The Very, Very Inspiring “DIKW” Hierarchy

D I K W hierarchy

Image credit: Sean Wood

I want to discuss a framework that’s new to me, but not that new: It’s called the Data > Information > Knowledge > Wisdom Hierarchy, or the “DIKW Pyramid.”

I was turned on to it very recently, but it’s been around since at least 1982. It, or variants of it, have been used in fields as diverse as Information Science, Engineering, and Geography.

Different academics in different fields of study seem to disagree about how useful or smart the framework is, but I’ve been thinking about DIKW in terms of Web Analytics and Optimization (natch). And, it’s working just fine for me! 🙂

This framework helps explain the kinds of work I’ve been focused on for the last 10 years or so in Digital Marketing. Kindly allow me to explain…

The Hierarchy, much like Maslow’s Hierarchy, illustrates that there is a large and necessary “foundation” to the pyramid, but that we must aspire to continue moving up to more refined states in our work.

The foundation is “DATA.” Data is all the rage these days, isn’t it? We are drowning in amazing volume and variety of Data. It is arguably the “new economy.” It made headlines recently that 90% of the data in the world was produced in the last 2 years, so we are on a very steep data curve, indeed!

There’s tons of data, and it’s very powerful, and that’s all well and good. But, the challenge with data (especially Big Data) is that it is generally unstructured, messy, and often meaningless without smart humans to interpret it. Still, we live in interesting, data-plethora times. If we map the base of the DIKW Hierarchy to Maslow’s Hierarchy of Needs, Data is now as important to humans as sex 😉

When all the 1s and 0s of Data are collected, stored, and structured over time, suddenly we move up the pyramid to INFORMATION. This is where Data starts to develop into recognizable patterns. This is where smart people (and algorithms written by smart people) can start to parse data into recognizable chunks of Information.

Still, information isn’t always action-able. It begins to have meaning, but it’s not ready to motivate C-level executives to change their business plans.

So we must keep moving; aspiring. With some diligence, we reach KNOWLEDGE. Now, the Data is structured, and we’ve attached some meaning and context to it. Knowledge starts to get people interested, and forward-thinking folks might even start to change their behaviors and ideas based on this Knowledge. Still, eCommerce conversion rates hover in the single digits…

Knowledge is good, but it doesn’t always spur us lazy humans to action. How many times have you said, “I should’ve done XYZ; I knew better!” So, to change the world for the better using Data, you better keep pushing towards WISDOM. The top of the DIKW Hierarchy is where you do the right thing, take the right action, because all the Data, Information, and Knowledge points you towards the answer.

Wisdom is where you can convince your CMO to invest company resources differently, hire more smart people, pivot her strategy, etc. Wisdom comes about when you have sufficient Data to be confident, sufficient Information to grok the inherent meaning, sufficient Knowledge to understand the full context of the situation and convey all of that in compelling stories to those in power.

Wisdom is where you automatically do the right, appropriate thing because you see reality clearly. It’s where you can elegantly balance the needs of your business with the needs of your current customers and prospects.

Let me end with a more concrete example, now that I’ve taken you to Abstractionville. Let’s looks at the tangible world of Web Analytics, where I play every day:

Data: Some user action (a click, a hover, a post) causes a javascript tag to “fire.” This sends a string of information to a database somewhere. It contains information about date and time, location, operating system, referrer, href, # of previous pages, time on page, etc. But, it is raw, Baby, really raw!

Information: After amassing enough historical Data about a page or a user experience, the data flows into canned or custom reports where dimensions of data are matrixed against other dimensions. Averages are calculated as well as deviances. The data set can be sliced by different segmentation rules. It can be filtered and cleansed. You can zoom in and out to look at micro and macro. Patterns and anomalies become visible.

Knowledge: After looking at trends over time, and segmenting the Information by what marketing effort drove the traffic, or demographic information, we can start to make educated guesses about why the people behind the data are behaving a certain way. We can start to test our Knowledge or theories using A/B, Multivariate, or other experimentation tactics. We can combine quantitative knowledge with qualitative knowledge to see a bigger picture of our target audience. And we can start to influence behavior.

Wisdom: After years of Data collection, Information gathering (Analysis), and testing the bounds of our assumptions, theories, and Knowledge, we now have a level of Wisdom about the people we’re supposed to be serving with our websites or applications. We have high confidence, based on past data, past analysis, and past experimentation, how we should respond in near real-time to the needs of our audience. We have the love of our customers because we can intelligently personalize their User Experience without being “creepy” or feeling “awkward.”

Closing Opinion

Technology can do a lot of things, but it can’t reach the utopian Digital Marketing state I just described. It will take motivated, smart humans who want to work their way up the DIKW Hierarchy for the greater good.

Agree? Disagree? Was this just a high-fallutin’ rant?


One thought on “The Very, Very Inspiring “DIKW” Hierarchy

  1. I like how you use Time to help distinguish Knowledge from Wisdom, and that you offer a measure as well: Confidence. You also suggest that Personalization is best implemented only once Wisdom has been achieved, which I have found to be absolutely true. Customers understandably want to see results, but I think it’s clear that those results should be measured and delivered only as appropriate. Perhaps this model will be useful in communicating that essential idea.

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