Taylor Davidson · Information, Intelligence, and Wisdom. There's a business in every part of the stack.

Data is great. Analytics are great. But the applications of data are even better.
by Taylor Davidson · 27 Apr 2011
Discussions, discussions. New York, NY

A couple weeks ago I tweeted:

Here’s what I meant by that.

Information, intelligence and wisdom are not the same, but they feed into each other. For the sake of a simplistic discussion, let’s think of these three areas like this:

Information = data
Intelligence = insights drawn from data through analytics and algorithms, a combination of pure qualitative number-crunching and qualitative thinking
Wisdom = combining data and insights into a broader view (over time, industries, areas, etc.)

“Big data” is a tremendously popular buzzword at the moment in the web world, and many entrepreneurs and investors are making big bets on big data (including, in a way, me) A common thought I heard at GigaOm’s Structure 2011 conference in NYC a couple months ago was that few people truly understood what big data meant, or how “big” is big. But to a degree, it doesn’t matter:

We’ll always need better ways to manage data and turn information into intelligence and wisdom. “Big data” isn’t new: the equilibrium level of “big” changed throughout the years, constantly changing our notion of what’s “big”. More importantly, the basic challenges of developing better ways to make better, easier, faster and cheaper decisions is constantly changing. Rather than investing in “big data”, I’d rather invest in “big wisdom”.

Four points about the data value chain

The data value chain isn’t static because the distribution of value changes over time as different data stores become available over time. As data becomes more available and easier to process, intelligence becomes relatively more important and a bigger driver of value in the chain. As intelligence becomes easier to create, more and more value is derived from wisdom, from the insight-driven actions taken with data.

The data value chain differs across industries. It’s very hard to get certain types of data, and very hard to get others. Take a look at traditionally-inefficient industries, and you’ll typically see information asymmetries at the root of the inefficiency. When one person holds power over a bit of data, they hold a bit of market power over other participants, and it’s traditionally in their best interest to hold onto that data as much as possible. Data can be a great source of economic rent.

The data value chain builds on itself. Wisdom is impossible without intelligence. Intelligence is impossible without information. Each one feeds into the other, in a stack reminiscent of the software stack. As much as building each part of this stack can create value, building better, easier, and cheaper ways to link these parts together are enormous opportunities for value and profit creation.

Thus, we can act on data, we can act on intelligence, we can act on wisdom. But wisdom is the most powerful and enduring source of value-creation. The difficulty: wisdom is hard to scale, and even harder to value. The real challenge isn’t in finding the most important bits of information, but customizing it to the individual level to reduce the transaction costs of integrating knowledge. In practical terms? How easy is it for you to give solid advice to a client without taking the time and effort to truly understand their situation? And how easy is it for the client to understand the value of the “black box” of your wisdom before they receive and implement your advice?

##What does this mean for business people?
There’s a business in every part of the stack. And, in large enough industries with large enough transaction costs, there’s a business in a) translating information -> intelligence and b) translating intelligence -> wisdom.

We all understand the value of aggregating, structuring, organizing and providing access to big data. It’s been the foundation of many businesses for years. Think of all the data providers out there tracking and selling data about who we are, what we do, what we buy, which websites we visit, etc. Examples abound.

The next step, intelligence, tends to be a core competence of a business rather than a business itself. Companies use data to derive insights and make decisions every day. What we see on the web, in what we read, in what we see on TV, every day, is targeted to us based on what a company thinks they know about us. This is a big part of what most of us do at work every day.

What businesses are based on wisdom? Strategy consultants are wisdom businesses, but they highlight a problem: wisdom businesses tend to be services rather than products. My biggest wonder right now: can a company create a productized-wisdom business?

And, which area of data / intelligence / wisdom in which industry is the biggest startup / investment opportunity right now?

In short: Data is great. Analytics are great. But the applications of data are even better.


Infographics. During a conversation among very smart people today, we declared our love for infographics for how they make data so easy to digest, understand, and act on. Infographics are traditionally very hard to do right, which isn’t surprising: translating data -> intelligence -> wisdom is hard, and can be the base of a business. JESS3, for example, is an agency that has built their business on creating data visualizations.

The thought: is it possible to turn the infographic creation process into a product? Take the example of Visually, a company that is working to create an easy way to create and share data visualizations (i.e. infographics). Will it work? Don’t know. But it’s an area someone, someday, will solve.

Related: Interesting thoughts on facts, noise, data and information by Michael Lewkowitz.