Data-Driven Collaboration Part 3: Sustaining Performance through Continuous Value Delivery

In Part 1 of our series on Data-Driven Collaboration, “How Rich Data Can Improve Your Communication,” we identified how to plan for collaboration by ensuring that goals were established and aligned with our organizational strategy. We then moved on to Part 2, “Recognizing Personas and Behaviors to Improve Engagement,” to explain how you can build engagement by managing behaviors. In this, the final post in our series, co-authored by Swoop Analytics and Carpool Agency, we will identify how to sustain the momentum to ensure that value is continuously delivered as a matter of course.

Previously, we identified the importance of migrating from simple activity measures to those that signify when collaborative relationships are being formed. It is through these relationships that tangible outcomes are achieved. Therefore, it is not surprising that analytics—as applied to sustained relationship-building—plays an important role in continuous value delivery from collaboration.

For example, a CEO from one of Carpool’s clients had been using Yammer to receive questions for a regular Q&A session, but they’d grown concerned that the CEO’s infrequent posts in the group were creating an echo chamber among the same small group of contributors. Careful analysis showed that this was more perception than reality, and the group showed a great deal of variety in cross-organization conversation. As this was precisely the executive’s goal in forming the group, the team doubled down on their investment in this executive-to-company relationship.

Monitoring Maturation Using Analytics

At SWOOP, we have been benchmarking Yammer Installations from start-up to ‘normal operations’ for some time. With Yammer, the typical pattern of start-up is a bottom-up use of ‘Free’ Yammer, which for some, lasts for many years. Without exception, however, sustained usage only occurred after a formal launch and the tacit approval of senior management. We observed different patterns of start-ups from the ‘big-bang’ public launch, through to more organic, yet managed approaches. Whatever strategy is used, organizations always reach a stage of steady-state operations or, at worst, a slow decline.

CLASSIC YAMMER

For an Enterprise Social Network (ESN) like Yammer, we have found that the average engagement rate of the 35+ organizations in our benchmark set is around 29% (i.e., non-observers) with the best at around 75%. It is evident from our benchmarking that for larger organizations—for example, more than say 5,000 participants—it can be hard to achieve engagement levels above 30%. However, this doesn’t mean that staff aren’t collaborating.

We are seeing a proliferation of offerings that make up the digital office. For a small organization, Yammer may be their main collaboration tool, where team level activities take place. For larger organizations, however, Yammer may be seen as a place to explore opportunities and build capabilities, rather than as an execution space. Increasingly, tools like Slack, HipChat, and now Microsoft Teams are being used to fill this space for some teams that depend on real-time conversations as their primary mode of communication.

A Collaboration Performance Framework

As organizations mature with their use of collaboration tools, it is critical not to be caught in the ‘collaboration for collaboration sake’ cycle. As we indicated in “How Rich Data Can Improve Your Communication,” collaboration must happen with a purpose and goals in mind. The path to achieving strategic goals is rarely linear. More regularly, we need to adopt a framework of continuous improvement toward our stated goals. For many organizations, this will take the form of a ‘Plan, Do, Check, Act’ cycle of continuous improvement. However, in this age of digital disruptions and transformations, we need a framework that can also accommodate transformational, as well as incremental innovation.

At SWOOP, we have developed a collaboration performance framework drawn from Network Science.

DIVERSITY GRAPHIC

The framework balances two important dimensions for collaborative performance: diversity and cohesion. It identifies a continuous cycle of value delivery, whether it be radical or incremental. Let’s consider an innovation example, with an organizational goal of growing revenue by 200%:

Individuals may have their own ideas for how this radical target could be achieved. By ‘Exploring’ these ideas with others, we can start to get a sense of how feasible our ideas might be, but also have the opportunity to combine ideas to improve their prospects. The important ‘Engaging’ phase would see the ideas brokered between the originators and stakeholders. These stakeholders may be the key beneficiaries and/or providers of the resources needed to exploit a highly prospective idea. Finally, the ‘Exploiting’ phase requires the focus and strong cooperation of a smaller group of participants operating as a team to deliver on the idea.

