless, under the right conditions, customer data can help build competitive defenses. It all depends on whether the data offers high and lasting value, is proprietary, leads to improvements that can’t be easily imitated, or generates insights that can be quickly incorporated. Those characteristics do give firms an advantage. And when learning from one customer rapidly improves an offering for others (think Google Maps), people will care about how many other people are adopting it, and it will enjoy those sought-after network effects.
Many executives and investors assume that it’s possible to use customer-data capabilities to gain an unbeatable competitive edge. The more customers you have, the more data you can gather, and that data, when analyzed with machine-learning tools, allows you to offer a better product that attracts more customers. You can then collect even more data and eventually marginalize your competitors in the same way that businesses with sizable network effects do. Or so the thinking goes. More often than not, this assumption is wrong. In most instances people grossly overestimate the advantage that data confers.
The virtuous cycles generated by data-enabled learning may look similar to those of regular network effects, wherein an offering—like a social media platform—becomes more valuable as more people use it and ultimately garners a critical mass of users that shuts out competitors. But in practice regular network effects last longer and tend to be more powerful. To establish the strongest competitive position, you need them and data-enabled learning. However, few companies are able to develop both. Nevertheless under the right conditions customer-generated data can help you build competitive defenses, even if network effects aren’t present. In this article we’ll walk you through what those conditions are and explain how to evaluate whether they apply to your business.
Companies built on data have been around for a long time. Take credit bureaus and the information aggregators LexisNexis, Thomson Reuters, and Bloomberg, just to name a few. Those companies are protected by significant barriers to entry because of the economies of scale involved in acquiring and structuring huge amounts of data, but their business models don’t involve gleaning data from customers and mining it to understand how to improve offerings.
Gathering customer information and using it to make better products and services is an age-old strategy, but the process used to be slow, limited in scope, and difficult to scale up. For automakers, consumer-packaged-goods companies, and many other traditional manufacturers, it required crunching sales data, conducting customer surveys, and holding focus groups. But the sales data often wasn’t linked to individual customers, and since surveys and focus groups were expensive and time-consuming, only data from a relatively small number of customers was collected.
That changed dramatically with the advent of the cloud and new technologies that allow firms to quickly process and make sense of vast amounts of data.
