6.14.DigitalSidekick.jpgJim Kane runs the Collaboration & Knowledge Management (CKM) Practice and manages the SharePoint consulting competencies at Paragon.
In his Paragon perspectives, Jim shares thoughts on SharePoint's evolution and pushing boundaries in knowledge management, as well as observations from knowledge management industry events.

I recently attended the APQC 2016 Knowledge Management (KM) Conference in Houston, Texas. In Carla O’Dell’s keynote speech, she quoted some statistics from a survey of over 500 APQC members:

  • 93% of organizations have specific budgets for KM.
  • 66% sponsor Communities of Practice.
  • 66% have some level of Enterprise Content Management in place.
  • 33% of Expertise Location systems.

No surprises there, though I bet if you survey organizations not part of APQC the number of organizations with specific KM budget and use of communities would be less Dr. O’Dell noted. That said, the conference was interesting (my first time) with participants from across the world and across all sorts of industries, from pharma though oil and gas through military organizations. 

Digital.Sidekick.2016.Knowledge.Management.jpgHello Digital Sidekick 

In the keynote address, Dr. O’Dell noted that the concept of “Cognitive Computing” is a new thought in KM. Essentially, cognitive computing is “… the real possibility of automating and/or augmenting human intelligence and insight.” Dr. O’Dell discussed this further in a follow up presentation titled “Say Hello to Your New Digital Sidekick.” 

How did Dr. O’Dell characterize cognitive computing? 

Essentially, the sheer amount of data and information is overwhelming. There are breakthroughs in computing power, speed, search, analytics and the user interface. These create the ability to take advantage of knowledge automation. Example?  Applications that understand the user role, user context, and what a user (or group of users) needs to do their job at that moment in time.  Examples in healthcare (diagnosis and research); pharma (molecular identification), and other ways of automatically improving insights in professional services, auditing, marketing, defense, and financial services. The “Digital Sidekick” is a concept where your personal devices (think Siri) understand and recognize your voice, but go further than that to interpret the intent of your needs to deliver personalize results in a narrative format, with language translation, recognition of emotion, and increasing accuracy through machine learning.

Dr. O’Dell provided several examples of cognitive computing in the workplace:

  • Healthcare: Diagnosis and disease research, radiology reports
  • Pharmaceuticals: Molecular identification
  • Smart “YXZ”: cities, transportation, utilities, supply chain
  • Insight and speed driven businesses: Professional services, auditing, fashion/marketing, defense, financial services

There are some 500+ cognitive computing applications being developed in 30+ plus industries, according to a 2016 a presentation on “Emerging Cognitive Patterns” by the IMP Watson team. The IBM presentation points out that Call Centers are leading adopters of cognitive technologies, with a focus on language translation, speech analytics, and chat tools and modules. 

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From a KM perspective, these tools are great, but I believe there is still a focus needed on outcomes, and behaviors required to optimize use of these tools to reach critical outcomes. Though I think we are a long way off from practical cognitive computing for most knowledge workers, for niche needs, there is ample reason to look to the escalating development of solutions that push the boundaries.

Digital.Sidekick.2016.Knowledge.Management.Trends.jpgPushing Boundaries

More practical, in my mind, were presentations by Caterpillar and a Keolis, a French company that focuses on management of commuter services across the world, including in Boston and Atlanta. Caterpillar focused on Technical Communities of Practice to help transform knowledge from a “passive” to an “active” state, and to address STEM and knowledge gaps of younger knowledge workers.  What I liked was that they did not take a throw-it-over-the-wall approach to communities, and have a formal steering group and community roles and functions/behaviors, with a feedback loop as well.  They focused on competency and skills knowledge, with technical staff serving as the community owners.

Keolis took a top-down model to create and support communities, but also gave the community owns and members free reign to make the community be what they wanted the community to be.  The provided enablement support and technologies, and took each community through a multi-week process to identify key community goals, set up the community, get trained, and release.  And the central group provides a form of community audit to help mature the group, or in some cases retire the group.

Keolis also had formal roles across the organization – from Community Champions (typically Director/VP level) through Community Owners in each business group. Community Champions are evangelists and own the implementation of knowledge communities within specific business organizations.  They are aligned to the corporate strategy, but have the independence to implement communities within their teams.

Digital.Sidekick.Knowledge.Management.jpgJim Kane's Key Takeaways from the APQC 2016 KM Conference

First, the supporting technology ecosystem for KM continues to advance.  The sponsor organization iKnow, LLS provided a session on technologies that are helping KM advance:

The promise of intelligent tools and digital assistants is still a ways off.  However, there are many new technologies that support advanced digital asset management, taxonomy tools and automated content structuring, content aggregation and personalization tools.  Look for these and the “digital assistant” technologies to rapidly advance.

Second, the tried and true Community model is still alive and well. And everything I heard reinforces the value of supporting communities, the model for supporting communities, and the effort required to make communities work. 

Third, the model and approaches to KM are not changing significantly, but the supporting technology ecosystem is rapidly advancing and care must be taken to avoid getting overly seduced by the “shiny new” syndrome that these technologies will solve our KM problems.

Finally¸ KM is alive and well.  There were over 200 dedicated KM evangelists at the conference, representing large and small organizations from all over the world.  Pragmatic case studies highlighted the value of KM and models for implementation.

We all agree, it is not easy to successfully create and sustain KM efforts with organizations, but the documented value can far outstrip the cost and effort. There are examples and books and papers about knowledge communities.  Probably far too many.  A tried and true approach is to focus on the drivers (issues/problems) and outcomes (ideal end-state) required by specific teams of users within specific contexts - and, to focus on behaviors. 

Technologies, even digital assistants and other cognitive tools, are still enablers ... not solutions