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 2: Recognizing Personas and Behaviors to Improve Engagement

In Part 1 of this series, “Data-Driven Collaboration Design”—a collaboration between Swoop Analytics and Carpool Agency—we demonstrated how data can be used as a diagnostic tool to inform the goals and strategies that drive your business’ internal communication and collaboration. 

In this post, we will take that thought one step further and show how, after your course is charted to improve internal communication and collaboration, your data continues to play a vital role in shaping your journey.

Monitoring More Than participation

Only in the very initial stages of the launch of a new Enterprise Social Network (ESN) or group do we pay any attention to how much activity we see. Quickly, we move to watching such metrics as average response time; breadth of participation across the organization, teams, roles, or regions; and whether conversations are crossing those boundaries. We focus on measures that show something much closer to business value and motivate organizations to strengthen communities.
For our purposes in this post, it will be useful to pivot our strategy to one that focuses on influential individuals. The community or team—whether it’s a community of practice, a community of shared interest, or a working team—isn’t a “group” or “si te,” but a collection of individuals, with all the messiness, pride, altruism, and politics implied. Data can be used to layer some purpose and direction over the messiness.

Patterns Become Personas

The Swoop Social Network Analytics dashboard uniquely provides analytics that are customized to each person who is part of an organization’s ESN. Using the principle of “when you can see how you work, you are better placed to change how you work”, the intent is for individual collaborators to receive real-time feedback on their online collaboration patterns so they can respond appropriately in real-time.
We analyzed the individual online collaboration patterns across several organizations and identified a number of distinct trends that reflect the majority of personal collaboration behaviors. With that data, we were able to identify five distinct personas: Observers, Engagers, Catalysts, Responders, and Broadcasters.

In addition to classifying patterns into personas, we developed a means of ranking the preferred personas needed to enhance an organization’s overall collaboration performance. At the top we classify the Engager as a role that can grow and sustain a community or team through their balance of posting and responding. This is closely followed by the Catalyst, who can energize a community by provoking responses and engaging with a broad network of colleagues. The Responder ensures that participants gain feedback, which is an important role in sustaining a community. The Broadcaster is mostly seen as a negative persona: They post content, but tend not to engage in the conversations that are central to productive collaboration. Finally, we have the Observer, who are sometimes also called ‘lurkers’. Observers are seen as a negative persona with respect to collaboration. While they may indeed be achieving individual learning from the contribution of others, they are not explicitly collaborating.
Using Personas to Improve Your Online Collaboration Behavior
Individuals who log in to the Swoop platform are provided with a privacy-protected personal view of their online collaboration behaviors. The user is provided with their persona classification for the selected period, together with the social network of relationships that they have formed through their interactions:

You may notice that the balance between what you receive and what you contribute is central to determining persona classification. Balanced contributions amongst collaboration partners have been shown to be a key characteristic of high performing teams, hence the placement of the ‘Engager’ as the preferred persona.

Our benchmarking of some 35 Yammer installations demonstrates that 71% of participants, on average, are Observers. Of the positive personas, the Catalyst is the most common, followed by Responders, Engagers, and Broadcasters. It’s therefore not surprising that an organization’s priority often involves converting Observers into more active participants. Enrolling Observers into more active personas is a task that falls on the more-active Engagers and Catalysts, with Responders playing a role of keeping them there.
At Carpool, during a recent engagement with a client, we encountered a senior leadership team that was comprised of Broadcasters who relied on traditional internal communications. Through our coaching—all the while showing them data on their own behavior and the engagement of their audience—they have since transformed into Catalysts.
One team, for example, had been recruiting beta testers through more traditional email broadcasts. But after just a few posts in a more interactive and visible environment, where we taught them how to invite an active conversation, they have seen not only the value of more immediate feedback, but a larger turnout for their tests. Now, it’s all we can do to provide them with all the data they’re asking for!
Identifying the Key Players for Building Increased Participation

