How Healthy is your Enterprise Social Network?

At the heart of any Enterprise Social Network (ESN) are the groups or communities formed within them. Understanding the health and productivity of these groups should therefore be front of mind. For ESNs we can look again to the more mature experiences with consumer and external customer communities for guidance. We have written previously about the need to take care when translating consumer network metrics to the Enterprise. But in the case of community health, we believe the mapping from external community to internal community can be fairly close.

What can we learn from consumer and customer networks?

Arguably the gold standard for community health measures was published several years ago by Lithium, a company that specialises in customer facing communities. Lithium used aggregate data from a decade’s worth of community activity (15 billion actions and 6 million users) to identify key measures of a community’s health:

  • Growth = Members (registrations)
  • Useful  = Content (post and page views)
  • Popular = Traffic (visits)
  • Responsiveness (speed of responsiveness of community members to each other)
  • Interactivity = Topic Interaction (depth of discussion threads taking into account number of contributors)
  • Liveliness (tracking a critical threshold of posting activity in any given area)

march-blog-1

march-blog-2

At the time of publishing, Lithium was hoping to facilitate the creation of an industry standard for measuring community health.

Other contributors to the measurement of online community health include online community consultancy Feverbee with their preferred measures as:

  • New visitors – a form of growth measure
  • New visitors to new registered members– conversion rate measure
  • % members which make a contribution– active participants
  • Members active within the past 30 days– time based activity
  • Contributions per active member per month– diversity and intensity measure
  • Visits per active member per month – traffic measure
  • Content popularity-useful content

Marketing firm Digital Marketer health measure recommendations include:

  • Measuring the total number of active members, rather than including passive members.
  • Number of members who made their first contribution as a proxy for growth.
  • A sense of community (using traditional survey methods).
  • Retention of active members i.e. minimal loss of active members (churn rate).
  • Diversity of membership, especially with respect to innovation communities.
  • Maturity, with reference to the Community Roundtable Maturity Model.

Using SWOOP for Assessing Enterprise Community/Group Health

SWOOP is focused on the Enterprise market and is therefore very interested in what we can usefully draw from the experiences of online consumer and customer networks. The following table summarises the experiences identified above and how SWOOP currently addresses these measures, or not:

Customer Community Health Measures SWOOP Enterprise Health Measures
Growth in Membership Measures active membership and provides a trend chart to monitor both growth and decline.
Useful Content Provides a most engaging posts widget to assess the usefulness of content posted.  We are currently developing a sentiment assessment for content.
Popularity/Traffic SWOOP does not currently measure views or reads. Our focus is more on connections that may result from content viewing.
Responsiveness Has a response rate widget that identifies overall response rate and the type of response e.g. like, reply and the time period within which responses are made.
Interactivity Has several rich measures for interactivity, including network connectivity and a network map, give-receive balance and two way connections. The Topic tab also identifies interactivity around tagged topics.
Liveliness The activity per user widget provides the closest to a liveliness (or lack of liveliness) indicator.
Activity over time The Active Users and Activity per User widgets report on this measure.
Contributions per member The Activity per User widget provides this. The New Community Health Index provides a 12 month history as well as alarms when certain thresholds are breached.
Sense of community Requires a survey, which is outside the scope of SWOOP.
Retention Not currently measured directly. The active members trend chart gives a sense of retention, but does not specifically measure individual retention rates.
Diversity Not provided on the SWOOP dashboard, but is now included in the SWOOP benchmarking service. Diversity can be measured across several dimensions, depending on the profile data provided to SWOOP e.g. formal lines of business, geography, gender etc. In the absence of profile data, diversity is measured by the diversity of individual membership of groups.
Maturity The Community Roundtable maturity assessment is a generic one for both online and offline communities. Our preference is to use a maturity framework that is more aligned to ESN, which we have reported on earlier. How the SWOOP measures can be related to this maturity curve is shown below.

march-blog-3

Thresholds for What’s Good, Not so good and Bad

We know that health measures are important, but they are of little use without providing some sense of what a good, bad or neutral score is. In the human health scenario, it is easy to find out what these thresholds are for basic health measures like BMI and Blood Pressure. This is because the medical research community has been able to access masses of data to correlate with actual health outcomes, to determine these thresholds with some degree of confidence. Online communities have yet to reach such a level of maturity, but the same ‘big data’ approach for determining health thresholds still applies.

