Tag Archives: ecosystems

We Change the World with Ecosystems Not Inventions

GUEST POST from Greg Satell

Imagine yourself as the CEO of a Dow component company in 1919. You are fully aware of the technological forces that would shape much of the 20th century, electricity and internal combustion. You may have even be an early adopter of these technologies. Still, everything seems like business as usual.

What you don’t see, however, is that these inventions are merely the start. Secondary technologies, such as home appliances, radio, highways and shopping malls, would reshape the economy in ways that no one could have predicted. Your company has a roughly 50% chance of remaining on the Dow a decade later.

We are at a similar point today. New inventions, such as quantum computing, neuromorphic chips, synthetic biology and advancements in materials science already exist. It is not those inventions, however, but the ecosystems they spawn that will shape the decades to come. We’re all going to have to learn how to compete in a new era of innovation.

A 50-Year Boom In Productivity

By 1919, electricity was already a 40-year old technology. In 1882, just three years after he had almost literally shocked the world with his revolutionary electric light bulb, Thomas Edison opened his Pearl Street Station, the first commercial electrical distribution plant in the United States. By 1884 it was already servicing over 500 homes.

Yet although electricity and electric lighting were already widespread in 1919, they didn’t have a measurable effect on productivity and a paper by the economist Paul David helps explain why. It took time for manufacturers to adapt their factories to electricity and learn to design workflow to leverage the flexibility that the new technology offered. It was the improved workflow, more than the technology itself, that drove productivity forward.

Automobiles saw a similar evolution. It took time for infrastructure, such as roads and gas stations, to be built. Improved logistics reshaped supply chains and factories moved from cities in the north — close to customers — to small towns in the south, where labor and land were cheaper. That improved the economics of manufacturing further.

Yet all of that was just prelude to the massive changes that would come. Electricity spawned secondary innovations, such as household appliances and radios. Improved logistics reshaped the retail industry, shifting it from corner stores to supermarkets and shopping malls. As Robert Gordon explains in The Rise and Fall of American Growth, these changes resulted in a 50-year boom in productivity between 1920 and 1970.

The Digital Revolution

In 1984, Steve Jobs and Apple launched the Macintosh, which heralded a new era of computing. Based on technology developed for the Xerox Alto in the early 1970s, with a bitmapped screen, a graphical user interface and a mouse, it made computing far more accessible to regular consumers.

Before long, personal computers were everywhere. Kids would use them to write term papers and play video games. Lotus 1-2-3 spreadsheet software became a staple for small businesses and entrepreneurs. Desktop publishing helped democratize the flow of information. The computer age had begun in earnest.

Yet much like electricity and internal combustion earlier in the century, the effect on productivity was negligible, causing the Nobel Prize winning economist Robert Solow to quip, “You can see the computer age everywhere but in the productivity statistics.” In fact, it wouldn’t be till the late 90s that we saw a measurable impact from computers.

Once again, it wasn’t any particular invention that made the difference, but an ecosystem that built up over years. The Internet paved the way for open-source software. Hordes of application developers created industry specific tools to automate almost every imaginable business process. Computers converged with phones to create the mobile era.

The 30 Years Rule

Look back at the two major eras of technology in the 20th century and a consistent theme begins to emerge. An initial discovery of a new phenomenon, such as electricity and internal combustion, is eventually used to create a new invention, like the light bulb or the automobile. This creates some excitement, and builds the fortunes of a few entrepreneurs, but has little impact on society as a whole.

Yet slowly, an ecosystem begins to emerge. Roads and gas stations are built. Household appliances and personal computers are invented. Secondary inventions, such as shopping malls, home appliances, the Internet and application software help create new business models. Those business models create new value and drive productivity.

The truth is that innovation is never a single event, but a process of discovery, engineering and transformation. As a general rule of thumb, it takes about 30 years for all of this to take place, because thousands, if not millions of people need to change their behavior, coordinate their activity and start new businesses.

That’s why the future will always surprise us. It is not any one great event that tips the scales, but some hardly noticeable connection that completes the network. Network scientists call this type of thing an ‘instantaneous phase transition’ and there’s really no way to predict exactly when it will happen, but if you learn to look for telltale signs, you can see one coming.

A New Era Of Innovation

Today, we appear to be in a very similar situation to what those executives faced in 1919. We have decoded the human genome. Artificial intelligence has become a reality that everyone, for the most part, accepts. New computing architectures, such as quantum computers and neuromorphic chips, are in late stages of development by a variety of companies.

Yet once again, the impact has been negligible and it’s not hard to see why. While these inventions, in some cases at least, are relatively mature, they have yet to create the ecosystems that can drive a true transformation. Today, however, we can clearly see those ecosystems being created.

In fact, in artificial intelligence we can already see a fairly well developed ecosystem emerging already. In synthetic biology and genomics we can begin to see one as well, although it is still nascent. IBM has created a Q Network of major companies, research labs and startups to support quantum computing.

Here’s what’s important to know: We can’t predict exactly when the system will tip, but it’s a good bet it will happen in the next decade. It is also likely that the impact will be equal to or greater than the 50 year boom that began in the 1920s. Finally, it won’t be driven by any particular invention, but by ecosystems. You need to start figuring out how you will connect.

— Article courtesy of the Digital Tonto blog and an earlier version appeared on Inc.com
— Image credit: Pixabay

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Competing Successfully in an Ecosystem World

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Competing Successfully in an Ecosystem World

GUEST POST from Greg Satell

In 1980, a young Harvard Business School professor named Michael Porter published Competitive Strategy, which drove thinking on the subject for the next 30 years. In essence, he argued that you build sustainable competitive advantage by maximizing bargaining power throughout a value chain.

Yet more recently, that kind of single firm level analysis has been called into question and leaders have learned to look more broadly at ecosystems. In fact, a recent report by Accenture Strategy found that because business models are being constantly disrupted, ecosystems have become a “cornerstone” of future growth.”

While value chains are strictly defined by “primary activities” such as “inbound logistics” and “support activities” like technology, ecosystems have mostly been a nebulous term. Clearly that’s not good enough. If we are going to compete in an ecosystem-driven world, we need to understand how they function and how we can leverage them to drive a business forward.

What Is An Ecosystem?

Ecosystem is a term that gets thrown around quite a bit, but people never seem to define what one is. All too often, it alludes to some indescribable ether that surrounds an enterprise. When you can’t define how an action would impact a customer or partner, you simply invoke “the ecosystem” and that’s supposed to make it all make sense.

Yet it’s important that we define terms that have meaning, because if we don’t they just become a catchall for things that we can’t describe. That’s a problem. As Wittgenstein pointed out long ago, if we can’t define something we don’t really understand it and if we don’t understand something we can’t hope to manage it very well.

