Do we lack the tools to steer ESN adoption?

It’s been a long time since I last used Facebook. I’d like to say it’s totally out of a philosophical belief that we aren’t meant to be the product – don’t get me wrong, it’s partly because of that-, but it’s got more to do with my dwindling motivation. I like to assess my use of any app through the Return On my Time Investment. And because of its recent (or not so recent) algorithmic updates, my FB newsfeed has lost its edge when compared to my Twitter timeline.

But this is just FB. Leaving it might disconnect you from the latest updates in your friends’ social lives, but it won’t hinder you professionally (unless you’re a web marketer or a Facebook employee that is). But what is of an Enterprise Social Network (ESN)?

Many vendors boast about the gain in productivity and the rise of innovation following the implementation of ESNs. Yet, what business value can you extract from a deserted social network? It is no surprise that adoption is the main issue with many ESN implementations. But how do you get people who are already swamped with work-related tasks to fully engage within a social network? And once there, how do you retain them on the network?

This is a heavy loaded question with no easy answer. A first step would require understanding the motivation behind our staying or leaving (aka churning) an online social network. A rather comprehensive presentation of the question has been issued by Karnstedt et al. in their paper “Churn in Social Networks”:

A key observation of user behaviour in online networks is that users, with the exception of spammers, make contributions to online discourse without expecting any immediate return [39,11]. In sociological discourse, this type of activity is described in terms of the ‘gift economy’ [58]. In contrast to the commodity or service economy, which is driven by the exchange of good/services for money, economic exchange in the gift economy is defined in terms of an im- plicit social contract. In a gift transaction, there is an unstated expectation that the benefits of a gift will be reciprocated by the recipient at some reasonable time in the future. A more risky transaction involves ‘generalised exchange’, whereby the giver’s generosity is reciprocated, not by the recipient, but by someone else in the group. In social networks, this exchange mechanism applies to those contributors who give of their time and expertise but do not appear to receive immediate benefits. However, there is a risk that the group will not assume responsibility for the debt and the contributor will never be reimbursed in kind. In the worst case, if all members of the group never contribute (free-load), no one benefits and the exchange system breaks down.

This gets more delicate when applied within an enterprise because, well the stakes are higher for obvious reasons, and because what’s going on offline (office politics and such) is bound to affect the dynamics within the social network. Fingers are often pointed towards Enterprise culture and justifiably so. Culture does eat technology for breakfast!

Some argue that internal community management could help ESNs thrive, but it can only do as much. Data-driven approaches that proclaim the capacity of steering the community through web-based analytics are abundant. They could help understand the dynamics of the network, if only they focused equally on the relational aspects of the social network as they do on the content and activities occurring within the network.

Maybe the difficulties of adoption are only made more poignant because of the lack of pertinent methodologies to support the endeavor. What if we could visualize the network in real-time (through Social Network Analysis)? Augment it with activity-based indicators (number of posts of a user, numbers of views of a profile etc.)? What if we could even envision the future state of the network based on the patterns in its historical data and thus predict the likeliest users to churn (As is the case for online games platforms or telecom companies)?

Maybe that will steer the adoption efforts in a more accurate manner and maybe it won’t. I’m nothing saying it’s not a complex question, but wouldn’t hurt to dwell on it, would it?


Which one would you rather be?

There are two kinds of employees:

  • Those who react to the day-to-day issues, and those who prevent them from occurring in the first place
  • Those who make themselves indispensable (mainly by retaining knowledge), and those who make their knowledge available (ensuring the organization’s sustainability)
  • Those who go fast by going alone, and those who go far by nurturing a culture of collaboration
  • Those who get things done, and those get things right
  • Those who get comfy in the status quo, and those who face challenges head-on
  • Those who set the bar, and those who choose to see no bar

One would survive, but the other will thrive. Which one would you rather be?