As noted earlier, Lithium has gone furthest in achieving this, from the large data sets that they have available to them on their customer platform. At SWOOP we are also collecting similar data for ESNs but as yet, not to the level that Lithium has been able to achieve. Nevertheless, we believe we have achieved a starting point now with our new Community Health Index Widget. While we are only using a single ‘activity per active user’ measure, we have been able to establish some initial thresholds by analysing hundreds of groups across several Yammer installations.

march-blog-4

Our intent is to provide community/group leaders with an early warning system for when their groups may require some added attention. The effects of this attention can then be monitored in the widget itself, or more comprehensively through the suite of SWOOP measures identified in the table above.

Communities are the core value drivers of any ESN. Healthy enterprise communities lead to healthy businesses, so it’s worth taking the trouble to actively monitor it.

 

 

 

 

 

 

 

 

 

 

Why we Should Worry about Response Rates in Enterprise Social Systems

Why we Should Worry about Response Rates in Enterprise Social Systems 

response-rates-cartoonThis post continues our series on key SWOOP indicators. We have %Response Rate as a key performance indicator for organisations embracing problem solving and innovation within their Enterprise Social Networking (ESN) platforms. Difficult problems require deep dialogue, discussion and debate to be effectively solved. A response to a posting is hopefully the beginning of a constructive discussion, hence an important indicator of the degree to which an organisation is predisposed to solving problems online. Our ESN benchmarking of close to 50 organisations has the average response rate at 72%, but with a large range from a low of 32% to a high of 93%. response-rate-chartresponse-rate

The Response Rate widget identifies the percentage of posts that have received a written ‘reply’ and/or a ‘like’, for the period selected. It will also identify the % posts that have received no response; a measure that community managers need to monitor closely. The timeliness of the response is also reported.  

The Response Rate widget is available at all SWOOP reporting levels, from the individual, right through to the Enterprise overall. While not all posts are framed as problems, the response rate does reflect how responsive an organisation is overall. A response is a tangible signal of value received. In the absence of specific value stories, it is the most direct measure of value being facilitated on the ESN platform.  

For the individual, a poor response rate can indicate that your postings are not framed appropriately for attracting a response. For a group, a poor response rate may indicate a lack of a critical mass of members, or inadequate community management. 

Business Imperative 

It sounds obvious, but before problems can be solved, they need to be shared. Sharing a problem can be construed as a weakness. When senior management openly share a problem, they run the risk of ‘losing face’. Isn’t solving difficult problems what they are being paid to do?  Yet it is the senior management that need to lead the way in generating a culture for collaborative problem solving. As David Thodey, the former CEO of Telstra told us,Management don’t know everything…we have been guilty of releasing poor policies that have taken us years to recover from’. Thodey used the ESN to share problems that new policies were required for, and then getting feedback before finally releasing a new policy. 

The first challenge therefore is to develop a culture which respects that sharing a problem is not a weakness but a strength of character. Think about using hash tags to monitor problems posted, and their journey to a hopeful resolution. Once problems are shared freely on the ESN, the Response Rate measure can be used to measure problems solved. Many of the online technical forms are established specifically for tracking problem resolutions. There is no reason that the ESN cannot be used in a similar way. 

 

Influential People – SWOOP Style

 

In this series of articles, we are profiling each of the SWOOP Analytics Widgets by referencing them to the Enterprise Social Maturity Framework, that we introduced previously. The SWOOP analytics widgets are designed to guide our end users through each stage of the maturity journey. The ‘Influential People’ widget is seen to be most valuable when you are looking to solve difficult problems and/or driving new innovations to positive outcomes: 

enter-collab-3

influential-peopleInfluential people, as the name suggests, are those people that are best positioned to influence others through their interactions. Platforms like LinkedIn and Twitter typically use the popularity of content published to measure influence. In LinkedIn’s  case, profile views contribute strongly to your perceived influence. SWOOP uses a different basis for measuring influence, drawn from the science of social network analysis (SNA). SNA bases influence measured on the size and nature of one’s connections. An individual’s influence in SWOOP is measured by the size of their personal network.  