Ecosystems are best understood as networks of networks and that tells us a lot. In fact, there is a whole science of networks to guide us. What’s most important about networks is that they are driven by links not nodes, so the most important network activity is connection. Networks are dynamic, always evolving, not static.

That’s where focusing on value chains runs into problems. Maximizing bargaining power within a value chain almost compels us to see things as a static, “winner take all” type of challenge in which you play one partner off against another. When you see things as an ecosystem, however, there is clear value in investing in connections and building up the nodes around you to improve your position.

It Is Ecosystems, Not Inventions That Drive The Future

We tend to think of history as a series of “great men” driving events. So electricity conjures up visions of Edison and his light bulb and automobiles remind us of Henry Ford creating the Model T. Yet the truth is that the impact from those inventions didn’t come till decades after those men brought those inventions to life.

In both cases, it was secondary inventions that drove the impact. Electricity allowed businesses to redesign factories to optimize workflow and drive productivity. Home appliances replaced backbreaking work and freed up energy for other tasks. Roads and gas stations revolutionized product distribution and led to the modern retail industry.

Computers followed a similar path. Digital technology had been around for decades when IBM launched the PC in 1981, yet it wouldn’t be till the late 90s that we first started to see an impact on productivity. The truth is that computers don’t do much by themselves. Applications need to be designed and people need to figure out how to put them to good use.

Notice that it’s impossible to point to any one thing that tipped the scale, because what drove impact was an ecosystem of connections between partners, suppliers and customers who needed to learn how to collaborate effectively. That has far less to do with technology than it does with forging meaningful human relationships and it takes time.

Power Today Lies In The Center Of Ecosystems, Rather Than At The Top Of Hierarchies

Traditionally we’ve seen the world as driven by hierarchies. Kings and queens ruled the world through aristocracies that carried out their orders. Corporate CEO’s outlined strategies that underlings would have to execute. Discipline was enforced through a system of punishments and rewards.

In a hierarchy driven world, you progress by climbing your way to the top. So you do your best to drive the performance of those under you to impress those above you. Success is determined by how high you rise. You learn to put great emphasis on signals that you have made it, such as the title on your business card and the size and location of your office.

In an ecosystem driven world, however, power does not lie at the top of hierarchies, but emanates from the center of networks. So an office on the executive floor may, in fact, diminish your ability to shape events if it leads to disconnection. At the same time, being seen as approachable, rather than high status, may enhance your power.

Here’s where Porter’s ideas about value chains can get you into trouble. If you are constantly trying to maximize your bargaining power, you are likely to weaken connections and find yourself at the periphery, rather than at the center, of networks. In an ecosystem driven world, displaying your power can often serve to undermine it.

You Move To The Center By Connecting Out

As I explain in my book Cascades, the best way move to the center of networks is by connecting out. At first, that may seem counterintuitive because it seems simpler to identify a central hub and connect in. Yet those nodes, by definition, already have a lot of links and your connection is less likely to be meaningful.

Once you understand that networks are dynamic and evolving, it becomes clear that a better strategy is to identify emergent nodes and connect to them early on. As the network grows, the center shifts and you are more likely to improve your position. In an ecosystem world, the best strategy is to widen and deepen connections throughout the network.

AnnaLee Saxenian gives an apt description of how this works in Regional Advantage, where she tells the story of how Boston’s “Technology Highway” lost relevance and Silicon Valley moved to the center of the technology universe. The Boston-based companies saw things in terms of value chains and focused on vertical integration to maximize their bargaining power. The Silicon Valley upstarts, on the other hand, saw an ecosystem and thrived on connection.

Today, of course, technology has exponentially increased our ability to make connections. However, what is crucial to understand is that relationships are essentially a very human activity. You don’t build them through gadgets or algorithms, but my investing your most valuable resource — yourself.

— Article courtesy of the Digital Tonto blog and an earlier version appeared on Inc.com
— Image credit: Pixabay

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What Pundits Always Get Wrong About the Future

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What Pundits Always Get Wrong About the Future

GUEST POST from Greg Satell

Peter Thiel likes to point out that we wanted flying cars, but got 140 characters instead. He’s only partly right. For decades futuristic visions showed everyday families zipping around in flying cars and it’s true that even today we’re still stuck on the ground. Yet that’s not because we’re unable to build one. In fact the first was invented in 1934.

The problem is not so much with engineering, but economics, safety and convenience. We could build a flying car if we wanted to, but to make one that can compete with regular cars is another matter entirely. Besides, in many ways, 140 characters are better than a flying car. Cars only let us travel around town, the Internet helps us span the globe.

That has created far more value than a flying car ever could. We often fail to predict the future accurately because we don’t account for our capacity to surprise ourselves, to see new possibilities and take new directions. We interact with each other, collaborate and change our priorities. The future that we predict is never as exciting as the one we eventually create.

1. The Future Will Not Look Like The Past

We tend to predict the future by extrapolating from the present. So if we invent a car and then an airplane, it only seems natural that we can combine the two. If family has a car, then having one that flies can seem like a logical next step. We don’t look at a car and dream up, say, a computer. So in 1934, we dreamed of flying cars, but not computers.

It’s not just optimists that fall prey to this fundamental error, but pessimists too. In Homo Deus, author and historian Yuval Noah Harari points to several studies that show that human jobs are being replaced by machines. He then paints a dystopian picture. “Humans might become militarily and economically useless,” he writes. Yeesh!

Yet the picture is not as dark as it may seem. Consider the retail apocalypse. Over the past few years, we’ve seen an unprecedented number of retail store closings. Those jobs are gone and they’re not coming back. You can imagine thousands of retail employees sitting at home, wondering how to pay their bills, just as Harari predicts.

Yet economist Michael Mandel argues that the data tell a very different story. First, he shows that the jobs gained from e-commerce far outstrip those lost from traditional retail. Second, he points out that the total e-commerce sector, including lower-wage fulfillment centers, has an average wage of $21.13 per hour, which is 27 percent higher than the $16.65 that the average worker in traditional retail earns.

So not only are more people working, they are taking home more money too. Not only is the retail apocalypse not a tragedy, it’s somewhat of a blessing.

2. The Next Big Thing Always Starts Out Looking Like Nothing At All

Every technology eventually hits theoretical limits. Buy a computer today and you’ll find that the technical specifications are much like they were five years ago. When a new generation of iPhones comes out these days, reviewers tout the camera rather than the processor speed. The truth is that Moore’s law is effectively over.

That seems tragic, because our ability to exponentially increase the number of transistors that we can squeeze onto a silicon wafer has driven technological advancement over the past few decades. Every 18 months or so, a new generation of chips has come out and opened up new possibilities that entrepreneurs have turned into exciting new businesses.

