All Posts

A New Approach to Data, Content and Knowledge Management - Do it Right

Our information landscape is changing faster than ever – solving problems in the short term while preparing for the future requires a different way of thinking about data, content, and knowledge management and the technologies that we use to create value.  The new way?  Do it right. 

The past decade has ushered in a vast amount of change for anyone who works with information.  Since everyone works with information, that means everyone has dealt with this change.  A decade ago we were not walking around with supercomputers in our pockets.  We could not connect with tens of thousands of people instantly.  Media was not turned upside down with consumers of content becoming producers.  Technology organizations did not have cloud computing at scale as they do now.  We had fewer tools, technologies, software applications, options for consumption, computing power, data sources, and analytical methods.

The information world is more mature, more capable, more accessible and more flexible than ever.   

Why do we still have trouble finding our stuff? 

The answer is that although most companies have tools, technologies, and applications in abundance for knowledge management, they are not using these resources in the correct way. The primary need at this point is to apply thoughtful human judgment in order to optimize the use of the knowledge resources that are already available. In addition, rather than seeing information access as a project with a beginning and an end, companies should see it as a program that requires continuous maintenance and investment in order to stay relevant. Otherwise, performance will gradually deteriorate.

It’s not about checking the knowledge management box

Here is a perfect example.

EIS was called upon by a professional services firm to make recommendations for improving information access and management.  At first glance, it seemed that this company was doing all the right things.  The company had collaboratively developed its taxonomies and content models, created use cases and tested them to validate assumptions, developed metrics and governance programs, implemented faceted search, and so on. 

But digging a little deeper, EIS discovered that the collaboration was not what it first appeared to be.  Rather than working sessions with exercises, post-it notes, discussions and example content, a manager had circulated a spreadsheet with the terms he thought were appropriate.  Other employees added or changed terms, and this was the extent of the collaboration. 

This level of interaction was not sufficient.  Asking detailed questions about the other steps made it clear that they were missing important details of information architecture best practices.  In response to our question: “Did you test the process by having users upload content and apply tags?” the manager replied “Not really.” Then we asked if other users were recruited to locate the content after it was uploaded.  “No, we did not have time for that.” 

After reviewing the various steps to the process and asking how they were accomplished, it became clear that though on paper it appeared that the company was “doing everything right,” this was not actually the case. We have found this scenario numerous times, when an organization thought it had done the right thing but key steps were missing.

Lack of funding?  Or, lack of expertise? Or, lack of discipline?

What’s interesting is that the reason typically given for this type of shortcoming is that the project was under-resourced—in particular, there was not enough funding.  While I understand that argument, I don’t buy it.  Content management, knowledge management and data quality programs burn enormous amounts of money, time, and organizational resources.  There are teams responsible for maintaining technology infrastructure.  Large consultancies and technology vendors bill their clients millions of dollars for information programs – in some cases without solving core findability problems.  

Here are a few possible reasons for the disconnect between state of the art and state of the practice with knowledge management:

  1. Vendors focus on the wrong part of the problem. Technology vendors focus their efforts on standing up the tool, addressing integration issues or migrating content and data.  Less thought is given to the curation of assets, architecture, and information lifecycles.
  2. Lack of expertise. Sometimes as part of a project we hold a stakeholder workshop on SharePoint IA.  There were always people who  attend and say, “I wish I had learned this two years ago.”  But when we would get into the exercises that followed the instructional portion of the class, it was still difficult for the students to apply principles correctly.  The reason is that they were not information architecture experts.  SharePoint IA was not their full time, day-to-day job—they did not have enough contact with the problems to build proficiency.   
  3. The right information management practices have not been correctly operationalized. In some cases, this failure is due to a knowledge shortfall, but it also stems from a lack of awareness of the impact of poor information management practices on organizational efficiency and effectiveness.  If leadership could see how much time people spend re-creating information and searching for things that should be at their fingertips, significantly more attention would be paid to this problem
  4. Insufficient socialization and change management.  Even when the problem is receiving attention and the correct architecture has been developed, not enough resources are devoted to changing how people interact with information and do their jobs.  If people don’t use the intranet and instead continue to email content, the problem will not be solved.
  5. Long-term funds have not been allocated to maintaining the desired state. Once the knowledge management system is in use and has been accepted by employees, the environment needs to be refined and maintained on a continuous basis.  Too often, resources are allocated to a project when what is needed is a longer-term program.

