Ten years ago, frigid temperatures in Texas caused rolling blackouts, and millions lost power. The state was warned to weatherize its power grid to prepare for more extreme weather but never got around to it. Then, in February of this year, plummeting temperatures again caused widespread outages. Nine hundred people died, mostly from frostbite. Members of ERCOT, the state’s “electricity reliability board” resigned.
What happened – or failed to happen — in Texas is emblematic of how we come to make decisions in a period of ongoing crisis. ERCOT’s failure to act on clear evidence of what needed to be done to avert future disaster is an all-too-common reaction in today’s disrupted age. We kick the can down the road. We cross our fingers and hope we’re not in charge when events hit the fan.
But the issue is not just how we mitigate or don’t mitigate risk. It is also about how leaders manage and plan for future opportunity.
Texas’ power grid reliability managers failed to weatherize. But the times we are living in demand that we futurize our thinking in order to avert future disasters, but also foresee future ways to add value, serve customers, and build new markets that don’t even exist today.
From pandemic to the dastardly attack on the US Capitol to a steady barrage of climate change-emboldened floods, wildfires, and hurricanes, we all seem to be suffering from Disaster Fatigue. Faced with too many warnings — and the need to make too many decisions — it’s easy to allow our thinking to lapse into what I call Defeatist Mode, and essentially shut down our Idea Factories.
To ward off Disaster Fatigue and get the creative juices flowing again, I recommend that you and your organization consciously start spending more time thinking about tomorrow. I call this process Managing the Future, and it involves managing a cultural shift from present circumstances to the future state we want to make manifest.
How to Manage the Shift
Economist Rudy Dornbusch once observed that things often take longer to happen than we think they should. But then they happen faster than we ever thought they would. That’s the sense I get as I have returned to the lecture circuit this fall and have spoken with dozens of leaders about where we are right now.
There’s a growing sense that Covid 19 is not going to go away completely for the foreseeable future. Instead, we are moving from Pandemic to Endemic (in other words the virus and its variants will still be with us, but enough people will have been vaccinated or become immune such that a semblance of normalcy returns).
During this period, leaders especially need to consciously shift attention away from a crisis management mentality and towards an emphasis on managing tomorrow’s potentiality.
As I see it, this is exciting news. For those willing to engage with the future, there is a wide-open field of opportunity. Never has there been a greater need for those with a vision of positivity as regards the future.
A recent survey conducted by Lancet, the British medical journal, found that 45 percent of Millennials in ten countries surveyed are so worried about climate change that it affects their daily life and functioning. So often the prevailing attitude is “we’re doomed.”
“As a young person, when you see a trend coming down the pike, you know it’s going to hit you,” writes Sara Kessler, in Gigged: The End of the Job and the Future of Work. No generation is allowed to sit out the future, and right now the 71 million strong Millennial Generation has decisions to make about Climate Change for which there will be no “do-overs.”
Yet even with climate disasters increasing at an increasing rate, history tells us that our attitude and belief in a more positive future determines more about outcomes than any other factors. We can muster the brainpower to invent and unleash massive climate-cleansing innovations that keep global temperatures from rising more than 1.5 degrees centigrade, but only if we believe we can.
To do so we must choose optimism over pessimism. We can choose optimism in the face of headlines that declare we’re doomed as a species. We can form study groups and tiger teams to look farther out and contemplate how our industry is changing, how our employee’s expectations are changing, how our customers’ needs are changing, and in doing so we can choose to think positive thoughts.
As we think, so we become. By consciously taking charge of our “self-talk” we can make the shift from defeatist, reactive, and crisis-driven thinking to deliberate, purpose-driven, future-focused thinking.
For those with an eye on their attitude, who monitor emerging technologies and social, demographic, and economic trends there are fewer surprises, fewer blindsides, and greater opportunities to own the future.
As Fleetwood Mac sang:
“Don’t stop thinking about tomorrow
It’ll be better than before…
Open your eyes and look at the day
You’ll see things in a different way”
In today’s rapidly evolving business landscape, organizations face the dual challenge of achieving short-term wins while steadily progressing towards long-term innovation goals. The ability to balance these two objectives is crucial for sustainable success. In this article, we will explore strategies for maintaining this balance and examine two compelling case studies that highlight the importance of aligning short-term and long-term efforts.
Strategies for Balancing Short-Term and Long-Term Goals
To successfully balance short-term wins with long-term innovation goals, organizations should consider the following strategies:
Set Clear Objectives: Outline specific, measurable objectives that align with both short-term and long-term goals.
Foster an Innovative Culture: Cultivate a culture that encourages experimentation, learning, and the sharing of ideas.
Ensure Agility: Implement agile methodologies to quickly adapt to changes and seize opportunities.
Allocate Resources Wisely: Allocate resources, including time, budget, and talent, strategically to support both immediate and future initiatives.
Monitor and Adjust: Continuously monitor progress and be prepared to adjust plans as necessary to maintain alignment with overall goals.