Your Personal Network Map, which can be viewed on your  personal tab, is a visual representation of your full network. At the Group, Business Unit or Topic level, influence is measured by an individual’s network within the Group, Business Unit or those engaging with a given topic.  

img_0101

A network connection is formed when you interact with someone online. It could be a ‘reply’ or ‘like’ you have made to a post, or vice versa. Activity levels are not considered; only the unique connections made.  

Business Imperative 

If you want to influence the activities of a group of people, the most efficient way is to engage with those that are best placed to influence them. Influence propagates through relationship links. Enrolling the influencers in your target audience can accelerate the change that you are seeking. You can aim to become an influencer yourself by looking to expand your network within your target audience. If you are identified as an influencer yourself, it is important to use your privileged location in the network to bring others into the network i.e. being the Catalyst/Engager, ensuring  diverse points of view are accommodated. 

Influencers can play a big part in helping their organisations to become more responsive. Their central position in the network enables them to become important role models by being personally responsive to problems they see. Influencers need not be able to solve the problems themselves, but they are ideally placed to identify those in their network that can. 

 

Enterprise Collaboration Maturity Frameworks

It’s popular for organisations adopting a new technology platform e.g. MS Office 365, or management practice e.g. agile working; to think of their progress in terms of maturity. Maturity frameworks have been a popular means for organisations to be able to assess their progress with a significant change initiative. When the change is related to an industry wide adoption theme, it may also be possible to compare levels of maturity between organisations.

In this article we identify two maturity frameworks developed for use with Enterprise Social Networking (ESN) platforms and show how we have combined them to come up with an ‘end to end’ journey, from simple technology use to facilitating a fully agile and innovation driven organisation.

The maturity framework draws explicitly from two previously published Enterprise Social Maturity frameworks. The first is Siemens’ ICUP (Impact, Connectedness, User engagement, Platform adoption) Model, and the second one is from enterprise social business consultant and evangelist Simon Terry.

Siemens Maturity Model

entre-collab-1

The Siemens model starts from ‘Platform Adoption’ where a new digital platform is being launched and where staff are initially just being encouraged to use the platform. The model then progresses to ‘User Engagement’, usually around published content.

Up to this point the traditional activity analytics such as number of users, number of posts and number of monthly active users is commonly found in the ‘out of the box’ analytics, provided by the ESN platform suppliers. These are all about measuring activity, but not about measuring the interactions between people. This is not surprising, since ESNs were originally inspired by consumer social networking sites in the first place.  The economic model for consumer social networking platforms is referral marketing through your friends and contacts. Consumer analytics are targeted at bringing qualified eyeballs to your advertising content.

The final stages in the ICUP model is the generation of business impact from the newly formed networks of collaborating staff through the stages of ‘connectedness’ and ‘impact’.

Simon Terry’s Maturity Model
enter-collab-2
Having had first-hand experience as a CEO in a financial services organisation, and a champion of a Yammer network, Simon Terry has now become an evangelist for the business value that can be gained from enterprise social platforms.  Simon Terry Maturity Model looks beyond simple adoption to full business value creation. As Terry notes,  “Adoption is a tool of value creation. It is not the result”. The model moves through the stages of Connect, Share, Solve and finally Innovate. 

The Combined Maturity Model

Both models are excellent for what they have been designed to do, but by combining the best pieces of both models we can represent the complete journey from the very earliest technology adoption challenges, right through to enabling the agile innovating enterprise. We’ve chosen to replace the ‘Connectedness’ and ‘Impact’ stages from ICUP with Simon Terry’s maturity model, which provides more distinct stages, where higher levels of business value start to materialize.

