What Is an Innovation Culture?

What happens if you ask a group of so-called innovation experts about their definition of innovation?

Nick Skillicorn did this and he gathered the answers in an interesting blog post that shows how vastly different even topic experts see the term “innovation”.

Here are some examples:

Steven Shapiro:

”Very simply put, innovation is about staying relevant. We are in a time of unprecedented change. As a result, what may have helped an organization be successful in the past could potentially be the cause of their failure in the future. Companies need to adapt and evolve to meet the ever changing needs of their constituents.”

Gijs van Wulfen:

“An innovation is a feasible relevant offering such as a product, service, process or experience with a viable business model that is perceived as new and is adopted by customers.”

Kevin McFarthing:

“The introduction of new products and services that add value to the organisation.”

Paul Hobcraft:

”The fundamental way the company brings constant value to their customers’ business or life and consequently their shareholders and stakeholders.”

Paul Sloane:

“Creativity is thinking of something new. Innovation is the implementation of something new.”

I was also asked to contribute to this experiment and this is my quote: “I try not to define ’innovation’ as we should tone down our use of the word and term.”

If you follow my work, this is no surprise. I believe we need to tone down the use of the word and the term, innovation, and we need to stop using the term “innovation culture” entirely.

On the latter, it is just impossible to create a strong innovation culture, when no one seems to be able to agree on the meaning of innovation. As Nick clearly revealed with his experiment, we have different views even among a group of experts, and I hope you trust me when I say that this problem of having different views and thus a lack of language and understanding around innovation is even worse in large companies and organizations. We need to build strong cultures, but don’t fall into the trap of calling this innovation culture.

However, I am also on a learning journey myself since I started my “crusade” against our usage – or misusage – of the terms. I had a session in New York recently, where the audience provided some compelling views that the term “innovation” is still quite popular among consumers. Thus, it still appears in sales and marketing efforts towards B-t-C target groups although I did get a fairly strong consensus that the work force in many places are fed up with the terms.

This makes me believe that we will see a similar sentiment among consumers in the coming years. They are also tiring on innovation. This raises a big question. What comes next?

Here, I believe that we need to look into an evolution of the terms. On a personal level, I am fond of the term “transformation”. As everything happens faster and faster, we see more and more changes to our business and corporate environments. Thus, we need to transform into something else. We don’t really know what this should be, but my guiding light here is that strong companies and organizations in the future do four things very well – and better than their competitors:

1. They listen better
2. They adapt to what they hear, see and learn
3. They are willing and able to experiment to get the best structures in place based on this
4. They execute better than anyone else.

Thoughts?

Reference: https://blog.hypeinnovation.com/the-definition-of-innovation

There are twin forces at work, feeding off each other. We are facing greater disruption and an increasing innovation pace. These are constantly combining, relentlessly adding new shape to our future. We are actually caught up in a very revolutionary period.

The days of simple product innovation are dwindling. It is through the fourth industrial revolution (also known as Industry 4.0), currently being undertaken, that technology, talent, and new innovation ecosystems are emerging – building greater complexity into our final innovation offerings. Intelligent automation and technology are fuelling this new industrial revolution. And this unprecedented, exponential pace of change is increasingly reliant on collaborative platforms to realize the result: more radical innovations.

Innovators struggle to manage in a new way

Organizations everywhere are facing mounting pressure to transform – to shift from product-centric business models to new models focused on creating and capturing different sources of new value. As a result, innovation is becoming more complex.

At the heart of this transformation is the fourth industrial revolution. Here, manufacturing is fast becoming the digital manufacturing enterprise (DME). The DME is designed to increase response rate and manage in more efficient, connected, and effective ways. There is this growing recognition that everything needs to be connected to bring a different perspective to any global value chain –one of being far more responsive and bringing manufacturing closer to the customer need.

How does your organization feel about our digitally connected world? We are all becoming more connected in the way we work, collaborate, and manage. Organizations are attempting to “fuse” different technologies to manage the existing physical world differently and are preparing themselves for the interplay between the physical and virtual world – one where this “connecting up” is promising to bring us. The ongoing investment in IT infrastructure is drawing in investments. It is changing the nature of where we will look for innovation outcomes in the future.