Social data interpretation: The human factor

Research claim that A full 90% of all the data in the world has been generated over the last two years. This tsunami of digital data have brought along incredible insights but also many many headaches. One of the most prominent challenges relates to the inferences we draw from these data. Kate Crawford argues in “The Hidden Biases in Big Data” on Harvard Business Review that “We give numbers their voice, draw inferences from them, and define their meaning through our interpretations. Hidden biases in both the collection and analysis stages present considerable risks, and are as important to the big-data equation as the numbers themselves.” O’Reilly Radar’s Mike Loukides stresses, in “Data Skepticism“, that “even when you have unlimited data, you have to be very careful about the conclusions you draw from that data. It is in conflict with the all-too-common idea that, if you have lots and lots of data, correlation is as good as causation.”

This particularly strikes a nerve when it comes to Social data (and Social Network Analysis). You must have, at least once, come across titles such as “Social Networks are making us anti-social” or “Facebook causes divorce” or “Twitter moods help predict stock markets” etc. This might reflect a mere misinterpretation of the original studies (causation sells way better than correlation as the comic promptly illustrates) or a defect in the analysis and interpretation processes of said studies. We have a tendency to jump into such conclusions because our minds react better to narratives and “because” is a good ideas’ connector.

When examining the virality of content in social networks, a tweet for instance, the observed contagion phenomena is often explained through ‘Peer influence’. It could be the case, but it’s good to stop and think ‘Maybe the answer isn’t that simple’, maybe there are alternative explanations. Sinan Arial, an associate professor at the MIT Sloan School of Management, delivers a compelling talk about social contagion and highlights just how Homophily (the tendency of similar people to bond together) is a viable explanation for some diffusion phenomena often attributed to peer-influence.

When stressing how ‘Big Data’ (Social Data) will revolutionize business or how ‘visualization will save big data’, vendors fail to stress these interpretation issues (which is understandable). Human intervention is an omnipresent part of the conception and analysis process. And unless our analysts (or data scientists if you like) are open minded enough to consider alternative explanations, or we come to find more appropriate models, we might just be digging ourselves into a much bigger hole.

“Everything is connected” – A paradigm to live by


Source: Tv Show “Touch” revolves around the idea that everything is connected.

While I was doing some  much needed winter cleaning of my laptop, I found the transcript of this talk I did two years ago (if memory serves) and it tackled how, in today’s interconnected world, It takes a network-paradigm to thrive. As it’s resolutions season, although I’m not a big fan of the whole ritual, I thought I’d share an excerpt to take into account while forming this year’s big plan. *Turning sleeves up* (And by the way, Have a blessed and productive 2014!)

“I’ve become convinced that how networks work has become an essential 21st Century literacy.” ~Harold Rheingold

In the Era of interconnectedness that we are witnessing today, we belong to many many networks And weaving various network is the key to thrive. That is why to my sense, brokers (people who tie together otherwise disconnected people and leverage what is called weak ties)  are actually what we can call great network players. And here is why.

Rene Fourtou once said that “Shock comes when different things meet. It’s the interface that is interesting”. We learn most from people who don’t resemble us. Great ideas come from cross-pollination, a combinatory process that remixes ideas from different backgrounds to give birth to novel ones. How much exposure you have to various ideas determines how creative you can be. So when brokers play the role of interfaces between groups they are actually getting exposure to different ideas, which causes a shock, and a shock causes a spark, and spark gives birth to disruptive ideas. Brokers are creative!

Brokers are Problem solvers. People connected across these groups, who cross those gaps, are more familiar with alternative ways of thinking and behaving. They can juggle and appreciate divergent outlooks and multiple realities. They know that answers don’t lie within. Hence, they are more prone to have a vision of options otherwise unseen.

Brokers are Change makers. A Network Weaver is someone who is aware of the networks around them and explicitly works to make them healthier (more inclusive, bridging divides). Network Weavers do this by connecting people strategically where there’s potential for mutual benefit, helping people identify their passions, and serving as a catalyst for self-organizing groups.

Creative, innovative, problem solver, change maker. Who wouldn’t want to be all this. But how Do we get to that? How do we become network weavers? It really start by having a network mindset. The “me” attitude should be replaced with a “we” attitude which fits in the networked ecosystem we live in today.