When Swoop looks at an organization overall, we will typically find that a small number of participants are responsible for the lion’s share of the connecting and networking load. In the social media world, these people are called ‘influencers’ and are typically measured by the size of the audience they can attract. In our Persona characterization, we refer to them as Catalysts. Unlike the world of consumer marketing—and this point is critical—attracting eyeballs is only part of the challenge. In the enterprise, we need people to actively collaborate and produce tangible business outcomes. This can only happen by engaging the audience in active relationship-building and cooperative work. This added dimension of relationship-building is needed to identify who the real key players are.
In our work with clients, Carpool teaches this concept by coaching influencers to focus on being “interested” in the work of others rather than on being “interesting” through the content they share, whether that’s an interesting link or pithy comment. With one client, our strategy is to take an organization’s leader, a solid Engager in the public social media space, and “transplant” him into the internal communications environment where he can not only legitimize the forum, but also model the behavior we want to see.
In the chart below, we show a typical ‘Personal Network Performance’ chart, using Enterprise Social Networking data from the most active participants in an enterprise. The two dimensions broadly capture an individual’s personal network size (number of unique connections) against the depth of relationships they have been able to form with them (number of reciprocated two-way connections). They reflect our Engager persona characteristics. Additionally, we have sized the bubbles by a diversity index assessed by their posting behavior across multiple groups.
The true ‘Key Players’ on this chart can be seen in the top right-hand corner. These individuals have not only been able to attract a large audience, but also engaged with that audience and reciprocated two-way interactions. And the greater their diversity of connections (bubble size), the more effective they are likely to be.

Data like this is useful in identifying current and potential key players and organizational leaders, and helps us shift those online collaboration personas from Catalyst to Engager and scale up as far and as broadly as they can go.

Continuous Coaching

Having data and continuous feedback on your online collaboration performance is one thing, but effectively taking this feedback and using it to build both your online and offline collaboration capability requires planning and, of course, other people to collaborate with! Carpool believes in a phased approach, where change the behavior of a local team, then like ripples in a pond, expand the movement to new ways of working through compelling storytelling, using the data that has driven previous waves of change.
To get started now, think about your own teams. Would you be prepared to have your team share their collaboration performance data and persona classifications? Are you complementing each other, or competing? If that’s a little too aggressive, why not form a “Working Out Loud” circle with some volunteers where you can collectively work on personal goals for personal collaboration capability, sharing, and critiquing one another’s networking performance data as you progress?
Think about what it takes to move from one behavior Persona to another. How would you accomplish such a transformation, personally? What about the teams you work in and with? Then come back for the next, and final, part of this co-authored series between Swoop and Carpool, where we will explain the value in gaining insights from ongoing analytics and the cycle of behavior changes, analysis, and pivoting strategies.

Connecting the enterprise – one tool breaks the rule

The world is getting more interdependent, and to get stuff done more people need to coordinate what they are doing with people in other business units. No wonder that collaboration is a hot topic. But what has surprised me is that in spite of an increasing number of tools, most of them are actually not connecting people across business unit boundaries. Sounds like a contradiction? Read on…

Collaboration is still mostly happening within business units

I’ve been involved in more than 100 social network analysis projects over the last 15 years, and most of these projects we’ve found that business units operate very much in silos having only limited interactions with other business units.

Physical location has a big impact in who you interact with. Professor Tom Allen discovered this many years ago and coined this the ’50-meter rule’. According to this rule, most interaction drops off when you are located more than 50 meters away from another person.

Given that employees from the same business unit are still being physically placed near each other i our workplaces, this only makes the likelihood of you interacting with someone from another business unit even smaller.

Tom Allen’s 50 meter rule:

Therefore, when I was running a collaboration analysis project for a professional services firm, I expected to find this same Business Unit silo pattern. But this time we uncovered something new.

