Part I
INTRODUCING IDEALS
1
Innovation in the Digital Era
1.1 A Mandate to Transform
We begin our exploration on how to engage people to make transformation happen today by examining why innovation and change are so radically different in the digital era. We also describe how transformative innovation requires a synchronicity of both innovation and change. In our research and advisory work, we are witnessing how our traditional theories and methods hinder innovation and change in the digital age. To illustrate this phenomenon within the context of innovation, we share the story of a personal care product (PCP) company which illustrates how our innovation methods are no longer fit for purpose in a digital era. We then examine in depth how our traditional theories of innovation are also not fit for purpose in the digital era and illustrate this phenomenon within the context of change by sharing the story of J. C. Penney. Finally, we examine in depth how our traditional theories of change are also not fit for purpose in the digital era.
To leverage the opportunity of learning from these failures, and to reflect on our collective experiences in the field, we then reframe the scenarios that an innovator confronts today. We argue that both leading innovation and engaging people for change must be pursued simultaneously. At this intersection, we see that the innovator's dilemma in the digital era is transformation â converging people in a new direction for collective action. In light of the wicked problems that we face as a society, we conclude the chapter with the mandate to seek transformative innovation â a change in the systems that circumscribe the products and services we use. We contend that only with such a mandate can we stimulate a collective search for how to engage people to make transformation happen.
1.2 Innovation â Disrupted
Leaders who seek transformative innovation â the change of a system, not just the product or service delivered within the system â face a new scenario unique to our digital age (e.g., Downes and Nunes 2014, Verganti 2017, Thomke 2020). Whether the system in play be education, health, social, environmental, financial, economic, or even political, the digital era presents a complex landscape for the innovator to navigate. Due primarily to hyperconnectivity, today we have a plethora of open innovation platforms, overcrowded communities of experts, an abundance of innovation training programs, and an unprecedented per capita concentration of accelerators and incubators. Today anyone can innovate, both inside and outside the organization. And digitalization amplifies and accelerates society's insatiable demand for innovation. Augmented by the multitude of digital creative tools, everyone can bring life to ideas through visual representation. This ecosystem is fueled primarily by billions in venture capital funds, but also a new generation of talent that is stimulating a tsunami of enthusiasm for the pursuit of the new and innovative.
In this landscape, the challenges of today are not the traditional ones. In fact, for the past 30 years and specifically the advent of social media platforms, the proliferation of experts, support, and methods has, in many organizations, mitigated the traditional challenges of innovation and its implicit mystique: ideas are no longer scarce due to a plethora of open innovation platforms. However, the duration of innovation adoption significantly decreased. Leaders are no longer blinded by the myths of innovation or the charlatanry of consultants. They generally do not seek lone innovators, rather teams. Nor are they desperately searching for those with the desire to make innovation happen. Moreover, by empathizing with the user â or consumer â of innovation, making innovation happen should be easier because it's what they asked for. As design thinking training is spread across the globe, innovation capabilities are close to becoming mainstream. With the proliferation of prototyping and digital tools, everyone involved can now create, see, and test ideas in action. Amplified by methods like lean and agile that espouse rapidity over perfection, and promoting a culture of iteration and remix, innovation should now be ubiquitous.
Nevertheless, in the corporate world, innovation has not delivered the anticipated return on investment (ROI) or impact. Research and Development (R&D) spending, a traditional metric of innovation, increased in 2018 to a record high of $782 billion, according to PricewaterhouseCoopers study of Global Innovation 1,000 publicly held companies (Jaruzelski 2018). Despite significant investment, measurable ROI on innovation remains elusive. Illustrative of this issue is that the rate of failed innovation initiatives continues to climb, as recently witnessed at Target, Alaska Airlines, Coca-Cola, The New York Times, and Chubb (Kirsner 2017). In all these cases, perhaps the issue is the one proposed by Stanford researchers: breakthrough innovation is simply becoming increasingly challenging because in the hyperconnectivity of the digital era, the complexity of connections is overwhelming (Bloom et al. 2020). As Verganti writes, we are overcrowded with innovation in the digital era (Verganti 2016).