What will we do now?

Yet there’s no real need to worry. There is no 11th commandment that says, “Thou shalt compute with ones and zeros” and the end of Moore’s law will give way to newer, more powerful technologies, like quantum and neuromorphic computing. These are still in their nascent stage and may not have an impact for at least five to ten years, but will likely power the future for decades to come.

The truth is that the next big thing always starts out looking like nothing at all. Einstein never thought that his work would have a practical impact during his lifetime. When Alexander Fleming first discovered penicillin, nobody noticed. In much the same way, the future is not digital. So what? It will be even better!

3. It’s Ecosystems, Not Inventions, That Drive The Future

When the first automobiles came to market, they were called “horseless carriages” because that’s what everyone knew and was familiar with. So it seemed logical that people would use them much like they used horses, to take the occasional trip into town and to work in the fields. Yet it didn’t turn out that way, because driving a car is nothing like riding a horse.

So first people started taking “Sunday drives” to relax and see family and friends, something that would be too tiring to do regularly on a horse. Gas stations and paved roads changed how products were distributed and factories moved from cities in the north, close to customers, to small towns in the south, where land and labor were cheaper.

As the ability to travel increased, people started moving out of cities and into suburbs. When consumers could easily load a week’s worth of groceries into their cars, corner stores gave way to supermarkets and, eventually, shopping malls. The automobile changed a lot more than simply how we got from place to place. It changed our way of life in ways that were impossible to predict.

Look at other significant technologies, such as electricity and computers, and you find a similar story. It’s ecosystems, rather than inventions, that drive the future.

4. We Can Only Validate Patterns Going Forward

G. H. Hardy once wrote that, “a mathematician, like a painter or poet, is a maker of patterns. If his patterns are more permanent than theirs, it is because they are made with ideas.” Futurists often work the same way, identifying patterns in the past and present, then extrapolating them into the future. Yet there is a substantive difference between patterns that we consider to be preordained and those that are to be discovered.

Think about Steve Jobs and Apple for a minute and you will probably recognize the pattern and assume I misspelled the name of his iconic company by forgetting to include the “e” at the end. But I could have just have easily been about to describe an “Applet” he designed for the iPhone or some connection between Jobs and Appleton WI, a small town outside Green Bay.

The point is that we can only validate patterns going forward, never backward. That, in essence, is what Steve Blank means when he says that business plans rarely survive first contact with customers and why his ideas about lean startups are changing the world. We need to be careful about the patterns we think we see. Some are meaningful. Others are not.

The problem with patterns is that future is something we create, not some preordained plan that we are beholden to. The things we create often become inflection points and change our course. That may frustrate the futurists, but it’s what makes life exciting for the rest of us.

— Article courtesy of the Digital Tonto blog and previously appeared on Inc.com
— Image credit: Pixabay

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39 Digital Transformation Hacks

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39 Digital Transformation Hacks

GUEST POST from Stefan Lindegaard

Here you get 39 hacks that can help yourself and your organization in its digital transformation efforts. The hacks are divided into these six main categories:

Corporate Mindset
Personal Leadership / Executives
People – Mindset, Skills and Toolbox
Organizational Structures and Processes
Networking and Ecosystems
Tools

This is work in progress and Grimur Fjeldsted, my co-author and partner at Transform XO and myself are very open to your feedback and input. Get in touch!

Here we go with the hacks.

1. Corporate Mindset

Strategy for a digital world: Your company needs new approaches to strategy that must be rooted in the belief that there is no such thing as a digital strategy; just strategy in a digital world. Besides crucial digital focus, your strategy approach must also be built on speed and flexibility which means that you must listen, adapt, experiment and execute better and faster than ever before – and than what your competition does.

Profitability: Digital acceleration should be geared towards driving economic benefits aimed of keeping – or developing – a healthy culture of profitability. So focus on growth and profitability and know that when setting up something new, it does not always mean that the old is bad. The key is to know the gaps and build the bridges.

Create a vision statement: You need a vision statement in order to build the narrative for the digital transformation your organization must undertake. Build upon the visions you already have in place, but have in mind that you need to think as if you are already in a digital world.

Align digital efforts to vision and overall corporate strategy: Executives – and later on their teams and the rest of the organization – need to think of digitalization as a tool to reach the goals stated in the corporate strategy – short, mid and long-term.

Ride the waves of merging industries: Exponential growth, mergers of technologies and disruption created by new business models will change the supply and value chains that make up the industries as we know them today. This will happen faster in some industries than others, but every company need to prepare themselves to be disrupted. Digital is a key enabler.

Be competitively unpredictable: Either your industry stays the same or it will be disrupted significantly in the coming years. The challenge is that you don’t know which scenario wins, so you need to prepare the organization to face either option. Agility is key for this. If you decide to be proactive on this and if you read the merging of industries right, you are on the way to become competitively unpredictable.

Develop the digital compass: Knowing where to go in the digital world is one of the biggest challenges. In this context, you must look at digital for operational elements as well as digital for transformation/innovation efforts. This covers all aspects of digital from social media, e-commerce, digital life to big data, artificial intelligence and IoT. It is difficult developing a digital compass so be ready to experiment to find the right way forward for your organization.

Step up the communication efforts: You have to develop a common understanding and a common language around digital transformation. Build your communication strategy on the above efforts.

2. Personal Leadership / Executives

Go from doing digital to being digital: Internal and external forces with a special focus on the shifts in customer expectations require new approaches for dealing with digital. Did you company react to these changes by doing digital or by being digital? Getting to know your patterns of action will help you on the long journey of understanding what digital transformation really is about.

Know the leadership challenges: Who leads on digital in your organization? Is digital leadership spread across silos, functions and business units or is it unified? Who has the ownership of the touch-points in the customer, supplier, innovation and other journeys? Do you have the capabilities and infrastructure to be data-driven or do you rely on your gut instincts? If the leadership team does not get this, all other efforts will be in vain.

Build a core team and give executives skin in the game: Set up a small core team with a mix of top level executives (at best led by the CEO him or herself) and people with the right mindset and skills towards digitalization. This team must make things happen and the key elements are to set the direction, build the belief and remove the obstacles for digital transformation. Don’t turn this into a talk, talk committee. It has to be action-driven and people – including the executives – need to be hold accountable for its success.

Focus on the root causes, not the barriers: Too many executives and their chosen teams keep fighting the barriers, but they will not go away if you don’t attack the root causes. Root causes are different for each organization. Know yours.

Bring Emotional Intelligence (EQ) into digital efforts: Develop your ability to have successful conversations with others, up, down, sideways, inside and outside the organization. The ability to empathize impacts employee engagement, retention and performance and it is critical to good teamwork. It it also critical for customer engagement and ecosystem driven innovation. This is about interacting rather than managing. It is important today and even more so in a growing digital world.

