Zach Wahl: Profiles in Knowledge

Originally published September 22, 2023

10 min readSep 23, 2023

This is the 95th article in the Profiles in Knowledge series featuring thought leaders in knowledge management. Zach Wahl is CEO and co-founder of Enterprise Knowledge (EK), the world’s largest dedicated knowledge, data, and information management consultancy, based in Washington, DC. He has expertise in knowledge management strategy, governance, taxonomy, and content management.

In his role as CEO, Zach is responsible both for the strategic growth of the organization as well as the organizational development and culture. Under his leadership, EK has grown every year since it was founded, being recognized on the Inc. 5000, Virginia Fantastic 50, and Arlington Fast Four for the organization’s noteworthy rate of growth. At the same time, EK has been consistently recognized as a great place to work and as a philanthropic leader in the community.

Zach is a globally recognized thought leader in knowledge management, having provided business, management, and IT solutions to a global range of clients for 25 years. He has worked with over 200 public and private organizations to define strategy, road map, implement, and evolve knowledge bases, intranets, content management, document management, taxonomy management, websites (eCommerce and informational), and other information management systems. In support of these activities, he has run over 250 taxonomy design workshops based on his own business taxonomy design methodology.

Zach is the co-author of Making Knowledge Management Clickable: Knowledge Management Systems Strategy, Design, and Implementation. The book bridges the gap between KM and technology. It embraces the complete lifecycle of knowledge, information, and data from how knowledge flows through an organization to how end users want to handle it and experience it.

Zach has also authored a series of courses on knowledge management and is a frequent speaker and trainer on the subjects of information governance, web strategy, and taxonomy design. He also serves as a member of faculty for the Knowledge Management Institute, teaching classes and providing workshops on taxonomy design. He is the host of the Knowledge Cast podcast series.

Enterprise Knowledge was one of the three sponsors of the 2023 Midwest KM Symposium, where Zach gave the afternoon keynote presentation. He interviewed me for a Knowledge Cast podcast episode.

Background

Experience

Enterprise Knowledge, LLC — Chief Executive Officer, 2013 — Present
Project Performance Corporation (PPC)

Vice President — Strategic Solutions, 2011–2013
Director of Knowledge & Information Management, 2010–2011
Practice Leader — Knowledge Management, 2005–2010
Analyst, 1998–2005

Education

Dickinson College — BA, Political Science, Environmental Science, 1994–1998
University of Oxford — International/Global Studies, 1997

