Influencing the Intelligent System
The tagline for my company includes three words: Strategy, Influence, Amplification.
Strategy, as a concept, is probably the most understood of the three — which is not to say that companies are good at strategy, but that most organizations understand that in a hyper-competitive world, you often need to be very strategic. Likewise, I think people generally understand the concept of amplification. With the growth of digital marketing and, specifically, content marketing, the definition has evolved a bit, but the core concept is to get your product or your message out to a wider audience more quickly. The one that is the most difficult to define — and certainly to measure – is Influence.
In an article on the topic of social influence a few years back (Yammer & Klout: An intranet game too far) when some of the then-new influence measurement technologies first entered the market, author Jonathan Phillips provided some insights into the mechanics of Klout, and — more importantly — the value of these tools to the enterprise (he also wrote a nice piece on the importance of content amplification). He also touched on the role of social influence in tracking and measuring outputs through system gamification, which is an important social collaboration capability.
The idea around measuring social influence is not exactly new — companies like Klout, Kred, PeerIndex and others have been around for some time, with varying degrees of success and acceptance. While these tools have largely been for consumers, there is most definitely science behind the efforts — and there is tremendous potential (and business value) in understanding social influence within the enterprise. Tracking influence within the enterprise could impact how end users act on the information received – prioritizing signals coming from the experts within the organization, helping increase the speed of decision-making while decreasing risk.
It’s still a wide open space for innovators and entrepreneurs, IMHO. It’s fair to say that no single company “owns” this category, with many people questioning the algorithms used and the subjective nature of the methods for capturing their data and the results they share. But the value that these concepts can provide within corporate collaboration and knowledge management platforms is a key indicator of where technology (such as Office 365 and Microsoft’s Office Graph) is headed.
Of course, the problem with the rise of tools like Klout is not whether or not the tool accurately measures actual subject matter expertise (which is not really their purpose), but that people quickly embrace any new analytical tool or data point as if they somehow hold all of the answers (they don’t). As with most analytical tools that looks to parse human behavior and correlate with content and conversation, the results are highly subjective — and at the same time can provide powerful insights to support your other collaboration measurements.
What makes social influence measurement useful is how it helps an organization begin to understand the depth of our social interactions (how far our message is amplified), not just the volume of our activities. Volume of content produced does not equal expertise.
Like most stats, the value of a measurement of social influence is not about a specific point in time, but in identifying movement and trends over time. But none of that is in any way connected to the quality of those interactions — such as what you’d expect from someone with deep subject matter expertise (SME) knowledge. Some of the most brilliant technical minds in our organizations are often not the prolific bloggers….or talkers, yet they are the people we turn to for definitive answers to tough technical questions.
As an example, I have always pointed to our best developers. On the surface, the typical dev SME may not be the most vocal within the team, or with customers. Because they’re not uploading as much content and being as interactive as someone from, say, the marketing department, you might label them as a low-influence employee through standard activity-based metrics. The reality is that this developer may be the leading expert on certain topics, even with his or her low participation. The true potential of social influence measurement are realized only when combined with other activity and engagement metrics, providing another dimension to the data and allowing teams to better understand how content and ideas are amplified in real-time.
Social influence measurement — along with marketing amplification — will continue to evolve, and I have a feeling that they will become as prevalent as CRM and collaboration technology. We have not even scratched the surface of how these tools might be utilized for internal systems. The social graph is the link between influence, amplification, and enterprise knowledge management, giving us another facet or refiner within our searches, and help us to find the right content at the right time in the right context, leading to widespread adoption across the enterprise.
Social influence measurement is inseparable from amplification — how many people hear your message, and take action on it (in other words, how successful you are at amplifying your message) will become an essential component of your own social influence. As influence and amplification become even more of a factor within the enterprise, and teams look to better leverage connected networks within the organization, filtering and prioritizing content, conversations and ideas based on subject-matter expertise will become increasingly important to how we leverage collaboration and knowledge management platforms, and will heavily impact our strategic thinking.
For organizations envisioning “the future of work” and the “intelligent enterprise,” this is the path to the intelligent future.