The fourth industrial revolution is one where we are gaining new knowledge and understanding. It is offering a very different potential for constructing new business models, products, services, and societal solutions. Many manufacturers are still in the early stages of this fourth revolution, but you have this sense of feeling that we are continuing to disrupt everything we know.

Welcome to the 4th industrial revolution

Wherever we turn in the manufacturing world, the technological revolution immerses us. The scale, scope, and complexity are things we’ve certainly never experienced. It is exposing us to exponential technologies. But what does that mean?

We seem caught up in such levels of velocity, scope, and systems impact – it is seemingly exponential, occurring at faster rates of change. Companies are radically overhauling entire systems of production, management, and governance on a constant basis of change. We have unprecedented processing power, storage capacity, and access to various avenues of knowledge. These are being combined with emerging technology in fields such as artificial intelligence, robotics, 3D printing, nanotechnology, biotechnology, material science, and quantum computing. It is creating fresh challenges and opportunities within innovation. Are we equipping ourselves to explore these?

Of course, we have faced industrial revolutions before. But, being caught up in one tends to leave us often conflicted. The first industrial revolution was based on water and steam to mechanize production. The second revolution was the use of electric power that led to the creation of mass production. Then we had the third revolution, where electronics and information technology started to deliver automated production. This fourth one builds on the third. It is the digital revolution where we are witnessing a fusion of technologies that seem to be blurring the lines between those past established borders to open up different meaning and business potential. It is truly exponential.

Confronted in multiple ways

We are looking increasingly to our engineers, designers, and scientists to unlock these new knowledge flows that bring us whole new areas of technological-based innovation. Product innovation is continually giving way to new concepts that have technology built into them. Our innovation has become increasingly complex, connected, and contextual.

Our industry value chains are being radically redesigned to accommodate “connected worlds” being more reliant on “everything” being digital. This is giving us new options for adapting quality to differently defined market needs. We are learning to respond digitally, in more dramatic and dynamic ways, to reflect pricing opportunity on increasingly opportunity marketing, so as we can appeal to wider sets of audiences or push our offerings out to explore different market potential.

As we continue to design manufacturing to be fully connected-up, we can adjust faster, scale differently, and deliver quantities to varying cycles of demand, closer to the need of the day and more appealing to the customers. Our innovation scope changes with these new dynamics.

Today, we see a different spectrum of choice. We can order personalized clothes online that reflect the latest fashion, seen only days before. Manufacturing and delivery are taking days and not months to be available in-store or delivered to your door. We can design our own shoes. We can build complete vacation packages, designing our travel to meet our specific needs and budget. More and more, we want tailored experiences or solutions that fit our design need, not just “items” sitting on the shelf.

Mass production has given way to tailored design. We can track our orders, and we can engage directly with those that can deliver to our specific needs. Our engagement and growing relationship with customer service, our needs, and the organization’s service and response are all changing. All provide innovation opportunity to exploit.

Manufacturing is in a massive transformation

Manufacturing has progressively formed around cyber-physical product systems (CPPS) that are merging our real and virtual worlds into a seamless one. Software is optimizing every process and task, whether performed by humans or machines. These are ongoing online networks of machines connected in similar ways to our social networks that are linked through technology and digital infrastructures. Everything has become “smart.”

The revolution underway is connecting all the parts: the “internet of things” (IoT), of data, of services, and of people. We are very much still in the middle of this revolution, but it is where innovation will greatly benefit as this connecting-up continues.

We are constantly seeing progress occurring all around us. For example, we’re now more dependent on cloud processing and data storage than ever before. We are recognizing the value of having digital twins to simulate our manufacturing environment. We are designing software solutions specifically to simulate different scenarios, mirroring our real time to test options and optimize different set-ups, to reflect demand.

Our manufacturing plants are becoming far more integrated – virtually integrated. We are building industry 4.0 open standards so increasingly we can connect across manufacturing ecosystems even more, so as to reduce disruption or provide greater flexibility. We are exploring data analytics for learning and predicting, and this is placing a greater emphasis on collaboration, experimentation, exploration, and coordination from all this connecting-up.

Consequences of the 4th industrial revolution

We must reflect on all these direct consequences of the fourth industrial revolution. Where technology has combined with the physical to raise our customer expectations even further, it has given us different product enhancements that fit with our lives, one where we can contribute and collaborate more.

