IMAGINE NEXT - The Power of Generative Research in a One Up World

In a world dominated by commoditization and disintermediation, revolutionaries and entrepreneurs are seizing the day. Incremental improvements and market share gains are rapidly giving way to an era of disruptors, disruption and creating the future. Fueling this imagination of next is the power of generative research.

 As the British author, humorist and satirist Douglas Adams once cleverly wrote,

 “Flying is easy, you just throw yourself at the ground and miss.”

 Arguably, innovation should be just as easy, all one really needs to do is:

 “Create the future just slightly ahead of its regularly scheduled time.”

Of course, it’s not that easy. If it were, today’s world would be a very different place. Assuming that tomorrow is somehow different from today and tomorrow will be just as different, the future we desire isn’t something upon which we passively stumble. Change doesn’t just happen. Creating a future we want requires creative forethought, thoughtful imagination and definitive action. Simply put, it requires innovation. The central questions are:

 “How does innovation happen?”

“How do you innovate?”

“How can I imagine the future?”

“How can I bring the future to life?”

“How do I make the future?”

“Is innovation an art or a science?”

In many ways design, art and science are interdependent. The lines between them have been distorted and obscured and this can create either great synergies or powerful antibodies. While science is the practical, systemic and sometimes intellectual study of the physical and natural world through observation and experiment, design is a behavior and activity focused on conceiving, activating and producing something of practical value. And art, unlike science or design, may have no practical purpose beyond entertainment, stimulation or inspiration. But what is common to design, art and science is the human need to know and to learn, to see beyond, to know more and to apply that knowledge in valuable, meaningful, practical or human ways.

In a world where volatility, uncertainty, complexity and ambiguity (what the Army War College first referred to as ‘VUCA’) abound, the lines between art, science and design are ever more confusing. Research, an essential effort in the act of knowing and learning, and so fundamental to science, design and art, could probably benefit from a better understanding and a less mystifying perspective.

 The Why and How of Research

No one would argue that doing one’s homework, gaining a deeper understanding or simply learning something new are worthless, aimless endeavors. Research, the systematic investigation of a subject and the study of information for the purpose of learning, establishing truths, identifying insights and reaching conclusions is fundamental to the creation of knowledge. From the beginning of civilization as we know it and still today, from survival and control to success and sustainability, knowledge is value. But exactly why that knowledge is important and how it can be used are inextricably linked.

Business research has been utilized since the beginning of modern commerce. Whether to assess the quality of an idea, investigate the means by which an idea would be brought to market, understand the competitive landscape or merely to make a case for future success, research efforts have sought to define strategies, refine directions, identify threats, reduce risk, increase comfort and ensure continued business success. But the bigger ‘why’ behind research; how it’s done and the value it can create, should remain essential questions to almost every organization.

Quantitative and Qualitative Research

Historically, there have been two approaches to research - Quantitative and/or Qualitative. But the difference between the outputs of these two ‘methodologies’ of research is relatively inconsequential when compared to the differences between their intents and fundamental purposes.

Quantitative research takes a more empirical, experimental and systematic approach to investigating the pragmatic properties of a set of variables or domain and the phenomena around their interactions and relationships. Quantitative research can be helpful in answering focused and more explicitly defined questions, identifying measurements to check facts, gauge specific performance, or collecting numerical data through various ‘instruments’ to allow for subsequent analysis and deductions. Because quantitative research is the domain of testing hypotheses, exposing correlations, revealing associations and causal relationships, how samples are defined and the size of those samples are critical to the validity of the results and outcomes. Statistical science becomes really important.

Qualitative research, which is the more natural and intuitive of research types, has traditionally been employed to understand human behavior and the underlying motivations, intentions and explanations of those behaviors. Qualitative research typically seeks to explore and identify questions that may lead to a deeper understanding without quantifying metrics or seeking to create direct connections between variables without statistical rigor. Qualitative research is typically a method of exploration and discovery where sample size is rarely a serious concern. The focus is on expanding meaning, stimulating new investigation and developing new understanding.

Evaluative and Generative Research

There are significant differences in techniques and outcomes between qualitative and quantitative research. Independently or together, they can be powerful forces for understanding. But an even greater difference, that transcends both approaches to research, is fundamentally around the very purpose or ‘why’ of any research. It is a general lack of awareness and even misunderstanding of this ‘why’ that creates significant problems, complications and enormous opportunities for many companies.

Research is done either to prove, test or validate something reasonably assumed to be known (a hypothesis) or it is done for the purpose of identifying and exploring entirely new knowledge. Some research is done to answer recognized questions, while some is done to help ask better questions. And this is where this rather simple difference can be so difficult to distinguish.

