BIG DATA
BIG DATA
Leveraging On Your Social Networks
By Timothy Oriedo
As the old adage goes , show me your friends and I will tell who you are . Each of us faces a daunting prospect each time we wake up in the morning and head off to our business : How do we manage all of the contacts in our networks ?
The problems of scattered data and information overload are simply outgrowths of the natural limits of our mammalian brain . Cold comfort , I ’ m sure , for roles where the problem is especially acute ( and where relationships matter most ): sales , business development , and recruiting , consulting , marketing and especially executive management , to name a few .
Ideally , attacking this problem requires a new way of thinking about relationships , even though it can be hard to think of our best relationships - professional connections included - as quantifiable . To help tackle this , and as is in the tech industry , it ’ s common practice to invoke “ Laws - e . g Moore ’ s Law and “ rules ” – 80 / 20 ( aka the Pareto Principle ) as a way to shorthand real-world phenomena that would otherwise take a long time to explain .
Dunbar ’ s Number is a prime example of one of these “ laws ” and is a critically important construct for contact management and , more broadly , social media . Created by Robin Dunbar , a British anthropologist , The Dunbar ’ s number is used by Data Scientists to model algorithms for analyzing social networks interactions .
There ’ s a lot of truth behind the theory of Dunbar ’ s Number . It posited that the average human brain is limited in that the number of neocortical neurons ( Cognitive ) limits the organism ’ s informationprocessing capacity and that this then limits the number of relationships that an individual can monitor simultaneously . When a group ’ s size exceeds this limit , it becomes unstable and begins to fragment . These social relationships number between 120 and 230 people at one time , but the “ number ” has been averaged out to 150 .
What ’ s the significance of this ?
It seems like every few weeks we ’ re inundated with yet another social network . The Internet , for all its glory and ability to connect us , should be exposing us to inherent risks . A popular meme of the last few years is the social media “ filter bubble ” - the idea that services like Facebook and Twitter serve to reinforce users ’ biases by feeding them content with which they are already inclined to agree . This theory has been widely applied to politics , and of course linked to so-called fake news which further polarizes an already politically divided population .
The average Facebook user has 338 “ Friends ”. The issue on LinkedIn is even more pronounced , where the number is over 500 . If you look through your Facebook Friends , there ’ s a good chance that you can break them out into buckets . I have a few family members , a number of people with whom I ’ ve connected because of work background and quite a large group of wellness and farming hobbyists .
So while I ’ m connected to 4000 + people on Facebook , I maintain relationships with most of them because of the metaphorical buildings in which we work . The same is true for LinkedIn . Over the course of my 15 years in the workforce , I ’ ve made connections in media , marketing , advertising , coaching , data and academia .
The process of networking is one of building relationships . Like any relationship in life , building your network is going to take some effort , but the payoff is huge . Taking time to organize your contacts , and then to stay in touch with them , gives you a definitive advantage over the vast majority of people that you ’ ll meet on any given day .
Use the tools that help you focus on building relationships with the right people and be amazed at what you produce .
Timothy Oriedo is Certified Big Data Scientist ( MIT ), Executive Coach , and Data Science Managing Consultant at Metropol Corporation . You can commune with him on this or related matters via mail at : Timothy . Oriedo @ predictiveanalytics . co . ke .
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