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Data vs. Information vs. Knowledge vs. Wisdom

Competitive Intel | Advisory | Fahrenheit Advisors

The world at large uses the terms data and information interchangeably. And sometimes the terms knowledge and insights are bundled with them as well. If you’re sitting around a table during Happy Hour (back when that was a thing) catching up with friends, odds are your audience doesn’t know (our care about) the differences. If you were to say step into a room join a Zoom call full of researchers and analysts and you better watch your tongue.

Experienced market intelligence and competitive intelligence practitioners know better, sometimes those new to the discipline may need a quick crash course in the proper use and definitions of these common terms.

Often we see when Market or Competitive Intelligence (M/CI) initiatives are launched, they are tasked to someone who has no formal training conducting M/CI work and yet they are leading the charge and learning as they go. If you consider yourself in this group, we are here to help.

You will soon see, the distinction between these terms is incredibly important for understanding how to make actionable decisions on strategic initiatives.



Data is raw, unanalyzed, unorganized material that is the result of observing events, environments, and ourselves by our senses and modern sensors.

It is the most primary form of all the various materials we will cover today.

Data is the most basic form of material you can collect. Let’s walk through an example to illustrate these difference. We will use a traffic light in our example. Two data points easily collect from traffic lights are the fact that they have three lights and there are different colors: red, yellow and green.

This amounts to two separate data points: numerical data (the number three) and data about color (red, yellow, green). By themselves these two data points mean very little.



Information is the set of data that has already been processed, analyzed, and structured in a meaningful way to become useful, and usually represents patterns that can be recognized from data.

Information helps us understand what things are. It takes data and makes it useful.

Returning to our traffic light example: information from a traffic light would consist of collecting the two data points mentioned above,  about the number three and the colors red, yellow and green. It would put that together to say that “a traffic light has three lights which are red, yellow and green.”



Experience and intuition leads to knowledge, which makes sense of information within the context surrounding that information.

Knowledge moves us from information, which helps us understand what things are, and allows us to now understand how things are.

Returning to the traffic light example: our experience with traffic lights tells us that red means stop, yellow means that a red light is coming, and green means go. Additionally, the context of our situation becomes relevant.

Say we see construction in the vicinity of a traffic light. Our experience with this contextual information may tell us that it will now take longer for us to get through this traffic light because of the construction.


Wisdom represents human beliefs, purposes, values and judgement which allows us to make decisions based on knowledge.

Wisdom builds upon the understanding of how things are from knowledge, and transitions us to making judgements about why things are.

Returning to the traffic light example: because of all the knowledge we have about how traffic lights work, and the understanding that construction will slow our movement through a traffic light, we can now transition to using that knowledge to make decisions.

We can now make a judgement call and choose to take a different route that does not require us to go through the traffic light, so as to get to our destination faster. My belief that the other route will be faster, based on the context I have applied to my situation gives me the wisdom to make a choice.


Other Related Terms

In this discussion, there are a few other related terms that often arise, which make sense to visit as part of the same discussion.


Insight is defined as the capacity to gain an accurate and deep intuitive understanding of a person or thing.

Within the context of our discussion of data, information, knowledge, and wisdom, insights fall into the realm of knowledge. Our ability to gain an accurate or deep intuitive understanding of something leads to our ability to create knowledge out of information.

A new insight about a topic will help you to better apply the context needed to turn information (what a thing is) about that topic into knowledge (how that thing works).

We can again use our traffic light example to illustrate. When you were a kid, sitting in the back seat of a car as your parents drove, you likely asked a question like: “What does the red light mean?”

At which point, your parents likely explained to you that a red light means “stop.” This insight into how traffic lights work helped improve your ability to apply context and increased your knowledge about traffic lights.


Analysis is defined as a detailed examination of the elements or structure of something.

Within the context of our discussion of data, information, knowledge, and wisdom, analysis again falls into the realm of knowledge. The act of analyzing information provides you with more context and information to inform your knowledge about that thing.

Let’s go back to our traffic light yet again!

Now that you are an adult, and no longer the kid sitting in the back seat, you’ve probably spent many years driving. And in those years, you’ve likely encountered construction on numerous occasions.

Without knowing it, after encountering it enough times, your brain analyzed all of the past times you ran into construction to more deeply understand the effects of said construction. Upon this detailed examination, you developed an insight that “construction at a traffic light makes it take longer to get through the light.”

Your subconscious analysis led to an insight which helped improve your knowledge about traffic lights.


How Does All of this Relate to M/CI?

So now the million dollar question, why is this important to those of us researching and analyzing our markets and competitors?

First and foremost, these definitions are important in understanding your role. As a M/CI practitioner, your job is to provide knowledge to your organization. That knowledge may have different recipients ranging from executives or members of your board to business unit leaders for various departments.

What they all require from you is knowledge. Data isn’t useful to them in its basic form. Information, while more useful than data, still doesn’t provide value. It is only after your analysis of information, that context is applied and knowledge is created.

Your responsibilities include gathering meaningful data, organizing it into information that only after analyzed by you will become the knowledge you share with your organization. It’s not until this third action, that your work has value.

The M/CI practitioners delivering the greatest value to their organizations are those that leverage tools to assist with collecting and organizing their data. Those using tools with artificial intelligence capabilities are able to further reduce the level of human effort needed to transform data to information. A key benefit M/CI analysts augmenting their work with a tool experience is more time to performs their most valuable task; creating useful knowledge for their organization.

The Fahrenheit team can help you earn a higher and faster return on your investment in market and competitive intelligence initiatives.  Schedule a call today.


Peter Grimm leverages his background in national security and experience as a strategy consultant and PE-backed CEO to help clients navigate rapidly changing environments. He is skilled in corporate strategy, market analysis, competitive intelligence, disruption planning, disruption preparedness, and organizational leadership.

Following service in the US Navy and as a counterterrorism analyst at a US government agency, Peter spent 8 years in the Strategy Practice of Deloitte Consulting.  Peter then served as CEO of a PE-backed consulting and technology firm, leading the company through two successful exits.  He’s helped middle market companies, Fortune 500 firms, and Federal agencies “see around the corner” and turn threats into opportunities.