A better way to describe the differences between these two fundamentally different reasons to do research is to define them based on why the research is being done in the first place. Regardless of a quantitative or qualitative approach, the intention or ‘why’ behind the research may be far more important than the methodology itself. That elevated purpose or ‘why’ reveals fundamental and actionable differences that can guide the use and justification of research in meaningful and sustainable ways. Rather than categorize research methodologies based on either a quantitative methodology or qualitative approach, seeing research through the higher-level perspective of intention can be far more useful when understanding the goal of the research. And these two ‘intention-based’ research views are ‘evaluative’ and ‘generative.’

 Evaluative research has largely been the domain of branding and marketing professionals. Generative research is emerging as a key instrument in the designers’, design thinkers’ and innovators’ toolkit. Both kinds of research are extremely valuable when used appropriately, by the right people and at the right time. They each have their purpose, their distinct value and unique outcomes. But, when used for the wrong reasons, at improper times, by the wrong people and in incorrect sequence, both evaluative and generative research can lead to wasted effort, unexpected outcomes, false directions and unintended results.

Surviving vs. Thriving

Business success and growth come in many different forms. The traditional metrics of business have largely been focused on income, profitability, optimizing operations, gaining market share, developing brand equity, sustaining repeat business and raising a company’s net promoter score. These measurements are the domain of incremental, organic and evolutionary growth. But in a world increasingly dominated by entrepreneurial disruptors, identifying and developing what’s ‘next,’ seizing the disruptive, transformative, revolutionary and new to the world ideas, have become not only a precondition for growth but also a prerequisite for survival.

Next vs. New

But getting to ‘next,’ as opposed to merely the ‘new and improved,’ is rarely obvious, never easy and often wrought with conscious resistance and unconscious antibodies. As the world gets ever more volatile, uncertain, complex and ambiguous, the human tendency to hide, maintain the status quo or avoid risk altogether may be our greatest enemy. Those most in need of owning ‘next’ are often least comfortable with creating it. As Bob Johansen so perfectly expressed in his book by the same name, “Leaders Make the Future.”

So, here’s the problem in a nutshell: If research is being used as the path to next, the difference between qualitative and quantitative methodologies is largely irrelevant to that journey. Both will yield results. Neither will likely get you to a new understanding, let alone what’s next. Getting to an enlightened state of ‘next’ through more traditional ‘evaluative’ research, regardless of it being qualitative or quantitative, is unlikely if not impossible. To ‘make the future,’ as Bob Johansen suggests, you need to see, to learn, to gain insights and to understand in fundamentally different ways. While understanding the past and seeing trends indicative of the present may help you survive in the short term, they will rarely if ever help you lead, make the future or thrive.

Familiarity with the Unfamiliar

The feeling of déjà vu is familiar to everyone – the experience of an unfamiliar situation and feeling like you’ve somehow experienced it before. But as the brilliant comedian George Carlin once famously remarked,

“Did you ever get that feeling that somehow none of this has ever happened before?”

Carlin coined the phrase ‘vuja de’ to define the experience of a familiar situation seen through fresh eyes, as if you’ve never seen it before. It is this fresh perspective that is the very essence of generative research, enabling a new perspective to inspire a future of our making.

Follow the Money

Any reasonable understanding of the relative budget allocations within most companies reveals that marketing and advertising budgets almost always exceed research and development budgets. Advertising and marketing budgets are largely concentrated on selling the existing offering, positioning and communicating what already exists and making incremental changes and improvements in features and functions. At best these efforts gain market share of an existing market or acquire consumers in new markets. And research and development budgets can also be focused on temporarily gaining operational, material or technologically competitive advantage over the competition. These efforts are about top and bottom line success. But, when significant and future growth is the goal, the parts of the organization that control the largest budgets and have the shortest term view, are often the least likely to create that growth.

What is poorly funded, ignored, left to chance or, even worse, left to the world of outside disruptors, is the conception and realization of entirely new to the world products, services and offerings. Most companies are unassumingly wired up to maintain the status quo and sell more of what they already have. These companies value innovation but ‘dis-innovation’ is often the prevailing paradigm.

The Behavioral Underpinnings of Dis-innovation

Neuroscientists and neurobiologists have largely concluded that of the two primary motivating factors behind all human behavior; the avoidance of pain and the pursuit of pleasure, we are pre-wired to favor survival and less pain over more happiness and adventure. So, it’s completely understandable that companies, organisms in their own right, would favor the safety of preserving the present over the risk of imagining and creating their own future.

