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4 Ways to Embrace Crowdsourced Knowledge

4 Ways to Embrace Crowdsourced Knowledge

People rarely take information at face value if they understand the consequences of using the wrong information, are unaware of the information source, or know that information has not been vetted. Moreover, peers trust peers and will value their curation of the content. Bottom-up messaging, created by peers, is often perceived as more valuable than top-down.

By Diane Berry CRM Buyer ECT News Network
05/02/14 10:05 AM PT

Traditional knowledge management programs focus on distilling knowledge into systems of record, which end up being underutilized for a number of reasons, chief among them because they cannot contain the long tail of knowledge. Conversely, nowhere are successful KM programs as impactful as where they intersect the customer experience -- from customer support to sales to marketing and product development.

In customer service and support, KM initiatives often focus on connecting the knowledge base with the CRM system -- or in some cases, purchasing the knowledge base module of a CRM system such as Salesforce.com. Quite often, SharePoint is used as a knowledge base; however, a number of research studies show that users quickly dismiss such systems. A third of enterprise content management initiatives are rejected by users as unpleasant to use, Gartner reported.

An APQC study on the effectiveness of expertise-finding programs -- key to customer support -- showed that even after 10 years, only about one-third were considered "very effective" -- and more than 60 percent of those surveyed were using SharePoint. No one loves their intranet.

Eliminating Knowledge Boundaries

Why have these initiatives largely failed? Precisely because they are confined to and constrained by the single knowledge base or system of record. Chris Anderson's long tail theory initially was applied to e-commerce; it described the large number of unique items available in small quantities -- unconfined by physical boundaries or systems -- with Amazon as the key example.

When applied to knowledge management, the same types of digital capabilities can eliminate physical and IT boundaries preventing employees' and customers' sharing of even highly specific knowledge and expertise -- within their own context and, importantly, in the flow of work.

Moreover, Chris Anderson's theory showed that 98 percent of items were sold at least a handful of times each and every quarter by the e-commerce companies studied, giving the boot to the 80/20 rule, which predicts that 20 percent of resources will provide 80 percent of value.

Again, applied to KM, this implies that companies will reuse 98 percent of their knowledge and information at least a handful of times each quarter. Considering that the most difficult customer cases (and in many cases the largest sales) are those that utilize highly technical or specialized information and knowledge, the long tail stands to significantly benefit customer engagement across the board, simply by reusing an existing enterprise asset: knowledge.

Crowdsourcing Knowledge

The long tail of knowledge is spread throughout all systems, both within and external to the organization, and it resides in the knowledge, often implicit, of employees and other constituencies.

Both explicit knowledge and information and traces of employees' implicit knowledge may be found in IMs and emails, phone records, databases, social media, ECM systems, KBs, CRM systems, blogs, desktop content, collaboration tools, file shares, etc. It is spread among global offices and often held by employees who may be working remotely.

Similar to printed encyclopedias, the head of the tail, generally the KB, will contain popular content -- that which is used most often -- and perhaps used mistakenly, due to a lack of better or more specific information stored elsewhere. There naturally comes a point at which our KM teams stop curating knowledge, and our IT teams stop making it available. This is the long tail, and it is generally more valuable because it is more specific. Until now, it also has been more difficult to reach.

Activating the long tail requires a cultural shift from single-(expert) sourcing and knowledge curation to crowdsourcing and curation from throughout the organization, potentially even including customers.

Technologies now exist to facilitate the crowdsourcing of knowledge and curation -- and, importantly, to enable contextual relevance, just as Amazon suggests relevant book titles from among its tens of millions. Most often, however, cultural implications will constrain an organization's willingness to share knowledge so openly.

In the past, concerns about security also prevented the opening of these information gates; however, that also has been solved by technology, which respects the underlying security protocol of each enterprise system.

Change is always difficult, and nowhere is it more difficult than when shifting paradigms appear counterintuitive. How can a crowd curate knowledge when knowledge is related to specific expertise? The answer may lie with Wikipedia.

The Wikipedia Example

Back in 2005, Wikipedia had 3.7 million articles, and its accuracy slightly trailed encyclopedias. Now, Wikipedia has 23 million articles, and its accuracy and references are on a par with Encyclopedia Britannica (which, by the way, has switched to online-only availability) as well as the leading encyclopedias in two other countries, in their native languages. This is based on research conducted by Oxford University and Epic Consultancy. The crowd has curated Wikipedia articles, successfully and at scale.

With Oxford providing the background, following are four ways to overcome cultural obstacles and become comfortable with enabling the Long Tail of Enterprise Knowledge.

  1. Identify the level of content curation.
    It is fairly easy with today's technology to identify the source and level of curation of each piece of information, either by explicit user endorsements (such as Likes) or through symbols that identify whether the information has been curated or is in-progress.
  2. Encourage crowd curation.
    Communicate the reasons for employee and community contributions to curation. For example, in the customer support environment, enabling the linking of information to cases (in the flow of work) increases participation. When consumers of the information and knowledge find benefit, they will participate more frequently, because they will understand that they also benefit from the efforts of others.
  3. Trust employees to think.
    People rarely take information at face value if they understand the consequences of using the wrong information, are unaware of the information source, or know that information has not been vetted. Moreover, peers trust peers and will value their curation of the content. Bottom-up messaging, created by peers, is often perceived as more valuable than top-down.
  4. Be sure to ensure relevance.
    Enabling the long tail of knowledge might seem like you're about to unleash an information wild, wild west -- and without handling relevance, that's exactly what would happen. Your initiative would be hung at high noon, never to be trusted again. However, just as Amazon sifts through millions of titles and presents you with those you may not have known about but which actually might interest you, technology now can enable the same relevance recommendations from throughout the long tail. Agents and other knowledge workers will simply experience the information, knowledge and experts relevant to their context, in the flow of their work. This can take the form of recommendations of information and experts who can help them solve a case or win a deal.

With these culture-changing steps in place, you'll be positioned to unlock the tremendous value in your organization's knowledge and information, regardless of where it is stored. Just imagine what your organization will do when it reuses 98 percent of its collective knowledge.


Diane Berry is chief knowledge evangelist with Coveo, which provides search and relevance technology for knowledge management initiatives. Berry is a frequent speaker on topics related to knowledge management, is a popular blogger on LinkedIn, and often is quoted in the media on topics at the intersection of knowledge and technology.


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