Knowledge Management and User Engagement – Weaving the Experience into Work Practices

Organizations are maturing in their understanding of knowledge management.  But true engagement and acceptance is still a major obstacle to success 

Years ago, we at EIS began our KM programs by educating enterprises about core concepts of knowledge capture and collaboration as well as the foundations of information management – content architecture, taxonomy, content lifecycles, tagging and curation.  As I revisit organizations or am introduced to new customers, the landscape is different now.  People have core capabilities and competencies in the space, and many use centers of excellence models to support the enterprise.  The industry is maturing. 

Not everyone is there yet, of course; some businesses have not needed to formalize knowledge capture, and instead have relied on knowledge embedded in the organizational memory and codified in systems and processes. Increasingly, however, every business is learning that real efficiencies can be gained by improving the KM Maturity and as AI and chatbots take hold, those that do not have curated knowledge will find themselves scrambling for “training data” to enable their bots. 

In fact, for many organizations, the problems of accessing and exploiting are still present. Organizations that rely on human judgement and creativity to produce value and solve problems, including those that have invested in knowledge processes, collaboration, content management, and search, often struggle with broader KM issues. 

And yet, people still can’t find their stuff

KM acceptance and culture change

In some organizations, the problem is that they have “checked the box” rather than truly embracing best practices in eliciting and elaborating user requirements and developing a compelling user experience. Sometimes, steps can be taken to clarify requirements and to present a solution that makes information more accessible. In other cases, the solution is not as simple.

A very significant part of the challenge for more complex knowledge management issues lies in socialization, user acceptance, communication and change management.  This challenge plagues every technical implementation and is especially difficult to overcome during large-scale digital transformations where the core of the business is transformed to new business models and practices. 

Enterprises are seeing that culture change is a significant obstacle, particularly in areas such as customer experience and digital marketing, where new tools and technologies are being adopted at a rate that is much faster than the ability of the organization to absorb change.  

Knowledge processes change faster than the business can adapt to

Let me elaborate on this last point.  The nature of business is that technology changes very rapidly and clock speed is always increasing.  Digital mechanisms enable the ability to turn the crank faster when it comes to messaging and market strategies.  The marketplace is in constant flux, and the job of the enterprise is to keep up with change by adapting its marketing strategies, messaging, pricing and product features. These are all knowledge-intensive processes. Upstream collaboration and knowledge sharing are frequently the bottleneck to creating a responsive customer experience.   

Knowledge and collaboration processes require finely tuned technical capabilities with frictionless sharing of information.  Because frictionless information flows depend on a high fidelity understanding of user requirements, and those user requirements are changing with changing market conditions, the IT organization will necessarily lag behind as the business adapts. This lag is the “impedance mismatch” between what IT is providing and what users need. 

IT is playing catch-up for two reasons: 

  1. Even though the available technology changes rapidly, IT cannot implement it fast enough to support the rapidly changing business needs
  2. The organization frequently lacks change triggers and mechanisms between new business requirements and updated technical capabilities. Therefore, IT may not be aware of these new requirements.  

The mismatch between technical infrastructure and the needs of users negatively impacts user acceptance of tools.   Users find that their needs are not being met. IT buys the latest and greatest, many times in response to user requests, and deploys those tools using state of the industry approaches.  But this is still not good enough.  Once users have the perception that the tool does not meet their needs, their attitude can be very difficult to change – even as tools and interfaces are redesigned.  They get turned off to whatever platform is in place, sometimes irrationally, and lobby for a new approach, technology, or application. 

How to get IT aligned with business needs

Users are frustrated that they can’t get what they need to do their jobs while the IT organization is beaten up for not meeting user needs – even when they are doing everything right.  What is to be done about this disappointing and frustrating state of affairs?

The formula is relatively straightforward; however, execution is never trivial.  It entails dealing more effectively with the impedance mismatch through validation of requirements, collaborative problem solving, judicious use of metrics, the ability to weave functionality directly into user work processes and objectives, and a scenario library of use cases. 

  1. Work collaboratively with users to demonstrate efficiencies offered by tools.  At the end of the day, users will do things that are in their best interests but only if they understand how doing something provides a benefit. Bringing together diverse audiences to work through scenarios will reveal gaps in functionality and process efficiencies.  These sessions have the added benefit of socializing insights from people who work in different parts of the value chain.
  2. Create baseline metrics around tasks and key processes.  Value is demonstrated through both subjective impressions and through objective data.  Even a subjective impression can be measured as a baseline.  As new functionality is socialized, the subjective impression can be re-evaluated.  More concrete measures of effectiveness of a process or efficiency in completing a task will bolster the business case and more clearly demonstrate value
  3. Create governance change triggers based on metrics.  Governance is a term that frequently has the connotation of boring nonproductive meetings.  However, linking change triggers to process measures (when something falls out of an expected range) keeps governance processes focused on the things that are important to participants.   Metrics-driven governance is both an overarching framework and part of the output of collaborative problem solving from step 1.
  4. Build out libraries of high fidelity use cases and scenarios: These are highly detailed representations of work tasks.  A library of use cases and scenarios becomes an asset of the organization that documents how user work and how systems help users accomplish their objectives.

User engagement is a result of two-way communication – of requirements and demonstration that those requirements have been translated into functionality.  Adoption of technology is the “last mile” of the change management that is inherent in digital transformation programs.  

IT should not be the “first mile.” The users' needs should be the first mile.

Digital processes and supporting technologies are part of a living ecosystem of the enterprise.  The ongoing collaboration is a commitment of time and resources and risks stakeholder fatigue if not handled correctly and facilitated artfully.  Though these approaches entail cost and risk, the alternative is a frustrated user community and having the good work of the IT organization be underutilized and undervalued.  

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Meet the Author
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.