How To Evolve Your Strategic Innovation Capabilities To Meet The Emerging Post-Coronavirus Value Landscape (Part II)

In Part I, innovation value landscapes were discussed and conceptualised to highlight how the pursuit of innovation has shifted and is changing due to Coronavirus (COVID-19). In this Part II, I discuss specifically how firms will need to adapt their existing innovation processes to meet the new challenges of an emergent value landscape to help successfully survive in the new normal.

Part II: The Limitations of Innovation During a Crisis

Where are our existing innovation capabilities?

‘Hang on!’ I hear you say. ‘Isn’t our new innovation process using Design Thinking, Lean Startup, business model innovation and Agile (invested in so heavily) designed to deal with exactly this kind of uncertainty and ambiguity of COVID-19? The short answer is, yes, they do. But they are suited to more normative levels of consumer-market uncertainty. The COVID global crisis extends the value-seeking landscape more broadly in all dimensions. It is no longer good enough to just gather insights about latent customer needs to start your innovation process. Typically, innovation methods are applied during two- to ten-week iteration cycles within a mostly stable supporting macro environment. During a crisis, consumer needs and desires change drastically overnight. What’s more, their desires are coupled with equally drastic and severe changes in the macro-environment (political, economic, social, environmental and legal domains).

It is no longer good enough to just gather insights about latent customer needs to start your innovation process.

Innovation tools and methods are designed to make sense of shifting and evolving customer needs in normal market evolution speeds, rather than expecting them to make sense of an entire crisis landscape. Ethnographic research methods alone can be too slow and too rigid.

This goes some way to explaining why innovation projects away from home are usually the first to be postponed or cancelled by leadership during such times. However, strong decision-making is needed to make sense of the consumer and wider macro environment being faced right now. Doing so places firms in the best position with the right capabilities to locate, create and capture value in the new emerging landscape once things start getting back to normal again. Research has repeatedly shown that economic growth and firm survival is dependent upon investing in innovation during, not after times of crisis (Paunov, 2012). Furthermore, firms that can emerge with the capability to map the macro-environmental shifts and customer needs and problems will be better equipped to move the fastest when finding and exploiting the most profitable unknown value peaks in the new market landscape ahead.

The role of research and development (R&D) and new technologies in a crisis

In more normal and stable times, new technological paradigms create a toolbox of new possibilities to serve unmet needs in better ways. These open up the near possible, triggering a subset of unrealised value peaks if used at the end of the innovation process (not as a starting point).

A good example here is the ARM microprocessor computing chipset. Originally developed for devices like the ill-fated Apple Newton, ARM chips can now be found in all types of digital devices from smartphones, wearables, Internet of Things devices, cars, airplanes, tablets, hard drives, music players, gaming systems, TVs, navigations systems, alarms, vending machines and many others. As of February 2020, 160 billion ARM chips have sold worldwide (Honan, 2013; ARM, 2020). It is fair to say ARM chips are a true architectural innovation. They have paved the way for new disruptive, radical and incremental innovation types consistently over the past forty years.

We usually apply the innovation process sequentially across three key pillars: customer desirability, business model viability and technological feasibility. However, during genuine architectural innovation like ARM chips, the innovation process in fact starts with technological feasibility, independent of customer desirability entirely. This is because core R&D is needed to open up the near possible consumer value landscape that will in the future comprise new unmet needs and problems. It is the role of R&D to expand the value landscape plane, but it is the role of methods like Design Thinking to figure out what to do with them at the end-consumer and user levels. More often than not, technology firms get into trouble when they over-invest in new technology R&D, only to then release something to market that doesn’t meet any customer needs and value preferences in the right way. See Apple’s Newton device with revolutionary features ahead of its time, but unable to be technically implemented in the right way for actual customer use, such as writing recognition. This caused a great device to ultimately fail in terms of market desirability.

Normally it is enough to understand your customer needs and problems, formulate a way to capture value back for your organisation, then use new and existing technologies to create your validated solution. However, the COVID-19 landscape is about more than needs-and-problems discovery in a relatively stable environment. At the moment (and in the coming years following the predicted recession), the external macro-environment should be held as equally important in driving the creation of new unmet needs, not just on a technology enabling trajectory of the near possible.

To address the new road ahead, the innovation process needs to adapt and meet the needs of organisations seeking to make sense of higher levels of uncertainty and ambiguity from multiple problem domains at once. The startup world continues to be in a strong position as it routinely makes sense of and addresses the evolving value landscape with relative speed and ease. It will be no easy task for established firms. But those that can reconfigure themselves will succeed to the highest levels.

The Innovation Process for Organisations Post-COVID-19

So far, we have looked at why organisations exist in relation to creating value types. We’ve looked at how value is conceptualised and uncovered when solving customer needs and problems during periods of environmental stability. We’ve also looked at how the global COVID-19 pandemic has shifted the value landscape. We will now look at another, equally important dimension that has not seen much light for the past twenty years.

