Making Visible the Invisible: Meaning, Not Content, Matters in Social Data

There is no question that in today’s connected world — where few activities go untracked and undigitized — social data is everywhere, being generated by the terabyte. Fast on the heels of social data are innumerable ideas for harnessing it. But all too often the focus seems to be on the vastness of data, the wow-factor of its proliferation, the fear-factor of its invasiveness. Lost from the discussion is that social data is not like other data — it cannot be calibrated, is often ambiguous, and the traditional tools of data analysis may not apply.

Given the buzz about Facebook’s data trove, you might think the only use for social data is to tap into consumers’ likes and dislikes. However, the potential to use social data extends far beyond consumer marketing. The free-flowing streams of data generated as people conduct their business and personal lives online hold insights into new ways to address old business issues and to discover new ones.

The question, then, is what is social data telling us about our organizations and the people around us? How do we accommodate these emerging insights to make business decisions, particularly when they challenge established practices, processes and organizational hierarchies?

Social Data Reveals Who We Are (and who we think we are)
Much social data reflects users’ interests, perceived expertise, social outlook, skills, and experience, either based on information they reveal directly in profiles or indirectly through the discussions they participate in and groups they join. Enterprise social media tools can make this previously hidden information more visible to employees and managers. The results range from improved problem solving to better staffing decisions and more engaged employees.

An employee facing a technical challenge might wonder if anyone has encountered it before. At Avaya, employees use social software (SocialCast) to find co-workers whose experiences might be relevant to a specific issue. The result has been quicker resolution of customer issues, which translates to lower customer support costs and higher customer satisfaction. LinkedIn provides a similar ability for employees to reach beyond the walls to external networks, accelerating problem solving and leading to new discovery.

A manager staffing for a new product might wonder, “Who has this skill set and is interested in product development? What have they been working on and will they fit with the team?” Facebook is just one company that uses social media to “work out loud.” This type of data increases the internal visibility of employees’ experiences and skills, to everyone in the company, and may highlight areas where a group is particularly strong or weak.

Reveals What Customers Really Think About Our Companies and Products
For businesses that understand that social media is about more than gaining followers and pushing ads, social data can explicitly inform product development. Giffgaff, a UK mobile telecom company, uses social media to engage customers in designing the phone itself as well as the service plans.
For a manager wondering what her employees are discussing or a business leader wondering how a news report has affected brand, behavioral data can reveal trends that impact decisions. Companies like Prosodic measure sentiment in real time, advising community managers about the most effective times to post content in order to sustain participants’ interest and engagement.

And Also Reveals What We Do (and Don’t Do)
The ubiquity of sensors and other means of digital tracking to collect data and the computational power to store and analyze data reveals that social data stretches beyond individuals’ online lives to encompass the geography, if not the content, of their interactions. This opens the door to looking beyond content to the patterns of behavior and interactions that occur.

High-performing teams have been kind of a Holy Grail, particularly in service industries. Yet when Deloitte Consulting LLP decided to analyze social data (including phone, email, and online interactions) from one of its own practice groups and tie the data to operative metrics (revenue per consultant, profitability and staff turnover), they discovered some “truths” about high-performing teams turned on their head. Notably, although the firm had focused on creating “tight” teams, high performance depended more on external connections to other parts of Deloitte than on internal interactions.

In a related effort, research at the MIT Media Lab using sensors to track live interaction found that the performance of teams at a call center was highest when they carried on “back-channel” communication and interacted outside of formal meetings, irrespective of skills, education or incentives. What leaders thought they knew about teams wasn’t supported by the data. This research led to insights about metrics that might better predict team performance and offer a means of creating interventions before performance levels dip.

How Do You Convert Social Data Into Social Insight?
The most challenging aspect of social data is making the connection from the data you have to actionable insights and turning insights into behavioral changes that move the needle on performance. If you are going to have a data-driven organization, you have to know how to use social data, and most organizations don’t.

The following questions can help you find the seeds of performance improvement in your data:

  • What question are you trying to answer? Start with questions relevant to your business, but allow for the discovery of new questions, in patterns you didn’t know to look for.
  • What does the data mean and what do the relationships represent? Each type of data may require different tools and interpretations. For example, social network analysis (SNA) of LinkedIn represents professional relationships while in Facebook it represents personal relationships.
  • How will the answer change the way you operate? The goal is to understand what social data represents well enough to craft useful indicators. Real-time social data makes it possible to approach business operations as an experiment, to design adaptive operational strategies that respond to the data and to have ongoing engagement with the data built into your processes.
  • If the answers are dramatic or break with tradition or accepted practices, how will you convey the insight to get others on board?

What do you think? Does your social data strategy amount to substituting social media for traditional print and air advertising? Or have you found opportunities to use social data to transform operations?

Eric Openshaw is Vice Chairman and U.S. Technology, Media and Telecommunications Industry Leader for Deloitte LLP. He also leads the U.S. technology sector group for Deloitte LLP and serves as the global technology sector leader.

Professor Pentland is Founder/Director of the new MIT Connection Science and Engineering Center, and the Media Lab Entrepreneurship Program. Formerly he directed the MIT Media Lab and Media Lab Asia in India. He advises the World Economic Forum and leadership of many of the Fortune 100 companies.


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