A social business is a company that uses social media to its maximum advantage, with all the different ways in which the social media data is seamlessly integrated into the business processes and decision making of all levels of the company.
To advance social business, a company has its central team – digital strategy and innovation – working with social media data in addition to other analysis functions. The combined results from these data sets are then cut and distributed to the different business sectors. The services required by the individual departments also differ, as do the logistics, targeting and marketing tactics of areas.
Structuring your business as a social business is the one thing, but without the right people in the right places you will not get any further. The selection of the right staff accelerates the progress of the social business project.
An investigation by Gartner suggests that seven to eight analysts should work per billion sales, two of which should be dedicated to the social media. For the majority of Fortune 1000 companies, this means a considerable number of employees for Social Analytics.
Beyond Technical Background
Obviously, most companies strive to gain the best analytical minds for their team. But to be successful, you have to pay more attention than just hiring data scientists with a strong qualitative background.
Many organizations focus now more on the charisma of the employees in the data area. The best analysts also radiate a certain attraction. And since training and qualification are becoming increasingly important in this role, they should convince both skillful and take for themselves as able to deal with a spreadsheet.
“What many companies teach data a scientist now is how to present their results to the management ideal: Storytelling is now a normal part of the curriculum analytics. At the same contact data scientists increasingly complex and advanced techniques. The bottom line, however, is the efforts to make analysis results more easily accessible, not keep up with the increasing complexity of the analysis.” (Dr. Sam Ransbotham, Data and Analytics Editor, at MIT Sloan Management Review)
People with passion
A team of passionate creators and pioneers help to uncover results that they have not expected and to pay more attention to the actions that result from the findings.
“Sure, people with a background in Analytics and data science are great. Yes, attention to detail is essential. Yes, they often come from academic programs that focus on the abilities of the left brain. What with all these skills is lacking, however, is this indomitable will to solve the mystery. Find exactly these people.” (Wans Mcinnes, CMO of Fire Watch)
People with visualization skills
Andy Frawley is CEO of Epsilon, an organization with more than 5,000 employees, who describes itself as a “global marketing company”. He believes that the effective dissemination of insights is at least as important as the actual extraction of the findings from the data collection. This means that he is much more concerned about combining employees with less technical background with classical data scientists, especially as the analysis technologies are always easier to use.
“In the field of data visualization is still great potential, and even some tools that provide predictive approaches can now be used by less tech savvy people. When it comes to hardcore machine learning and things like that, employees are required with other qualifications. “ (Andy Frawley, CEO of Epsilon)
People who can handle real-time data
Another dynamic that supports this way of thinking is that many of the data must be provided in real time, in particular social media data. So is an increased need to Insights, the use of technologies is emerging largely be recovered instead of people calculus.
“Previously, it was said, ‘I want to develop a model to assess who will take out a mortgage’. Then we spent six weeks developing the model and another six weeks of application. But all of that is happening today in real time, as well as consumers to act in real time. This results from the marketing standpoint, a completely new rhythm. ” (Dr. Jerry Kane, Associate Professor of Information Systems at Boston College)
What is the perfect balance?
There are opposing views about which demographic pool is best used to compile this optimal “science-meets-marketing” team from analysts for a successful social business.
While larger companies rather focus on data specialists of Generation Y, and rapidly expanding companies prefer digital informed Millennials, Mike Volpe represents perhaps the most balanced setting.
“Looking for people who speak digitally without an accent, digital natives or immigrants are equally suitable as long as they have the full ‘citizenship’. “ (Mike Volpe, Angel Investor and Former HubSpot CMO)
This balanced ratio of forces pays the social media data – under the right conditions – the necessary respect and keeps them in the river, while at the same time, allows a healthy critical look at the findings.
The younger digital natives bring mobility and consumer understanding, which is essential in order to survive in the 2010s. Moreover, their very own understanding of the digital landscape, gives the output of the team context, depth and value.
This is obvious that most of the teams are a mix of experience, backgrounds and abilities. Finding these people sometimes is difficult. Social analysis departments themselves are relatively young. Therefore, it is advisable to search for graduates or people early in their careers. The best way to find those that are taken for more complex data science careers and qualified them for the roles that team are currently needed in social insights.
It is not surprising that there is no fixed methodology for structuring and building a first-class social analysis operation. The specific requirements depend on the internal corporate structure, objectives and of course the aspirations and attitudes of management. However, some best practices developed by the practices of the world’s most successful companies. And as more and more companies work with new and untried implementations, we can expect more changes in the coming years.