Case Study 1: Adobe – Embracing Continuous Innovation
Background
Adobe, a multinational software company known for its creative tools such as Photoshop and Illustrator, faced a critical decision in the early 2010s. The company needed to transition from traditional software licensing to a cloud-based subscription model to ensure long-term growth and innovation.
Short-Term Wins
To gain buy-in and demonstrate immediate value, Adobe introduced Adobe Creative Cloud, allowing users to subscribe to their software on a monthly basis. This move provided immediate financial gains by creating a steady, recurring revenue stream, and giving customers more flexibility.
Long-Term Innovation
While the transition to a subscription model was a significant short-term win, Adobe also invested heavily in long-term innovation. They focused on integrating AI and machine learning across their platforms, as well as expanding their ecosystem with new tools and services. The shift to Creative Cloud allowed Adobe to continuously update their software, ensuring that customers had access to the latest innovations without the need for new purchases.
Impact
The balance of short-term wins with a focus on long-term goals enabled Adobe to thrive in a rapidly changing market. Today, Adobe Creative Cloud is a cornerstone of the company’s success, providing substantial value to customers while ensuring sustained innovation.
Case Study 2: Amazon – Innovating for the Future
Background
Amazon, the global e-commerce and technology giant, has consistently balanced short-term operational efficiency with long-term innovation. One notable example of this balance is their approach to Amazon Web Services (AWS).
Short-Term Wins
Initially, Amazon focused on optimizing its retail operations to achieve short-term wins. They streamlined logistics, optimized the supply chain, and enhanced customer experience. These efforts generated immediate gains and established Amazon as a leader in the retail space.
Long-Term Innovation
Simultaneously, Amazon recognized the potential of cloud computing and invested heavily in the development of AWS. This long-term vision required substantial investment but promised a revolutionary shift in how businesses manage their IT infrastructure. AWS allowed Amazon to introduce new services and products, such as data analytics and machine learning, which have had a transformative impact across industries.
Impact
The strategy of balancing short-term improvements with visionary, long-term projects has paid off profoundly for Amazon. AWS is now a significant revenue generator and a critical driver of the company’s future growth and innovation. Amazon’s ability to balance the two has made it one of the most valuable and innovative companies in the world.
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: Pixabay
Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.
In 1998, the dotcom craze was going at full steam and it seemed like the entire world was turning upside down. So people took notice when economist Paul Krugman wrote that “by 2005 or so, it will become clear that the internet’s impact on the economy has been no greater than the fax machine’s.”
He was obviously quite a bit off base, but these types of mistakes are incredibly common. As the futurist Roy Amara famously put it, “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” The truth is that it usually takes about 30 years for a technology to go from an initial discovery to a measurable impact.
Today, as we near the end of the digital age and enter a new era of innovation, Amara’s point is incredibly important to keep in mind. New technologies, such as quantum computing, blockchain and gene editing will be overhyped, but really will change the world, eventually. So we need to do more than adapt, we need to prepare for a future we can’t see yet.
Identify A “Hair-On-Fire” Use Case
Today we remember the steam engine for powering factories and railroads. In the process, it made the first industrial revolution possible. Yet that’s not how it started out. Its initial purpose was to pump water out of coal mines. At the time, it would have been tough to get people to imagine a factory that didn’t exist yet, but pretty easy for owners to see that their mine was flooded.
The truth is that innovation is never really about ideas, it’s about solving problems. So when a technology is still nascent, doesn’t gain traction in a large, established market, which by definition is already fairly well served, but in a hair-on-fire use case — a problem that somebody needs solved so badly that they almost literally have their hair on fire.
Early versions of the steam engine, such as Thomas Newcomen’s version, didn’t work well and were ill-suited to running factories or driving locomotives. Still, flooded mines were a major problem, so many were more tolerant of glitches and flaws. Later, after James Watt perfected the steam engine, it became more akin to technology that remember now.
We can see the same principle at work today. Blockchain has not had much impact as an alternative currency, but has gained traction optimizing supply chains. Virtual reality has not really caught on in the entertainment industry, but is making headway in corporate training. That’s probably not where those technologies will end up, but it’s how they make money now.
So in the early stages of a technology, don’t try to imagine how a perfected version fit in, find a problem that somebody needs solved so badly right now that they are willing to put up with some inconvenience.
The truth is that the “next big thing” never turns out like people think it will. Putting a man on the moon, for example, didn’t lead to flying cars like in the Jetsons, but instead to satellites that bring events to us from across the world, help us navigate to the corner store and call our loved ones from a business trip.
Build A Learning Curve
Things that change the world always start out arrive out of context, for the simple reason that the world hasn’t changed yet. So when a new technology first appears, we don’t really know how to use it. It takes time to learn how to leverage its advantages to create an impact.