Reaching out of your bubble: Going to event outside your normal sphere can enhance your exposure to new ideas. If you are a techy, try going to modern art expositions, literature events etc. Mingle with people with social science, philosophy, quantum mechanics backgrounds. The furthest you go outside that filter bubbleyou unconsciously locked yourself into, the better chances you have to come out with unique ideas. 

Always look for fresh blood: we are people of habit, we seek the comfort of familiar faces, of people who share our world view. There is nothing wrong with that. Greatest opportunities of growth though come from reaching out and connecting with those whose views are very different than ours. Intellectual diversity is a great creativity catalyst. Let’s then make it a point not to shun away from those who challenge us intellectually. 

Never miss a chance for a new experience: Spend your money wisely. Material things have a short life span, experiences on the other hand are life-long companions. Make it a point to try a new experience whenever the chance presents itself. An Arabic class? A travel to a multicultural destination? Anything that widens your range of interests is welcome.

Leverage the power of the web: In the words of Tapscott “The web, -indeed the world- is your stage, so get ready to deliver your star performance”.  Go out there and shine!

Each network you reach out to gives you access to a whole new reality you may have been oblivious to. The more exposure you get, the more your mind expands and the more creative you can be.

Links & Notes

Here are few links that captured my attention this week.

  • If a network is broken, break it more: New research from Northwestern University suggests that, instead of replacing the damaged lines in a network, we could restore the whole network by strategically disconnecting even more lines
  • Social Network Analysis: making invisible work visible: The paradox is that organizations continue to allocate a significant proportion of their IT budgets on communications infrastructure and ‘social software’ and virtually nothing on systems and tools that can analyze how effective this investment is.
  • Unstoppable march of big data: The driving force of big data is not technology, but the economics of data storage. Cell phones, lifts, doors and weather stations always used to throw out tremendous amounts of data every few seconds; we just never used to record it. Now we can.


  • Interesting app I spotted this week called Coffitivity that supposedly offers just enough noise to get work done
  • A great compilation of resources for obtaining, handling and visualizing data
  • A video, inspired from Sherry Turkle’s book Alone Together, “the innovation of loneliness” is worth pondering as you unplug this weekend!

“Network theory” vs “Theory of networks”

It should also be noted that SNA theorizing encompasses two (analytically) distinct domains, which we refer to as “network theory” proper and “theory of net-works.” Network theory refers to the mechanisms and processes that interact with network structures to yield certain outcomes for individuals and groups. In the terminology of Brass (2002), network theory is about the consequences of network variables, such as having many ties or being centrally located. In contrast, theory of networks refers to the processes that determine why networks have the structures they do—the antecedents of network properties, in Brass’s terms. This includes models of who forms what kind of tie with whom, who becomes central, and what characteristics (e.g., centralization or small-worldness) the network as a whole will have.

Source: On Network Theory – Borgatti & Halgin

Along came the Dinosaur!


Photo courtesy of Daniel Ferenčak 

I like dinosaurs. I find them intriguing to say the least. Probably because they belong to a distant era that we only read about in our science curriculum. Or maybe because they have been the subject of public imagination for so long. To be honest, I mostly like them because I know for a fact that those life threatening creatures (well, most of them anyway) don’t live among us anymore…. Well that’s what I thought until I heard this :

« I’m offered a training in ****** (an IT technology that needn’t be named) along with a to-be signed commitment to stay in the organization for the period of 7 years after the training. Of course if I’m willing to leave, all I need to do is pay back the « whole » amount of the training before leaving »

Ok, so let me get this straight. You’re offered a training that will obviously not only benefit you but benefit your organization as well. And you are to either seal 7 years of your life with the organization or pay back the whole, apparently not subject to depreciation, amount whenever you choose to leave. That, despite the fact that the technology can become obsolete by the time you hit your second year. Hmmm.

So I asked myself the question : who does that ? Who still does that ? … Dinosaurs, exactly ! But since dinosaurs are supposedly extinct, those must be some special kind of dinosaurs with special powers. So here is today’s realization : Super dinosaurs are still living among us. And here is how you can spot one :

  1. Doesn’t know he’s a dinosaur
  2. Horrible at math* (Not sure he knows of the existence of a calculator)
  3. Still thinks that employees are cogs in his machine and that they can only have access to the knowledge he gracefully hands them (Internet? what’s that?)