 

enter-collab-3

We have purposely drawn a dotted line between the ‘User Engagement’ stage and the ‘Connect’ stage. This is the point where ‘Social’ becomes less about content and more about relationships. The analytics therefore need to be different, since the economic model for Enterprise social networking is different. Enterprise value is generated through collaborating staff solving problems and creating new products and services. Activity-based analytics alone are not sufficient to support true Enterprise business value generation. This is the point that separates those organisations simply looking to drive staff to using a platform, to those looking to drive true business value, facilitated by the platform.

In future articles we will build on this maturity framework by showing how each of the SWOOP analytic widgets identify with each stage of the maturity journey; and also how our benchmarking activities are being used to assess organisations using this new combined ESN maturity framework.

Smart Collaboration = Smart Money

smart-collaboration-artwork

Smart Collaboration’ is the title of Harvard’s Heidi Gardner’s latest book. The book builds and expands on her well cited HBR article  “When Senior Managers Won’t Collaborate” , smart-collab-1where she presents some compelling data demonstrating that collaboration does pay, big time. Her network representation comparing the networks of two lawyers, with Lawyer 2 responsible for generating much higher revenues from her larger and more diverse network, may seem quite logical. Additionally, she shows that greater peer-to-peer collaboration does indeed generate much higher revenue levels; the key measure of success for most advisory firms. But those whom have worked in Partner led advisory firms, will understand the tribal norm of ‘Eat what you Kill’, can actively work against cross-enterprise collaboration. Gardner’s research will hopefully go a long way toward convincing the leaders of advisory organisations that it is time to abandon this tradition. But in the book she acknowledges and addresses head on, the challenges ahead.

In a decade of conducting survey based Organisational Network Analyses (ONA) projects around the world and across many industry sectors, we have found that it is the partner led organisations that fall most strongly into the ‘tribal’ area (High cohesion/Low Diversity) of our Network Performance framework.

smart-collab-2

The above graph plots a representative set of results from client projects undertaken over a decade. In our surveys we use a common question of “Who do you rely on to get your work done?”; to identify people to people relationships. We then look at the proportion of reciprocated (two-way) relationships to devise a cohesion score. The y-axis diversity score is determined by the proportion of cross-departmental activity, similar to Gardner’s ‘cross practice’ measures for consulting organisations. The bottom right region (High Cohesion/Low Diversity) is populated by advisory firms i.e. consulting/engineering etc.. Our advice to these firms mimics that of Gardner’s, to grow the diversity of their work teams, without sacrificing the existing levels of cohesion. This is easier to say than do, as you can see from the above data; diversity and cohesion are often traded off against each other, yet this doesn’t have to be the case.

So How can Partner-Led firms be Disrupted by Smart Collaboration?

In her book, Gardner uses role archetypes to characterise the different behavioural dimensions typically found in partner led organisations. Interestingly, we find a strong correspondence to our own ONA characterizations, and more recently our on-line collaboration personas.

Gardner also identifies the increasing use of collaborative software platforms by professional services firms to help ‘break down the silos’, to better facilitate ‘smart collaboration’. While we agree with the principle, the devil can be in the detail. Without a supporting collaborative culture, these platforms can be used to actually reinforce existing silos. We have seen many instances of teams creating private groups on the pretense of ‘competitive sensitivities’; sometimes warranted, but more often not.

The following chart identifies the synergies between Gardner’s archetypes overlaid onto our Personal Networking Performance framework, to provide a link to our network centric perspective. Additionally, we also overlay our online networking personas to extend the view further to the online collaboration environment within which SWOOP’s analytics operate.

collab-3

As we can see, there is a direct mapping between Gardner’s archetypes and our Networking archetypes. The ‘Seasoned Collaborator’ is Gardner’s key role supporting ‘Smart Collaboration’. Likewise, our ‘Ambassador’ role plays the key brokering role in networks, bridging the diversity/cohesion divide. The ‘Solo Specialists’, like our ‘Specialists’ have strong, cohesive, yet localised networks. The ‘Ring Master’, like our ‘Agent’ are playing an oversight role. They have diverse networks, but not the power to necessarily drive positive actions to the same degree as the ‘Seasoned Collaborators/Ambassadors’. Finally, the ‘Contributor’ / ‘Practitioner’ have both limited diversity and cohesion in their networks. They are more regularly younger or new to the organisation staff; or staff that are comfortable to ‘do their bit’, without trying to ‘push the envelope’.