Moving forward, organisations need to equally and continually make sense of two key insight domains:

1. The rapidly evolving macro-environment
2. Radically shifting consumer/customer needs and problems

How should organisations adapt and transition to a post-COVID-19 world to achieve new value creation throughout the innovation process?

Firms will need to develop two new sense-making competencies.

1. Deploying a continual external scanning capability
2. More rapid ethnographic empathy research methods

New technology R&D is hard and takes time to do safely. We can’t rely upon R&D alone to provide solutions. We’re facing life and death challenges. We need solutions now.

Dynamic capabilities are routines to learn new sensemaking routines within organisations. They are required to allow firms to find external knowledge and insights about the outside world. Once found, they need to be quickly absorbed across organisational boundaries to build upon within innovation teams. Spanning from the outside world to internal, we need remote teams who can quickly deliver the right value to solve new unmet needs (Cohen and Levinthal, 1990; Teece, Pisano and Shuen, 1997). Organisations don’t have time, money or luxury of not invented here syndrome, especially during a crisis. Defined as the dysfunction where external solutions to problems are rejected in favour of internally developed solutions (Katz and Allen, 1982). Solutions need to quickly come from where ever possible to meet unmet value peak needs and problems.

1. Developing a continuous external scanning capability

During my studies in international business and management, much focus was given to industrial organisation economics in understanding the theory of the firm from a macro-environmental perspective for strategic decision making. Authors from the 1980s and 1990s such as Kotler, Porter, Tirole, Scherer, Shapiro, Maslow, et al. As we’ve seen earlier, standard management practice has more recently shifted to understanding networks and ecosystems of value exchange as a source of competitive advantage.

Examples of industrial organisation economics tools and frameworks:

• 5 Forces Framework
• PESTEL Analysis
• SCLEPT Analysis
• Issues Priority Matrix
• Tows Model
• Five Product Levels
• Ansoff’s Growth Matrix
• Value Chain Analysis
• Hofstede & Trompenaar’s Cultural Value Dimensions
• Value Network Analysis
• Strategy Canvas
• Life Cycle Model
• Issues Priority Matrix
• Competitive Rivalry Analysis

To make sense of the pandemic impacts on the emerging value landscape in the coming years, it is vital to re-train your innovation teams in more traditional (perhaps seen as outdated) tools and frameworks.

Sometimes you have to look back to move forward. A retrospective look back to the shock of the old to solve the now (Edgerton, 2008). A story well told in the movie Hidden Figures in 2017, whereby Katherine Johnson, a NASA research mathematician, had to refer back to ancient mathematics using an ancient approximation technique called Euler’s Method in order to solve the vastly complex Mercury Mission orbital mechanics re-entry calculations for safe astronaut return (Meyers, 2017; Intmath, 2018).

It is important to stand on the shoulders of giants during significant uncertainty and volatility to solve problems quickly and effectively. Our body of knowledge serves specific purposes and can help make sense of what is happening outside your organisation to inform effective management and decision making. What’s more, older tools can now easily be adapted for use in distributed digital innovation teams using tools such as Mural and Miro remotely for innovation project sprints; something that was not possible when they were first introduced.

An up-to-date understanding of what is happening in the macro-environment is more crucial now than before, particularly as we are under lockdown for months at a time with no sense of the outside world. Organisations need to empower their innovation teams with this reincarnated external scanning capability because they are not part of the current iterative customer-centric innovation process applied within organisations today. The future of work will very likely continue to occur remotely, so teams need to intimately understand what is happening out there by capturing and absorbing changes in market conditions, competition, government interventions, fiscal policies, protectionism, legal frameworks and the like as they emerge.

Organisations need to empower their innovation teams with a reincarnated external scanning capability because they are not part the current iterative customer-centric innovation process applied within organisations today.

This needs to happen on a weekly and daily rhythm basis in the short-to-mid terms, continually updating the tools and frameworks as key changes and trends emerge. Innovation teams looking for radical and disruptive triggers and insights for new innovation projects should be carefully analysing and documenting what is happening externally in order to feed and uncover key common insights triangulated from multiple stakeholder perspectives. In effect, we need to devote as much importance to understanding the external environment as we would normally give to understanding customer needs and problems alone. These external insights should then be used in combination with more traditional innovation methodologies, such as Design Thinking, lean startup and business model innovation (in a modified form). Doing so will enable you to address COVID-19-related business challenges for your organisation.

Equal importance needs to be given to understanding the external environment as much as we would normally devote to understanding customer needs and problems alone.

2. Building rapid ethnographic empathy research methods

Many world-leading organisations have been investing in iterative innovation methodologies over the past twenty years, accelerated largely by competition; the speed and agility of the startup world; the rate of technological change; and the democratisation of the means of production through digitalisation. The good news is that a customer-centric innovation process is as important now as it always has been; perhaps more so. In addition to understanding the external environment, we need to deprioritise Design Thinking, Lean Startup and business model innovation so that they run in parallel with understanding changes in the macro world in order to trigger the innovation process. This also needs to happen quicker than ever before.

