#collaboration #crowdsourcing #wisdomofthemany
Companies like Jive, Yammer, Telligent and more promised to take social into the enterprise to drive a long list of business benefits, from improving productivity to fostering company culture, to boosting the bottom line.
Ten years later, Facebook and LinkedIn remain the 400-pound gorillas of the consumer social market, with tremendous growth, engagement and market value.
On the other hand, most enterprise social networks have been acquired and faded into the background as new digital workplace tools proliferated. New collaboration apps, notably Slack, took their place and their cache, although it’s beginning to look as if the newcomers may suffer a similar fate.
Why Did Consumer Social Networks Thrive While Workplace Counterparts Stalled?
One view is that consumer social networks like Facebook and LinkedIn thrived because they focused on people, while enterprise social networks put their focus more on the content being shared. Community forums. Document collaboration. Group messaging. All of these are good things.
In fact, the teamwork they enable is the heart of enterprise social. But these elements alone can’t make a community thrive without an understanding of the people driving it. The stickiness of Facebook and LinkedIn stems from the “network” part of social network: the relationships between people, with their content as a supporting function of those relationships.
To further complicate matters, wrangling all that content has become increasingly difficult. The communication and collaboration enterprise social networks enable provides real value. One company, for instance, found its enterprise community helped reduce the cost of sales by $2 million, while another increased employee satisfaction by 10 percent.
But eventually, like Facebook and LinkedIn, every organization ends up suffering from digital crowding. There is simply too much stuff in too many places for a human brain to comprehend. Searching for information requires an out-of-pattern activity that delays output and pulls our attention in a million different directions. Instead of fostering productivity and harnessing corporate memory, it hinders it. Eventually, this whittles away at any collaboration app’s adoption until the next shiny tool is brought in — only to suffer the same fate as the cycle continues.
Is Collaboration in the Digital Workplace a Lost Cause?
Not at all. To succeed, interactive intranets and enterprise communities must learn from their consumer counterparts and shift their focus from content to emphasize their organization’s greatest asset: its people. While this may sound more philosophical than tactical, it’s anything but. Creating a network based on relationships requires technology that both understands the connections between members of the network and dynamically personalizes their experience based on those connections. As more people and content enter the community, and relationship signals dial up or dial down with each interaction, the network should become even more powerful.
Bringing Graph Technology into the Collaboration Mix
One of the most powerful ways to achieve this is through graph database technology. Amazon Neptune is one example, and describes the concept well: it works “with highly connected data sets … optimized for storing billions of relationships and querying the graph.” When applied to an enterprise community, a graph database enables the platform to go far beyond the relatively simple constructs of “are you a friend/connection? (yes or no)” to understand much deeper levels of relationships, such as:Organization chart relationships.Explicit personal and professional relationships that aren’t hierarchical, with differences between friends, team members, colleagues, mentors/mentees, doctors/patients, etc.Implicit relationships, where commonalities exist between people based on their skills, location or activities, but without formal connections.By putting people at the core of the collaboration experience, graph databases can help enhance and even transform traditional content and collaboration capabilities into a richer set of people-to-people, people-to-content or content-to-content experiences. Take search: When your platform can understand what you work on and who you work on it with, its ability to deliver meaningful results will be dramatically improved. It can parse huge data sets about individuals as well, so it will “know” you too, not just your relationships. Combined with emerging technologies like text analytics and deep learning, that knowledge will enable semantic search that understands your context and finds what you need, when you need it, rather than just processing keywords.Search, of course, is only one example. A people-powered engine can help improve all of the standard enterprise collaboration use cases and makes new ones possible. By intelligently leveraging the connections between people and their work activities, platforms should prevent the creation of duplicate work and enhance commenting, versioning and more. Graph databases can also potentially streamline the chat experience, both within your primary digital workplace and externally, by curating conversations to serve up what’s most important and weed out the rest.
Finding Knowledge in the Crowd
If I sound excited about these possibilities, it’s because I am. After years of watching enterprise social “innovation” translate to new features that barely move the needle, the technology has finally caught up to the vision. Big data has brought us big opportunity. With the intelligence of a people graph, enterprise communities and interactive intranets can now facilitate true collaboration and connection, and in turn, deliver results around engagement, alignment and retention. The modern enterprise social network will no longer contribute to digital crowding — it will help you find the most valuable people and knowledge in the crowd.