Consider electricity, which as the economist Paul David explained in a classic paper, was first used in factories to cut down on construction costs (steam engines were heavy and needed extra bracing). What wasn’t immediately obvious was that electricity allowed factories to be designed to optimize workflow, rather than having to be arranged around the power source.
We can see the same forces at work today. Consider Amazon’s recent move to offer quantum computing to its customers through the cloud, even though the technology is so primitive that it has no practical application. Nevertheless, it is potentially so powerful—and so different from digital computing—that firms are willing to pay for the privilege of experimenting with it.
The truth is that it’s better to prepare than it is to adapt. When you are adapting you are, by definition, already behind. That’s why it’s important to build a learning curve early, before a technology has begun to impact your business.
Beware Of Switching Costs
When we look back today, it seems incredible that it took decades for factories to switch from steam to electricity. Besides the extra construction costs to build extra bracing, steam engines were dirty and inflexible. Every machine in the factory needed to be tied to one engine, so if one broke down or needed maintenance, the whole factory had to be shut down.
However, when you look at the investment from the perspective of a factory owner, things aren’t so clear cut. While electricity was relatively more attractive when building a new factory, junking an existing facility to make way for a new technology didn’t make as much sense. So most factory owners kept what they had.
These types of switching costs still exist today. Consider neuromorphic chips, which are based on the architecture of the human brain and therefore highly suited to artificial intelligence. They are also potentially millions of times more energy efficient than conventional chips. However, existing AI chips also perform very well, can be manufactured in conventional fabs and run conventional AI algorithms, so neuromorphic chips haven’t caught on yet.
All too often, when a new technology emerges we only look at how its performance compares to what exists today and ignore the importance of switching costs—both real and imagined. That’s a big part of the reason we underestimate how long a technology takes to gain traction and underestimate how much impact it will have in the long run.
Find Your Place In The Ecosystem
We tend to see history through the lens of inventions: Watt and his steam engine. Edison and his light bulb. Ford and his assembly line. Yet building a better mousetrap is never enough to truly change the world. Besides the need to identify a use case, build a learning curve and overcome switching costs, every new technology needs an ecosystem to truly drive the future.
Ford’s automobiles needed roads and gas stations, which led to supermarkets, shopping malls and suburbs. Electricity needed secondary inventions, such as home appliances and radios, which created a market for skilled technicians. It is often in the ecosystem, rather than the initial invention, where most of the value is produced.
Today, we can see similar ecosystems beginning to form around emerging technologies. The journal Nature published an analysis which showed that over $450 million was invested in more than 50 quantum startups between 2012 and 2018, but only a handful are actually making quantum computers. The rest are helping to build out the ecosystem.
So for most of us, the opportunities in the post-digital era won’t be creating new technologies themselves, but in the ecosystems they create. That’s where we’ll see new markets emerge, new jobs created and new fortunes to be made.
In today’s competitive business landscape, achieving success requires more than just a great idea.
Entrepreneurs need a systematic approach to quickly identify what works and what doesn’t, all while minimizing waste.
Enter the Lean Startup Methodology – a revolutionary approach that involves building a business by experimenting, iterating, and validating with minimal resources.
Understanding Lean Startup Methodology
The Lean Startup Methodology, coined by Eric Ries in his seminal book “The Lean Startup,” is based on the principles of lean manufacturing.
It emphasizes the importance of creating a Minimum Viable Product (MVP), validated learning, rapid iteration, and pivoting based on customer feedback.
This approach allows startups to validate their business ideas quickly and efficiently, reducing the risk of investing time and money into unproven concepts.
Case Studies
Case Study 1: Dropbox
One of the most well-known examples of the Lean Startup Methodology in action is Dropbox. Before investing heavily in product development, Dropbox’s founders aimed to validate their idea: a simple-to-use file-sharing service.
Instead of building a fully-featured product, they started with a short video demonstrating the core functionality of Dropbox. This MVP helped them gauge interest and gather valuable feedback from potential users.
The video went viral on various tech forums and social media platforms, quickly securing thousands of sign-ups for the beta version of Dropbox. By using this minimally viable form of validation, Dropbox managed to refine its product with minimal waste and significant user input.
Today, Dropbox is a multi-billion dollar company, and it all started with a simple MVP and a clear focus on validated learning.
Case Study 2: Zappos
Zappos, now one of the largest online shoe and clothing retailers, also adopted a Lean Startup approach in its early days. Rather than investing in a large inventory upfront, founder Nick Swinmurn started with a simple website that displayed photos of shoes.
Whenever a customer placed an order, Swinmurn would personally go to local shoe stores to buy the shoes and ship them directly to the customer.
This MVP allowed Zappos to validate the demand for online shoe shopping without the risk and expense of holding inventory. It also provided valuable insights into customer preferences and buying behavior, allowing Zappos to fine-tune their business model.
The information and insights gained during this MVP phase were critical in building the foundation for Zappos’ subsequent growth and success.