Perhaps for the first time in its history, the successful application of Design Thinking is dependent upon looking back at and incorporating older methodologies and frameworks to make it effective for organisations addressing the COVID-19 challenges we’re facing today.

We are lucky enough to have the digital collaboration tools to get close to our customers (even under a pandemic lockdown) with a plethora of tools at our fingertips at low cost or free. It is easier now than ever before. Millions of consumers, users and employees working from home or under furlough schemes globally. We can quickly deploy traditional research methods in remote form. These may include contextual qualitative interviews, cultural probes, remote home-shadow, focus groups, participant observation and large-scale quantitative surveys.

Perhaps for the first time in its history, the successful application of Design Thinking is dependent upon looking back at and incorporating older methodologies and frameworks to make it effective for organisations addressing the COVID-19 challenges we’re facing today.

Fortunately for innovation purposes, the qualitative research methods required during the empathise phase of the innovation process are still achievable thanks to digital technology. Innovation teams do not have the excuse that they can’t get close enough to customers to understand their needs and problems during lockdown and beyond.

Combining insights for innovation

Once your teams have uncovered new opportunity areas from both the macro-environment and outside of your existing markets, you will be able to spot the overlaps in problems and need and determine jobs-to-be-done that did not exist prior. Macro-world and customer-driven insight domains should be fed into your current innovation capability. Firstly, by defining challengingly broad how-might-we (HMW) statements for your organisation. Secondly, by sending your teams more divergently across adjacent and new markets which may provide product and service areas that you might not otherwise have been given the strategic green light to pursue.

How the innovation process needs adapting to meet the challenges of a post-COVID-19 world

Fig 5. How organisations need to adapt the innovation process to effectively deal with COVID-19 challenges ahead

Summary

In order to survive in the short-term crisis, organisations and their leaders need to shore up their businesses and protect the core revenue streams. In the mid-to-longer term, organisations need to internalise and harness enhanced uncertainty as part of their innovation strategies, realising that the value landscape will look very different in the months and years ahead. Business-and innovation-level strategies need to support this by making the confident decision to allocate a proportion of people, time and resources to disrupting the core of their own business, now. Once this decision has been made, relearn, digitise and deploy generations-old frameworks to your strategic innovation project teams to help quickly understand the macro-environment. Improved capabilities that enhance existing customer-centric knowhow in terms of speed, breadth and frequency need to be used.

Organisations must make the strategic decision to allocate a proportion of people, time and resources, specifically aimed at disrupting the core business, now.

Once both pieces of the COVID-capability are in place, your organisation will have effectively developed an external macro-environment scanning radar, coupled with a deep and extensive understanding of your target market both beyond your existing segments and into new markets entirely. Using these two insight perspectives in parallel will ensure that a proportion of your resources are spent solving the right disruptive and radical customer needs, independent of your existing business. You will then be in a position to identify nascent value peaks before they have become fully saturated towers. Identifying value peaks quickly and early will provide emerging kernels for your organisation’s survival post-pandemic and beyond.

Stay safe (written in quarantine in Belgium).

About Mike Pinder

Mike is Innovation Expertise Lead at Board of Innovation, working cross industry in B2B & B2C helping Fortune 500’s to innovate like start-ups. He applies a multi-disciplinary background spanning design, business & innovation management through hands-on consulting, training & facilitation of tailored innovation programmes. He regularly authors thought leadership pieces and gives international keynotes on innovation. Mike guides innovation strategy, designs and runs corporate accelerator’s, builds long-term cultural transformation programs and grows strategic innovation partnerships to name a few.

• See how he can help your innovation efforts in person or virtually: https://www.mikepinder.co.uk/

Special thanks

This article was edited in collaboration with Alexandra Sutton. A freelance SEO & UX copywriter, she’s helped such brands as Board of Innovation, Toyota and Pioneer DJ tell stories that strike a chord. Looking for the right words? Get in touch with her on LinkedIn to find out how she can help.

Footnotes

[1] This topic has significant philosophical implications, based upon a mixture of subjective, objective ontologies among other viewpoints and lenses. For further reading on this, I recommend a booked titled, Creative Research: The Theory and Practice of Research for the Creative Industries (Collins, 2010).

[2] Further reading: (Schumpeter, 1942; Hannan and Freeman, 1977; Williamson, 1979; DiMaggio and Powell, 1983; Wernerfelt, 1984; Kogut and Zander, 1992; Denison and Mishra, 1995; Burgelman and Grove, 1996; Podolny, Stuart and Hannan, 1996; Tushman, Anderson and O’Reilly III, 1997; Teece, Pisano and Shuen, 1997; Gulati, 1998; Sherman, Kashlak and Joshi, 1998; Santos and Eisenhardt, 2009).

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