Based on these topical data, despite significant progress in the innovation industry, it seems that our current approaches to accelerating innovation are not as effective as envisioned. But why? To begin with, the technology advances of the digital age have brought an enormous voice to the world. With the proliferation of digital platforms, everyone can be part of the problem-solving exercise. The rise of social media has given us all both the right and the opportunity, not only to become aware but also to contribute and create. This enables innovation conversations to enjoy an entirely novel experience of tangibility, which in turn provokes critique as an innovation catalyst (Verganti 2016). Moreover, with the increasing use of AI, blockchain, and augmented/virtual reality (AR/VR), collaboration within and outside the organization raises even more complexities.
Digital's reach also unearths the plethora of opportunities for innovation â not only in the realm of products and services but also across entire value chains and ecosystems. Innovation platforms today act as digital crowdsourced suggestion boxes, encouraging everyone to contribute. Empowering people in this new scenario is the democratization of information. As the depth and breadth of knowledge expands, the notion of expertise in the digital era has dramatically evolved. Fueling the potential impact of knowledge on innovation is the digital dust from all our online interactions. It is not difficult to imagine the insights gleaned from our conversations, feedback, pivots, iterations, decisions, and convergence. Such visibility on innovation renders Rogers' diffusion of innovation (Rogers 1962, 2003) meaningless. Specifically, his notion of âearly adoptersâ no longer makes sense because the amount of time it takes to adopt innovation, like an app or business model, is significantly compressed.
As digitalization democratizes innovation itself, it is disrupting the traditional roles and responsibilities of subject matter experts. Historically, the R&D function was the place where organizations allocated resources for innovation. Here, innovation was led by innovation âexperts.â Their raison dâĂȘtre was to obsessively seek out new ways to solve old or new problems. The expertise of innovators and their love of their creations is the source of their resilience, essential for bringing new ideas into existing situations. However, in the digital era, where innovation has moved beyond the silos of professional innovators, we have a new breed of innovator. These nontrained innovators experience innovation as a nice to have. Their identity is grounded in other nonrelated domains. For these individuals, it is acceptable for innovation to be a pleasant Post-itÂź party or what Manzini refers to as âpost-it designâ rather than an existential exercise of self-actualization (Manzini 2015).
Not surprisingly, implementation and impact remain the major challenges for the innovation leader in the digital age (McKinsey 2015). As innovation leaders see their control wane with increased transparency and accountability, collaboration across a multitude of boundaries becomes even harder. Managing the ebb and flow of different ecosystems and experts is essential for innovation to happen. However, with digital, it is much more complex. By disrupting those traditional roles and introducing new actors, digital is also disrupting the institutional processes of decision-making. Whether it be decisions related to design or implementation, stakeholders with an interest in the outcome are never in short supply. This represents a profound change for organizations that seek innovation via the traditional methods such as stage-gate process. When the transition from an innovation group to the business unit still âneeds serious workâ (Kirsner 2017) we reveal the need to revisit our rigid organizational structures and processes. In our digitally networked world, the spread of partnerships, networks, and ecosystems demonstrate the need to develop new ways to organize the way we are innovating in ways that weren't a challenge in the predigital era. These organizational challenges for leaders expose the shelf life of many predigital innovation models, defined in painstaking process mapping workshops. Moreover, with the prevalence of cloud-based, white-label technologies, new business models and collaboration teams are now available on demand. The emergence of these new agile organizational models and flexible ways of working necessitates co-creating partnerships essential for internal networks and external ecosystems.
As new technologies rapidly reshape the structure and culture of organizations, the change management and leadership methods used to facilitate adoption are limited. In the face of constant change, these methods are unable to overcome the fact that most organizational units are still structured around protecting the products and services they provide. Managing the implications of change was another driver promoting ambidexterity â continuing core business activities while simultaneously sponsoring innovation to spark transformation (March 1991, O'Reilly 2016). Many corporations that have created separate units and programs, such as âacceleratorsâ and âincubatorsâ with the aim to protect and nurture innovators, still await the financial benefits. A 2019 report on the impact of business accelerators and incubators in the United Kingdom states: âMost types of support offered by accelerators and incubators are positively associated with at least one outcome measure, but few interventions can be positively linked with multiple outcomesâ (Bone et al. 2009). Given the lack of a clear ROI (Frimodig and Torkkeli 2013, Bauer, Obwegeser and Avdagic 2016), it would seem that organizational leaders are challenged to manage the inherently opposing objectives that ambidexterity espouses. It seems that the linear models of innovation and change that guided past practices no longer fit today's rapidly-evolving, complex, and fluid digital world. In this scenario, a leader's search for ways to engage people to make transformation happen in the digital era is existential.