The customer is increasingly at the epicenter of the economy. The products and services are enhanced through the digital capabilities that boost their value and worth. New materials are making our assets more durable and resilient, and data and analytics provide valuable feedback needed to build even better services and performance for the future. All this connecting and reacting is requiring new forms of collaboration, and we are seeing new types of organizations emerging. They are far more dependent on platforms and ecosystems. Innovation is the unlocking mechanism.

We are required to alter our understanding of Innovation due to this 4th revolution

The consequences of the fourth industrial revolution can be seen in the shifts of our emphasis taking place around innovation. We are focusing more of our innovation spend on technological innovation. We are constantly looking at the changes to our existing business models to reflect these changes, and we are integrating our innovation systems to explore entirely new business models.

We are connecting innovation more than ever. For example, choosing a blockchain technology requires significant collaboration and technology understanding. We are reliant on so much to generate “our” innovation solutions, far more than in the past.

The interactive World Economic Forum map is worth exploring. As you click on the links, you quickly recognize how interconnected our innovation has become. Not just in being able to produce accepted solutions but being having a ‘richer’ choice on where to focus our innovation efforts. Our innovation is becoming reliant on the fourth revolution and how it is all connecting us up, to provide our future growth through greater collaboration.

Reference: https://blog.hypeinnovation.com/innovation-fourth-industrial-revolution

To address these challenges, our deep tech fund team will focus on deficiencies at both the firm and ecosystem levels to help companies realize their market value in a more compressed period.

1. Improve coordination among government departments

Many countries have made it a priority to develop strong deep tech ecosystems. Canada is no exception. Numerous federal departments and agencies are keen to increase collaboration with deep tech firms. However, government players often have a hard time engaging with the private sector, while start-ups struggle to access public procurement programs.

BDC Capital’s Deep Tech Venture Fund team will try to act as a matchmaker between government and start-ups. Our goal is to connect departments and agencies with leading technology companies.

For example, quantum company Xanadu recently secured a $150,000 federal research project and a follow-on $1 million prototype project. We believe that this kind of industry-government collaboration can go a long way to helping commercialize these technologies in Canada.

2. Strengthen links to corporations

Large corporations are not investing enough in Canadian R&D and, as a result, our country is losing talent and important IP to other countries. While many large local and foreign corporations are eager to collaborate with Canadian deep tech firms, start-ups are often ill-equipped to explain their value proposition and generate interest. In general, the ecosystem is still young and needs to do more outreach to corporations.

Our deep tech team has a successful track record of building relationships with the senior management of leading corporations interested in supporting the development of Canadian firms. The fund will work to encourage corporate support for Canadian deep tech firms by becoming major customers and/or development partners for them.

3. Bolster technical and managerial support

The development of start-ups is often slowed by gaps in technical and managerial expertise. Because the ecosystem is so young, there is also little engagement and coordination between deep tech communities in Canada. Instead, deep tech clusters tend to coordinate more with foreign markets than with each other.

Our team we will provide technical expertise, insights on specific segments and facilitate market entry to portfolio companies. We will also provide them with coaching, networking opportunities, market insights and access to potential customers. At the ecosystem level, we have many partnerships that position us well to cultivate a Canadian deep tech community, bringing together a diverse set of participants from different industries for mutual benefit.

4. Compress the runway to commercialization

Deep tech firms typically have a longer timeline to maturity than other VC-backed firms. Besides their novel technologies, applications often have a hardware component, which requires a longer development period. Additionally, a lack of funding for Canadian deep tech companies has tended to slow their development.

We recognize the longer development timelines for these industries and that’s why our fund’s life is 12 years in contrast to the usual 10-year life of a general VC fund. We will be a patient partner for firms, investing enough capital in successive funding rounds to allow them to scale up and develop their products. Nevertheless, we believe that with better funding, stronger links to government and private sector actors and better access to technical and managerial support, start-ups in this domain can substantially accelerate their timeline to commercialization.

On the path to a vibrant deep tech sector

As BDC Capital, we are confident that Canada has everything it needs to build a vibrant, globally competitive deep tech sector. However, much work needs to be done to ensure that start-ups have the support they need to turn exciting discoveries into transformative products and services.

Our new Deep Tech Venture Fund knows bringing Canadian innovations to global markets will take more than just dollars. That’s why we will play a leading role in nurturing partnerships between government department and agencies, private sector players and start-ups to grow international champions for the benefit of Canadians for decades to come.