By extending this framework to the online world, we are escalating the analytics from ‘snapshot’ project based analyses, to the real-time online analytics that SWOOP provides.  Online analytics can measure and monitor ‘Smart Collaboration’ in process. We have now benchmarked close to 50 organisations on a series of collaboration indices, which include the behavioural personas indicated. The correspondence is not one-to-one, but nevertheless still informative.

The ‘Engager’ maps closely to the ‘Seasoned Collaborator / Ambassador’ archetype, by identifying those participants whose online networks are both diverse and cohesive. The important ‘Catalyst’ persona instigates interactions. They are key to growing online communities, but are not always those that broker connections. Hence they are located between the ‘Agents/Ringmaster’ and ‘Ambassadors/Seasoned Collaborator’. The ‘Responder’ persona will regularly have a diverse, yet less cohesive online network. There is not a correspondence with the pro-active ‘Agent/Ringmaster’ role, as the role is more re-active, than pro-active. The ‘Broadcaster’ tends to prioritise ‘telling’ over ‘discussing’. In this sense the behaviour is similar to the solo specialist, but ‘Broadcasters’ do not have highly cohesive networks; hence their positioning toward the ‘Contributor’/’Practitioner’. Finally, the ‘Observer’ persona has minimal participation in the online platform and therefore has low or non-existing online diversity and cohesion. The ‘Observer’ is an artefact of online platforms and there is little, if any, correspondence to the ‘Contributor / Practitioner’ archetype.

So can digital ‘Smart Collaboration’ disrupt the current status quo of the big end consulting companies? Well Harvard Professor Clayton Christensen thinks so. He wrote an article on Consulting on the cusp of Disruption back in 2013, citing the clients’ drive for more transparency and also the increased availability of big data analytics and predictive analytics. More recently, this article on Big Four Firms face tsunami of threats from Digital Groups’ also explores the digital disruption potential. And of course Heidi Gardner’s ‘Smart Collaboration’ might be framed as a helpful guide to partner led advisory firms, but could also be read as a ‘if you don’t, someone else will’ warning to the incumbents.

Final Comments

In this article we aimed to draw linkages between Heidi Gardner’s recent work on ‘Smart Collaboration’ and firstly, our own organisational network analysis consulting work. We both used survey techniques to elicit our insights, though Gardner also drew from personal interviews and observations. The extension of these insights toward insights that can be drawn from online interactions is still ‘work in progress’. Unlike surveys, interviews and observation; online analytics has to create its insights through more indirect means. That said, the wealth and volume of data available online swamps the data that can be gained from traditional surveys and interviews. At SWOOP we have now collected and analysed collaboration data from more organisations in less than two years, than from a decade of consulting projects. While consulting projects are often necessarily constrained to a limited scope, the online analysis, drawing its data from the collaborative online platforms, covers the full breadth of these organisations.

We are excited by the potential for online analytics to facilitate ‘Smart Collaboration’ in real-time. Watch this space for updates on our collaboration benchmarking research.

 

 

 

 

 

 

 

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.

Yammer Benchmarking Insights #3 – Collaboration at the Personal Level

 In this episode we drill down to the most detailed level. That’s you, the individual collaborator.

At SWOOP we have designed behavioural personas to characterise individual collaboration patterns based on your pattern of activity.For example, if you are a Catalyst, you are good at getting responses to your posts. Catalysts are important for energizing a community and driving the engagement of others. If you are a Responder, you are good at responding to other people’s posts. Responders are important for sustaining a community and extending the discussions. An Engager is able to balance their Catalyst and Responder behaviour and is seen as the Persona to aspire to, as the Engager effectively balances what they give to others in the form of posts, replies, likes etc. and those that they receive from others. Therefore they are well placed to broker new relationships. Broadcasters tend to post without engaging in conversations. Observers are simply not very active, with less than a single activity every 2 weeks. We see Broadcasting and Observing as negative personas.