Conclusion
The Lean Startup Methodology offers a powerful framework for building a business with minimal waste. By focusing on validated learning, creating MVPs, and iterating based on customer feedback, entrepreneurs can quickly determine the viability of their ideas and pivot as needed.
The examples of Dropbox and Zappos illustrate how this approach can lead to tremendous success when executed correctly.
As you embark on your entrepreneurial journey, remember that the key to success is not just having a great idea, but also having the ability to learn, adapt, and evolve with minimal waste. The Lean Startup Methodology provides the tools and mindset needed to achieve this goal.
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: Pixabay
Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.
From the computers that are used to develop your app to the AI that’s incorporated into your chatbot, many of the technologies that are foundational to our digital world were either massively moved forward or funded by the military. Let’s go over some of those technologies.
Microchips
The microchips that we know today are composed of millions of transistors which were first developed by Bell Labs in 1949. Through military funding, microchips were further improved and incorporated in airplanes and missiles for complex communication and guidance systems.
Today, microchips are one of the basic building blocks of modern electronics, from calculators and cameras to hearing aids, pacemakers, and spacecraft guidance systems, they’re found almost everywhere electronics exist.
Computers
Did you know that the very first computer was funded by the US Military? The ENIAC, built between 1943 and 1945, was the first large-scale computer to run at electronic speed without being slowed by any mechanical parts. It enabled the military to calculate complex wartime ballistic tables, decryption, etc.
Apart from our phones and laptops, computers can be found in our cars, washing machines, manufacturing companies, 3D printers, power plants, banks, and more.
Cellular Technology
The original versions of cellular phone technology were heavily backed by the military for point-to-point soldier communication on the battlefield since they were more beneficial and secure than conventional radio technology.
Today, 80% of the US population owns a smartphone, and our ability to text, call, and video chat with others is a direct result of improved cellular technology.
The Internet
What we know as the internet today started out as the ARPANET. Backed by the US Military, it was initially used for military and academic communication for joint development projects and as a means of communication in the event of a nuclear attack.
As of 2020, 4.66 billion people around the world are internet users. This interconnectivity gave rise to our digital world and serves as the backbone behind almost all digital transformation initiatives today.
GPS
Originally developed for the military to help them navigate terrain and develop weapon targeting systems, the first 20 satellites launched for GPS were funded and driven by the military.
Without GPS technology, we wouldn’t have Google Maps, Waze, or Uber. Depending on your business, there are many ways you can incorporate GPS technology to streamline processes and collect data.
Digital Cameras
The digital sensors used by cameras were developed by the military because of their need to capture and send images wirelessly from satellites in space for terrain mapping and espionage operations.
DSLRs, mirrorless cameras, product advertisements, and face recognition technology all came as a direct result of these digital sensors.
Drones
While there are a lot of non-military applications for drones today, the development of drones was initially funded by the US military to avoid any risk to pilots, fly undetected, and provide real-time footage of an area.
A common use for drones is to help farmers scatter seeds, deliver goods to customers, and collect photos or videos of different places, but there are plenty of other ways we can incorporate them into media, architecture, construction, and emergency response.
Artificial Intelligence
The defense sector is projected to spend about $2 billion in Artificial Intelligence this year. The ability to play out simulations, analyze and understand satellite communications, and improve disaster preparedness are just a few of the many ways AI can be utilized by the military.
Commercially, we see AI in digital assistants like Siri, Bixby, and Google Assistant; chatbots on websites and messaging apps; disease mapping; automated financial investing; virtual booking; and social media monitoring.
So the next time you use your smartphone, Alexa, computer, or GPS, remember to say thank you to a soldier!
In my Wall Street Journal bestselling book, Winning Digital Customers: The Antidote to Irrelevance, I walk you through a simple five-step process to successful digital transformation. This methodology is proven and has worked for many companies that I’ve helped in the past. You can access the first chapter for free here or purchase the hard copy here.
In today’s rapidly evolving business landscape, the need for sustainable innovation has become more pressing than ever before. Companies across all industries are realizing the importance of developing new and innovative solutions to address current and future challenges, such as climate change, resource scarcity, and social inequality. And while individual efforts can certainly yield results, it is becoming increasingly clear that collaboration is key to driving truly impactful and sustainable innovation initiatives.
Collaboration brings together diverse perspectives, expertise, and resources, enabling companies to tackle complex problems more effectively and efficiently. By working together with other organizations, companies can leverage each other’s strengths and experiences, share knowledge and best practices, and collectively drive innovation that is not only socially and environmentally responsible, but also economically sustainable.
Case Study 1: Adidas and Parley for the Oceans
One powerful example of the impact of collaboration on sustainable innovation initiatives can be seen in the partnership between Adidas and Parley for the Oceans. The two organizations joined forces in 2015 to create a line of sneakers made from recycled ocean plastic. Through this collaboration, Adidas was able to leverage Parley’s expertise in sustainability and ocean conservation, while Parley gained access to Adidas’s global reach and manufacturing capabilities. The result? The successful launch of the Adidas x Parley line, which not only raised awareness about the issue of marine plastic pollution, but also demonstrated the potential for sustainable fashion to make a positive impact on the environment.
