How A Sandwich Shop Explains The Value Of Data
The word “data” can trigger some intense reactions, putting up metaphorical red flags in some consumers’ eyes. This is especially true in conversations around the technology industry. But we can get a clearer understanding of some common misconceptions about data by stepping outside of the digital world and into, say, your favorite neighborhood sandwich shop.
Before we go for lunch, a few important points about data to keep in mind:
1. Consumer Benefit: Data is collected to improve user experiences and provide more relevant content and lower costs.
2. Limited Utility: Data is often useful only for a short period of time, and only in certain contexts.
3. Use-Case Value: The real value of data lies in how it is used—not in the data itself.
4. Ubiquity: If one company has some of your data, that doesn’t preclude another company from also collecting it.
5. Not Oil: Data is not a scarce resource and lacks an inherent value.
Every day you stop by your neighborhood sandwich shop for lunch…
You visit the same sandwich shop every day, so the cook of course knows your favorite order and can have it premade and waiting for you. The shop can make sure they stock the right meats and breads so your sandwich is always available. By having more predictable ordering, the shop gets a discount from its purveyors, and passes the savings on to you. Data allows businesses to predict customer demand and use that information to lower costs and improve experiences.
Expert insight from Assistant Attorney General Makan Delrahim: “Platforms and apps pair large amounts of data with technology to create some of the economy’s most important innovations, including in medical diagnoses, weather forecasts, transportation safety, and language translations. These innovations are having a significant impact on almost every aspect of our daily lives, making possible many of the conveniences we have begun to take for granted.”
The cook notices you have switched it up recently by ordering no-meat sandwiches. She takes the liberty to recommend the new vegetarian options on the menu to accommodate your changing tastes. Data on past preferences has only limited utility as consumer preferences and behavior change over time.
Expert insight from Gregory Fell and Mike Barlow: “Most companies find it difficult to assess the current value of their data assets. Different companies place different values on similar assets. Additionally, the value of data changes over time. Data that was highly valuable two years ago might have depreciated in value—or its value might have risen. In either case, the level of control should be adjusted accordingly.”
Now a hypothetical: consider another sandwich shop in the neighborhood knows your preferences but doesn’t make the effort to analyze it and other customers’ order history, taking note of which sandwiches and types of bread are most popular. The cook at your go-to place, however, uses the information she’s gathered to make her restaurant the best it can be—offering the most popular sandwiches and providing strategic deals. It should come as no wonder that it’s your favorite place. The way a business uses data, and not how much data it collects, determines how competitive it can be.
Expert insight from Daniel Sokol: “It’s not how much data you have, it’s what you do with the data where there seem to be diminishing returns on data size, and we’ve seen that, in terms of companies that have lots of data don’t use most of it.”
You love your local sandwich shop, but when its competitor debuts a new menu, you decide to check it out. The shop across the street can now begin to take note of your preferences, just like your original favorite does, and can vie for your business in that way. Data is not exclusive to one business.
Expert insight from David S. Evans: “A similar story was true for Spotify. When it entered the U.S. 2011, Apple had more than 50 million iTunes users and was selling downloaded music at a rate of one billion songs every four months. It had data on those people and what they downloaded. Spotify had no users, and no data, when it started. Yet it has been able to grow to become the leading source of digital music in the world. In all these cases the entrants provided a compelling product, got users, obtained data on those users, and grew.”
It’s quite possible that your sandwich tastes will change over time. The cook at your favorite place has some stored-up knowledge about your years of frequenting his place, but now that you’re a vegetarian, you now prefer the new place across the street. The information the sandwich shop has, however, can still be useful for the owner in analyzing customer trends. Data can serve multiple utilities, and is only limited by the costs to store and analyze it.
Expert insight from Jakob Kucharczyk: “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.”