Results-only innovation is an exploration of what is viable and pragmatic. This can help produce additional value for businesses and end users.

Every business wants to be innovative, but not all companies understand what innovation is—and isn’t. Large companies with well-funded research and development programs often point to those as evidence of their innovation capability. In reality, their teams are usually engaged in work that’s more akin to invention than innovation.

There’s a difference between invention and innovation. The invention process involves creating something entirely new, whereas innovation is the process of recombining, repositioning, or reimagining the fundamental elements of an existing concept to produce new value—a remix. The size of the team engaged in this process and the tools and techniques they use are irrelevant. What matters is creating demonstrable, quantifiable value rather than focusing on upfront research and development or generalized “experimentation.” The focus should be on scalable, industrialized services.

Firms that consistently engage in this kind of pragmatic innovation, or “results-only innovation,” can disrupt industries and change consumer behavior. Others can expand product lines or gain operational efficiencies. Not every attempt is successful, but the chances of success are inherently better when firms employ results-only innovation.

The Art of the Pragmatic

While innovation is often viewed as an exploration of what’s possible, results-only innovation is an exploration of what is viable and pragmatic. It requires practitioners to continually ask why things are the way they are. For instance, why choose a particular design? Why prioritize user-centricity? Why focus on a certain development?

Rather than look for ways to replace a product or process, practitioners determine what value that product or process delivers to end-users and to the business. Then, they seek ways to amplify it.

One modest alteration to the design and development process can introduce a broader understanding of potential value. Firms with innovative corporate cultures are always improving. They understand that creating new value doesn’t necessarily mean overhauling what already exists. Rather, they invest in results-only innovation by pinpointing what needs to change.

Many firms focus on the minimum viable product or first release product to the detriment of moving toward a scalable solution. Too often, considerations regarding the creation or augmentation of the business built around the product are given short shrift. For some, this might be the tech infrastructure (e.g., DevSecOps or CloudOps), but in many cases, it’s a series of added factors (e.g., the tech infrastructure plus team capabilities, go-to-market initiatives, organizational change management, and executive buy-in).

How Data Makes a Difference

The best way to pursue pragmatic innovation is to introduce a new, equally-weighted facet: data. When deciding whether to pursue innovation, practitioners might ask a multitude of questions related to this important business asset. For example, what data becomes available through a modification? How can it be mined? Can it inform other product or business decisions? Can it be sold? Should it be sold? Could it power artificial intelligence models or advanced analytics?

Smart firms will also ask whether the data generated through the process of innovation can contribute to further innovation in the future. Innovative companies are far more likely than competitors to invest in data-intensive technologies and projects, according to a recent Harvard Business Review report.

Innovation ROI is often viewed as something separate from the pursuit itself. However, practitioners of results-only innovation take the opposite viewpoint. By weighing the prospective business value, user value, and data value that could be derived from their work, teams gain a clear understanding of success and can focus their efforts and investments accordingly.

Investing in Results-Only Innovation

The Harvard Business Review report revealed that 42% of organizations planned to increase their innovation budgets in 2021. Those that adopt the principles of results-only innovation will likely see significant returns in terms of greater efficiency, more revenue, or increased customer satisfaction, among others. Companies that want to be among them should keep these three tips in mind:

1. Don’t be afraid to challenge central expectations

A recent McKinsey & Co. survey found that many global executives are halting innovation to focus on other priorities in the wake of the COVID-19 pandemic. Unfortunately, doubling down on what has worked in the past is not a path to stability or growth. In fact, it can make organizations more vulnerable as time goes on. Firms should continually question their expectations so they can adjust them when necessary—and before it’s too late. Impact requires commitment even when things don’t go according to plan.

2. Strive to reject orthodoxy that exists for its own sake

Just as firms should question their expectations, they should also feel comfortable challenging the assumptions they’ve relied on to get where they are. Even if those assumptions were correct in the past, they might not be in the future. Companies tend to have good reasons for doing things a certain way, but that shouldn’t stop them from looking for better alternatives. A culture of innovation and creativity is also one of perpetual discontent with the status quo. Innovators should welcome debate, as the ideas pursued should hold up to the scrutiny of multiple viewpoints and the rigor of multiple challenges. Any decisions made should be supported by facts, evidence, and data.