Case Study 2: Unilever and Solidaridad
Another compelling case study of collaboration driving sustainable innovation is the partnership between Unilever and Solidaridad. Unilever, a global consumer goods company, teamed up with Solidaridad, a non-profit organization focused on sustainable agriculture, to implement the Sustainable Soy Sourcing Guidelines. These guidelines set out a framework for responsible sourcing of soy, a key ingredient in Unilever’s products, and aimed to improve supply chain transparency and promote sustainable farming practices among soy producers. By working together, Unilever and Solidaridad were able to drive positive change across their supply chains, enhancing the environmental and social sustainability of their products while also fostering innovation in the agricultural sector.
Conclusion
In both of these examples, collaboration played a vital role in driving sustainable innovation by bringing together diverse stakeholders, fostering creative thinking, and enabling the co-creation of solutions that would not have been possible through individual efforts alone. As companies continue to prioritize sustainability and social responsibility in their business strategies, the importance of collaboration in driving meaningful change will only continue to grow. By working together towards a common goal, companies can amplify their impact, accelerate their progress, and create a more sustainable future for all.
Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.
Image credit: Unsplash
Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.
In today’s rapidly changing and fiercely competitive business landscape, companies are constantly seeking ways to stay ahead of the curve and drive innovation. One of the key ingredients to building a truly innovative culture is diversity and inclusion. By embracing a wide range of perspectives, experiences, and backgrounds, organizations can unlock creativity, drive progress, and ultimately, achieve greater success in their endeavors.
Case Study 1: Google
A prime example of a company that has prioritized diversity and inclusion in fostering an innovative culture is Google. The tech giant has made significant strides in promoting diversity within its workforce, with initiatives such as unconscious bias training, diversity recruiting efforts, and employee resource groups for underrepresented groups. By actively seeking out diverse talent and creating a culture of inclusivity, Google has been able to tap into a wealth of diverse perspectives and ideas, leading to groundbreaking innovations such as Google Maps, Gmail, and other products that have revolutionized the tech industry.
Case Study 2: Airbnb
Another company that has demonstrated the power of diversity and inclusion in driving innovation is Airbnb. The hospitality platform has made diversity and inclusion a core part of its company culture, with initiatives such as unconscious bias training, diversity and inclusion workshops, and partnerships with organizations that support underrepresented communities. By actively promoting diversity in its workforce and fostering a culture of inclusion, Airbnb has been able to attract a diverse range of talent, leading to innovative ideas such as the Experiences feature, which allows users to book unique activities and experiences hosted by locals around the world.
In both of these case studies, we see the tangible benefits of diversity and inclusion in building an innovative culture. By bringing together individuals from a variety of backgrounds, experiences, and perspectives, companies are able to foster a culture of creativity, collaboration, and innovation. Diverse teams are more likely to challenge the status quo, think outside the box, and come up with innovative solutions to complex problems. Inclusive cultures also create a sense of belonging and psychological safety, encouraging employees to share their ideas, take risks, and push the boundaries of what is possible.
Conclusion
The importance of diversity and inclusion in building an innovative culture cannot be overstated. Companies that prioritize diversity and inclusion are not only able to attract top talent, but also drive creativity, foster collaboration, and ultimately, achieve greater success in their industries. By embracing diversity and creating a culture of inclusion, organizations can unlock the full potential of their employees, drive innovation, and stay ahead of the competition in today’s rapidly evolving business landscape.
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: misterinnovation.com
Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.
Given that innovation is responsible for roughly 85% of economic growth, it’s without a doubt a pretty big deal for the success of both individual organizations, as well as for the society at large.
However, to achieve the level of impact that many are looking for from innovation, you can’t simply “create something new”, and then just hope the results will come. You will need to commit to systematically pursuing those results by scaling viable ideas into products or businesses that create value – at scale.
That is of course easier said than done. If you think it’s hard to come up with innovations, just try scaling one up. In this article, we’ll explore the topic in more detail and provide you with actionable tips on how to actually scale an innovation.
What does it mean to scale an innovation?
To explain what it means to scale an innovation, let’s first take a step back and look at the lifecycle of an innovation.
To begin, every innovation starts from a rough idea or concept. Often you may have a specific goal in mind, or a problem to be solved, but sometimes it can just be a cool idea that you think could really make an impact. From there, you first need to validate that the idea makes sense, and then build a product or a service that meets a real need in the market.
With these steps taken care of, the next part is to scale the innovation. At this point, we have all the pieces in place to create value, but we haven’t yet unlocked that value for the vast majority of the available market.
So, as you may see from the chart above, scaling is the part where most of the value creation and impact comes from. With that said, we can define scaling an innovation as the process of expanding the presence and the use of the innovation to be as widespread as possible to maximize that impact.
