Thursday 16 October 2014

Data Storytelling for Disruptors

Disruptive innovations have become common in these 'postnormal' times. Organisations that seek to be disruptive are fusing big data analytics with storytelling to nurture better business cultures. Narratives and data stories encourage participation in innovation. We share our recent experience and insights into data storytelling and disruptive innovation.

Disruptors take big leaps into the future by optimising operations at the core whilst riding the edges of innovation. They recognise the value of data in shaping mindsets and facilitating shifts in conventional thinking during "post-normal times", a period described by Ziauddin Sardar, a London-based scholar and futurist in 2010:
Welcome to postnormal times. It’s a time when little out there can be trusted or gives us confidence. The espiritu del tiempo, the spirit of our age, is characterised by uncertainty, rapid change, realignment of power, upheaval and chaotic behaviour. We live in an in-between period where old orthodoxies are dying, new ones have yet to be born, and very few things seem to make sense. 
Sardar explains how the exponential growth of information technology is a considerable factor of today's unprecedented change, which encompasses emerging forms of nanotechnology and molecular computing. What is known as 'Big Data' is only going to become bigger. Sardar says these times demand "new thinking, effort and participation by everyone." Disruptors are unafraid to face the challenge.

Rapid streams of signals are found flowing in from an ever-expanding pool of sources. Executives want to be aware of any hint of disruption on the horizon - to defend against or seize the opportunity. Analysts sift through incoming data for any evidence of changes, risks and opportunities that executives may need to anticipate. Textual data keeps pouring in: blogs, social media, news, comments, reports, journals and whitepapers. The disruptors are the ones who synthesise data to tell stories that drive innovation into their culture and world.

Who are the Disruptors?

Disruptors, according to Caroline Howard of Forbes, are the ones who see "no one company [as] so essential that it can't be replaced and no single business model too perfect to upend." Cause Analytics thinks that disruptors disrupt by undertaking big pursuits with internal and external data. They engage in exploratory forms of analysis by using data visualisation tools that bring innovative possibilities into the focus of decision-makers. In this Age of Abundant Data, they are unafraid to sift through messy volumes of text and numerical content to come up with powerful stories that attract clients and disrupt industry norms.

Disruptors become leaders in their industries during complex, postnormal times. McKinsey Global Institute (MGI) suggests that leaders plan for "a range of scenarios, abandoning assumptions about where competition and risk could come from, and not [being] afraid to look beyond long-established models." As Disruptors, they leverage the coming economic impact of disruptive technologies. Their insights lead to innovations that unleash creative destruction on their respective industries. By fusing narrative with analytical thinking, the Disrupters' art of data storytelling can change mindsets to meet today's challenges head on, overcoming the biases of business un-intelligence.

Balancing the little with the big

Most analysts, executives and managers are busy with everyday operational inputs: sales, contacts, supply chain, and employee performance. An insufficient amount of time is spent thinking about either disruption or optimisation, let alone the formation of data stories.

To tell stories that drive innovation, Disruptors realise the dual-focus of innovation: big and little. From time-to-time, improvements are identified that may deliver a small boost. These small, incremental improvements are what service innovation company Imaginatik describes as the "little 'i' of innovation". In contrast, "Big 'I' Innovations" involve long-term initiatives with high risks that are often reserved for the largest corporations or nimble start-ups with ample capital resources.

Organisations with strict budgets usually stick to a straightforward game plan that doesn't stray toward the edges of disruptive innovation. For example, day-to-day operations remain a dominant focus, and are said to take 85 per cent of executive leaders' time.

Many organisations are simply not in the position to be Disruptors. Incremental improvements and small sustaining innovations, along with potentially disruptive innovations, take up about 5 per cent each of leaders' time, according to Harvard Business Review's article, 'How to Prioritize Your Innovation Budget'.

Having the desire to be disruptive means little when the reality is that internal stability must be maintained in order to survive. Continual optimisation can be simplified, however, when automated feedback and real-time data analytics are in place. 

Unifying analysis with a narrative

When time is spent keeping up with the feedback of everyday operations, stories of disruption can go ignored. However, storytelling that seizes data from across a multitude of sources can inspire innovation. For forward-thinking organisations seeking to become Disruptors, analysing data through a "unified approach" is helpful. Duncan Ross, Director of Data Science at Teradata International, describes the unified approach as a combination of unstructured and structured analysis environments. Traditional data warehouses are used for structured data analysis. For unstructured data processing, Big Data software frameworks are used, such as Hadoop. He argues that "utilising the strengths of each data analysis environment" can allow the organisation to "support its users as a whole and drive innovation".

Disruptors engage in multiple forms of data analysis that also include a narrative-focus, a blend of analytical with narrative thinking. Steve Denning, author of books on leadership, innovation and organisational storytelling, explains:
"Analytic, abstract thinking is ideal for reporting the regular, the expected, the normal, the ordinary, the unsurprising, the mundane, the things we often take so much for granted that we are hardly conscious that we know them at all. 
"By contrast, narrative thinking, encapsulated in stories and storytelling, is ideally suited to discussing the exceptional. Narrative thrives on the disruptions from the ordinary, the unexpected, the conflicts, the deviations, the surprises, the unusual. Stories flourish in the overthrow of the existing order by some event or thought that changes our perspective."
Analysts can undertake this blend by linking the micro elements of a story with the macro perspectives of a narrative. Big data researchers, Ramesh Jain, a UC Irvine professor, and Malcolm Stanley of Microsoft theorise that data-powered storytelling can be broken down into two categories: micro stories and macro (mega) stories. In 2013 they wrote about how micro stories are as simple as sharing or liking something on social networks. They explain that “Micro stories reflect a person’s experience with just one small event – really a moment in the event." Mega stories are broader narratives composed of micro stories and are effectively shared by revealing "a large volume of relevant events in big data,” according to the goal of the storyteller.