Identify the heroes and make space for the first rebels: Who sounds the alarm horn, when the rest of the organization steers towards the abyss? You need to identify the heroes who really make a difference for your digital transformation and you must beware that many of the future heroes might have the label of being a rebel today. Once you know what to look for in people and later on who the heroes are, make sure they are close to your inner circle.

Build belief, instill a sense of urgency: First, the executives and their teams must believe – and upgrade their own mindset and competences. Then, they must build belief within the organization and external stakeholders. Communication including networking and stakeholder management is key. The paradox is that this must be done with a sense of urgency that very few people can understand.

Manage speed plus complexity: Today, we all try to handle speed, but in the near future it will also be about handling complexity. The rising complexity gives leaders headaches, and thereby resistance to take the first steps towards change. Establish a collective realization to embrace change og listen and adapt much more dramatically than ever before. Maybe AI will soon help us on this.

3. People – Mindset, Skills and Toolbox

Asses your digital maturity: You need to assess not only the organizational maturity but also your personal maturity for digitalization. Once you know your starting point as well as your objectives, it becomes easier to develop in the right direction. You can find many assessment tools online although it can take some time finding one that works for you. We are working on this.

Know your network and skills: Assess your network and skills with regards to the elements that are the most important for your work and career issues today and in the near future. If you read this, you already know that digital is important. The next questions to consider are how you can grow your network in this direction and context.

Learn in new ways: You need to challenge yourself constantly in the next couple of years in order to keep up with the best – or just stay relevant. You can do this through reverse mentoring, taking classes at platforms like Singularity and Udacity and by expanding your network in directions that works for your new future. As a starter, you could look into exponential growth and how this brings along merging technologies and even industries.

Embrace the positive aspects: There are so many public perspectives on digitalization and they are both positive and negative. If you want to prosper in this new era, you must embrace the positive aspects and explore the opportunities while still keeping a healthy balance by having a realistic view and understanding of the less positive consequences. And remember that the worst you can do is to do nothing at all.

4. Organizational Structures and Processes

New ways of working: Explore the “new” ways of working which often includes buzz words such as lean, agile, experimentation, MVP, holocracy, RACI and boss-less management. Adapt the ways that can work within your organization and experiment on how to bring the past and future together.

Don’t act like a startup: You are not one, but you should still adopt a beginner’s mindset. This means you need to look at things with a fresh perspective, stay curious and be open for experimentation while learning from the failures that come along with experimentation.

Experiment, implement and standardize on digitalization: Set up small teams that work in new ways, capture the lessons learned from successes as well as failures and communicate strategically about this. Build from this to float more projects into the organization and consider establishing a new competence center. Validate and standardize well consolidated working methods across the corporation and focus on the next development.

Break down silos, review governance structures: Internal resistance is often caused by business units and functions that are working towards different objectives. This will be a major issue with digitalization as it has strong impact across the board. Assess the processes, policies and systems that prevent success in this context. Update.

Educate in new ways: Forget Harvard, INSEAD, London Business School and all the other business schools that are rooted in the last century. Ok, that might be a tad too much, but you should definitely find ways to complement traditional training and educational efforts with the offerings by the likes of Singularity University and Udacity. Learn by doing and train the trainers.

Work with HR – when/if they are ready: Most HR teams lack a strategic role when it comes to corporate transformation, digitalization and innovation. This is a paradox as everyone agrees that people are the key element here. This has to change and the core team need to help them upgrade their capabilities in this context. If successful, HR becomes a powerful partner as they have a strong influence on corporate training including the executive level.

Don’t go full frontal with learning activities: Before you push learning, use 3-6 months to influence the executives by sharing short pieces of information and insights that fit their specific situation and objectives in the context of digital transformation. Build further on this to help them develop their own ideas on how digital can help their personal agendas. Then, develop a program to upgrade their mindset, skills and toolbox (and for their key people and teams). Make it action-driven.

Note: several of the below hacks on networks and ecosystems are also highly relevant to organizational structures and processes.

5. Networking and Ecosystems

Digital business models are platforms based on networks and communities: Products have features, platforms have communities and networks. Platforms are connected, collaborative and scalable. You do not have to replace your current business models based on products as the digital business models often live alongside the traditional ones (at least for now). The key is to learn the new rules of strategy based on a platform-driven world or begin planning your exit.

Develop a networked business structure: A next generation organization is highly networked. It is plugged into physical as well as virtual assets and resources and entrepreneurial and industrial ecosystems on a global scale. The external strategic stakeholders (current and potential) must be identified and mapped based on their role in the value chain, business model ecosystem and/or supply chain. Better interaction and flow across ecosystems must be enabled.

The internal networked business structure: The same as the above needs to be done internally where the focus is also to break down silos. Here it is critical to know how to navigate the fine line between the existing corporate culture and the different culture that is often needed for a successful transformation. A mindset upgrade program must be initiated in this context, and key internal resources should get their feet wet fast.

Form a strategic alliance with IT: You cannot do it without them. But make sure IT also sees opportunities that everyone can pursue together rather than just risk that IT wants to shut down.

Be the accelerator for your ecosystems: Strive to become the accelerator that brings together your ecosystems and takes the lead in developing the services, processes and products needed for everyone to win with digitalization.

Win early and reap the benefits: The key benefit of being perceived as the thought/action leader within your industry and the preferred partner of choice within your (innovation) ecosystems is that your organization get the first look on new opportunities as well as the important heads-up on new directions within the industry.

Work with multi-layered approaches: Today, networking and ecosystems is not just organizations with its teams and people working with other organizations and their teams and people to form ecosystems. It is also the digital and virtual infrastructures of these companies and ecosystems. Furthermore, we need to have in mind that competition today is not between two or more companies, but between two or more ecosystems.

6. Tools

Current versus new services, systems and tools: What is already in place to facilitate digital transformation? How do we learn what else is needed? How do we get the new things and how do we bridge the new and the existing in ways that build competitive advantages? Getting the overview here is a job for the top executives. You might need new tools just to get this overview.

Tap into existing structures and opportunities for digital development: Many companies and service providers have been working on digital transformation for years. Just think of Watson in general (and their narrow approaches towards health and law) and the new partnership between IBM and Salesforce with regards to digital-driven sales structures. As above, you first need the overview and then you find out how to tap into what is already on the market and link this with your own efforts.

Metrics and KPI’s in a digital world: Many traditional metrics are outcome-driven in the sense that they are based on 1-3 year old decisions and the actions taken around these decisions. In the future, we need to balance traditional metrics and KPI’s with new ones that focus more on behavior in order to provide an overview of the corporate capabilities and a sense of the direction that the organization and its partners is taking. This is important in order to facilitate much faster strategy development processes and even faster responses to the markets.