behavioural-personasWhat does an organisation’s portfolio of Personas typically look like? The results below are generated from our benchmarking results from close to 40 organisations. The lines indicate the minimum-maximum range and the blue square is the average score.

persona-proportions

The large range of % Observers, between less than 10% to over 70%, may reflect the large variation in maturity amongst the organisations we have benchmarked. It may not only be the case of maturity though, as it is fair to say that the smaller organisations have an easier time engaging a higher proportion of their staff with the Enterprise Social network (ESN).  We show the break-up of the active (non-observer) Personas, which shows that Catalysts lead the way with just over 40%, followed by Responders at just under 30%, Engagers just over 20% and Broadcasters at 10%. This would indicate that in general, ESNs are relying on Catalysts to continue to drive participation and then Responders to sustain it.

Personas within Groups

Given that groups are the space where most of the intense collaboration is likely to happen, we were interested in what the Persona patterns were for the leaders of the best performing groups. We used a combination of two-way connection scores and activity scores to identify the strongest groups. We then applied the same measures to the group members to identify the group leaders. In other words, a group leader is someone who has a high number of two-way connections with other group members, and meets a threshold level of overall activity.

Firstly, we plotted all members on a graph, locating them by the size of their network (y-axis) within the group and the number of 2-way connections they have in the group (x-axis). The bubble is sized by their relative levels of interactions (activity). As you can see, the group leaders are clearly identified in the top right hand corner of the graph as different coloured nodes.

persona-tracking

Secondly, we then plotted the top 5 leader’s Persona movements in 1 week intervals, over a 6-month period. In the example above you can see that the leaders played the Catalyst, Engager and Responder roles primarily. The size of the bubbles reflects their relative number of connections made (breadth of influence), for that week. Not all leaders were active every week. What becomes interesting is that we find some leaders have preferred Personas that are sustained over time. Leaders 1 and 4 in this case have a preference for Catalysing and Engaging. Leader 5 prefers Responding. Leaders 2 and 3 appear to be comfortable switching between Personas.

What appears to be important here is that high performing groups need leaders that can cover the spectrum of positive Personas i.e. Catalyst, Engager, Responder. While it’s fine to have leaders who have a preference for a certain behavioural Persona, it is useful to have leaders who can adapt their Persona to the situation or context at hand.

Personal Networking Performance

At SWOOP we use a fundamental network performance framework, which measures performance against the complementary dimensions of cohesion and diversity. We have indicated that individuals with a large number of two-way connections are likely to have more closed and cohesive networks. Cohesive networks are good for getting things done (executing/implementing). From an innovation perspective however, closed networks can be impervious to new ideas. The best ideas come from more open and diverse networks. In our view therefore, maximum network performance occurs by optimising diversity and cohesion. In other words, it’s good to be part of a strong cohesive network, but this should not be at the expense of maintaining a healthy suite of more diverse connections.

In the graphic below we have plotted the members of one large group on the Network Performance graph. In this case the diversity is measured by the number of different groups that an individual has participated in. The size of the bubbles reflects the size of the individual’s network (breadth of influence).

personal-network

We have labelled regions in the graph according to our Explore/Engage/Exploit model of innovation through networks. We can see that the majority of group members exist in the ‘High Diversity/Low Cohesion’ Explore region. This is consistent with what many people give for their reasons for joining a group. The ‘Engage’ region shows those members who are optimising their diversity/cohesion balance. These are the most important leaders in the group. In an innovation context, these people are best placed to broker the connections required to take a good idea into implementation. The bottom right corner is the Exploit region, which for this group is fairly vacant. This might suggest that this group would have difficulty organically deploying an innovation. They would need to take explicit steps to engage an implementation team to execute on the new products, services or practices that they initiate.

The Innovation Cycle – Create New Value for Your Organisation

We conclude this third edition of Yammer Benchmarking insights be reinforcing the role that individuals can play in creating new value for their organisations. For many organisations, the ESNs like Yammer are seen as a means for accelerating the level of innovation that is often stagnating within the formal lines of business.