As Albert Einstein once remarked,

“We cannot solve our problems with the same level of thinking that created them.”

But these wise words were focused on problem solving NOT opportunity creation. If Einstein had been an innovation adventurer focused on the world of opportunity creation and application, as opposed to a theoretical physicist focused on theories and discovery, he might have just as easily said,

“We cannot create the future with the same approach we used to generate the present.”

When those tasked with creating the future rely on evaluative research, they dramatically diminish, if not completely inhibit the ability to gain new understanding, develop new insights or find new inspirations that can lead to reframing, redefining or revolutionizing the present in the form of an amazing next offering, product, service, experience, business model, etc. Innovation at a revolutionary standard, does NOT begin with an idea, a concept or even a hypothesis. It begins with an insight or an inspiration.

True innovation is rarely if ever about problem solving, addressing known challenges or making existing things better. Revolutionary innovation begins with deeper insights into the behaviors, aspirations, unmet needs and unexpressed desires of people. It’s almost never about expressed consumer need gained from listening to the ‘voice of the customer.’ The inspirations that lead to ‘next’ most often come in the form of slow, deliberate, often unexpected, even surprising and counter-intuitive understanding. As the celebrated science fiction writer Isaac Asimov once said,

“The most exciting phrase to hear in science, the one that almost always heralds new discoveries, is not Eureka, I found it!, but hmmm, that's interesting.”

Whether one employs qualitative or quantitative research methods, the key to discovering what’s ‘next’ and disrupting through innovation is in generatively not evaluatively exploring what is not yet known.

Common Traits of Most Disruptive Innovation

Curiosity, optimism and a deeply empathic understanding of human behavior have been empowering teams and fueling the creation of what’s next since the beginning of time. The greatest innovations of the modern era are almost all characterized by a few commonly held traits:

1. There was rarely a consumer expressed need.
2. The source or genesis of the idea was rarely the ultimate or total market for the product.
3. The big, disruptive innovations rarely if ever emerged from the prevailing industry players.
4. The ultimate market rarely if ever existed in advance of the offering.
5. The most successful innovations of our time rarely if ever tested well in the early stages of development.

 Considering each of these five traits, it is no surprise that well-meaning but fully entrenched marketing, finance, operations, research and development professionals may unconsciously inhibit or even consciously obstruct innovation if they rely on the outputs of evaluative research.

History of the Future

If one looks back at those that created the future, the common held traits of significant innovations are validated with amazing clarity. The history of innovation clearly establishes that:

 No one was asking for a new search engine, a $5 cup of coffee or overnight delivery before Google, Starbucks and FedEx each disrupted their industries.

 The music pirates, digital thieves and hackers that inspired the iPod were never going to buy a $250 mp3 player or buy music for $1.29 a song before Apple changed the music business for ever.

 None of the big hotel chains imagined Airbnb and none of the big cab companies imagined Uber or Lyft.

 Christies and Sotheby’s could never have conceived that the Internet could power the world’s garage sale before eBay created an entirely new industry.

 Few people understood what they would ever use a tablet computer for before the iPad changed the landscape of the world of computers.

 Amazon, Facebook and LinkedIn were widely panned by consumers and business analysts alike before they became some of the planet’s largest companies.

 And right now, given the obvious risks, self-driving cars sound like a really bad idea to many people.

These innovations, the innovators, and those designers that brought them to life were not hit by bolts of lightning, were not responding to some need the market was demanding and certainly were not supported by the prevailing paradigms or status quo. Innovations do not emerge from focus groups, statistical surveys, big data sets, trend analysis or any of the evaluative methodologies that many companies rely upon. Rather, they were inspired by generative insights into the deeper needs, behaviors and aspirations of real people, living their lives, enriching their existence, seeking happiness and fulfillment and raising their families.

Data, Understanding, Meaning and Impact

The difference between market-driven evaluative research traditionally focused on validating an idea, proving a value proposition, sizing a market or identifying a trend and the generative research done to inspire and conceive an idea could not be more evident. As new research methodologies like big data and new applications of technologies like neuroscience emerge and grow, there will be a movement to leverage these more evaluative tools in more generative ways. The truth is that big data is best at understanding what happened in the past, optimizing the present and incrementally improving what already exists. But it’s far more likely that really small data sets or ‘smart data’ sets will lead to more evolutionary, revolutionary and new to the world ideas. And that may simply be due to the fact that, in the right hands, these data sets often identify odd, unusual and seemingly irrational behaviors that can rattle the prevailing paradigm, inspire new understanding and provoke new thinking. Neuroscience research shows great promise as brain scans can accurately indicate human reactions to specific stimuli. But when the challenge is to imagine new stimuli, it remains to be seen how tools like FMRI brain scans will serve a more generative understanding.

