Forward-looking HR executives and chief learning officers know that their job is not only about facilitating the delivery of operational knowledge to their organization’s employees, consultants, and suppliers. They also realize that they can increase the overall operational efficiency and performance of their organization by identifying and leveraging the paid-for knowledge that has been neglected or lost within their organization. It’s the age-old question: “How do we get more for less with what we have?”

This simple question has deep implications that, if answered, can result in HR’s and CLOs’ having a permanent seat on the board because the answer to the “more for less” question directly relates to the advantage and survival of an organization in a globally competitive world.

What is “paid-for knowledge”?

Paid-for knowledge includes two basic groups of knowledge. General records knowledge includes sales, customer service, inventory, accounting, and other records management that is aggregated during an organization’s daily activities. Deep knowledge is that vital, enduring knowledge that requires specialized training to define, understand, and use. These two groups of knowledge operate together, but deep knowledge transcends general knowledge in several different ways.

General knowledge tends to be rule-based and more routine, requiring users to know how to use specialized data and the applications that manage that data. Deep knowledge tends to be more intellectual and results in the development of intellectual property, trade secrets, operational know-how, and the lessons-learned knowledge that produces or enhances products, services, or operational functions and processes.

Once conceived, deep knowledge is gained through a trade-off process that involves planning, evaluation, refinement, and, ultimately, implementation.

For example, imagine the development of a policy and procedure manual that is distributed in numerous languages with unique content that is culturally sensitive and periodically updated due to regulatory and operational demands by a country or culture. This type of knowledge includes a matrix of deep legal, HR, distribution, and end-user training requirements that collectively increase the cost of managing the policy and procedure manual well beyond what the finished product would indicate. Two advantages of the manual’s deep value might include improved employee relations and a reduction in operational risk.

As organizational paid-for knowledge is made available and applied within an organization, its cost decreases while the leveraged value of that knowledge increases. This is especially true when deep lessons-learned knowledge is effectively transferred to others within and across an organization.

The paid-for knowledge problem

Large corporations may easily use a hundred or more different computer applications to develop and manage general records and deep knowledge, while an average employee may only know how to efficiently use two or three of these applications. As a result, relevant content developed and stored on disparate systems is very often duplicated and/or inaccessible to individuals who could use that knowledge to enhance their work effort. Over time, when knowledge is not distributed, it becomes forgotten or lost. This is especially true of knowledge that is applied on an intermittent or periodic basis.

When valuable organizational knowledge is inaccessible, under-utilized, or lost, the cost to an organization can be staggering in terms of reduced efficiency, performance, lost opportunity, and overhead. It is hard to see, but the reality of an organization’s knowledge deficit usually shows up in sales and financial statements. When this occurs, managers start asking themselves hard questions about how to solve abstract problems that most find difficult to grasp.

Another major problem with organizational paid-for knowledge is the old “infoglut” problem; that is, knowledge that is lost due to the sheer volume of data and information an organization amasses during the course of business.

At a deeper level, the infoglut problem also relates to knowledge resources that are structured with preambles, filler and connector words, and explanations to the point that core knowledge within these resources is difficult to find and comprehend—especially in the “heat of battle.” The reason for this is that organizational document creators write as much for the benefit of their peers as they do for the benefit of the reader/end user. Creators consider the reading audience, but in the process, they make sure that their work is properly structured and worded according to well-established conventions and formats so as to withstand the scrutiny of their peers. Sound structure, of course, is required for articles like this, but there are other, more effective ways to present knowledge for consumption.

Meaningless and useless information

Filler words such as “the,” “and,” “as well as,” and conventional information structures that require the reader to wade through preamble paragraphs before getting to key knowledge are a waste of time and effort for eLearners. In most cases, people are turned off by the time they reach the end of the preamble that tells a reader why the following information exists and how it should be used. In the heat of battle, people need the key information, insight, or step-by-step process without all the verbiage that the creators feel they need to insert into tutorials. Covering all the bases should not be the goal for eLearning presentations; answering key questions should be.

The fact is that the human brain naturally connects all the relevant information within information resources with or without all the filler and connector words. It can do this because most documents are usually developed around well-researched, well-justified rational threads (applied theory) that organize and bind the material facts and content together. The human brain doesn’t need the filler and connector words to comprehend the context, meaning, and purpose of the material because all of that is implicit within the relationships between the rational thread and the facts. Speed reading is based on this principle.

If I say that Jane is creative, studies art, paints, attends Columbia University, likes chocolate and hanging plants, runs along the Hudson River, drinks coffee at Starbucks, and so forth, the brain fills in the associated connections to provide insight into Jane’s personality, character, and interests without paragraphs of explanation.

Processes—such as step 1, step 2, step 3—operate the same way. The human brain automatically fills in most of the details on its own without the writer having to ramble on. This is how most people think: in chunks. In general, eLearning software should work the same way.

Emerging technologies leverage knowledge

Thankfully, there are knowledge-centric (rather than data-centric) systems that are showing up in the software market—such as Knowledge Owl, a handy web program that allows end users to create knowledge trees, and robust enterprise-class knowledge systems such as IQxCloud that are designed for eLearning, eMentoring, and organizational knowledge acquisition and management. These systems work the way people think because organizational information and data are wrapped around common, rational threads of thought that provide associated content its context, meaning, and purpose.

What this means is that once vital organizational knowledge “snippets” (the who, what, when, where, and how-much information and how, why, and what-if knowledge) are decoupled from the structural formatting limitations of conventional documents, books, manuals, and applications, these knowledge snippets can be dynamically reassembled in whole, or in part, with any other relevant knowledge content to provide a highly flexible, intuitive, 360-degree user experience. Now, these modern technologies allow eLearners to learn and apply vital organizational knowledge faster and more easily.


HR professionals and CLOs have powerful options available to them that could make a major difference to their organizations, and to their careers. New knowledge technologies provide advanced knowledge acquisition, management, and paid-for knowledge leveraging capabilities to solve immediate and unforeseen problems related to the acquisition and distribution of organizational knowledge. The short and long-term implications for an organization include:

  • General records learning—Organizational knowledge on demand
  • Deep learning—Insights and understanding
  • Problem solving—Application of lessons-learned knowledge to situations and circumstances as they occur
  • Leadership—Achieving sapient authority through knowledge acquisition, retention, and application