Innovations can be discovered by connecting micro stories with macro narratives form. Telling stories as a Disruptor requires a focus on changing perspectives by blending evidence with creative insight. Multiple sources and a unified approach to analysis involving both structured and unstructured data sets is ideal in revealing possibilities of disruption.

Embracing the tension of opposites

Disruptors embrace the "dynamic tension between creative disruption and operational efficiency". This point comes from an executive report released in July by the IBM Institute for Business Value. The authors, Barbara J. Lombardo and Daniel John Roddy, assert that this goes beyond ‘either/or’. They point to the metaphor of the human body as an organisation that is both creative and operational:
Complex systems (for example, the human body) are able to adapt in an orderly fashion to unexpected challenges because their many distinctive parts work smoothly together.
During these postnormal times of data abundance we seek stories that satisfy our thirst for a new normalcy. This involves embracing dynamic tensions, not just between operational efficiency and disruptive creativity, as the IBM Institute for Business Value noted, but "business, society, and the environment" as well.  

Discovering data stories as a team

Disruptors don't just rely on their analysts and executives to come up with insights, but welcome managers and many organisational members to engage in the process of exploration. They broaden the adoption of dashboards and data storytelling tools in their organisations by opting for 'self-service' tools. The main advantage of self-service business intelligence tools is that they enable non-technical team members to access data, participate in decision-making and win big.

Innovation management often involves people from across the organisation, especially during the gathering of ideas. When teams work together to share their ideas as data stories, they invite more participation. As teams connect their ideas, unending possibilities emerge in the sense that John Hagel, Co-Chairman of Deloitte Center for Edge Innovation, defines "narratives":
Narratives ... are stories that do not end – they persist indefinitely. They invite, even demand, action by participants and they reach out to embrace as many participants as possible. They are continuously unfolding, being shaped and filled in by the participants. In this way, they amplify the dynamic component of stories, both in terms of time and scope of participation. Stories are about plots and action while narratives are about people and potential.
There are an increasing number of data visualisation tools that offer storytelling features. Tableau's "Story Point" is one of them. Ellie Fields, Tableau’s vice president of product marketing, told Datanami:
Dashboard and reports will tell you the ‘what’ in your data. Stories can tell you the ‘why' ... Stories give you a way to create a narrative rather than just dropping a lot of data on someone and expecting them to just swim through it.
Even with user-friendly self-service analytics, not everyone in the organisation is likely to know what to look for in data. When interesting ideas and insights are shared in an interactive way - involving data storytelling - more of the organisation can participate. According to Jeffrey Phillips, a senior leader at OVO Innovation, "firms that often need innovation the most face corporate cultures that are the least open to change". He recommends implementing overarching frameworks that nurture the development of innovative culture by "welcome different points of view, different perspectives and seek to association disparate ideas and technologies into new products and services."

One way to welcome participation is through data storytelling. Stanford researchers of data storytelling, Edward Segel and Jeffrey Heer, explain the interactive benefits of "narrative visualisation":
Data stories differ in important ways from traditional storytelling. Stories in text and film typically present a set of events in a tightly controlled progression. While tours through visualized data similarly can be organized in a linear sequence, they can also be interactive, inviting verification, new questions, and alternative explanations.
Not every member of an organisation can, or even will, find meaningful signals in their company's data. Analysts may not either. To become a Disruptor, nurturing a culture of innovation is necessary. The journey can begin with outsourcing the data crunching and business intelligence challenge to fast and affordable service providers with experience using data storytelling to drive innovation.

Finally, mull on this...

Consider the impact that Uber (a mobile app and ridesharing service) has had upon taxi services. When cabbies in London began protesting the legality of the service, Uber launched UberTaxi to include the disrupted group in the mobile app. First, Uber disrupted the existing model for taxi services, then second, the company adapted to serve those negatively affected by it. As Disruptors, their business model is fueled by data and the stories of their users. Simply put, Uber sensed the resistance of the cabbies and then figured out how to include them in the ecosystem and, most importantly, in the narrative of change.

Disruptors ride the advantages of postnormality with strategies born out of both analytical and narrative thinking. Data storytelling engages their cultures and drive innovation forward.

For one company, this could involve a twist into mobile consumerisation. For another, it could mean manufacturing intelligent services through the Internet of Things. Whatever the case may be, a tsunami of data is rising in the the wake of accelerating technologies. The organisations that fail to surf this tsunami may meet their downfall. The survivors who adapt by seizing the winds of disruptive innovation will be the Disruptors of old narratives and creators of new ones.

Dan Durrant, Content Analyst at Cause Analytics
David Pidsley, Executive Director of Strategy at Cause Analytics

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