3. Understand the need that underlies a process or workflow

Don’t approach reimagining as merely an exercise in iterative improvement. Ask why a process exists in the first place, and strive to quantify the business, data, or user value that it delivers. This is especially useful when designing customer experiences. About 58% of innovation leaders believe that customers will pay a premium for better experiences, according to the same Harvard Business Review report. By starting the innovation process with a clear understanding of customers’ needs and desires, leaders can augment the value they deliver and design new and exciting experiences that customers are ready to purchase.

Although firms should always aim to create new value, the innovation process won’t always result in success. But a failed experiment is not a failure of the entire effort. It represents a tested hypothesis — and those don’t always come back with the expected results. Companies should aim for measurable results with quantifiable value. If they fall short, then they strengthened the workflows and thought processes necessary for future success.

Source: https://innovationmanagement.se/2021/11/18/create-better-business-outcomes-with-results-only-innovation/

Established firms’ strategies remain characterized by the inability to master—some will say even comprehend—the economics of choosing. It is particularly surfacing unresolved relationships between [1] technical-technological, [2] economic and [3] social combinations taking place within established firms e.g. manufactured product.

Hayek (1937) already explained that “Since equilibrium is a relationship between actions, and since the actions of one person [here the board of directors] must necessarily take place successively in time, the passage of time is impossible to exclude from a meaningful equilibrium theory.” Lakatos (1970) brought a contextualization by saying that since we replace a theory in the light of an alternative, we should consider not isolated theories but a sequence of them in a “scientific research program.” Decisively, Senge (1990) declared that system thinking is a philosophical alternative to pervasive “reductionisms” in Western culture including the pursuit of simple answer to complex issues. Recently, Noteboom (2010) circumscribe a description as “hard core explanatory principles, surrounded by a protected belt of subsidiary assumptions.”

Reconciled Candidate Innovation Methods

1. On the technical-technological front, Clayton Christensen (1997) demonstrated that “successful, outstanding companies can do everything ‘right’ and yet still lose their market leadership—or even fail—as new, unexpected competitors rise and take over the market.” In this vein, Clayton explained that the technical trajectory of the firm was becoming obsolete because a new one was interfering, overnight, coming from “the low end of the market,” in the form of new economic patterns, leaving the owners of the market at bay.

2. On the organizational front, with entry thinking initiated by Penrose (1959), David Teece, (1997, 2017) argues that production function is quite sterile and demonstrated that intellectual impasse could be opted out while applying the capabilities principles. In short, tangible and intangible resources, and more, upscale themselves into capabilities. As such, ordinary capabilities allow “to do things right” (efficiency) and dynamic capabilities “to do the right thing” (innovation).

3. Both theories enjoy an overwhelming consensus and admiration, although with an enduring quality of being “abstract” and “with limited utility.” In fact, practitioners agree both, but do not mark out quantitatively any. To my assumption, both principles are belonging to the same mechanism and therefore are both part of the solution. Accordingly, it must be reconciled.

Disruptive Innovation Capability = Technical Path Dependency

4. Regarding the disruption theory, we are now accustomed that “lucky entrepreneur” can take over the market from the established firm. Technically speaking, it means that we can find a continuum, but economically there is a shift in ownership. The process turns in “new hands of competencies,” organized “against” the established firm (Christensen, 1998). As a matter of fact, innovation scorecards of established firms eventually reveal a “hard core.” Academics call it path dependency, which is singled out in the disruption phase. Schumpeter (1934) already told us “that the economic perfect and the technological perfect need not, yet very often do diverge, not only because of ignorance and indolence but because methods which are technologically inferior […]. At this point the economic element is sharply contrasted with the technological.” Critically, practitioners need a new repertoire of action that isolates the path dependency i.e. disruptive capability.

5. Regarding the capabilities theory, researchers like Ambrosini and Bowman (2008) support that “while many fields address change-related issues (eg. organization learning, cognition, innovation …) none, expect the dynamic capability perspective, specifically focuses on how firm can change their valuable resources over time and do so persistently.” Yet, Winter and Nelson (2002) alerted us that, amid “an impressionistic level of competence puzzle,” a repetitive enforcement of capabilities seems to hold a secret, an opaque meaning that is trapped in the bizarre. “Real actors simply do not have the vast computational and cognitive powers that are imputed to them by optimization-based theories. Decisions defy basic principles of rationality and sometimes border on the bizarre.” Disruptive capability “at the heart of innovation” aims to unlock the philosophical bizarre.