As individual’s we may have a preference for a given style of working, as characterised by our Personas. Your personal networks may be large, open and diverse; or smaller, closed and cohesive; or indeed somewhere in between. It is important however to see how your collaboration behaviours contribute to the innovation performance of your organisation. Innovation is a collaborative activity, and therefore we recommend that in your groups you:

  1. Avoid lone work (Observing/Broadcasting) and look to explore new ideas and opportunities collaboratively, online (Catalysing/Engaging/Responding).
  2. Recognise that implementing good ideas needs resources, and those resources are owned by the formal lines of business. Use your network to engage with the resource holders. Make the connections. Influence on-line and off-line.
  3. When you have organisational resources behind you, it’s time to go into exploit mode. Build the cohesive focussed teams to execute/implement, avoiding distractions until the job is done.

 

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.

Diversity is Essential but not Sufficient

diversity-imageDiversity is a big word in business today. We are preached to continuously about how important having diverse leadership is to improving your performance. HBR in their article on ‘Why Diverse teams are Smarter”, identify studies showing that diversity based on both ethnicity and/or gender can lead to above average returns. In our own work with networks, research has shown that individuals with more diverse personal networks are more likely to be promoted and succeed in their occupations. Although I’ve always thought that my own personal network was quite diverse, I received a wake-up call from the recent US elections. I was not aware of any of my fairly extensive US citizen network that were voting for Trump! So it does take a conscious effort to build and sustain a diverse network of connections. It’s far too easy to fall back to the comfortable relationships with those just like us.

But diversity alone is only a pre-condition to high performance. One must be able to exploit the diversity in one’s network to actually deliver the superior results that it promises. In a previous post we introduced our network performance framework, which identifies a balance between Diversity and Cohesion in networks, for maximizing performance:

swoop-diversity

In this framework we identify that high performers are those that can effectively balance their diverse connections i.e. identifying high potential opportunities, with their close connections, with whom they can collaborate to exploit those opportunities. From our project consulting experiences these people are either recognised as organisational ‘ambassadors’ or are completely invisible i.e. the quiet achievers. The fact that we find so few people in this quadrant is testimony as to how hard achieving this balance can be.

UGM Consulting explores this tension in their recent article on Innovation and the Diversity Paradox. They nominate the following attributes for those diverse networks that can successfully exploit the opportunities that they identify:

They have a sense of shared common goals and purpose;

  1. They know how to genuinely listen to each other, seeking out elaboration and novel combinations;
  2. They have high levels of mutual trust, so speaking up and disagreements can be had, risk free;
  3. They have the skills to constructively explore alternatives and agree on a direction; and
  4. There exists a strong co-operative atmosphere at both the team and enterprise levels.

For leaders this will mean actively enabling or creating such conditions. For the individual it could boil down to simply developing a diverse network that you actively consult with.  At times you may leverage these relationships by enrolling others in selected joint activities, to bring about positive change in your own areas of influence.

Top Image credit: http://www.ispt-innovationacademy.eu/innovation-research.html

Are we Getting Closer to True Knowledge Sharing Systems?

knowledge-systems

(image credit: https://mariaalbatok.wordpress.com/2015/02/10/religious-knowledge-systems/)

First generation knowledge management (KM) systems were essentially re-labelled content stores. Labelling such content as ‘knowledge’ did much to discredit the whole Knowledge Management movement of the 1990s. During this time, I commonly referred to knowledge management systems as needing to comprise both “collections and connections”, but we had forgotten about the “connections”.  This shortcoming was addressed with the advent of Enterprise Social Networking (ESN) systems like Yammer, Jive, IBM Connect and now Workplace from Facebook. So now we do have both collections and connections. But do we now have true knowledge sharing?

Who do we Rely on for Knowledge Based Support?