Harness the power of big data: This will be the starting point for many organizations. You can start start small by forming data collection and insight teams and build up your analytical capabilities. But starting small does not mean that you should not invest heavily in this. If you are at this stage, you are years behind and you have to catch up fast.

Use digital to work smarter, not harder: What good are all the tools if they do not enable your organization to work smarter rather than harder?

Thanks!

Image Credit: Unsplash

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Is China Our New Sputnik Moment?

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Is China Our New Sputnik Moment?

GUEST POST from Greg Satell

When the Soviets launched Sputnik, the first space satellite, into orbit in 1957, it was a wake-up call for America. Over the next year, President Eisenhower would sign the National Defense Education Act to spur science education, increase funding for research and establish NASA and DARPA to spur innovation.

A few years ago, a report by the Council on Foreign Relations (CFR) argued that we are at a similar point today, but with China. While we have been steadily decreasing federal investment in R&D over the past few decades, our Asian rival has been ramping up and now threatens our leadership in key technologies such as AI, genomics and quantum information technology.

Clearly, we need to increase our commitment to science and innovation and that means increasing financial investment. However, what the report makes clear is that money alone won’t solve the problem. We are, in several important ways, actually undermining our ability to innovate, now and in the future. We need to renew our culture of innovation in America.

Educating And Attracting Talent

The foundation of an innovation economy is education, especially in STEM subjects. Historically, America has been the world’s best educated workforce, but more recently we’ve fallen to fifth among OECD countries for post-secondary education. That’s alarming and something we will certainly need to reverse if we are to compete effectively.

Our educational descent can be attributed to three major causes. First, the rest of the world has become more educated, so the competition has become stiffer. Second, is financing. Tuition has nearly tripled in the last decade and student debt has become so onerous that it now takes about 20 years to pay off four years for college. Third, we need to work harder to attract talented people to the United States.

The CFR report recommends developing a “21st century National Defense Education Act” to create scholarships in STEM areas and making it easier for foreign students to get Green Cards when they graduate from our universities. It also points out that we need to work harder to attract foreign talent, especially in high impact areas like AI, genomics and quantum computing.

Unfortunately, we seem to be going the other way. The number of international students to American universities is declining. Policies like the muslim ban and concerns about gun violence are deterring scientific talent coming here. The denial rate for those on H1-B visas has increased from 4% in 2016 to 18% in the first quarter of 2019.

Throughout our history, it has been our openness to new people and new ideas that has made America exceptional. It’s a legitimate question whether that’s still true.

Building Technology Ecosystems

In the 1980s, the US semiconductor industry was on the ropes. Due to increased competition from low-cost Japanese manufacturers, American market share in the DRAM market fell from 70% to 20%. The situation not only had a significant economic impact, there were also important national security implications.

The federal government responded with two initiatives, the Semiconductor Research Corporation and SEMATECH, both of which were nonprofit consortiums that involved government, academia and industry. By the 1990s. American semiconductor manufacturers were thriving again.

Today, we have similar challenges with rare earth elements, battery technology and many manufacturing areas. The Obama administration responded by building similar consortiums to those that were established for semiconductors: The Critical Materials Institute for rare earth elements, JCESR for advanced batteries and the 14 separate Manufacturing Institutes.

Yet here again, we seem to be backsliding. The current administration has sought to slash funding for the Manufacturing Extension Partnership that supports small and medium sized producers. An addendum to the CFR report also points out that the administration has pushed for a 30% cut in funding for the national labs, which support much of the advanced science critical to driving American technology forward.

Supporting International Trade and Alliances

Another historical strength of the US economy has been our open approach to trade. The CFR report points out that our role as a “central node in a global network of research and development,” gave us numerous advantages, such as access to foreign talent at R&D centers overseas, investment into US industry and cooperative responses to global challenges.

However, the report warns that “the Trump administration’s indiscriminate use of tariffs against China, as well as partners and allies, will harm U.S. innovative capabilities.” It also faults the Trump administration for pulling out of the Trans-Pacific Partnership trade agreement, which would have bolstered our relationship with Asian partners and increased our leverage over China.

The tariffs undermine American industry in two ways. First, because many of the tariffs are on intermediate goods which US firms use to make products for export, we’re undermining our own competitive position, especially in manufacturing. Second, because trade partners such as Canada and the EU have retaliated against our tariffs, our position is weakened further.

Clearly, we compete in an ecosystem driven world in which power does not come from the top, but emanates from the center. Traditionally, America has positioned itself at the center of ecosystems by constantly connecting out. Now that process seems to have reversed itself and we are extremely vulnerable to others, such as China, filling the void.

We Need to Stop Killing Innovation in America

The CFR report, whose task force included such luminaries as Admiral William McRaven, former Google CEO Eric Schmidt and economist Laura Tyson, should set alarm bells ringing. Although the report was focused on national security issues, it pertains to general competitiveness just as well and the picture it paints is fairly bleak.

After World War II, America stood almost alone in the world in terms of production capacity. Through smart policy, we were able to transform that initial advantage into long-term technological superiority. Today, however we have stiff competition in areas ranging from AI to synthetic biology to quantum systems.

At the same time, we seem to be doing everything we can to kill innovation in America. Instead of working to educate and attract the world’s best talent, we’re making it harder for Americans to attain higher education and for top foreign talent to come and work here. Instead of ramping up our science and technology programs, presidential budgets regular recommend cutting them. Instead of pulling our allies closer, we are pushing them away.

To be clear, America is still at the forefront of science and technology, vying for leadership in every conceivable area. However, as global competition heats up and we need to be redoubling our efforts, we seem to be doing just the opposite. The truth is that our prosperity is not a birthright to which we are entitled, but a legacy that must be lived up to.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Top 10 Human-Centered Change & Innovation Articles of December 2022

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Top 10 Human-Centered Change & Innovation Articles of December 2022 Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are December’s ten most popular innovation posts:

Forbidden Truth About Innovation — by Robyn Bolton

A Letter to Innovation Santa — by John Bessant

Preserving Ecosystems as an Innovation Superpower — by Pete Foley

What is a Chief Innovation Officer? — by Art Inteligencia

If You Can Be One Thing – Be Effective — by Mike Shipulski

How to Drive Fear Out of Innovation — by Teresa Spangler

3 Steps to Find the Horse’s A** In Your Company (and Create Space for Innovation) — by Robyn Bolton

Six Ways to Stop Gen-Z from Quiet Quitting — by Shep Hyken

Overcoming the Top 3 Barriers to Customer-Centricity — by Alain Thys

Designing Innovation – Accelerating Creativity via Innovation Strategy — by Douglas Ferguson

BONUS – Here are five more strong articles published in November that continue to resonate with people:

What Are Strategic and Market Foresight? — by Braden Kelley

Innovate for Good – Breaking Paradoxes — by Teresa Spangler

Leading Your Way Through Crisis — by Greg Satell

Innovating in a Downturn — by Geoffrey A. Moore

Brewing a Better Customer Experience — by Braden Kelley

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last three years:

Top 40 Innovation Bloggers of 2020

Top 40 Innovation Bloggers of 2021

Top 40 Innovation Bloggers of 2022

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America Needs to Innovate Its Innovation Ecosystem

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America Needs to Innovate Its Innovation Ecosystem

GUEST POST from Greg Satell

The world today just seems to move faster and faster all the time. From artificial intelligence and self-driving cars to gene editing and blockchain, it seems like every time you turn around, there’s some newfangled thing that promises to transform our lives and disrupt our businesses.