6. Unfortunately so far, economic reality does not necessarily carry out the methods to their logical conclusion and with technological completeness, but subordinates the execution to economic points of view (Schumpeter, 1934). A possible transcript could be that zero level, ordinary and dynamic capabilities are economic in nature and disruptive capability is technical. To prevent falling into the hands of lucky entrepreneur, practitioners need to overcome this bizarre sequence by isolating a firm’s disruptive capability that will be instrumental to sense, seize and reconfigure.

Systemic Economic Phenomenon Unfold During Consecutive Materialisation of Four Types of Capabilities

7. Upon Nelson and Winter, solution paths may include a steady state or a set of them. But the commitment to the […] behavioral assumptions does not depend on the achievement of steady state. [On the contrary], modelers typically sought to analyze behavior and phenomena under roughly out of the equilibrium. Edmund Hesser (1859-1938) is speaking about “pure consciousness” which can be reached through “phenomenal reduction;” a method whereby all factual knowledge and reasoned assumptions about a phenomenon are set aside so that pure intuition of its essence may be analysed.

8. This is where disruptive innovation and its dilemma settle into its firm phenomena. All four does magnify an organic and systemic economic phenomenon that is composed of zero level capability [Nelson and Winter, 2002], ordinary and dynamic capability [Teece, 1997-2020] and disruptive capability [Chenevier, 2021]. Dilemma becomes phenomena paradigm; the later bearing one passage of time ref. ad infinitum (Collis, 1994).

9. This mental model, definitively optimistic, intends to comprehend the end of an economic phenomenon (yours as a board member?) as blackboard time to reconfigure the technical orchestration, on the premises of “the last thing.”

Source: https://innovationmanagement.se/2021/12/07/innovator-dilemma-vs-innovator-phenomena-the-theory-of-the-firms-phenomena/

Innovation transformation requires multi-faceted talents who can combine a profound understanding of big-size organizations, with a rebel spirit and a drive for change.

We summarized 10 peculiar traits of these talents. 

1. REBEL

To make a corporation change, you need to be a rebel by nature. This role requires you to challenge the WoW of a company that is just not as innovative/rebel as you are. You’ll have to provoke and instigate change in people, for the better.

2. EMPATHETIC

When you’re transforming the culture of a 400,000-employee organization, you’re impacting on the life of 400,000 individuals. Great empathy is required to understand the point of view of multiple people, so that you can design a change program that takes everyone into consideration and impacts people’s life positively.

3. INSPIRER/STORYTELLER/MOTIVATOR

Most people see change as a scary, perilous path. A great Change Manager has the innate capability to inspire and motivate, by showing how the new ending point would impact positively the organization, and by building a strong relationship with the people involved.

4. PROJECT-ORIENTED

Many Change Managers have to follow up on dozens of innovation projects. Project management experience is certainly required to keep the pace of multiple initiatives running in parallel and to deal with dependencies.

5. BUT ALSO… BIG-PICTURE ORIENTED

Project management skills are just as important as the ability to look at all the projects from a global perspective. A multi-layer viewpoint is required, to have a good view of both the project and the organizational level.

6. EXPERIENCED IN INTERNAL POLITICS

A corporate is packed with internal politics. Innovation projects are the perfect fuel to spark internal fires. A Change Manager will need to spend a lot of time on internal communication.

7. RESILIENT

It takes a certain energy to transform the culture of a company. Great transformation leaders get their fuel from extreme challenges and are persistent to make change happen, even if it takes a while before they see concrete results.

8. EXPERIENCED IN DT AND LS

Solid knowledge of Design Thinking and Lean Startup methodologies is a fundamental requirement for anyone who is building new capabilities at an organizational level. This knowledge should combine a theoretical approach with hands-on experience, thus assuring a perfect overview of both pros and possible challenges of these techniques.

9. ADAPTIVE TO EXCEPTIONS AND FAILURE

An Innovation Transformation program deals with a monstrous number of uncertainties. A great Change Manager can find quick answers when the plan needs to change and can find a learning experience every time failure occurs. In other words, keep the transformation goal in sight, while being open to change how to get there.

10. STRATEGIC SIGHTED

Innovation projects fall by definition out of your companies’ comfort zone. Can you inspire others with a clear vision of where else the company needs to look?