Scaling innovation is the process of expanding the presence and the use of the innovation to be as widespread as possible to maximize the impact the innovation can have.
While on paper that sounds straightforward enough, it’s extremely important to first clarify the vision of what successful scaling looks like for your innovation, and what metrics you will use to measure your success here. For some, it might just be revenue or profit, for others it could be the number of customers or users, the impact you’ve delivered, and so on.
Most of these metrics are of course related, but when you start with the end in mind and gradually work backwards from there, you are much more likely to succeed because everyone in the organization will know what it actually is that you’re aiming for.
With that goal in mind, you can start narrowing in on the methods required to get there, which is what we’ll be focusing on next.
Dimensions of scaling an innovation
Traditionally, scaling innovation is seen as a matter of advancing the adoption, or the diffusion, of innovation. This is best visualized with a chart depicting the adoption curve, which you’ll find below.
The idea is that to scale an innovation, you need to cross that chasm and go from a few early adopters to the mainstream market where the volumes are significantly higher.
While that is certainly true, we can dig a bit deeper to understand scaling in a more nuanced, and more practical, way.
In reality, there are three dimensions to scaling an innovation.
Let’s look at each of them a little closer.
Scaling Up
First, scaling up is about creating the preconditions for scaling effectively.
Before we start talking about scaling up, we’ll assume that the basic prerequisites for scaling are in place, namely that there’s a clear vision and a product-market fit for your innovation, and that the market potential is large enough for there to be something to scale to, even if the market isn’t there today.
Assuming those prerequisites are there, you need to ensure that:
you can produce enough of the innovation to scale
you can do that efficiently enough to be financially and operationally viable
For some products, such as software and other immaterial goods, that first part is pretty straightforward. For others, such as most complex manufactured goods, even the first one will be a real challenge.
Having said that, the second part of being efficient enough will prove to be a challenge for virtually every innovation. Even for a software product, acquiring, serving, and retaining customers profitably at scale is often more difficult than people realize. For other, fundamentally less scalable goods and services, this is often excruciating.
In addition to these two more practical aspects, there’s a third and more ambiguous component to scaling up, and that is the social and institutional adoption of the innovation.
How well you scale up affects how large of a scale you can ultimately reach.
For example, with an innovation as mundane as the modern umbrella, men who used it were initially ridiculed. So, before the umbrella could really take off as an innovation, societal norms needed to change. In other cases, there may be regulatory hurdles or other institutional considerations that might need to be addressed before an innovation can ultimately scale.
Regardless of the specifics, scaling up is necessary for every innovation that wants to reach significant scale.
However, what many people don’t pay enough attention to is that how well you scale up affects how large of a scale you can ultimately reach. If you can’t produce the goods at volume, and at low enough of a price while still being profitable at a unit economics level, there’s an obvious limit to your potential to scale.
Scaling Out
Scaling out is what most people think of when it comes to scaling an innovation. It’s the geographical or demographical expansion of the innovation to a larger audience.
In its simplest form, scaling out simply means getting a wider market share and audience for the innovation within an existing market. As we covered earlier, this typically means moving from those early adopter market segments towards the mainstream.
Scaling out is what most people think of when it comes to scaling innovation as it’s where you expand the innovation to a larger audience.
However, it doesn’t have to be limited to just that. Sometimes the same products or services can be sold and used in other geographical areas, or even in other industries or entirely different use cases, both of which unlock new markets and additional demand, and thus lead to a larger impact for the innovation. A well-known example of this is Tesla using their experience and innovations in electric car batteries to expand to stationary energy storage.
Regardless of which path you choose, often these efforts to scale out to new segments or industries do require additional work to adapt the innovation or its positioning to the differing characteristics of these new segments, markets, and audiences.
Scaling out to new market segments can increase complexity a lot, so be mindful of the operational implications of your strategic decisions here.
This naturally adds complexity, which makes the scaling up part we covered earlier more challenging. So, be mindful of how you scale out and what the operational implications of your strategic decisions here will be.
Scaling Deep
The third, and the least well-known method for scaling innovation is scaling deep. This essentially means that you unlock more impact for your innovation by expanding and maximizing the use of it, typically for the people who already have access to it.
This usually requires you to either change people’s behavior to increase usage, or alternatively come up with innovative means for improving the utilization rate by enabling more people to make use of the same assets. Scaling deep is partly a matter of culture and mindset, and partly a more practical matter of having the right components in place for enabling and encouraging active use of the innovation.
A classic, albeit somewhat controversial example of the first type would be social media algorithms. They are designed to provide users with engaging content to keep them entertained and thus stay in the service for longer, which leads to more revenue from the same number of users.
An example of the second type would be cloud computing. By adding network, virtualization, and software layers on top of the computing hardware, cloud providers can get more use out of the same hardware, which unlocks value for both the service provider and the customers.
This is how Amazon not just significantly reduced costs in one of their major cost centers, IT infrastructure, but actually turned that into Amazon Web Services (AWS), an additional growth business that now accounts for the majority of the profits for the entire organization.