The bottom line is that there is a lack of discipline in information management.  People don’t follow the process, or perhaps the correct process was never established.  This approach would not be acceptable in the finance department.  No one would say, “Controls are just too time consuming,” or “I’d rather not have to do things that way,” or “I’m too busy.”    

Informed leadership is key to Knowledge Management program success

The answer to these issues is an informed leadership that understands the fundamentals.  In organizations that depend on curated information (for example, industrial supply companies that compete based on how they expose data to customers), the C suite gets it.  They know that customers who can’t find a product will go to a competitor. 

The challenge with internal processes is that “customers” (the internal users) can’t go someplace else.  They have to suffer through poorly organized information and rely on workarounds and fixes.  The impact on the organization is not readily apparent.  Rather than losing customers, processes become less efficient, the inefficiencies add friction that slows down information flow. 

As a result, programs take longer to implement, products get to market more slowly, the pace of innovation drops, and the organization becomes less responsive and less agile. Competitors can then take advantage of marketplace gaps and a slow, inexorable decline begins to erode sales and market share.  The impact of poor information hygiene is insidious and almost invisible.  It takes longer to get things done across the enterprise, but this decline happens in such small, almost imperceptible ways because it just becomes how the business operates. 

AI to the rescue?  I don’t think so…  

Ahh, but now we have artificial intelligence applications that will save the day, right?  No, I am sorry to say that AI runs on knowledge and data, and not having one’s house in order will make it more difficult to leverage these powerful new tools. Some AI applications can help with remediation and information extraction, curation, migration, and clean up, but they are not a quick fix. 

We still need to have the fundamentals in place. 

If you have knowledge management systems in place and you still can't find anything... well, then. you’re doing it wrong.

Need help with your own transformation program? Lay the foundation for your organization’s success with our Digital Transformation Roadmap. With this whitepaper, assess and identify the gaps within your company, then define the actions and resources you need to fill those gaps.

Seth Earley
Seth Earley
Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.

Recent Posts

Use Customer and Behavior Data To Create Personalized Experiences

The more quickly customers can find the product they are seeking, the more likely they are to complete a transaction and to return to the site in the future. Personalizing offers and making well- targeted recommendations can bring customers and products together faster, and are effective ways to engage customers by creating a more positive customer experience. In order to do this, companies need to capture and use as much relevant information as possible. The more that is known about the customer, the more effectively the recommendation system works. Customers generate many signals through their online behavior, and those signals can also be used to understand their interests, purchasing patterns, and needs. Reading their digital body language accurately and creating a valid customer model is essential to anticipating and fulfilling those needs.

How to Instrument KPIs Throughout the Customer Journey

You're probably using metrics to determine if your marketing programs are effective. But, have you selected the right metric at each stage of the customer journey?  Which ones connect to your strategic goals? In this session Seth Earley and Allison Brown talk about how each stage of the journey can be instrumented to use feedback from course corrections to further improve the process. You'll learn: Types of operational and user experience metrics and KPI’s How to select and collect the right metric for each stage of the customer journey How KPIs can be used for data-driven decisions How to manage conflicting goals and metrics

First Party Data - Managing and Monetizing the "Data Exhaust" From Your MarTech Stack

Understanding, anticipating and responding to the wants, needs and behaviors of your customer is the competitive battlefield of 2022. However, with new limitations and regulations regarding second and third-party data and tracking cookies, marketers, digital leaders and ecommerce executives have to consider their own methods of collecting and acting upon the data they gather about customers. In this webinar Seth Earley will talk with industry experts about how you need to model, collect, normalize, organize, manage, analyze, and act on customer information. The time to do so is now and we’ll discuss practical ways to move the needle on customer data, customer analytics and orchestration of the customer experience.