Bridgebuilders - the phenomenon & the streetlight effect

Does this joke somehow sounds familiar??

When you check the Human Resources Management Systems, you can find a number of attributes to yourself, e.g. Age, Tenure, Job Role, Job Stage, Department, Organization, which are all assigned to you as an individual. In the same logic, we speak of individual contributors or line managers as the substantial categories of employment.

However, when I think of my successes and achievements in my professional life, rarely there is something that I can allocate to me as individual only. Most of the best is realized in the interactions, in the collaboration with others, and the interaction is very different whether I speak to a large group, work in a team, get sponsorship by my manager or doing coaching to a junior person.

What comes into focus with these reflections are not attributes of individuals but the interaction between employees. Who is connected to whom? Which social patterns appear in these interactions. That is, we are talking not about the individual, but the network. The network that manifests itself in the interaction of employees. With the praise of collaboration goes the fundamental assumption / truth that there is value in these interactions. Or with Robert Putnam, Bowling Alone: ”The core idea of social capital theory is that social networks have value”. Therefore there is the distinction between Human Capital, allocated to the individual, and Social Capital originating in the interaction with others.

While conceptually outlined (Better People Analytics: Measure Who They Know, Not Just Who They Are (hbr.org)) and analyzed for small sizes The People Who Make Organizations Go—or Stop (hbr.org), it is fairly recently, when the network structures were analyzed on a larger scale: Patterns Hidden Inside the Org Chart (microsoft.com).

We have been looking at collaboration in terms of interactive meetings. These are meetings of up to 15 participants, separating interactive meetings from broadcast meetings with a very large number in the audience, which are not interactive, but one-way very much.

In this data we encounter a phenomenon, that is difficult to explain in the conventional attribute analytics, because conventional analytics is showing the streetlight effect, and does not provide neither the tools nor the terminology to describe and understand the phenomenon. We argue that this phenomenon is of such an importance for the corporate that it deserves its own streetlight. We call this phenomenon Bridgebuilders.

This is what we are beginning here, talking about the phenomenon and its importance. In further blog posts we focus on the characteristics of these Bridgebuilders that we see in the data but also refer to qualitative findings as well as connecting it to adjacent, but not so much yet connected perspectives. So more to come.

In Human Network Analysis there is a metric called Betweenesscentrality. ?Betweenesscentrality counts the number of shortest paths going through a node. In every day’s language we say Betweenesscentrality is measuring the importance of a node (in our collaboration data, of an employee) for the overall network. Importance here can be imagine as the effect of the overall network if this particular node is removed from the network. If you remove a person from the very periphery of the network, the overall network is hardly affected, if however, you remove from the network a node that is in between / connecting many different areas of the network, the effect on the network will be immense, the network even might fall apart in disconnected islands. We also use the shorthand for the Betweenesscentrality metric and say someone with a high Betweenesscentrality score (compared to others in the network) has high Social Capital.

In business life and corporate contexts, we are often trained to only think in mean values, and at the most at normal distributions, with a parameter of center (mean value) and variance (standard deviation). For Human Network Analysis this means we have to unlearn. Unlearn, as often networks do not follow a normal distribution with a center but power-laws (Brachiosaurus distributions).

Focusing on the center means the outliers are usually discarded. Boxplots and Intervalplots are tailored tools to describe centered distributions. When looking at Boxplot of the Betweenesscentrality of a collaboration network, then we hardly see the box, but there is a substantial Christmas tree (form) of outliers (marked by Asterixes). What does this mean in our collaboration context? These outliers have the highest Betweenesscentrality in the network. That means they are of extraordinary importance for the overall network, they have the highest Social Capital. This is why we call them Bridgebuilders. Bridgebuilders are of extraordinary importance for the overall network, and they have the highest Social Capital. There is a lot of talk about silos in companies. If someone is connecting the silos, then it is usually the bridgebuilders.

In summary, the occupation with the collaboration and interaction has shown a new signal. A signal that is not detectable in conventional analysis. And in the specific context of our collaboration data the bridgebuilders are of business relevance.

There are a few questions on the sanity checklist before we can celebrate the discovery of a new species:

Is the phenomenon stable in size?

According to the definition shown above in various context we have seen bridgebuilder + bridgebuilders extreme in the proportion of 10-20% of the population. It slightly of course varies with the network and duration of analysis, but it is a signal that reproduces and is stable in size.

Is the phenomenon stable over time?

Once a bridgebuilder always a bridgebuilder. Well, of course the data is sensitive to things like vacation, but it is not that bridgebuilder characteristics show and vanish completely from one sample to another, we see consistency. Over 7 samples taken for 7 different months, we see that roughly 60% appear in the majority of samples a bridgebuilders this shows a stability in the bridgebuilder behavior far beyond being arbitrary.

Is it a new phenomenon or is simply a property of line managers?

Of course, it would not be adequate, to speak of a new discovery of a species if it is only a property in which line managers distinguish themselves from individual contributors. So, our findings confirm that a higher proportion of line managers (27%) than employees (8%) show bridgebuilder collaboration performance. However due to the span of control of the line managers, if we look at the absolute numbers the picture is not confirming that bridgebuilders are line managers only: While ~ 2000 line managers are bridgebuilders, there are 8000 individual contributors that are bridgebuilders, so the vast majority of the bridgebuilders are individual contributors and not line managers.

Finally, is this a topic a corporate should be interested in at all?

A We have used the term Social Capital on purpose. As any other asset category, Social Capital deserves to be managed.

B The bridgebuilders have the highest Social Capital of all employees, a Gedankenexperiment (thought experiment) on real collaboration data, removing bridgebuilders from the network has got a catastrophic impact on the network (in our case it was 27-times higher than the removal of the Human Capital)

C With bridgebuilders in the range of 10%-20% of all employees they form a target group at least as big or bigger than the line managers, thus this group is not marginal and deserves a special treat in Talent Management and Learning & Development.

D As we are only at the beginning of the understanding, I am sure, some things we have not got right so far, but defining the concept and language opens the door to a deeper understanding of Social Capital in the corporate world, the meaning of bridgebuilders and interaction dynamics. It can help to open the field of Human Network Analysis in People Analytics.