Yet a paper published by a team of researchers in Harvard Business Review argues that things aren’t as they appear. They point out that total factor productivity growth has been depressed since 1970 and that recent innovations, despite all the hype surrounding them, haven’t produced nearly the impact of those earlier in the 20th century.

The truth is that the digital revolution has been a big disappointment and, more broadly, technology and globalization have failed us. However, the answer won’t be found in snazzier gadgets or some fabulous “Golden Era” of innovation of years long past. Rather we need to continually innovate how we innovate to solve problems that are relevant to our future.

The Productivity Paradox, Then and Now

In the 1970s and 80s, business investment in computer technology was increasing by more than 20% per year. Strangely though, productivity growth had decreased during the same period. Economists found this turn of events so bizarre that they called it the “productivity paradox” to underline their confusion.

Yet by the late 1990s, increased computing power combined with the Internet to create a new productivity boom. Many economists hailed the digital age as a “new economy” of increasing returns, in which the old rules no longer applied and a small initial advantage, a first mover advantage, would lead to market dominance. The mystery of the productivity paradox, it seemed, had been solved. We just needed to wait for technology to hit critical mass.

Yet by 2004 productivity growth fell once again and has not recovered since. Today, more than a decade later, we’re in the midst of a second productivity paradox, just as mysterious as the first one. New technologies like mobile computing and artificial intelligence are there for everyone to see, but they have done little, if anything, to boost productivity.

Considering the rhetoric of many of the techno-enthusiasts, this is fairly shocking. Compare the meager eight years of elevated productivity that digital technology produced with the 50-year boom in productivity created in the wake of electricity and internal combustion and it’s clear that the digital economy, for all the hype, hasn’t achieved as much as many would like to think.

Are Corporations to Blame?

One explanation that the researchers give for the low productivity growth is that large firms are cutting back on investment in science. They explain that since the 1980s, a “combination shareholder pressure, heightened competition, and public failures led firms to cut back investments in science” and point to the decline of Bell Labs and Xerox PARC as key examples.

Yet a broader analysis tells a different story. Yes, while Bell Labs and Xerox PARC still exist, they are but a shadow of their former selves, but others, such as IBM Research, have expanded their efforts. Microsoft Research, established in 1991, does cutting edge science. Google runs a highly innovative science program that partners with researchers in the academic world.

So anecdotally speaking, the idea that corporations haven’t been investing in science seems off base. However, the numbers tell an even stronger story. Data from the National Science Foundation shows that corporate research has increased from roughly 40% of total investment in the 1950s and 60s to more than 60% today. Overall R&D spending has risen over time.

Also, even where corporations have cut back, new initiatives often emerge. Consider DuPont Experimental Station which, in an earlier era, gave birth to innovations such as nylon, teflon and neoprene. In recent years, DuPont has cut back on its own research but the facility, which still employs 2000 researchers, is also home to the Delaware Incubation Space, which incubates new entrepreneurial businesses.

The Rise of Physical Technologies

One theory about the productivity paradox is that investment in digital technology, while significant, is simply not big enough to move the needle. Even today, at the height of the digital revolution, information and communication technologies only make up about 6% of GDP in advanced economies.

The truth is that we still live in a world largely made up of atoms, not bits and we continue to spend most of our money on what we live in, ride in, eat and wear. If we expect to improve productivity growth significantly, we will have to do it in the physical world. Fortunately, there are two technologies that have the potential to seriously move the needle.

The first is synthetic biology, driven largely by advances in gene editing such as CRISPR, which have dramatically lowered costs while improving accuracy. In fact, over the last decade efficiency in gene sequencing has far outpaced Moore’s Law. These advances have the potential to drive important productivity gains in healthcare, agriculture and, to a lesser extent, manufacturing.

The second nascent technology is a revolution in materials science. Traditionally a slow-moving field, over the past decade improved simulation techniques and machine learning have improved the efficiencies of materials discovery dramatically, which may have a tremendous impact in manufacturing, construction and renewable energy.

Yet none of these gains are assured. To finally break free of the productivity paradox, we need to look to the future, not the past.

Collaboration is the New Competitive Advantage

In 1900, General Electric established the first corporate research facility in Schenectady, New York. Later came similar facilities at leading firms such as Kodak, AT&T and IBM. At the time, these were some of the premier scientific institutions in the world, but they would not remain so.

In the 1920s new academic institutions, such as the Institute for Advanced Study, as well as the increasing quality of American universities, became an important driver of innovation. Later, in the 1940s, 50s and 60s, federal government agencies, such as DARPA, NIH and the national labs became hotbeds of research. More recently, the Silicon Valley model of venture funded entrepreneurship has risen to prominence.

Each of these did not replace, but added to what came before. As noted above, we still have excellent corporate research programs, academic labs and public scientific institutions as well as an entrepreneurial investment ecosystem that is the envy of the world. Yet none of these will be sufficient for the challenges ahead.

The model that seems to be taking hold now is that of consortia, such as JCESR in energy storage, Partnership on AI for cognitive technologies and the Manufacturing USA Institutes, that bring together diverse stakeholders to drive advancement in key areas. Perhaps most conspicuously, unprecedented collaboration sparked by the Covid-19 crisis has allowed us to develop therapies and vaccines faster than previously thought possible.

Most of all, we need to come to terms with the fact that the answers to the challenges of the future will not be found in the past. The truth is that we need to continually innovate how we innovate if we expect to ever return to an era of renewed productivity growth.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Four Innovation Ecosystem Building Blocks

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Four Innovation Ecosystem Building Blocks

GUEST POST from Greg Satell

It’s hard to find anyone who wouldn’t agree that Microsoft’s 2001 antitrust case was a disaster for the company. Not only did it lose the case, but it wasted time, money and—perhaps most importantly—focus on its existing businesses, which could have been far better deployed on new technologies like search and mobile.