Our collaboration research partner Dr Agustin Chevez from HASSELL had cleverly designed the study for the client in such a way that the data sources we analysed (see below) covered the exact same 4-week period. That meant that we could precisely compare interaction patterns across collaboration tools/methods:

  1. Face-to-face interaction (via traditional social network analysis survey)
  2. Email data (Exchange)
  3. Instant messaging data (Lync)
  4. Timesheet data (billable hours analysed to find out who works with who)
  5. Enterprise social network data (Yammer).

One tool breaks the rule

While face-to-face, email, instant messaging and timesheet interaction patterns all stayed mostly within business unit boundaries, one tool broke the rule. Yammer, the enterprise social network, was the only tool in the portfolio that broke the traditional 50m rule. This also meant that it was the only tool that was busting business unit silos.

Screen Shot 2016-12-08 at 10.28.58 am.pngOn reflection that makes a lot of sense. You really don’t bump into someone via email, phone or instant messaging as these tools have a clearly defined list of recipients. However, when you post something on an enterprise social network it is not limited to a set of intended recipients, and the audience is therefore anyone and anywhere in the organisation. We also know from our global Yammer benchmarking study that while enterprise social networks do cater for private conversations, the clear majority of messages (about 80%) are actually public.

These two characteristics (open for all, and fully transparent) that are hallmarks of an enterprise social network, and are completely different from email, instant messaging and phone calls that are by nature restricted to a defined (any typically small) set of recipients. You might find it amusing to know what we discovered that 95% of all emails only had single recipient, and the about 50% of emails sent were to a person sitting less than 6 meters away.

Collaboration within teams or collaboration across business units

We have an increasing number of collaboration tools at our disposal, and these are doing a terrific job enabling people to get work done. But as you’ll now appreciate they are far from equal. Some are making existing teams work more effectively together within the team and that is undoubtedly of tremendous value. But it is up to the enterprise social network to foster new connections across business units.

To drive organisational performance, we must have collaboration tools that serve different objectives, and we need to be very clear about their strengths, weaknesses and fundamental differences. Professor Andrew Hargadon writes in his book How Breakthroughs Happen: The Surprising Truth About How Companies Innovate (Harvard Business School Press 2003) that innovation happens at the intersection of people and ideas. To do this at on a global scale we need enterprise social networks. They play a fundamentally important role in enabling people to connect across business unit boundaries.

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

Q&A: Start-ups vs Large Corporates

start-up-versus-corporate

SWOOP Analytics celebrated its 2nd Birthday late last month with our distributed workforce face to face, many for the first time; and also many of our early adopter partners and clients. Unlike most start-ups addressing the consumer market, SWOOP Analytics targets the ‘big end of town” i.e. large corporates and public institutions who’s procurement practices go far beyond someone simply pushing the ‘buy’ button. We have been fortunate to have several highly experienced executives and consultants advising us on our product startup journey. We thought we would take advantage of their presence to conduct a mock Q & A panel session, modelled on the ABC show Q & A. We chose our panel members based on their experience with working and advising both start-ups and large corporations. Our panel topic was “How can Startups work Effectively with Large Corporates”.

Here were our selected panel members:

Dr. Eileen Doyle

Eileen is an experienced executive and company director for big end of town companies like BHP, OneSteel, Boral, GPT, Port Waratah Services, Oil Search and the CSIRO. We also identified Eileen as one of the most connected female company directors on the ASX in our ASX networking studies. But most importantly she is also an Angel investor in Swoop and a former chair of Hunter Angels, so she was well qualified to join our panel.

Ross Dawson

Ross is recognized as one of the world’s leading futurists. He is regularly engaged for keynote speeches and consulting advice by the ‘big end of town’ clients like Macquarie Bank, Ernst & Young, Proctor & Gamble, News Ltd and many more about what is coming ‘down the pipeline of future technologies’. A long term friend of the Swoop founders, Ross is an entrepreneur himself, with several startup initiatives on the go.