A common occupation for KM professionals is to try and delineate a boundary between information, that can be effectively managed in an information store, and knowledge, which is implicitly and tacitly held by individuals. Tacit knowledge, arguably, can only be shared through direct human interaction. In our Social Network Analysis (SNA) consulting work we regularly surveyed staff on who they relied on to get their work done. We stumbled on the idea of asking them to qualify their selections by choosing only one of:

  • They review and approve my work (infers a line management connection)
  • They provide information that I need (infers an information brokering connection)
  • They provide advice to help me solve difficult problems (infers a knowledge based connection)

The forced choice was key. It proved to be a great way of delineating the information brokers from the true knowledge providers and the pure line managers. When we created our ‘top 10 lists’ for each role, there was regularly very little overlap. For organisations, the critical value in these nominations is that the knowledge providers are the hardest people to replace, and therefore it is critical to know who they are. And who they are, is not always apparent to line management!

So how do staff distribute their connections needs amongst line managers, information brokers and knowledge providers? We collated the results of several organisational surveys, comprising over 35,000 nominations, using this identical question, and came up with the following:

work-done

With 50% of the nominations, the results reinforce the perception that knowledge holders are critical to any organisation.

What do Knowledge Providers Look Like?

So what is special about these peer identified knowledge providers? Are they the ‘wise owls’ of the organisation, with long experiences spanning many different areas? Are they technical specialists with deep knowledge about fairly narrow areas? We took one organisation’s results and assessed the leaders of each of the categories of Approve/review, Information and Knowledge/Advice looking for their breadth or diversity of influence. We measured this by calculating the % of connections, nominating them as an important resource, that came from outside their home business unit. Here are the results:

external-links

As we might anticipate, the inferred line management had the broadest diversity of influence. The lowest % being for the knowledge providers, suggests that it’s not the broadly experienced wise old owls, but those specialising in relatively narrow areas, where people are looking for knowledge/advice from.

Implications for Knowledge Sharing Systems

We have previously written about our Network Performance Framework, where performance is judged based on how individuals, groups, or even full organisations balance diversity and cohesion in their internal networks:

personal-networking

The above framework identifies ‘Specialists’ as those who have limited diversity but a strong following i.e. many nominations as a key resource. These appear to be the people identifying as critical knowledge providers.

The question now is to whether online systems are identifying and supporting specialists to share their knowledge? At SWOOP we have aimed to explore this question initially by using a modification of this performance framework on interactions data drawn from Microsoft Yammer installations:

performance

We measured each individual’s diversity of connections (y-axis) from their activities across multiple Yammer groups. The x-axis identifies the number of reciprocated connections an individual has i.e. stronger ties, together with the size of their personal network, identified by the size of the bubble representing them. We can see here that we have been able to identify those selected few ‘Specialists’ in the lower diversity/stronger cohesion quadrant, from their Yammer activities. These specialists all have relatively large networks of influence.

What we might infer from the above analysis is that an ESN like Yammer can identify those most prospective knowledge providers that staff are seeking out for knowledge transfer. But the bigger question is whether actual knowledge transfer can happen solely through an ESN like Yammer?

Is Having Systems that Provide Connections and Collections Enough to Ensure Effective Knowledge Sharing?

The knowledge management and social networking research is rich with studies addressing the question of how social network structure impacts on effective knowledge sharing. While an exhaustive literature review is beyond the scope of this article, for those inclined, this article on Network Structure and Knowledge Transfer: The Effects of Cohesion and Range is representative. Essentially this research suggests that ‘codified’ knowledge is best transferred through weak ties, but tacit knowledge sharing requires strong tie relationships. Codified knowledge commonly relates to stored artefacts like best practice procedural documents, lessons learned libraries, cases studies and perhaps even archived online Q&A forums. Tacit knowledge by definition cannot be codified, and therefore can only be shared through direct personal interactions.

I would contend that relationships formed solely through ESN interactions, or in fact any electronic systems like chat, email, etc. would be substantially weaker than those generated through regular face to face interactions. Complex tacit knowledge would need frequent and regular human interactions. It is unlikely that the strength of tie required, to effectively share complex knowledge, can be achieved solely through commonly available digital systems. What the ESN’s can do effectively is to help identify who you should be targeting as a knowledge sharing partner. Of course this situation is changing rapidly, as more immersive collaboration experiences are developed. But right now for codified knowledge, yes; for tacit knowledge, not yet