Today, Microsoft is a much different organization. Rather than considering open source software a cancer, it now says it loves Linux. Its cloud business is growing like wildfire and it is partnering widely to develop new quantum computers. What was previously a rapacious monopolist, is now an enthusiastic collaborator.

That’s no accident. Today, we need to compete in an ecosystem-driven world in which nobody, not even a firm as big and powerful as Microsoft, can go it alone. Power no longer comes from the top of value chains, but emanates from the center of networks. That means that strategy needs to shift from dominating industries to building collaborative ecosystems.

1. Connect to Startups

In its heyday, Microsoft enthusiastically followed Michael Porter’s five forces model. It saw threats coming not only from direct competitors, but also suppliers, customers, substitute products and new market entrants. Startups, in particular, were targeted for either acquisition or destruction if they were seen as posing a potential threat.

Today, however, Microsoft actively supports startups. Take, for example, its quantum development effort, in which it is partnering with more than a dozen entrepreneurial companies. These firms also get free access to Microsoft technologies, such as its Azure cloud platform and go-to-market resources and advice, through its Microsoft for Startups program.

Another approach that many firms take is corporate VC programs which actively invest in promising new companies. Unlike a typical investor, corporations bring a wealth of market and technical expertise, can help with things like distribution, supply chain management and marketing acumen. Corporations, for their part, get far more insight into new technologies than they could as an operating company.

Scott Lenet, President of Touchdown Ventures, which operates venture funds for corporations, told me that, “Startups thrive on new ideas and big firms know how to scale and improve those ideas. We’ve seen some of our investments really blossom based on that kind of partnership.”

2. Form Ties to the Academic World

When Sun Microsystems co-founder Bill Joy said, “no matter who you are, most of the smartest people work for someone else,” he was explicitly referring to Bill Gates’s assertion that Microsoft was an “IQ monopolist.” Joy’s position was that “It’s better to create an ecology that gets all the world’s smartest people toiling in your garden for your goals. If you rely solely on your own employees, you’ll never solve all your customers’ needs.”

Make no mistake. Innovation is never a single event. It is a process of discovery, engineering and transformation and those three things almost never happen in the same place or at the same time. That’s why the most innovative companies work hard to build links to the best minds in the academic world.

Today Microsoft has an extensive academic program that extends grants to graduate students and faculty members that are pursuing research that is of interest to the company. Google takes it even a step further, inviting dozens of the world’s top minds to work alongside its scientists and engineers for a sabbatical year.

Microsoft and Google are, of course, firms with enormous resources. However, just about any business can, for example, support the work of a young graduate student or postdoc at a local university. For even a senior researcher to collaborate with your staff is rarely prohibitively expensive. Researchers care far more about genuine support of their work than the size of your investment.

3. Leverage Domain-Specific Consortia

By the mid-1980’s, the American semiconductor industry seemed like it was doomed. Tp respond to what it saw as a national security threat, the American government created SEMATECH in 1986. It was a consortium of government agencies, research institutions and private firms focused on making the industry more competitive. By the mid 1990’s, the US was once again dominating semiconductors.

Any significantly complex technology takes years—and often decades—to develop before it becomes mature enough to engineer into a marketable product. So there is great potential in collaborating, even with competitive firms, in the pre-competitive phase to figure out the basic principles of a nascent technology.

For example, Boeing and Airbus are arch-rivals in aviation, much like DowDupont and BASF are in chemicals. Yet all of these companies, along with many others, collaborate at places like the Composites Institute (IACMI). They do this not out of any altruism, of course, but self-interest, because it is at places like the Composites Institute that they can collaborate with academic scientists, National Labs and startups working in the space.

As technology becomes more complex, domain specific consortia are becoming essential to any ecosystem strategy. The Composites Institute is just one node in the network of Manufacturing Institutes set up under the Obama Administration to support this type of collaboration. In areas ranging from advanced fabrics and biofabrication to additive manufacturing and wide-gap semiconductors, firms large and small are working with scientists to uncover new principles.

And the Manufacturing Institutes are just the start. The Internet of Things Consortium is helping bring computation to the physical world, while the Partnership on AI focuses on artificial intelligence and the Joint Center for Energy Storage Research is helping to develop advanced battery technology. All are open to the largest multinationals and the smallest startups.

4. Move From Hierarchies to Networks

Back in the 90s, when Microsoft still dominated the tech world, markets were still based on linear value chains dominated by one or two industry giants. Yet as I explain in Cascades, we are quickly moving from a world of hierarchies, to one dominated by networks and ecosystems. That changes how we need to develop and grow.

In a hierarchy-driven world, the optimal strategy was to build walls and moats to protect yourself against would-be invaders, which is why Microsoft fought tooth and nail to protect its operating system monopoly. Today, however, industry lines have blurred and technology moves too fast to be able to build effective barriers against disruption.

That’s why today “Microsoft loves Linux”, why it developed an academic program to collaborate with scientists at universities and why it often partners with startups instead of always trying to crush them. The technology being developed today is simply too complex for anyone to go it alone, which is why the only viable strategy is to actively connect to ecosystems of talent, technology and information.

Power today no longer sits at the top of hierarchies, but emanates from the center of ecosystems and you move to the center by widening and deepening connections. Closing yourself by erecting barriers will not protect you. In fact, it is an almost sure-fire way to hasten your demise.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Building an Innovation Ecosystem: Lessons from Silicon Valley

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Building an Innovation Ecosystem: Lessons from Silicon Valley

GUEST POST from Chateau G Pato

Innovation has become the driving force behind economic growth and societal progress in today’s highly competitive global landscape. As the birthplace of countless revolutionary technologies, Silicon Valley has emerged as the epicenter of innovation, setting a blueprint for other regions aspiring to foster their own vibrant ecosystems. In this thought leadership article, we will explore the key elements that have made Silicon Valley thrive. By examining the pivotal role collaboration, access to venture capital, and a culture of experimentation have played, we will extract valuable lessons that can be applied when building innovation ecosystems elsewhere. To illustrate these principles, we’ll highlight two compelling case studies that demonstrate successful implementation beyond the confines of Silicon Valley.

Case Study 1: Singapore’s Rise as “Asia’s Silicon Valley”

Singapore, once regarded as a financial hub, has leveraged its favorable regulatory environment and strategic partnerships to create a thriving innovation ecosystem. The city-state’s pivotal initiative, “Smart Nation,” emphasizes collaboration between academia, industry, and the government. By fostering close relationships between research institutions such as Nanyang Technological University, startups, and multinational corporations through collaborative projects, Singapore has developed a dynamic exchange of ideas and knowledge. Furthermore, the government’s proactive involvement, manifested in unique initiatives like the Data Innovation Lab, has facilitated access to resources and intellectual support, mirroring Silicon Valley’s approach.