….And to think that people are discussing Social Capital. Not around here anyway !

On a final note: I stumbled upon this article from Forbes that lists the 10 reasons top talents leave organizations. Something to learn from, I hope!

* A friend made the pertinent remark that he’s not really horrible at math, He just makes all the wrong calculations.

The Challenge of Network Analysis

“To represent an Emprical phenomenon as a network is a theoretical act. It commits one to the assumptions about what is interacting, the nature of that interaction and the time scale on which that interaction takes place. Such assumptions are not “free” and indeed they can be wrong”

~ Carter T Butts – Revisiting the Foundations of network analysis

The “Power of We”


This post is here to celebrate “The power of we” as part of the blog Action Day 2012.

It is undeniable that there is an amazingly huge power in the “We”. Common wisdom affirms that two heads are better than one. But truth is, it takes more than just gathering two, three, hundreds of heads to render better results. The real power of we comes from an understanding of the underlying forces of the social ties that we weave among ourselves, a better grasp of our social networks. I find the bucket brigades example, from Nicholas Christakis’ book connected, a telling illustration of the difference: 

Imagine your house is on fire. Luckily, a cool river runs nearby. But you are all alone. You run back and forth to the river, bucket in hand, toting gallon after gallon of water to splash on your burning home. Unfortunately, your efforts are useless. Without some help, you will not be able to carry water fast enough to outpace the inferno.
Now suppose that you are not alone. You have one hundred neighbors, and, lucky for you, they all feel motivated to help. And each one just happens to have a bucket. If your neighbors are sufficiently strong, they can run back and forth to the river, haphazardly  dumping buckets of water on the fire. A hundred people tossing water on your burning house is clearly better than you doing it by yourself. The problem is that once they get started your neighbors waste a lot of time running back and forth. Some of them tire easily; others are uncoordinated and spill a lot of water; one guy gets lost on his way back to your house. If each person acts independently, then your house will surely be destroyed.
Fortunately, this does not happen because a peculiar form of social organization is deployed: the bucket brigade. Your hundred neighbors form a line from the river to your house, passing full buckets of water toward your house and empty buckets toward the river. Not only does the bucket brigade arrangement mean that people do not have to spend time and energy walking back and forth to the river; it also means that weaker people who might not be able to walk or carry a heavy bucket long distances now have something to offer. A hundred people taking part in a bucket brigade might do the work of two hundred people running haphazardly.

So when the ties are purposely woven to accomplish a common goal, the group/network becomes more powerful than the nodes, and the power of We shines in all its brightness. Pretty simple, right? Then why are most of us still running into the second situation? Why are we incapable of effectively leveraging  the networks around us to achieve the change we’re hoping for?

Technology has made us more densely networked than ever. The six degrees of separation are shrinking to a mere four, proving that we are closer to each other than we ever were. It is a fact though that technology has gotten ahead of us, that we aren’t catching up fast enough and that our culture is not following. In today’s interconnected world, we are still operating with a traditional mindset when we should fully adopt a networked one. 
What does adopting a networked mindset entail?In a nutshell, wiring our brain for Openness, peering, sharing and acting globally.
In the words of Tapscott himself “It’s a question of stagnation versus renewal. Atrophy versus renaissance. Peril versus promise.” So, What are we waiting for?

How Networks Can Revolutionise the World

The world is one big network problem. Some even affirm that we can only survive the future through connections. One thing is sure, Network theory is becoming more and more profoundly important to understand the world. 

In a compelling RSA talk, the economist and author Paul Ormerod makes the case of how “we have to see the world through the lense of networks in order to be able to design and think about better policies to achieving our ends whether in politics or the corporate sphere”. Through examples of network systems that range from popular culture to modern economy, Ormerod presents how observing network properties such as resilience or fragility can help explain some aspects of today’s world, including the economic crisis.