Profiles

Content

Enterprise Knowledge

Beyond Find: The Five Levels of Artificial Intelligence for Knowledge

Knowledge Management Trends in 2023

KM at a Crossroads — The organizations that learned their lessons from the pandemic and staffing shortages will continue to invest in KM, recognizing the critical business value offered. KM programs are much more visible and business critical than they were a decade ago, thanks to maturation in KM practices and technologies. Knowledge Management programs can deliver business resiliency and competitive advantage, ensure that knowledge is retained in the organization, and enable employee and customer satisfaction and resulting retention. The executives that recognize this will continue their investments in KM, perhaps scaled down or more tightly managed, but continued nonetheless. Less mature organizations, on the other hand, will repeat the same mistakes of the past, cutting KM, and with it, walking knowledge out the door, stifling innovation, and compounding retention issues, all for minimal and short-term savings. This KM trend, put simply, will be the divergence between organizations that compound their existing issues by cutting KM programs and those that keep calm and KM on.
Focus on Business Value and ROI — For KM practitioners, this means being able to measure business outcomes instead of just KM outcomes. Examples of KM outcomes are improved findability and discoverability of content, increased use and reuse of information, decreased knowledge loss, and improved organizational awareness and alignment. All of these things are valuable, as no CEO would say they don’t want them for their organization, and yet none of them are easily quantifiable and measurable in terms of ROI. Business outcomes, on the other hand, can be tied to meaningful and measurable savings, decreased costs, or improved revenues. Business outcomes resulting from KM transformations can include decreased storage and software license costs, improved employee and customer retention, faster and more effective employee upskilling, and improved sales and delivery. The KM programs that communicate value in terms of these and other business outcomes will be those that thrive this year.
Knowledge Portals — The use cases for Knowledge Portals vary, with some treating the system as an intranet or knowledge base, others using it as a hub for learning or sales, and still others using it more for tacit knowledge capture and collaboration. Regardless of the use cases, what makes these Knowledge Portals really work is the usage of Knowledge Graphs. Knowledge Graphs can link information assets from multiple applications and display them on a single screen without complicated and inflexible interface development. CIOs now have a way to do context-driven integration, and business units can now see all of the key information about their most critical assets in a single location. What this means is that Knowledge Portals can now solve the problem of application information silos, enabling an organization to collectively understand everything its people need to know about its most important knowledge assets.
Context-Driven KM — We’ve all heard the phrase, “Content is King,” but in today’s KM systems, Context is the new reigning monarch. The new trend in advanced knowledge systems is for them to be built not just around information architecture and content quality, but around knowledge graphs that provide a knowledge map of the organization. A business model and knowledge map expressed as an ontology delivers a flexible, expandable means of relating all of an organization’s knowledge assets, in context, and revealing them to users in a highly intuitive, customized manner. Put simply, this means that any given user can find what they’re looking for and discover that which they didn’t even know existed in ways that feel natural. Our own minds work in the same way as this technology, relating different memories, experiences, and thoughts. A system that can deliver on this same approach means an organization can finally harness the full breadth of information they possess across all of their locations, systems, and people for the purposes of collaboration, learning, efficiency, and discovery. Essentially, it’s what everyone has always wanted out of their information systems, and now it’s a reality.
Data Firmly in KM — Historically, most organizations have drawn a hard line between unstructured and structured information, managing them under different groups, in different systems, with different rules and governance structures. As the thinking around KM continues to expand, and KM systems continue to mature, this dichotomy will increasingly be a thing of the past. The most mature organizations today are looking at any piece of information, structured or unstructured, physical or digital, as a knowledge asset that can be connected and contextualized like any other. This includes people and their expertise, products, places, and projects. The broadening spectrum of KM is being driven by knowledge graphs and their expanding use cases, but it also means that topics like data governance, metadata hubs, data fabric, data mesh, data science, and artificial intelligence are entering the KM conversation. In short, the days of arguing that an organization’s data is outside the realm of a KM transformation are over.
Push Over Pull — When we combine an understanding of all of our content in context, with an understanding of our people and analytics to inform us how people are interacting with that content and what content is new or changing, we’re able to begin predictively delivering content to the right people. Sometimes, this is relatively basic, providing the classic “users who looked at this product also looked at…” functionality by matching metadata and/or user types, but increasingly it can leverage graphs and analytics to recognize when a piece of content has changed or a new piece of content of a particular type or topic has been created, triggering a push to the people the system predicts could use that information or may wish to be aware of it. Consider a user who last year leveraged twelve pieces of content to research a report they authored and published. An intelligent system can recognize the author should be notified if one of the twelve pieces of source content has changed, potentially suggesting to the content author they should revisit their report and update it.
Personalized KM — This trend has a lot to do with content assembly and flexible content delivery. It means that, with the right knowledge about the user, today’s KM solutions can assemble only that information that pertains to the user, removing all of the detritus that surrounds it. For instance, an employee doesn’t need to wade through hundreds of pages of an employee handbook that aren’t pertinent to them; instead, they should receive an automatically generated version specifically for their location, role, and benefits. The customized KM trend isn’t just about consuming information, however. More powerfully, it is also about driving knowledge sharing behaviors. For example, any good project manager should capture lessons learned at the end of a project, yet we often see organizations fail to get their PMs to do this consistently. A well-designed KM system will recognize an individual as a PM, understand the context of the projects they are managing, and be able to leverage data to know when that project is completed, thereby prompting the user with a specific lessons learned template at the appropriate time to capture that new set of information as content. That is customized KM. It becomes part of the natural work and operations of systems, and it makes it easier for a user to “do the right thing” because the processes and systems are engineered specifically to the roles and responsibilities of the individual.

Another way of thinking about these trends is by invoking the phrase “KM at the Point of Need,” derived from a phrase popularized in the learning space (Learning at the Point of Need). We’re seeing KM head toward delivering highly contextualized experiences and knowledge to the individual user at the time and in the way they need it and want it. What this means is that KM becomes more natural, more simply the way that business is done rather than a conscious or deliberate act of “doing KM.” This is exciting for the field, and it represents true business value and transformation.