Scaling deep is about unlocking more impact for your innovation by expanding and maximizing the use of it. This can help reduce the need to scale up or out, or alternatively maximize the impact from doing so.
Scaling Deep can reduce the need to scale up or out, or alternatively, maximize the impact from doing so. As such, it’s an excellent compliment for most innovations. However, it’s just that: a compliment. Your primary method of scaling should always be either to Scale Up or Scale Out depending on whether your bottleneck is more on the supply or demand side.
Even in the case of AWS, which has created entirely new vectors for scaling out and has dramatically subsidized their costs for scaling up, it obviously wouldn’t have been possible without Amazon already being at significant scale.
What’s the takeaway? These dimensions are distinct but very much intertwined.
If you can scale on all three of these dimensions in a coordinated way, you will not only be much more likely to achieve significant scale with your innovation in the first place, but also maximize the potential for scale and impact from those efforts. If you build momentum on one of the dimensions, some of that momentum will carry over to the other dimensions, which again helps you accelerate change going forward.
As such, pay attention to each of these dimensions and try to consider all of them in your plans to scale innovation. That doesn’t mean you should focus on all three from the get-go, on the contrary, but planning with the big picture in mind can allow you to make much more educated decisions.
Scaling innovation in practice
As we’ve established above, there unfortunately isn’t a one-size fits all solution to scaling innovation.
Achieving breakthrough success with an innovation, which is the goal of scaling innovation, always requires many related and adjacent (usually more incremental) innovations.
This is an extremely common pattern that you will see happening over and over again if you just start paying attention to it. Square co-founder Jim McKelvey has done a great job in describing that in more detail in his recent book called the Innovation Stack.
A well-known example is the lightbulb. Edison patented his famous design back in 1879, but most households didn’t yet have access to electricity, so it wasn’t something they could benefit from. It took countless other innovations and another 45 years before even half of US homes had one, even though the benefits were obvious.
In practice, scaling an innovation is simply an iterative and exploratory process where you focus on eliminating whatever bottleneck is preventing you from scaling, one by one. And, as we saw in the example of the lightbulb, sometimes these can be much bigger and more fundamental than you may think at first.
Often you can just copy solutions other people have already used for the same or a similar problem (which you should always go for if you can), but many times you will also need to innovate something completely new and occasionally even go beyond your core product.
With that said, there are some common patterns that can be helpful for structuring your thinking when faced with some of these bottlenecks. However, as each innovation is ultimately new, and thus unique, these won’t necessarily fit every case.
Having said that, we’ll share one framework for each dimension of scaling below. We’ve also created a toolkit that includes the frameworks as editable templates, along with some examples and other supporting material, which you can download here.
Demand side
For most organizations and innovations, the demand side is likely the source of most bottlenecks.
The way we see it, this is not just about drumming up interest and demand for your product, but also about making sure that it fits the needs and budgets of the buyers in your market. And of course, you need to make sure you’re in a market, or at least one that has the potential to become, large enough to accommodate your scaling efforts.
Unlike what people often think, product-market fit isn’t enough for a business to be scalable. You also need to have the right business and operating models, as well as use the right channels.
In other words, scaling out isn’t just about product-market fit, as people often mistakenly think. You also need to have the right business and operating models and use the right channels. Brian Balfour has written an excellent five-part series about this, which I highly recommend you read.
The basic idea is pretty simple: your business needs to align all of these aspects in a cohesive manner to be able to scale. If even one of them is wrong, growth will feel like, as Balfour puts it, “pushing a boulder uphill”. It will take way too much capital, effort, and time. However, get the four elements right together, and the growth will come naturally.
What’s important to understand here is that the model isn’t a static picture you just do once. If the market changes, or you run into challenges that force you to change one of these elements, you’ll need to review each element and make sure the big picture still works.
Supply side
For some products and businesses, especially those with physical products, the supply side often becomes a key consideration.
Here, the bottlenecks can be extremely varied, and dependences on external suppliers can lead to challenges that are hard to overcome.
In general, what top innovators do differently from the rest of the companies is that they almost always vertically integrate their value chain as they are working towards scaling up.
There are many benefits to this approach, such as reduced overhead, but the key differences are in increased quality, and most importantly, the company’s ability to control their own destiny and innovate more freely because they’re not being constrained by their supply chain.
Top innovators vertically integrate their value chain to address bottlenecks and turn cost centers into additional sources of growth and profit.
The classic example is Apple, and the way that they control both the hardware and software of their products. In recent years, they’ve been increasing that integration in both directions. They’re moving upstream to offer more services on top of their operating systems, as well as downstream by designing their own processors, which has provided them with a big performance advantage.
However, there are many others. Amazon, Microsoft, Tesla, Google, Netflix, Nvidia, and pretty much every innovative company is trying to do the same in the scope of their own business.