Insights from the Outliers

The key to getting to ‘next’ lies less in analyzing big data sets, understanding the norm or listening to common ‘voice of the customer’ needs and more in the unknown, unexpressed or latent needs of people including outliers and extreme users. And those outliers and extremes can take many forms.

‘Extremes’ might be hardcore, obsessed users or even the consummate abusers of products and services. It was not the average, casual or even devout music listener that led to the inspirations behind the iPod. If the needs of the sweet spot of the market had been relevant, we’d still be listening to CD’s or their smaller cousins MD’s and there would be a plethora of CD wallets stashed in our homes and being sported on our car visors. Rather it was the hacker, pirate and music thieves who were stealing (‘pirating,’ as it became known as) music, sharing and copying music illegally, making their own compilations, etc. that lead to the insights that drove the conception and development of the iPod. And, it’s worth noting that had the entire concept behind the iPod been presented to those same hackers, pirates and thieves, they would clearly have been harsh critics of buying music for $1.29 a song and not being able to replicate or share that music.

‘Outliers’ could be newbies and people unfamiliar or completely unaware of a product or service that are the source of inspiration. It was the creation of the ‘third place,’ where people could gather and meet outside of work or the home, not the coffee per se, is the value proposition ultimately behind Starbucks. You needed not be a coffee expert or caffeine addict to understand how Starbucks could serve a completely unmet and latent need.

‘Outliers’ and ‘extremes’ could mean people completely peripheral to the product or service area. Or they might be a completely analogous context that could drive new insights or become inspirational in some unexpected and equally valuable way. Tasked with imagining the future of the emergency room, an innovation team focused on the world of NASCAR pit crews, the very definition of mission critical, time constrained, equipment rich environments, believing it could lead to more new stimulus and greater provocations than studying every best in class emergency room in existence. And, if tasked with helping to imagine the future of hospitality, one might gain far more insight by studying character and role development along with stage set design in theatre than endlessly speaking with hotel guests or management.

Comedy can also be an incredibly rich source of understanding and insights. Something is actually funny and humorous because it reveals a truth, reframes the perspective, exposes a prevailing paradigm or voices an insight. These four underpinnings of what makes anything ‘funny’ are directly parallel to the inspirations behind innovation. Faced with rethinking the waiting room experience in a doctor’s office or clinic, carefully studying the comical insights exposed by Jerry Seinfeld’s funny and insightful standup routine on waiting rooms, could help uncover a level of human understanding that weeks of research may be challenged to reveal.

Investment, Risk and Outcomes

Evaluative research, because of its need for scale and certainty can be quite expensive and time consuming despite the ability to automate much of the process in the form of surveys and studies. But, generative research, because of its need for depth, human connection and empathy can be time consuming and emotionally demanding. But the difference in value and outcomes is more about risks and benefits than cost and expense.

Choice and Consequences

If the ultimate driver of sustainable growth is to imagine and create the next big thing, it would be equally absurd to suggest getting hit by lighting or meekly doing nothing. These, after all, would likely be the most risky and most expensive strategies. Evaluative research can build confidence, but only when an idea already exists to be tested. No one ever got fired for assessing whether people like something or would buy something in advance of making it available. All those trend charts, pie charts and scatter diagrams can, after all, assuming anyone really understand them, be quite comforting. On the other hand, generative research is risky, often raising immense suspicion and generating huge organizational antibodies.

When ‘next’ level, revolutionary ideas fly in the face of logic, feasibility and viability, people can and do get fired. But in a world increasingly being disrupted by fresh start-ups, entrepreneurs and provocateurs, entire enterprises and even industries are at risk. If a company is not actively working to transform its industry or even better, put itself out of business, they can rest assured that someone is doing just that. Those steeped in the philosophy that ‘failure is NOT an option’ are destined to crash and burn in some fundamentally unpleasant ways. And getting fired may not be the worst that could happen as people can find their jobs and related skillsets increasingly rendered obsolete.

Companies could employ a short-term strategy, bury their heads in the sand, deny the disruptions destined to happen and focus their evaluative research entirely on incrementally improving their existing offering, positioning it more effectively and selling it more successfully.

Or companies can choose to balance their efforts between evaluative research and generative exploration – using evaluative research to sustain and extend their existing success while using generative research to identify and seize entirely new opportunities and create what’s next for everyone.

Thomas Stat is an innovation consultant, design strategist, designer, speaker and teacher with over 25 years experience helping start-ups, global companies, associations and other organizations innovate through a human-centered, generative design approach.