An article written for the industry.
If information was depicted as water, would the information in your organization look like the stream on the left, or more like the stagnate water on the lower right?
To compete in today’s world you need a constant, reliable supply of fresh, clean information. But what does that look like?
If you grew up in a city, and had never been out of the city, you might think fresh, pure water came out of the faucet. That water is probably “safe”, but tastes of chemicals and might even be off color. If you grew up in the mountains and came to the city, you might not even want to drink the city water.
The responsibility of today’s CIO is to provide the best, purest, information to the organization. Years ago, the CIO’s responsibility was to be a “data processor” and we did that with truck loads of green and white paper, fresh and hot off the printers.
The IT organization of the future will have data volumes that we can only guess at. “Users” will be data savvy, more so than ever before. They will have tools that will replace many of the functions of the current IT staff. IT will, and should look different from what it is today.
When telephones were invented and usage started to grow dramatically, someone estimated that the growth in phone usage would eventually require that everyone would have to be employed as a telephone operator.
Phone usage has exploded far beyond that individual’s imagination but we essentially have no telephone operators today. IT departments like today, will be extinct in the future.
The CIO of the future will be the provider of “Pure Information” and the custodian/protector of the data. In order to do that, the CIO will not be a “geek”, but rather someone with strong business acumen who knows technologies; is part of the executive team; understands what Pure Information is; and has the ability to provide and protect it.
Definition of “Pure Information”
If the future is all about Pure Information, what is it and how do we get it?
First, let’s define what it is.
Years ago I was asked to start a collegiate program in “Information Management”. I was often asked what that was. I didn’t have a satisfactory answer because the word “information” was misused and very loosely defined.
I searched for an adequate definition without success. I found that there were as many different definitions of information as there are differences in the quality of water.
If I had to put out a fire, and asked you for water, I wouldn’t care what the quality was. If I were serving water to a guest at dinner, I would care. If someone was going to inject water into my veins, the type and quality of water would be critical.
The same is true of information. Some of what we call information is worthless. Do we settle for information as we have been given, or do we thirst for something better?
As I worked on the definition, I started to list the criteria that would describe what information is, and what data is. Information can be described on a scale where “Raw Data” is on one end, and “Pure Information” is on the other end.
The term “Information”, as used today, can be anywhere on the scale from Raw Data to Pure Information.
Let’s start by defining “Data”. “Data is simply the raw building blocks of information. Data is a value associated with an attribute about something. Data has no value”.
The fact that data has no value is critical.
If I told you, “The car is red”, it would have no meaning and no value. The fact that the car is red is data. I have associated “red” with the car.
When I take this fact and associate it with “the car that hit your car in the parking lot”, it has meaning, relevance, and value. It is now not just data, but has some value. You now know that the car that hit your car is red.
Pure Information further defined
One of the first conclusions I came to was that there had to be a decision to be made before there was any value.
In the previous example, we assumed that your car was hit in the parking lot and you were looking to find out who did it. What if you already knew who did it? Would you really care what color the car was? No. So in that case, the color red is really still just data.
Let’s start building the criteria for, or qualities of, “Pure Information”.
1 By definition, information has value.
2. The second criteria, there must be a decision to be made. There must be a problem to be solved or an opportunity to be taken.
3. And third, there must be a decision maker. It could be human or automated. It doesn’t matter. If there is no mechanism for making a decision, nothing changes, and the data has no value.
I have seen many cases where corporations bring in data that could bring real value but there is nothing in place to alert someone and no automated process to take advantage of it. That is a lost opportunity.
Let’s further refine Data into Pure Information.
Most everyone makes decisions at one time or another without any information. Our past experiences and knowledge allow us to make good decisions. “I want steak for supper” is an example. I don’t have to be presented with any data or information to make that decision.
We do the same thing at work. We are presented with a problem or opportunity and we instantly make a decision. Often times, it is a good decision with real value but we didn’t get, or need, any information to make that decision.
However, when a decision maker is presented with Data that alters a good decision into a better decision, the Data that was presented is really Information. That leads us to the next point.
4. There is a change in behavior. A different decision, with a higher value is made. Instincts and knowledge suggested one course of action but the Information presented changed the decision and outcome.
If the decision maker would have made the same decision anyway, there is no increased value. The Data remains just Data. It might make the decision maker feel better, but that adds no real value.
When the decision maker changed the decision, the decision maker was surprised with the Information. This is the last criteria.
5. Information has a surprise value. Something wasn’t anticipated.
Note that if the decision maker makes a different decision that results in a worse outcome, there is a negative value and that is called “Misinformation”.
