Four Ways Social Data Can Generate Business Value

Big data has been described as the new oil, but perhaps a more apt metaphor is the new solar — it is a renewable source of energy, but must be cost-effectively captured and processed to be converted into new forms of value.

Companies both large and small have access to a growing stream of social data from an increasing number of sources. This stream is continually being enriched and renewed as our interactions unfold over time and as our ability to efficiently capture data about those interactions increases.

While many firms are investing time and resources into mining this data, the bulk of the attention thus far has been placed on how social data can help public relations, marketing and sales engage more relevantly with consumers. Indeed, the amount of data available for this purpose is staggering: according to a Forrester blog from 2010, American consumers were already posting more than a 1.6 billion reviews of products and services online in 2009. That number continues to climb as more sites enable user-generated reviews and ratings.

We believe, however, that firms are missing a significant opportunity to use social data to gain intimate and real-time knowledge about what is going on within, not just outside, the organization.

We have identified four ways that employee-based social data can generate substantial business value:

1. Social data can help organizations improve team performance.

MIT professor Alexander (Sandy) Pentland has explored the connection between team performance and communication patterns by analyzing social data collected from small physical sensors called sociometric badges. (The article “Understanding ‘Honest Signals’ in Business,” from the MIT Sloan Management Review archive, provides an excerpt of Pentland’s book about this topic.)

Pentland’s question of the data was: among teams with very different performance levels, are there differences in physical behavior and interaction that explain the difference in performance? His research found patterns of communication to be the most important predictor of team success — greater than individual intelligence, personality, skill and even the substance of the discussion combined.

The analysis was so robust, in fact, that Pentland’s team was able to predict the success of a product launch by looking only at the communication patterns of team members. His findings suggest questions that business leaders might ask about their own teams to identify data-driven opportunities to improve performance: Who are team members communicating with and how often? Are teams interacting primarily internally or with many others outside of the team? Do team members communicate with each other or mostly through the leader?

2. Social data can help organizations anticipate financial performance.

Executives have long been aware that financial metrics are lagging indicators — they tell us how we did in the past, but offer little insight into where we’re going. Operating metrics can help anticipate financial performance, but often, by the time they are measured, it is too late to act upon the findings.

Now, flow metrics generated from analyzing interaction patterns can help executives anticipate operating performance and, in turn, financial performance. For example, early and rich interaction flows across product development, marketing and sales and manufacturing organizations (and not just within a cross-functional team charged with driving a new product introduction) could indicate faster product introduction lead-times — which could in turn drive more rapid growth of revenue.

3. Social data can help organizations drive financial performance.

Enterprise social software can expose information that has historically lacked appropriate checks and balances — from vacation day reporting inaccuracies and expense management to ‘green-ness’ and energy consumption — and improve outcomes for all.

Imagine if firms exposed expense data via internal social tools and let employees compete with one another to spend the least on travel meals per day. Transparency and peer influence may motivate individuals to make purchasing decisions with the best interests of the firm in mind, rather than based on what’s purely acceptable (say, spending $99.99 on a $100 per diem).

4. Social data can help organizations identify high performers.

By mining social data, companies can gain more insight about the role of individuals in the organization based on their interaction patterns.

Such insight can be used to optimize cross-functional teams and ensure that promotion and compensation discussions are backed with more systematic data as well as personal observation. Insight can also be used to identify high performers early in their careers to target them for more active development.

Today, many organizations take either a 30,000-foot view of social data or an intensely granular, technical approach. Few firms have tapped into social data in a way that allows them to connect it explicitly to operating performance data and execute on it effectively.

Social data science leaders and business thought-leaders must meet in the middle to collaborate on both how to analyze the data and why such analysis would be meaningful. We have only begun to understand social data’s potential value in the workplace, but much of this potential is dependent on having the mindsets and methods in place to make the most of our newest natural resource.