Reference: https://www.boardofinnovation.com/blog/innovation-transformation-lead-change-manager/

Contrary to common belief, open innovation is not only about collaborations between big companies and startups. It’s about leveraging partnerships based on when in the funnel time-line they come into place.

It seems that nearly every economic conversation these days revolves around inflation. Each question seems to lead to another. Is it transitory? Will it get worse? If so, when? And for how long? Which of the many factors — including soaring post-Covid-19 demand, supply chain shortages, fiscal and monetary stimulus, energy politics, or all the many changes in how we live, work and play post-pandemic — should matter most as we try to build a picture of what’s happening?

In all the debate, one point gets very little discussion: the role of technology as arguably the most important variable in what might happen to inflation over the coming several years. For every inflationary factor, from labour shortages to transportation bottlenecks, fuel costs, or even longer-term pressures like an ageing population, there is a looming technological change that could shift the calculus around pricing in ways that are hard to predict.

Consider the clean energy transition. Already, demand for electric vehicles is pushing up the price of commodities such as copper, lithium, nickel, and cobalt. Green vehicles and power plants are much more metal-intensive than the technologies they are replacing. As more companies and nations move towards a carbon tax and seek to limit fossil fuel production, energy prices may rise further in the short term.

But the wider timeline is, of course, what matters. While a fast transition to a cleaner world will create some inflationary pressure, it will dramatically cut the cost of the climate-related disasters in the longer term. What’s more, technological innovation itself eventually lowers costs. Morgan Stanley data show that short-term spikes aside, commodity prices have trended down for 200 years. That’s because every time one energy source became too expensive, a new one was invented to take its place. We might be heading into a cold and expensive winter. But given the plummeting costs of renewable technologies such as solar panels and wind farms (and increasing public and private investment in them) there is good reason to hope that, with time, the final destination could be a much better and cheaper place — one that would put a dent in some of the 1970s stagflation analogies.

What about the inflationary aspects of supply chain delays? Some logistics experts believe port backups will last for years. And yet, already, we’re seeing the largest and richest companies (Amazon, Walmart and Costco, for example) adjusting to the problem with innovations of their own.

Those innovations will include more vertical integration (for example, owning rather than renting some of their own shipping containers to allow more control) but also using artificial intelligence systems to better track deliveries. Autonomous vehicles, both trucks and ships, are getting a new boost of interest. The first autonomous container vessel will be tested in Norway by the end of the year. If such systems smooth traffic, some supply chain-related delays and price pressures would begin to abate.

As the internet of things becomes ubiquitous, more companies will use new technologies to improve efficiency. As the chief executive of Ark Investment Management, Cathie Wood, noted in a recent interview, such innovations, which include autonomous mobility, blockchain, gene editing, adaptive robots and neural networks, are more likely to usher in a period of longer-term deflation than inflation, given the depth and breadth of their impact across all areas of business.

Certainly, they will disrupt labour markets in ways we can’t yet envision. Technology could, for example, play an important role in offsetting the inflationary pressures of ageing baby boomers, who will require more care at exactly the time the labour force is shrinking, by increasing the productivity of existing healthcare workers and the system. China, which has poured $1.5bn into using big data in healthcare over the past decade (and many billions more into artificial intelligence) is likely to be the epicentre of AI-driven diagnostics and healthcare innovation.

The politics of using big data in sensitive areas such as healthcare and finance will, of course, vary from country to country, as regulators grapple with the social implications of such cutting-edge technologies. Those differences in national policies could themselves be inflationary if they contribute to cross-border frictions in global business and when it comes to the movement of people, goods and capital.

In a multipolar world, there will inevitably be more delays, shortages and supply and demand mismatches in the short term. And yet, the fact that the global economy has become somewhat more fragmented over the past couple of years is also an opportunity for technology-driven innovation that could eventually bring prices down. Think about vertical farms that grow produce minutes from where people eat it, telehealth and virtual education platforms that eliminate travel costs, and 3D manufacturing that cuts through complex and far-flung supply chains.

These are just a handful of the many new technologies that are currently booming. The change such innovation could bring is arguably the only major disinflationary trend right now. But it may prove to be the most powerful.

Reference: https://www.ft.com/content/57bccc8f-e75d-4be6-a92e-96470aa7e7de