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.

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

 

Who Should Decide How You Should Collaborate or Not?

In a recent post pre- Microsoft’s recent Ignite 2016 conference, we intimated that we hoped that in the push to build the ultimate office tool that the core features of the component parts were not sacrificed in the name of standardisation. I can happily say now that post MS Ignite it appears that, at least for the product we are most interested in, Yammer, has re-surfaced as a more integral part of Office 365, without sacrificing its core value proposition. As a Yammer core user, it appears now that as circumstances arise, where our collaboration partners might need to manage content, collaborate in real time, schedule and manage an event, we will be able to seamlessly access these core functions of other components like Sharepoint, Skype, Outlook etc.. Now while of course we know events like MS Ignite are mostly to announce intentions, more so than working products, it is comforting to see a positive roadmap like this.

In effect Office 365 is now offering a whole multiplex of collaboration vehicles. There will be individuals looking for a simple ‘usage matrix’ of what to use when. Yet collaboration can mean different things to different people. Is working in your routine processing team a collaboration? Is reading someone else’s content a collaboration? Is sending an email a collaboration?

How do we define Collaboration?

A couple of years ago Deloitte Australia’s economics unit produced a significant report on the economic value of collaboration to the Australian economy. As part of the process Deloitte surveyed thousands of workers looking for how they spent their time at work, specifically related to collaboration activities:

collab-blog-tif

While the numbers will vary between individuals, we can look at the categories as typical work tasks and then look to map them to O365 components. For me the nearly 10% ‘Collaboration” is a natural home for Yammer, and probably “Socialising”. Routine tasks fit nicely into Sharepoint and Team sites. Outlook for Routine Communication. The individual work maps very nicely to core office 365 tools like Word, Excel and Powerpoint. So what we can see is that O365 can be nicely mapped to the O365 components. But does just knowing this help us use it productively? Who decides how we should interact and how?

Who should control collaboration?

The Deloitte work characterisation separates “collaboration” out from “interactions” as activities that staff engage in to be able to improve the way they work; improvising and innovating. While it may constitute only 10% of their work time on average, the impact is in improving the productivity of say routine tasks, routine communication and even individual work. So is it the role of managers to dictate modes of collaboration for their staff? Maybe its community managers of workplace improvement specialists? As the workplace moves to become more distributed and networked it is quickly becoming beyond that capability of specialist roles to orchestrate collaborative processes, without bloating the middle manager layers.

So what are we left with? I believe that it all comes back to the individual to “negotiate” how they interact and collaborate and how. As it turns out, the one who knows best as to how to improve your productivity is yourself. This comprehensive study on time-wasting by Paychex found that the most effective way to reduce time wasting is more flexible time scheduling or time off. Carpool recently ran an experiment in working from anywhere. Carpool CEO Jarom Reid speaks about the productivity improvements available when you have the flexibility of not being tied to a physical office. In the industrial age we became used to executives jobs being solely about linking and communication. However Reid, being the leader of a digitally enabled organisation, values having personal time where he can feel more productive than in the office. Andrew Pope writes about the dangers of over-collaboration. We all want our collaborations and interactions with colleagues to be productive. We feel we are over-collaborating when we feel we have wasted time in non-essential meetings. Pope suggests that individuals should take control of their collaboration activities to match their natural styles and tendencies, rather than trying to adhere to a particular organisational norm.

How will Office 365 Help?

So how would the new world of Office 365 support individual preference led collaboration? For those of us that have been used to living in Yammer or Sharepoint or Outlook it does put the onus on the individual to become competent in all the key toolsets, if we are to accommodate the potential preferences of our collaboration partners and avoid “tool solos”.

The nice thing about the Office 365 roadmap is that the tool silo walls have become more elastic. We can form a group from Yammer to explore an idea and then form a team to exploit the idea still inside Yammer, without having to move to a Teamsite. Alternatively, we can reach out from a Teamsite into a broader community group inside Yammer, if and when the need arises.  The benefits in making this investment in learning is the flexibility it can afford to enable you, as an individual, to be in charge of your own productivity and performance.

 

 

 

 

Yammer Benchmarking Edition 1

 

First in a series of SWOOP Yammer Benchmarking video blogs. Swoop has benchmarked some 36 Yammer installations to date. This first video blog shares some insights gained on the important measures that influence collaboration performance.

 

Video script:

SLIDE 1

Hello there

My Name is Laurence Lock Lee, and I’m the Co-Founder and Chief Scientist at Swoop Analytics.

If you are watching this you probably know what we do, but just in case you don’t, Swoop is a social analytics dashboard that draws its raw data from enterprise social networking tools like Yammer and provides collaboration intelligence to its users, who can be anyone in the organisation.

Our plan is to provide an ongoing series of short video blogs specifically on our Yammer benchmarking insights, as we work with the data we collect. We will aim to use this format to keep you appraised of developments as they happen. We have also recently signed a joint research agreement with the Digital Disruption Research Group at the University of Sydney in Australia. So expect to see the results of this initiative covered in future editions.

The Swoop privacy safeguards means its pure context free analysis, no organisational names, group names, individual names…we don’t collect them.