To summarize, Pure Information requires:
- information has value,
- a problem or opportunity exists,
- there is a decision maker,
- there was a change in behavior, a different alternative was selected, and
- there is a surprise value.
Definition of “Pure Information”
I define “Pure Information” as data with a surprise value, in the hands of a decision maker with a problem, that causes that decision maker to make a decision that otherwise would not have been made. That decision must have a real value greater than the value of the original alternative.
Simply put, Pure Information causes someone to make a decision that he wouldn’t have made and that decision resulted in a better outcome.
And what is the value of the Pure Information? It is the delta of the two outcomes.
Value of new process
less Value of previous process
Value of Information
It should be noted that the value of information always diminishes over time. The speed with which information is provided is another dimension. Information needs to be provided quickly. Decisions must also be made quickly.
If your “Information Systems” were changed to “Pure Information Systems” you would have increased revenue, reduced costs, and better customer service.
CEO’s should require that the CIO’s and the rest of the organization work to provide Pure Information Systems.
Now that we know what Pure Information is, how do we get it?
Creating Pure Information Systems
Just like water, we can start by filtering. We see that in many of our systems today. We then go through efforts to clean up the data just like cities do to make our water safe. In the end however, we end up with data that is safe to use.
The data is safe but it may not look right, taste right, or pass the smell test. We accept it and get used to it.
I often find that a new employee comes into the organization and notices that the information doesn’t look right, taste right, or has a smell. They might initially say something about the systems but they quickly get used to it like we get used to a city’s water after we move there.
If you have ever changed companies, you know what I mean.
Traditionally, if we don’t like the quality of our data and want to do something about it, we reprocess it and refine it. We invest in new systems, we patch up the old, and we bring in experts. But, in the end, we still end up with something like city water. Safe.
If we really want Pure Information, we must rethink the strategy. Take a look at the source. If it isn’t right, find another source. Then pipe it in and don’t let it become contaminated. And then be able to deliver it where it is needed, when it is needed.
If you do that you’d better be prepared. People will demand more and more. Just look at our cities. Billions are spent on bottled water.
Pure Information Systems should be our goal but that is far from easy.
Some of the issues that make Pure Information difficult are:
- Decision makers are all different. What might influence one individual will be different from another individual. Systems need to be extremely flexible.
- Decisions made at the executive level have a different criteria than those made at the transactional level. Systems need to be level sensitive.
- How do you provide pure information to a situation that has never occurred before? Properly defined Business Intelligence systems.
- How do you prevent “Data” from being presented? How do you filter out the data so that decision makers are only presented information? That requires systems intelligence.
- How do you bring in data from possibly hundreds of sources and still protect the quality and integrity? You must have exceptional database teams with the tools and properly trained staff schooled in data management and Pure Information concepts.
Pure Information Systems have to be flexible, dynamic, and quickly responsive. The databases and other infrastructure have to be well designed. The staff must be able to understand and appreciate the principles of Pure Information and data management.
Pure Information 100% of the time is very costly. However, we don’t need 100%. Even the purest of mountain streams are not pure. Note however that there is a huge upside potential to be realized when you have nearly Pure Information. It will be the savvy organization that can move from raw data towards Pure Information at just the right mix.
CEO’s and CIO’s of the future will have to understand these principles. The benefits are huge and the costs not insignificant. The successful CIO’s of the future will have to understand the principles of Pure Information and understand how to implement the systems.
- Recognize that the IT department of the future, and maybe even today, needs to be different. Focus has to be on creating data structures and sources so that information can be created from the vast amounts of dispersant data. Data security must be part of that plan.
- Ensure that your organization has its best talent managing data sources and data.
- Business Intelligence systems need to be created and maintained that provide Pure Information, not just pretty dashboards. (See BI definition below).
- Multiple databases and other sources must be able to be linked into one source of data. Inconsistent and separate data create misinformation and lost opportunities.
- The focus of your IT resources must be on creating Pure Information while still providing the transactional systems that are needed to support the business.
This concept, if applied, has proven to greatly improve the quality of systems. I have seen real payback in terms of improved revenue, reduced expense, and improved customer service. Once you make the effort to obtain Pure Information there is no turning back. You will wonder how you ever got along without it.
Additional Pure Information Terms:
Knowledge is the association of data in the form of facts based on past experiences. Knowledge has potential for value when combined with information.
Data is the raw building blocks of knowledge and information. Data is values associated with attributes about an entity. Data has no value.
Metadata is knowledge about data. There are two types of Metadata; Business Metadata and Technical Metadata.
Database is a managed collection of data such that knowledge is created. It is often managed through the use of a database management system.
BI (Business Intelligence) or Decision Support is the state of having the tools, and data in place to immediately answer the questions not yet conceived.