CIOREVIEW >> Knowledge Management >>

Avoiding the One-size-fits-all Trap in Knowledge Management Technologies

Laura Lerner, Adjunct Professor, Knowledge Management, University of Maryland University College, Former VP Knowledge Management, ADP
Laura Lerner, Adjunct Professor, Knowledge Management, University of Maryland University College, Former VP Knowledge Management, ADP

Laura Lerner, Adjunct Professor, Knowledge Management, University of Maryland University College, Former VP Knowledge Management, ADP

Does this sound familiar? A stakeholder approaches you and says, “I need knowledge management in my organization. Can you help me find a knowledge management system?” Being the supportive business partner you are, you respond, “Of course” and then dutifully find a few knowledge management system (KMS) vendors so you can pick a KMS as requested. You might point your stakeholder to something you already have on hand. When you roll out the solution, adoption lags, maintenance eats time and money, and no one knows what they’re getting out of it.

  ​No two KM programs are alike. Commonalities exist, but an effective one must be tailored to meet the unique needs of an organization   

How did it go wrong?

It’s a scenario that plays out in many organizations. Why?

• We don’t take the time to understand the problem. As with any technology selection, you need to understand why you need something in the first place. Knowledge management (KM) encompasses many business challenges, and those challenges come with their own requirements and functional needs. Some challenges need collaboration tools such as instant messaging and online communities; some need document and content management systems. Still others need eLearning solutions, talent acquisition tools, and project management and business intelligence software.

• We lack an understanding of what KM really is. As a discipline, KM has been around for about 30 years. In that time, you’d think we’d get it. Still, many definitions persist, and, practically speaking, because customer service operations relied on shared knowledge bases to answer calls, KM developed a bit of a reputation as a call center thing, with software built around customer service-focused methodologies, like Knowledge-Centered Support. But that’s just a narrow application of what KM is at its core– the practice of enabling organizations to collectively and systematically create, organize, share, and apply knowledge to better achieve their objectives.

• We expect too much of one technology and not enough of our people and processes. We all know there’s an app for everything — there’s just not an app that does everything. Even if there was, people must still participate in the processes facilitated by these applications. Too often, instead of going through the work to weave KM activities into the fabric of people’s responsibilities and the culture of the organization, we balk at the effort change requires, participation becomes optional, and as a result, we de-prioritize KM activities until very little happens at all. That’s not a failing of technology; it’s our failure to prioritize the care and feeding of our intellectual capital.

• We lack data that’s trapped in other systems and in people’s heads. The knowledge we need to manage exists in various forms–policy and procedure documentation, instant messaging threads, proprietary databases, sticky notes, conference presentations, the person two cubes down, patent applications, source code, and so many more. In most cases, we can only find and access a fraction of what’s available (assuming we know to look for it) because the knowledge, if it’s codified, is in disparate formats that can’t be consumed in a standard way or managed to ensure viability. So we do without or we recreate again and again.

• We expect people to go to another tool and they don’t. According to “The State of Knowledge Management: 2016-17 KM World Survey,” over half of the respondents listed the lack of knowledge sharing integration as a major hurdle to implementing KM. We might advertise that this new KMS is a single source, but they know the truth. It’s another place–a place they don’t have time for because it’s not part of how they normally do their work.

What to do instead? Before you look for that KMS, consider a different approach. Understand the desired outcomes

Ask the hard questions:

• What’s the business problem we’re trying to solve?
• Who is our end user? What knowledge do they need and how will they get it?
• How will we know if we’re successful?
• What level of sponsorship from the business can we expect?

Until you and your business stakeholders can clearly articulate the answers to these questions, no KM (or KMS) implementation will be successful. Ultimately, you need a KM strategy, which will define answers to these questions and outline the best KM approaches to address the problem. Partner with a KM practitioner to understand your options and reduce the costly risk of trial and error.

Think Ecosystem

In nature, ecosystems consist of a physical environment, the organisms that live there, and the exchange of energies and elements to power it all. Similarly, your organization’s knowledge fuels the operation and value of your organization as part of your organization’s ecosystem.

When it’s time to talk technology as part of the KM strategy:

• Understand what technologies you have, what role they play in KM activities, and what activities you still need to enable.

• Fill specific gaps in capabilities with technologies purpose-built to provide them. You’ll have many applications supporting critical KM activities, rather than a proprietary panacea.

• Focus on application interoperability. Eliminate the seams among your technologies and within the user’s experience.

• Opt for cloud first, when you can, to scale and adapt to changing needs quickly.

Free the data

Siloed information systems are the second biggest hurdle to implementing KM and handling large data in a variety of formats is a growing problem, according to “The State of Knowledge Management: 2016-17 KM World Survey” respondents. To address these challenges:

• Prioritize open over proprietary systems for investment. If you can get your data in, be sure you can get it out easily and in a portable format.

• Take the time to create common metadata architectures and supporting vocabularies — then use them fanatically.

• Be sure your KM applications have user behavior analytics from which to continually learn and evolve your ecosystem. 

Onward to KM success

No two KM programs are alike. Commonalities exist, but an effective one is tailored to the unique needs of an organization. Understand the outcomes you need, optimize your technology investments to address specific gaps, and eliminate silos between applications and data to avoid one-size-fits all solutions and put your ecosystem first.

Read Also

"Well, How did I (we) get here?"

Louis DiModugno, Chief Data Officer with HSB
How to Build a Techforce

How to Build a Techforce

Christian N. Schmid (Managing Director and Partner), Raffael Kazda (Associate Director), Daniel Wagner (Manager) and Annika Melchert (Senior IT Architect), all core members of the Banking Practice Area of BCG and BCG Platinion
Data Archival - Rest in peace

Data Archival - Rest in peace

Himali Kumar, Director Data Management, AutoZone
What Does RBG's Death Mean for the Investing World?

What Does RBG's Death Mean for the Investing World?

Jenny Abramson, Founder & Managing Partner, Rethink Impact
The New Bridges and Barriers to an Integrated World view

The New Bridges and Barriers to an Integrated World view

Brandon Beals, Director of Data & Analytics, Dot Foods