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.
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.
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.
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.
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.
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.
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.
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 has a team of strategists who are ready to help you grow your business today.