SLIDE 2

This is the “Relationships First” benchmarking framework we designed for our benchmarking. But we also measure traditional activity measures, which we tend not to favour as a collaboration performance measure…but more about that later. The 14 measures  help us characterise the organisations we benchmark by comparing them against the maximum, minimum and average scores of those in our sample set,  which currently sits at 36 organisations and growing rapidly. They represent organisations large and small from a full cross section of industries and geographies.

SLIDE 3

For those of you who have not been exposed to the Swoop behavioural online personas, you will find a number of articles on our blog.

Because I will be referring to them it’s useful to know the connection patterns inferred by each of them. We don’t include the ‘Observer’ persona here as they are basically non-participants.

Starting with the Responder; Responders make connections through responding to other people’s posts or replies. This can be a simple ’like’, mention or notify..…and it often is, but sometimes it can be a full written reply.

In contrast the catalyst makes connections through people replying to their posts. A good catalyst can make many connections through a good post. Responders have to work a bit harder. They mostly only get one connection per interaction.

The Engager as you can see is able to mix their giving and receiving. This is a bit of an art, but important as engagers are often the real connectors in the community or group.

And what about the broadcaster? Well if your posts don’t attract any response, then we can’t identify any connections for you.

SLIDE 4

This is how we present our benchmarking results to the participants. You can see that we have the 14 dimensions normalized such that the ‘best in class’ results are scored at 100 points and the worst performance at zero. The orange points are the score for the organisation with lines connecting their scores to the average scores.

A few points to note are that we only count ‘active users’ being those that have had at least one activity in Yammer over the period we analyze, which is the most recent 6 months.

Some of the measures have asterisks (*) , which means that the score has been reversed for comparison purposes. For example, a high score for %Observers is actually a bad result, so this is reversed for comparison purposes.

Finally, not all of the measures are independent of each other, so it is possible to see recurring patterns amongst organisations. We can therefore tell a story of their journey to date, through seeing these patterns.  For example, a poor post/reply ratio indicates to us that the network is immature and therefore we would also expect a high % observers score.

SLIDE 5

One way of understanding which of the 14 measures are most important to monitor is to look at the relative variances for each measure across the full sample set. Where we see a large relative variance, we might assume that this is an area which provides most opportunity for improvement. In our sample to date it is the two-way connections measure which leads the way. I’ll go into a bit more detail on this later on. The % Direction measure relies solely on the use of the ‘notification’ type, which we know some organisations have asked users to avoid, as it’s really just like a cc in an email. So perhaps we can ignore this one to some extent. The Post/Reply measure is, we believe, an indicator of maturity. Foe a new network we would expect a higher proportion of posts to replies, as community leaders look to grow activity. However, over time we would expect that the ratio would move more toward favoring replies, as participants become more comfortable with online discussions.

It’s not surprising that this measure shows up as we do have quite a mix of organisations at different maturity stages in our sample to date. The area where we have seen less variance are the behavioural personas, perhaps with the exception of the %Broadcasters. This suggests that at least at the Enterprise level, organisations are behaving similarly.

SLIDE 6

This slide is a little more complex, but it is important if you are to gain an appreciation of some of the important relationship measures that SWOOP reports on.

Following this simple example:

Mr Catalyst here makes a post in Yammer. It attracts a response from Ms Responder and Mr Engager. These responses we call interactions, or activities. By undertaking an interaction, we have also created a connection for all three participants.

Now Mr Engager’s response was a written reply, that mentions Ms Responder, because that’s the sort of guy he is. Mr Catalyst responds in kind , so now you can see that Mr Catalyst and Mr Engager have created a two way connection.

And Ms Responder responds to Mr Engager’s mention with an appreciative like, thereby creating a two-way connection Between Mr Engager and Ms Responder.  Mr Engager is now placed as a broker of the relationship between Mr Catalyst and Ms Responder. Mr Catalyst could create his own two-way connection with Ms Responder, but perhaps she just responded to Mr catalyst with a like…leaving little opportunity for a return response.

So after this little flurry of activity each individual can reflect on connections made…as Mr Engager is doing here.

So in summary, An interaction is any activity on the platform. A connection is created by an interaction and of course strengthened by more interactions with that connection. Finally, we value two-way interactions as this is reciprocity, which we know leads to trust and more productive collaboration

SLIDE 7

Finally I want to show you how the two-way connections scores varies amongst the 36  participants to date. Typically, we would look to build the largest and most cohesive Yammer network as possible, though we accept this might not always be the case. While the data shows that the top 4 cohesive networks were relatively small, there are also 3 organisations that have quite large networks with quite respectable two-way connections scores.

So there is definitely something to be learnt here between the participants.

SLIDE 8

So in summing up, as of September we have 36 participants in our benchmark and growing rapidly now. The two-way connections measure, which is arguably the most important predictor of collaborative performance, was also the most varied amongst the participants.

By looking at the patterns between the measures we can start to see emerging patterns. We hope to explore these patterns in more detail with our research partners in the coming year.

Finally, we show that network size should not be seen as a constraint to building a more cohesive network. We have reported previously that another common measure, network activity levels are also an unreliable measure for predicting collaboration performance.

SLIDE 9

In the next video blog we will be looking at Yammer groups in more detail. We are aware that for many organisations, it’s the Yammer groups that form the heart of the network, so it makes sense to take a deeper dive into looking at them.

Thank you for your attention and look forward to seeing you next time.

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/