Allan Ryan

Allan is the founding director of the Hargraves Institute, celebrating its 10th birthday this year as a leading community for major corporations focusing on innovation.  Many of Australia’s leading organisations have been sharing their innovation experiences and practices in the Hargraves community. And Allan has had a front row seat in observing how large and complex organisations are addressing the innovation challenge.

swoop-panelists

The panel were actively ‘grilled’ by an enthusiastic audience. And the panel to their credit, responded in good spirit. Here are some nuggets of wisdom shared by our panel:

  1. How can big corporations work more effectively with start-ups?

Eileen shared the mindset is different in a large corporate, where you have to look at risk in a different way. The balance between risk and reward is tilted to risk in a large corporate and reward in a start-up, which is why the majority of start-ups fail. Interaction between the two works well when there’s a genuine need that the large corporate has, which aligns with what start up is doing. Her advice is investors will not get rewarded if corporations don’t take risks, it’s ok to fail which we need to learn to celebrate.

Ross shared that it’s key for big corporations to set up mechanisms to deal with start-ups, like accelerators, incubators and hackathons. There needs to be more structures and governance to support transformation. As a Futurist he helps people think about the future to make better decisions today, that will make a different in the future.

From his work at Hargraves Institute, Allan shared that large organisations are maturing rapidly. His advice to start ups was to find the most mature area which has the need for your service and give them a solution that doesn’t give them great risk to test and try.

  1. Quality versus innovation?

An audience member asked about the importance of IT security for starts ups and another shared it can be boring to get the basics right, how crucial is this for successful innovation? Panelist’s shared:

  • Start-ups need to get their disaster recovery and IT security right, at least to the level of the Organisation they’re engaging with.
  • Start–up products need to have their quality right and be tried and tested. Quality is more important than innovation where there are winners and losers.
  • Start-ups need to adopt a philosophy of forever getting better in the basics and making sure they’re improving.
  1. Can Australia become the Silicon Valley of the Southern Hemisphere?

For Australia to further foster the success of start-ups Panelist’s suggestions included:

  • Linking the quality of Australia’s research to effective commercialisation on a global scale
  • Promoting innovation as ‘invention accepted by the market’ by private and public businesses spending more in this area.
  • The Government providing tax breaks and recognition of greater risk.
  • Universities taking a what’s best for the whole country mindset versus what individual academics might want to do.
  • Encouraging small businesses to be more innovative and teaching kids how to have fun doing new things.

Our takeaway message was large corporates have multiple entry points, so it’s important not to get discouraged and keep looking for the people that have roles with a larger risk profile in them.

Image citation: https://www.tnooz.com/article/startup-chic-vs-corporate-geek-can-gen-y-retention-predict-success/

 

 

Need to convince someone? Bring Data (and a good story)

Big data

As Daniel Pink suggests “to sell is human”.  Even if we do not have a formal ‘selling’ role we are always looking to ‘sell’ someone on our point of view, our recommendations, our need for their help etc.. As data analysts we live and breathe data every day, whether we are looking to develop some new insights, prove a case or simply explore possibilities. In the end we are doing it to influence someone or some group. In these days of ‘evidence based decision-making’ I am wary that one person’s ‘evidence’ is another person’s ‘garbage’. You don’t have to look much further than climate change sceptics to appreciate that. I was therefore intrigued when I came across Shawn Callahan’s recent blog post on “The role of stories in data storytelling”. Shawn talks about the use of ‘story’ before, during and after data analysis.

Before data analysis stories

Before data analysis is about understanding the dominant ‘story’ before your analysis. For us a good example of this is our recent work on comparing relationship analytics with activity analytics. The dominant storyline was (and probably still is) that social analytics used in the consumer world i.e. activity measures, are sufficient for use inside the enterprise.