The performance framework can be deployed at all levels, from enterprise-wide to individual business units, informal groups, teams, and right down to the individual. In a typical Carpool engagement, we work with smaller teams to demonstrate this cycle and then use the success stories to replicate the pattern more broadly. A current client started with a smaller community of interest of 400 people, and is now expanding the pattern to their global, 4,000-member division.

Deploying Analytics and the Performance Framework

Like any performance framework, it can’t operate without data. While the traditional outcome measures need to be present, the important predictors of collaborative success are relationship-centered measures. For example, your personal network can be assessed on its diversity by profiling the members of your network. Your personal network’s cohesiveness can be measured, firstly, by how many of your connections are connected to each other; and secondly, by how many of these connections are two-way (reciprocated). We can then add layers provided from HR systems such as gender, geography, organizational roles, age, ethnicity, etc. to provide a complete picture of diversity beyond typical dimensions.

In the example below, we show the collaboration performance of participants in a large Yammer network over a 12-month period. You can see how challenging it might be to become an ‘Engager’, maximizing both diversity and cohesion.

BUBBLE GRAPH

We profiled their personal networks for their diversity, cohesion, and size, and plotted them on the performance framework. Interestingly the data exposed that the nature of this Yammer network is a place for exploring and, for some, engaging. There is a gap, however, in the Exploiting region. This is not to say that these individuals were poor at putting projects into motion. More likely, at least in this organization, the ESN is not the usual place to collaborate as a team. If there is no easy transition from the ESN to a team environment, then we have a problem that many ESNs experience: lots of activity but a perception of few tangible results directly from the ESN. Carpool’s approach puts this data together with data from other services and sources to create a holistic picture of the results and impact of the organization’s collaboration evolution.

Continuous Monitoring

For many organizations, continuous monitoring simply means monitoring activity on digital platforms. As we indicated in “Recognizing Personas and Behaviors to Improve Engagement,” activity monitoring can be a poor predictor of performance. At SWOOP, we look at activity that establishes or strengthens a relationship. In the screenshot below, you can see measures such as the number of two-way reciprocated relationships; the degree to which relationships are forming between the formal organizational departments; and who is influential, based on the size of their network, not how frequently they contributed. We identify key player risk by looking at how polarized a network may be among a selected few leaders. Even the Activity/User measure inside groups predicts how cohesive that group may be. By providing this data in real-time, we have the best opportunity for both leaders and individuals to adapt their patterns of collaboration as they see fit.

COLLABORATION CHART

At Carpool, our engagements use a set of such dashboards to regularly check in on all the various channels and stakeholders, and make recommendations on an ongoing basis that accounts for the holistic communication picture.

Final Thoughts

In this series, we have taken you on a journey from planning for, launching, and productively operating a digital office. At the very beginning we emphasized the need to collaborate for a purpose. We then emphasized the need to ‘engage’ through relationships and adopting appropriate behavioral personas. Finally, we have explained the importance of adopting a collaboration performance framework that can facilitate continuous delivery of value.

In order to do all of this effectively, we not only need analytics, but interventions triggered by such analytics to improve the way we work. Analytics on their own don’t create change. But in the hands of skilled facilitators, analytics and rich data provide a platform for productive change. Collaboration is not simply about how to get better results for your organization, but also to get better results for yourself, by helping you to be a better collaborator.

Want More?

We hope these insights into data-driven collaboration will give you new ideas to innovate your own approach to internal communication. If you have any questions, or would like to learn how to establish, nurture, and grow deep internal communities, Carpool and SWOOP has a team who are ready to help you grow your business and drive collaboration today.

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

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.

Below, you see one of Carpool’s chord chart diagrams we use to map the interview data we gather. We can filter the information to focus on specific channels and tools, which we then break down further to pinpoint where we have weaknesses, strengths, gaps, and opportunities in our information flow.

CHORD CHART

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 6 months of operations.

Below, we show a typical first 6 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.

BUBBLE GRAPH

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. This new picture extends across platforms and prescribes the design for an ecosystem that meets user and business needs, aligns with industry trends, and is informed by actual usage patterns.

ECOSYSTEM DESIGN

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.