Don’t Get Bogged Down by Semantics and Other Tips for IM Pros

What’s next for information management? Information management professionals, like all of their business colleagues, are at an inflection point as we come up on the second year of the pandemic. I recently participated in an AIIM webinar entitled, “Like a Phoenix Rising From the Ashes, IM Leaders Should Seize the Opportunity” which tackled the challenges and opportunities for information management moving forward. 

AIIM president and CEO Peggy Winton led the discussion, based on issues identified in AIIM’s recent report, “State of the Intelligent Information Management Industry” (registration required).

The webinar covered a lot of ground, but I wanted to focus on a few important threads: namely our long-term response to the COVID-19 pandemic, the future of information literacy and the importance of definitions and the use of language for information management professionals.

Information Management’s Next Move as the Proverbial Phoenix 

In discussing the near future, and the potential post-pandemic midterm (2023?), Winton envisioned information management rising from the ashes, phoenix-like, to assist organizations in reaching better outcomes for customers, employees or other stakeholders. Winton rightly noted that “IM for IM’s sake” has failed to gain traction, budget or indeed create any value beyond perhaps highly regulated industries, where it is more “IM for the regulators’ sake.”

One highlighted item from the state of the industry report which came up in the discussion was the lack of executive-level ownership and responsibility for information across an organization. It seems to me this problem has been prevalent for my 20 years as an AIIM member. If we still can’t get to the point where the chief information officer is actually responsible for information itself, and not just the IT organization, then perhaps we should just give up trying. I mean it’s almost 15 years since Bob Boiko wrote his book, “Laughing at the CIO.”

Instead, information managers should focus on supporting a line of business to achieve its business goals and show how information management can actually create business value. Find a line of business, group or team that needs help in achieving their goals, and dive in to help them.

Related Article: Enterprise Content Management at the Crossroads

Are We Managing Data or Information?

During our conversation, Winton noted she was seeing a lot of confusion between data and information. She quoted the Gartner definition of data literacy: “The ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied, and the ability to describe the use case, application and resulting value.”

AIIM describes the practice of intelligent information management (IIM) in a very similar way. So are data and information interchangeable words? No. The two have very specific meanings, and are no more interchangeable than information and knowledge are. Each has very specific meanings and we can describe how they work together, but as I have said in many of my articles on knowledge management, don’t get caught up in the somewhat academic debates about definitions. Instead, work together inside your organization and figure out what definitions work for you, in your context. When everyone is in agreement that you are talking about the same things, when you have a shared understanding, then you can progress and do good work together.

That being said, let’s look at the basic progression, often called the DIKW pyramid, to help tease out the differences. Data provides the broad base at the bottom of the triangle, progressing all the way up to Wisdom at the pinnacle. But as Wisdom rarely comes up in the enterprise conversation, let’s focus on the main three:

1. Data: Individual items that create sets of qualitative or quantitative variables about an object.
2. Information: Data that has been analyzed in a given context. The context is often provided by metadata.
3. Knowledge: An understanding of a subject based on applying experience to information.

Data to Information to Knowledge in Context

Let’s bring these abstract definitions to life with a little story: Imagine a retail organization that sells large numbers of a widget. Every time a widget is sold, the Point of Sale system updates a database with information on that sale. At any time we can visualize that data by pulling into various graphical representations to show that we have sold 100 widgets per hour, or 10,000 per day.

However such raw data isn’t particularly useful to our sales teams. They add context, such as the specific type of widget, the location it was sold, whether the customer has bought our widgets before etc. This information is more useful, as we can see that we sell more widgets in fall in Toronto than we do in Dallas. But why does Toronto outperform Dallas?

When we process that information with other items of information, including the vast experience of our sales team, we can synthesize knowledge to provide actionable insights. In this case, the sales team can figure out that the widget has a seasonal sales cycle, that the store in Toronto positions the widgets differently, and that there was a sale on an adjacent item, all adding up to greater sales of our widget.

So depending on your field, you may have strong feelings about data being different from information, especially if you have a bunch of certifications and the word appears in your job title!

Related Article: Knowledge Management vs. Organizational Intelligence: What’s in a Name?

Work With the Definitions That Work for You

If using the term “data literacy” instead of “information literacy” or “knowledge management” helps your organization’s digital transformation progress, by all means, go with the flow. If your organization historically has put effort and investment into an information management center of excellence and less into a master data management team, that will influence where you want to locate your new robotic process automation team, for example.

The bottom line is that, while definitions are crucial for our academic and professional development, tied to training courses, certifications and job titles, when it comes to the specific context, business objectives and strategy of your organization — be prepared to be flexible. Read the room. Don’t get stuck in an argument about whether its data or information, but consider the good you can do and the business value you can generate if despite being a Certified Information Professional (as I am) you can talk about data literacy and how improving it across your organization is going to bring benefits.