During data analysis stories

The ‘during the data analysis’ story is about how stories evolve from your act of data analysis. Our story in the interactions vs activity debate was about one of our clients observing some analytics provided by Swoop and finding that the measure for social cohesion was far more reflective of their view of how different communities were collaborating and performing than the activity measures reported beside them. For us the ‘stories during data analysis’ is continual. We are always looking to find the ‘story behind the data’. And this usually comes when we can talk directly to the owners of the data, in what we call ‘sense making’ sessions. As an example, we are currently looking at adoption patterns for Yammer using some of the benchmarking data that we have collected. We have learnt from experience that collaboration happens best within ‘groups’. Our prior analysis showed that the social cohesion between groups varies a lot and follows a typical ‘power curve’ distribution when sorted from best to worst. We are now looking at how these groups evolved over time. What patterns existed for those highly cohesive groups versus those that were less cohesive? Is there a story behind these different groups? Our evolving stories are merely speculations at the moment, until we can validate them with the owners of the data.

After data analysis stories

Knowing Doing GapShawn Callahan identifies these stories as needed to bridge the gap between what the data analyst ‘knows’ and what the decision makers need to act on.  He goes on to describe types of data stories, being a chronological change, explanation or discovery stories. He recommends that if you are trying to instigate change from a dominant current story, then it has to be a better story than that one. Thankfully in our case we don’t believe there is a dominant story for the use of activity analytics with Enterprise Social Networking (ESN) implementations. Of course there are supporters, some quite passionate, but the majority point of view is that they are insufficient for the needs of the Enterprise. That said, you still need to come up with a good story. And that is still work in progress for us. We can use a discovery story to relate the trigger for the data analysis we conducted being a simple comment from a client. But our sense is that we will need even more data (evidence) couched in some powerful stories told by individuals, who have changed their interaction behaviours for the better, based on the analytics that they were provided with.

I should finish by giving Shawn’s recent book “Putting Stories to Work” a plug, since I have just completed reading it to help us develop that story. So watch this space!

How can you tell if your Enterprise Network is Innovative?

 

One of the most commonly stated objectives for establishing online enterprise social networks (ESN) is to facilitate greater levels of innovation. But how do we know if we are being more innovative or not? One way is to wait to see what sorts of tangible outputs emerge from the cross enterprise communities within the network.  This may result in some good individual cases, perhaps enough to claim an increase innovation capability. More likely these may be seen as random outcomes if the organisation doesn’t ‘feel’ like its being more innovative. In a recent article on behaviours that can create an innovation culture, Rob Shelton identifies five key behaviours that can lead to creating an innovating culture. The behaviours were: broad based collaboration, measuring and rewarding intrapreneurs, emphasising speed and agility, thinking like a venture capitalist and balancing operational excellence and innovation.

There are now many online tools designed specifically to support innovation activities e.g. Spigit, Innovation Cast, Hype and some that are built on top of existing Enterprise Social Networking (ESN) platforms e.g. Sideways6. Typically, these systems are used to facilitate pre-defined innovation challenges or campaigns; if you like, ‘programmed’ innovation. The heavy use of tools and innovation programmes may also result in an organisation ‘feeling’ more innovative.

In the absence of specific innovation tools or programmes how could we identify if our organisation is developing an innovation culture? To guide our thinking we will use the five behaviours identified by Shelton and our own Swoop Personas (Engagers, Catalysts, Responders, Broadcasters and Observers) to explore this:

  1. Build collaboration across your ecosystem

This is the most straightforward one. The Swoop social cohesion measure  applied across the whole enterprise and measured over time will provide an accurate assessment of this.

  1. Measure and motivate your intrapreneurs

Intrapreneurs are the entrepreneurs inside the enterprise. A true entrepreneur is more than an ‘ideas person’. Successful entrepreneurs are able to deliver on ideas, whether they are their own or not. We would see the behaviour patterns of a successful intrapreneurs as essentially displaying the behaviour of a Swoop Catalyst. Over time, however,  as they drive ideas to successful completion, their networks will become denser and more cohesive i.e. their personal social cohesion measure will increase over time. They also may migrate from being a catalyst to an engager as they become more active and focussed in their contributions to the network, as ideas progress to execution. Successful execution is typically characterised by tighter, more cohesive teams.

