Data-Driven Collaboration Part 1: How Rich Data Can Improve Your Communication

Collaboration Visual

Originally published on Carpool.

This is the first of a series, coauthored by Laurence Lock Lee of SWOOP Analytics and Chris Slemp of Carpool Agency, in which we will explain how you can use rich, people-focused data to enhance communication, increase collaboration, and develop a more efficient and productive workforce.

It’s safe to say that every enterprise hungers for new and better ways of working. It’s even safer to say that the path to those new and better ways is often a struggle.

Many who struggle do so because they are starting from a weak foundation. Some are simply following trends. Others believe they should adopt a new tool or capability simply because it was bundled with another service. Then there are those organizations that focus primarily on “reining in” non-compliant behaviors or tools.

But there’s a way to be innovative and compliant that also improves your adoption: focus instead on the business value of working in new ways—be data-driven. When you incorporate information about your usage patterns to set your goals, you are better positioned to track the value of your efforts and drive the behavior changes that will help you achieve your business objectives.

While it’s assumed that doing market research is critical when marketing to customers, investments in internal audience research have gained less traction, yet they yield the same kinds of return. Data-driven internal communication planning starts at the very beginning of your project.

Here we will demonstrate—using real-world examples—how Carpool and SWOOP use data to create better communications environments, nurture those environments, and make iterative improvements to ensure enterprises are always working to their full potential.

Use Data to Identify Your Actual Pain Points

One team Carpool worked with was focused on partnering with customers and consultants to create innovations. They thought they needed a more effective intranet site that would sell their value to internal partners. However, a round of interviews with key stakeholders and end-of-line consumers revealed that a better site wasn’t going to address the core challenge: There were too many places to go for information and each source seemed to tell a slightly different story. We worked with the client to consolidate communications channels and implemented a more manageable content strategy that focused on informal discussion and formal announcements from trusted sources.

In the end, we were able to identify the real pain point for the client and help them address it accordingly because of the research we obtained.

Use Data to Identify New Opportunities

Data can drive even the earliest strategy conversations. In Carpool’s first meeting with a global retail operation, they explained that they wanted to create a new Yammer network as they were trying to curb activity in another, unapproved network. Not only did we agree, but we brought data to that conversation that illustrated the exact size and shape of their compliance situation and the nature of the collaboration that was already happening. This set the tone for a project that is now laser-focused on demonstrating business value and not just bringing their network into compliance.

Use Data to Identify and Enhance Your Strengths

In-depth interviews can be added to the objective data coming from your service usage. Interviews reveal the most important and effective channels, and the responses can be mapped visually to highlight where a communication ecosystem has broadcasters without observers, or groups of catalysts who are sharing knowledge without building any broader consensus or inclusion.

Turning Data Into Action

These kinds of diagnostic exercises can reveal baselines and specific strategies that can be employed with leaders of the project or the organization.

One of the first activities organizations undertake when implementing an Enterprise Social Networking (ESN) platform is to encourage staff to form collaborative groups and then move their collaboration online. This is the first real signal of ‘shop floor empowerment’, where staff are free to form groups and collaborate as they see fit, without the oversight of their line management. As these groups form, the inevitable ‘long tail’ effect kicks in, where the vast majority of these groups fall into disuse, in contrast to a much smaller number that are wildly successful, and achieving all of the expectations for the ESN. So how can organizations increase their Win/Loss ratio? At Swoop Analytics we have started to look at some of the ‘start-up’ patterns of the Yammer installations of our benchmarking partners. These patterns can emerge after as little as six months of operations.

Below, we show a typical first six months’ network performance chart, which measures group performance on the dimensions of Diversity (Group Size), Cohesion (Mean 2-Way Relationships formed), and Activity (postings, replies, likes etc.). We then overlay the chart with ‘goal state’ regions reflecting the common group types typically found in ESN implementations. The regions reflect the anticipated networking patterns for a well-performing group of the given type. If a group’s stated purpose positions them in the goal-state region, then we would suggest that they are well positioned to deliver tangible business benefits, aligned with their stated purpose. If they are outside of the goal state, then the framework provides them with implicit guidance as to what has to happen to move them there.

Defining Group Types by Network Behaviour

Defining Group Types by Network Behaviour

At launch, all groups start in the bottom left-hand corner. As you can see, a selected few have ‘exploded out of the blocks’, while the majority are still struggling to make an impact. The 6-month benchmark provides an early opportunity for group leaders to assess their group against their peer groups, learn from each other, and then begin to accelerate their own performances.

Painting the Big Picture

The convergence of multiple data sources paints a holistic picture of communication and collaboration that extends beyond team boundaries. The discussion about the ROI of adopting new ways of working, such as ESNs, hasn’t disappeared. While we believe it’s a waste of resources to try measuring a return from new technologies that have already been proven, it’s clear that developing business metrics and holding these projects accountable to them is just as critical as any effort to increase productivity.

The nature of these metrics also needs to shift from a focus on “counts and amounts” to measures of a higher order that tie more closely to business value. For example, knowing that posting activity has risen by 25% in a year may make you feel a little better about your investment in a collaboration platform. Knowing that there is a higher ratio of people engaging vs. those who are simply consuming is much better. Showing a strong correlation in departments that have higher percentages of engaged users with lower attrition rates … that’s gold.

So now is the time to look at your own organization and wonder: “Do I track how my people are connecting? Do I know how to help them become more engaged and productive? When was the last time I measured the impact of my internal communication ecosystem?”Then take a moment to imagine the possibilities of what you could do with all of that information.

Stay tuned in the coming weeks for Part 2 and Part 3 when we address the topics of driving engagement by identifying types of enterprise social behavior in individuals, and the results we’ve seen from being data-driven in how we shape internal communications and collaboration.

Previous
Previous

How to Use Hashtag Analytics to Track Employee Engagement

Next
Next

Diversity is Essential but not Sufficient