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Looking to the future: 2021 Insight

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Better governance and online behavior

One way to improve virtual collaboration is to insist on better governance and standards for online behavior. Nearly half the respondents to APQC’s survey said their organizations either lack norms and guidelines for virtual collaboration or allow them to emerge organically as groups work together. This erratic “Wild Wild West” approach breeds confusion and frustration, and it discourages employees from relying on virtual platforms to enable deep, complex work.

Survey respondents overwhelmingly say that strengthening norms and guidelines would make virtual collaboration in their workplaces more effective.

Specifically:

♦ 52% want set criteria for virtual meetings, such as a requirement to share a set agenda ahead of time.

♦ 40% want guidelines to navigate collaboration options and determine which tool to use when.

♦ 36% want rules for turning on video in virtual meetings, and 35% want expectations for attentiveness during those meetings.

♦ 35% want set hours when collaboration will (and will not) occur, as well as the option to block off time for solitary “deep work.”

KM can demonstrate its value by working with managers to implement and standardize these kinds of policies. It can also reinforce behavioral expectations through consistent communications, training, and gentle “nudges” when people color outside the lines. Employees are excited by the promise of virtual collaboration, but they’re exhausted by the lawlessness and fragmentation of the current online work experience. Better guidelines and guardrails will make people more productive in their virtual workspaces and increase the scope and quality of the interactions that occur there.

KM must seek new options for expertise location

Expertise location has been a “wicked problem” for KM for decades—and it remains so. When asked about their most pressing knowledge needs, better options to find and connect with colleagues is almost always at the top of the list. Organizations have thrown solution after solution at the problem, from expert lists to LinkedIn-style profiles to social network recommendations. Some tools have enjoyed limited success, but most are either restricted in scope, too complicated to set up and use, or overly reliant on employees manually inputting and updating information about themselves.

APQC’s survey highlights the lack of progress KM has made on expertise location. When asked how they would seek out a colleague with needed expertise, the vast majority of respondents say they would ask a colleague or manager for recommendations (Figure 2).

This option feels comfortable and easy, but is unlikely to yield the best result, especially in a large, dispersed organization where the most relevant contact may hail from a different region or business unit. By contrast, less than one-third of respondents said they would use more systematic methods to cast a wider net, such as searching via expertise location tools or asking in a community of practice or enterprise social network.

A combination of technology and culture

KM teams have work to do, both in providing efficient ways to search for colleagues and in driving adoption of those tools. This will require a combination of new technology and culture change.

Capabilities such as natural language processing and machine learning have massive potential to analyze information about employees and then recommend relevant contacts for a topic area or search term. But these systems can be time-consuming and expensive to implement, especially when they must be integrated with other software. Some also raise questions about employee privacy, depending on the sources they use to “learn” about people and what they know.

Even if KM successfully implements a good expertise locator enhanced with automation and AI, it may struggle to convince employees to use it. When it comes to seeking out connections, people trust their personal networks. Many would rather “phone a friend” than rely on an algorithm to suggest someone—even if the algorithm objectively has better insights than Jill in accounting. Once KM gets the technology (mostly) right, it will need a compelling communications strategy to sell expertise location to the workforce.

Employees know they need better tools to find people, but they require proactive encouragement, hand-holding, and manager reinforcement to push them out of their comfort zone. Fortunately, KM has vast experience promoting its value and convincing employees to experiment with new tools and capabilities. It just needs to iterate the technology and then put its change management toolkit to work.

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