  1. Emphasize speed and agility

Speed and AgilityThis is perhaps best observed at the team or community level. We know that speed comes with trust and trust is generated through reciprocated relationships, so again the Swoop social cohesion measure is the one of choice. However, speed does not mean agility. The world’s fastest vehicles achieve their speeds by not having to turn corners! So how do we know if a team or community is agile? Here we would have to observe team goals and how quickly a team or community can adapt to a change of direction. One way of achieving this in Swoop would to get into the habit of hash tagging all community/team initiatives. Using the Swoop Topic analysis, one could monitor over time how quickly, and to what extent, conversations evolve around each tagged imitative. An agile community would see a rapid and broad based network of conversations emerge on the launch of a new tagged initiative. Therefore, a combination of the social cohesion measure across the group (speed) and then indicators like the interactions and relationships built around a new topic/initiative over a short period; perhaps a variety of conversation leaders for different topics; a large and rapidly growing number of conversation threads on the launch of a new tagged initiative (agility), could all inform on progress and performance on this dimension.

  1. Think like a venture capitalist (VC)

Venture Capitalist.tifShelton describes this as coming up with the ‘Big Ideas’, rather than dismissing them out of hand. He suggests protecting them by addressing the potential challenges/barriers. One idea to implement this is to establish a group where these ideas can be captured for discussion. Perhaps the group could be called “Moonshots” and the ideas hash tagged to track engagement around the ideas, as the inevitable challenges are surfaced. For most enterprises, ‘#Moonshots’ rarely make it out of the ‘ideas lab’. The rare ones that do will have been adapted as challenges are addressed. They will also have a consistent suite of discussants that will have to include the senior decision makers. Even a single successful ‘#Moonshot’ is enough to have an organisation labelled as “innovative”. I can think of a hardware company called Sun Microsystems inventing Java; Apple, a company making personal computers creating a game changing mobile phone; the dominant provider of large corporate mainframe computers, IBM, building a highly successful personal computer.

Using SWOOP we would monitor the discussion patterns around #Moonshot ideas and the seniority of the discussants over time, to sense whether the organisation was really thinking like a VC.

  1. Balance operational excellence with innovation

BalanceThis is a nice one to finish with, as many organisations struggle with achieving the right balance between the shorter term and more visible operational excellence initiatives and the less visible and perceived riskier innovation initiatives. In the academic literature this is often coined the “Explore vs Exploit” challenge. I have written extensively on this issue, suggesting that they are not ‘choices’ and that explorations only create value when they are exploited; so it should be thought of more as a ‘flow’. Many years ago we published a short paper on this called the ‘3 E’s of Innovation’  for Explore/Engage/Exploit, where the Engager, was identified as the link between exploration and exploitation. For those with more of an academic bent this journal article “Corporate social capital in business innovation networks” explores it in more detail.

The SWOOP monitoring suggestion for this would mimic the ‘Speed and Agility’ behavior. The social cohesion measures will predict speed of execution, viz Operational Excellence. The innovation aspect would look at the breadth of the conversation topics and the diversity of the participants, across geographies, formal business units and/or levels of seniority. In essence we are characterizing the operational excellence/innovation balance as a social cohesion/diversity balance. The diversity measure in Swoop is yet to be installed, but to operate, will require profile data on business unit membership, location and if available, seniority or job/role classification attributes, to be made available.

So to summarise; how can your ESN analytics flag if you are developing an innovative culture or not?

  • Monitor your enterprise social cohesion measure over time; is it travelling upward?
  • Identify your Catalysts that have highly cohesive personal networks. Are they increasing in number?
  • How diverse are your conversation topics and those participating in these discussions? Is your diversity increasing in line with your social cohesion?
  • Do you have a space where “Moonshot Ideas” can be proposed and discussed? If so, to what extent are the senior leaders engaged in these discussions?