Data is not the future
Data is not the future—it's the past.
I mean that literally.
Everywhere you look there is talk about how data is the future, data will be the currency of the future, and data is the new oil.
And in the midst of it, we've lost sight of what data actually is and what it isn't.
Data is not an oracle.
Data is a record of the past. How many cities there are in my home state of Washington, what time I posted this newsletter, how many of you engage with it, what cities you are from—each one is a record of something that has already happened.
I used to work at an office directly next to a Top Pot Doughnut store (s/o to my fellow Seattleites🍩), and every day a record of my trip to this location was logged as data.
One day as I was pulling out of my driveway, Siri predicted where I wanted to go and suggested that traffic was light, so it would only take 13 minutes to get to Top Pot Doughnuts. I was amused that Siri was enabling my supposed donut addiction, and it's a powerful example that data is only a record of what has happened (knowledge), but data doesn't understand anything.
Data can tell me our current sales figures, and how well we're doing against our targets, but it can't tell me why.
"Wait a minute!" my friends in consulting and tech firms are no doubt thinking. Hang with me:
Diagnostic analytics is a process by which humans endeavor to develop analyses and reports to answer the question of why something happened, but the data itself does not know why anything has happened.
So, in the sales example, there are countless instances where the sales teams are hitting their numbers, as are the marketing team, the product team, and the support team. Everywhere you look, the data records indicate that the business is on track.
Yet customers are leaving for competitors.
Answering the question of why can be done by expert systems in situations with steady, predictable repetition. In all other cases, it requires humans.
Data is like a book.
The data that exists in your organization is like a set of books in a library. Every library has irrelevant and poorly written books as well as relevant and well-written books.
In the current dialogue about data, the emphasis is placed on data as if it is valuable in and of itself. I propose that we instead place the first emphasis on our people, because the greatest book in the world, if never read or if misunderstood, would have little to no effect on the world. Even merely a good book, on the other hand, in the hands of a great person, could spark tremendous effect.
In attempting to harness the potential of data, many well-meaning leaders are bringing in experts from technology companies and consulting firms to assess the value and possible application of their data while excluding the experts of whose work the data is a record. I call it Data Science Taylorism.
The problem is that all of that data is written in a language only the experts at your organization can understand.
You can spend your whole R&D budget having data scientists find correlations to predict something that doesn't matter or is from a system that the experts know is being discontinued in 2 years (I've seen it at more than a few Fortune 500 companies).
If data is like a book, and your organization's vast amounts of data a library, then the most important question is who is going into that library, what are they reading, and how are they using the knowledge they are gaining?
We are the future.
When the data predicts x% probability of a xyz outcome for something you're planning, regardless of how good the data science team is, how well structured the data—it's still only a prediction. Someone still needs to make the decision and take the risk to invest, not invest, hire or not hire.
And that isn't going to change for any work that isn't highly repetitive.
When you set out on an initiative, especially anything innovative, your ability to access knowledge/data records of the past related to the project is important, but it is less important than the humans you choose to partner with, their expertise, how well you all work together, and your collective ability to understand both the data and all of the context that hasn't been or can't be captured in a dataset.
The data showed that the smartphone market wasn't worth investing in in the early 2000s. It also showed that you couldn't land a rocket. And it showed Blockbuster that they should stop investing in Blockbuster On Demand (a streaming platform they had successfully piloted in 1995).
This is why organizations need to evolve from being Data-Driven to Reason-Driven (more on that in Chapter 15 of Autonomous Transformation or a sample here). Our human skill of reasoning is more valuable than data alone, and data + reasoning, especially when accounted for rigorously, is the most powerful and scientific combination for commissioning expeditions into the unknown and accomplishing work that is innovative and meaningful.
Thanks for reading,
Brian
*Special footnote for my friends who couldn't stand my use of "data" in singular tense. Please direct any concerns to Merriam-Webster, where it states "Data leads a life of its own quite independent of datum, of which it was originally the plural."
Whenever you're ready, here are 3 ways I can help you:
My LinkedIn Learning Course launched on October 3rd: Organizational Leadership in the Era of AI. This 48-minute course is packed with frameworks and insights to help you lead in the era of AI using the new system of leadership I introduced in Autonomous Transformation and is free to anyone with a LinkedIn Learning subscription.
If you want to go deeper as an individual, you can sign up for my live course Future Solving Fundamentals. My flagship live course on how to position yourself in the future in the era of AI. I share over a decade of AI strategy expertise, proven methods, and actionable strategies. This course sets the stage for a new era of value creation with artificial intelligence. Join leaders from Microsoft, Accenture, Amazon, Disney, Mastercard, IKEA, Oracle, Intel, and more.
If you want to go deeper as a team or organization, I’ve partnered with LinkedIn Learning, Emeritus, and Duarte to create tailored Future Solving™️ programs that leaders at Fortune 500 companies are implementing to help reembrace science in their decision-making and meet the complexities of the 21st century with a system of leadership, strategy, and decision-making that is built-for-purpose for era of artificial intelligence. You can reach out to connect and learn more here.