1.3 Innovating with Design Thinking: A Consumer Product Story
To explore the challenge of innovating in the digital era, we will examine an innovation engagement led by one of the authors for a consumer product company. The divisional head of a global PCP manufacturer acknowledged that its brand was now losing its shine and resonance with customers. As part of a pioneering global consumer goods company known for its design thinking methodologies and tools, he was confident he could deliver transformation across the organization. He anticipated that a strategy of deploying trained design thinkers across the entire business and cultivating a community of innovation catalysts would define and open up a steady stream of disruptive innovation for the company.
Starting in 2008, he conducted a series of design thinking workshops involving several people across R&D and marketing, in conjunction with a global external consulting firm. The workshops explored the future of personal appliances around major trends such as light and flexible, emotional interactions, sensing, and diagnosis, and were structured along the following lines: persona development, ideation, prototyping, testing, pitching, and prioritization. Key outputs included detailed demographic personas of consumers of their product as well as a clear identification of immediate innovation opportunities in line with well-articulated long-term aspirations. From a compendium of 23 possible exploratory directions, over 100 ideas emerged. A follow-up workshop centered on an extrapolation of eight opportunities, of which three were prioritized as concepts that warranted further exploration with consumers.
However, despite the huge volume of ideas, the R&D manager of the PCP was still frustrated. âWe still keep coming up with the same old ideas. They're just incremental ideas and we're still missing that really big idea!â Workshop participants nevertheless responded positively by saying they were hopeful of the emergence of that really big idea at the next workshop. Unfortunately, either that big idea just never materialized, or, if it were indeed there, it was neither recognized nor implemented as such. Even more frustrating was this: ânow that we have a mass of ideas, we honestly do not know what to do with them.â
Four years later, and with no significant innovation emerging, the R&D manager took a different course and embarked on an entirely new journey. This time, he laid out two potential paths to take. The first path followed an outside-in direction which involved first meeting external experts, collecting insights, and then using these insights internally to decide what to do. The second path took an inside-out direction by first conducting an internal workshop where his team could propose new visions, and then checking with external experts whether these visions made sense. The R&D manager's preference was the approach espoused by design thinking.
We had better begin by meeting people from outside of our context. If we start by generating visions ourselves, I'm afraid we will keep coming up with the same old visions that have been circulating in our organization over the last few years.
It sounded like a reasonable approach to take, so his innovation team embarked on their journey by meeting external experts, most of whom they had never met before, to introduce fresh new stimuli. The underlying premise was twofold. First, the team needed to be brought back to a ânaĂŻve state of mind.â This meant completely letting go of any past insights and worldviews that had been circulating around the organization. Second, starting afresh would mean embracing any new insights introduced by the external experts. In reality, however, neither of these premises stood any chance of holding true. When the team proposed possible meanings post workshop, the same old ideas still flowed out â to the utter dismay of the executive team. It was as if meeting the external experts had produced nothing at all, and despite the team's exposure to fresh insights, nothing really had changed.
In reflecting on the PCP case, it's understandable to see the inherent limitations of design thinking. First, the program lacked any clear methodology to imbibe participants with any sense of personal meaning. Granted, the PCP had invested in developing the requisite skills for deploying the prescribed methodology and tools to enable participants to complete all the process steps. Equally, this most likely increased the overall ability to innovate. However, it did not provide the participants with any stimulus to delve deeper into those ideas that arose, and this most likely would have lowered any motivation to implement those ideas. With over 100 ideas generated, any use of empathy in the human-centered design process seems to have been successful within the context of the process itself. Creativity did act as the primary experience, thereby achieving overall high levels of participation, and this would seem to indicate equally high levels of engagement. However, we observed that in the absence of any articulation of our own cognitive worldview first, action simply did not and could not follow. Articulating one's initial frame is the primary basis for reframing. Without this, no new meaning or transformation is possible, whether cognitive or communal.
Second, the program lacked a clear methodology for engaging participants in the co-design of an object. Common in any design thinking is the pathology of the prototype, where objects are created without any emotional investment. Any representation of a product that is generated from standard templates, such as personas, empathy maps, and experience journeys, can only generate information that is captured at each step of the design process. However, it still fails to capture the hearts and minds of the participants, and this is what is missing. Any suspension of critique or deep reflection during group discussion can only lead to a sort of banal l...