Case Study 2: Tel Aviv’s “Startup Nation” Success

Tel Aviv, Israel’s vibrant tech hub, has earned international recognition as the “Startup Nation.” Its tremendous achievements can be attributed to a unique blend of collaboration and a culture of experimentation. Tel Aviv’s success began with the establishment of the first technology incubator program, Yozma, in the 1990s. It attracted venture capital funds from abroad, providing startups with the necessary financial backing they needed to thrive and turning Israel into a hotbed of innovation. Additionally, the Israeli Defense Forces’ Unit 8200, known for its exceptional technological prowess, has served as a breeding ground for entrepreneurs, contributing to a robust talent pipeline. By cultivating a supportive network where government, startups, academia, and investors collaborate, Tel Aviv has successfully emulated Silicon Valley’s recipe for innovation.

Key Lessons for Building Innovation Ecosystems:

1. Collaboration is Key: Facilitating collaboration among academia, industry, and government creates a vibrant exchange of knowledge and resources. Implementing initiatives like innovation hubs, incubators, and public-private partnerships can foster collaboration and create synergistic relationships, ultimately driving innovation forward.

2. Access to Venture Capital: A well-developed venture capital ecosystem is crucial. Governments can incentivize venture capital investments through tax breaks, subsidies, and the establishment of government-backed funds. Encouraging institutions to invest in promising startups promotes growth and attracts talent, mirroring the success of Silicon Valley and Tel Aviv.

3. Cultivating a Culture of Experimentation: Encouraging risk-taking and embracing failure as valuable learning experiences are fundamental aspects of nurturing innovation. Governments and organizations should provide a supportive environment for entrepreneurs and allow room for experimentation, empowering individuals to push boundaries and disrupt existing industries.

Conclusion

Silicon Valley’s innovative ecosystem has demonstrated that collaboration, access to venture capital, and a culture of experimentation are key ingredients for success. By examining Singapore’s “Smart Nation” and Tel Aviv’s “Startup Nation,” it becomes evident that these principles can be adapted and applied in other locations, spurring their own innovation ecosystems. Building a dynamic environment that brings academia, industry, government, and investors together can unlock tremendous potential and accelerate progress towards a more prosperous future. Emulating these lessons from Silicon Valley will undoubtedly create a fertile ground for innovation to thrive, establishing a legacy that will endure for generations to come.

SPECIAL BONUS: The very best change planners use a visual, collaborative approach to create their deliverables. A methodology and tools like those in Change Planning Toolkit™ can empower anyone to become great change planners themselves.

Image credit: Unsplash

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Innovation Ecosystems and Information Rheology

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Innovation Ecosystems and Information Rheology

GUEST POST from Arlen Meyers

Rheology is the study of flow. There are many ways to measure flow. For example, Volume Flow is defined as the volume quantity that flows through a given section at a considered time interval. The most common volume units are:m3/s, m3/h, l/h, l/min, GPM (gallons per minute), Nm3/h (normal cubic meter per hour), SCFH (normal cubic foot per hour), among others.

Information rheology is the study of how information passes from the sender to the receiver, the resistance to that flow, and how to address it.

The concept applies also to how products and services flow from one place in the world to another.

A reverse innovation is any innovation that is adopted first in the developing world. To be clear: What makes an innovation a reverse innovation has nothing to do with where the innovators are, and it has nothing to do with where the companies are. It has only to do with where the customers are.

Historically, reverse innovation has been a rare phenomenon. In fact, the logic for innovations flowing downhill, from the rich world to the developing world, is natural and intuitive. After all, it is the richest customers in the richest countries that will always demand the newest technologies. In due time, the costs of new technologies come down, and incomes in the developing world rise. As a result, innovations trickle down. Right?

Be careful. The intuitive assumption that poor countries are engaged in a process of gradually catching up with the rich world has become toxic. It is a strategic blind spot that has the potential to sink an increasingly common aspiration: to generate high growth in the emerging economies. The assumption can even inflict long-term damage in home markets. That is because surprisingly often, reverse innovations defy gravity and flow uphill to the rich world. As a result, a defeat in a developing country half a world away can lead directly to a stinging blow in your own back yard.

How information flows, like on cell phones during riots and protests, is not an exact science. Percolation theory illuminates the behavior of many kinds of networks, from cell phone transmissions to the COVID R number.

Most discussions of innovation ecosystem creation and growth focus on the anatomy i.e. the components necessary to be successful. For example, one author describes the 5P’s of human capital:pillars, patrons, pioneers, professionals and partners.

However, equally as important is the physiology of clusters -how the cluster elements work together .One of the key determinants of an innovative organization or cluster is information rheology. There are three basic elements to the equation.

The first has to do with the number of nodes in the network, both internally and externally. Network theory tells us that the more nodes, the more value. Having one fax machine in the world added nothing. It took a lot to unleash the value , as the development of social media has exemplified.

The second has to do with how the nodes are connected. Some are robust and some are not. The connections between the nodes are called edges.

Finally, and most importantly, the two previous parts are not nearly as important as the velocity, relationships, acceleration and lack of resistance to the flow of information from one node to the next. We usually refer to this as a cluster or innovation district being “user friendly” and is typified by the free and rapid flow of information from one place to the next. Malcolm Gladwell described facilitators in the process as mavens, experts and connectors.

There are many causes of poor information flow, but, fundamentally, they come down to :

1. The sender does not communicate effectively or in a an appropriate way

The receiver is unaware that the message was sent or does not understand it

The systems for transmitting information and verifying receipt are inadequate

Third party interference muddles the message

Poor information flow in sickcare results in dropped handoffs and referral leaks which are the primary causes of medical errors and waste. The lack of data interoperability is one of the root causes.

There are several kinds of intermediaries that facilitate information flow in an ecosystem.

Architects engage in strict agenda-setting and coordination activities

Gatekeepers support the knowledge extraction and dissemination of the information

Conductors take care of information acquisition, transmission, and task sharing

Developers create concrete assets for the network based on knowledge mobility

Auctioneers set the agenda and joint vision for the innovation network

Leaders motivate and foster the voluntary collaboration and identifying roles of network members

Promoter support ecosystem members to work towards the same goal

Facilitator bring together quite different, even competing, parties to work together

Whether it is making clinical handoffs better or improving the flow of information in an ecosystem or cluster, the obstacles are substantial and the systems for preventing information flow blockage need to constantly be maintained, which can be costly and time consuming.

If you want to accelerate regional innovation clusters and communities, don’t concentrate so much on connecting the senders and receivers. Focus on removing the barriers to the flow of information and how to push and pull it through the pipes.

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