The basic idea is again simple: if a part of your supply chain becomes a major bottleneck, or is a major cost center, you should try to take control of those parts to address the bottlenecks and turn cost centers into additional sources of growth and profit, just like Amazon has done with AWS, but also warehousing and shipping.
That isn’t to say that vertical integration wouldn’t be challenging or have downsides. It certainly is and does. Because of these limitations, it’s generally advisable to only vertically integrate to the parts of your supply chain that either are a clear bottleneck or could become a key competitive advantage for you. However, top innovators often have little choice but to take these steps if they want to move fast enough and have enough control to be able to scale their innovation to its full potential.
Another key consideration on the supply side is simply the architecture of your products and services, and the process you have for delivering them. It’s obviously much easier to have a scalable architecture and automated processes for purely software or content focused businesses, but how you craft these does play a huge role for complex physical products too.
This is again a very extensive topic on its own, but the goal should be to try to make the manufacturing, delivery, and service of your products as seamless and scalable as possible. As with everything else we’ve discussed so far, this too is an iterative process.
However, to provide you with a slightly more practical framework to get started, here’s Elon Musk explaining how he’s learned to approach this topic after his early struggles of trying to do that with the extremely complex products at SpaceX and Tesla.
While Musk specifically talks about the process in the scope of engineering for scale, these same principles also apply to your organization and internal processes too.
And, as Musk explained in the video, it’s easy to get tempted by the promises of optimizing for efficiency and automation, but if you haven’t addressed the big picture first, these will often end up just being a big waste of time and money.
So, make sure to start by first eliminating those unnecessary requirements and parts or tasks, and try to simplify the design before you focus too much on optimizing for efficiency and automating.
Utilization
In addition to supply and demand, we still have the third dimension of utilization to cover. The idea with this “scaling deep” part is to find creative ways to make the most out of existing supply to either unlock new demand, maximize the utilization of those assets, or simply to increase your customer retention by finding ways to get more value for them from your products.
As you may have guessed by now, the specifics vary quite a lot on a case-by-case basis, but the flowchart below can hopefully serve as a starting point for your efforts in this area.
To summarize, there are three common paths you may take here.
The first is to find ways to increase the usage of assets that are only being used a fraction of the time through practices such as asset sharing and virtualization.
The second is to move from one-off purchases to a subscription to eliminate friction and increase the usage of the services.
The third is to find additional ways to expand the use of the product. This is usually done either by finding new value-adding uses for the same product, or simply by activating usage through means such as improved quality, usability, better communication etc.
However, sometimes it might even be necessary to work around tougher and more pervasive issues, such as regulatory considerations or even the changing of societal norms.
While increased utilization isn’t often that glamorous or exciting, it can really make a difference in making your business and operating models efficient enough to allow you to scale volume faster and more sustainably.
Conclusion
Scaling an innovation won’t be easy. It will always take years, and an endless amount of hard work with an extreme focus on solving each and every bottleneck standing in your way.
Hopefully you’ll find some of the frameworks and playbooks we’ve introduced in this article useful for shaping your thinking, and for building your organization and processes, but you’ll inevitably come across plenty of challenges where you’ll just need to figure out the solutions yourself. Still, if you want to truly succeed with innovation, that’s what you’re in for.
So, be prepared for those challenges, and be realistic with your expectations and timelines. For example, the “growth gap” can easily sneak up on your organization if top management has unrealistic expectations for the financial returns of innovation.
In general, large organizations have some disadvantages, but they also have huge advantages when it comes to scaling an innovation, so look for ways to leverage those advantages to your benefit.
And finally, make sure to surround yourself with top talent that’s prepared for the ride. Scaling innovation is teamwork, and it takes a special kind of a team to pull it off. You need people that are used to constant change, have a growth mindset, and the skills needed to solve whatever problems your domain may have.
As mentioned, scaling innovation is a journey that happens in small increments, and at times, it will feel frustrating. But if your team persists, keeps on learning and solving problems, you can eventually close in on whatever the full potential of your innovation is.
Image credits: Pexels, Viima
This article was originally published in Viima’s blog.
Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.
In the regulatory filing for Facebook’s 2012 IPO, Mark Zuckerberg included a letter outlining his management philosophy. Entitled, The Hacker Way, it encapsulated much of the zeitgeist. “We have a saying,” he wrote. “‘Move fast and break things.’ The idea is that if you never break anything, you’re probably not moving fast enough.”
At around the same time, Katalin Karikó was quietly plodding away in her lab at the University of Pennsylvania. She had been working on an idea since the early 1990s and it hadn’t amounted to much so far, but was finally beginning to attract some interest. The next year she would join a small startup named BioNTech to commercialize her work and would continue to chip at the problem.
Things would accelerate in early 2020, when Karikó’s mRNA technology was used to design a coronavirus vaccine in a matter of mere hours. Just as Daniel Kahneman explained that there are fast and slow modes of thinking, the same can be said about innovating. The truth is that moving slowly is often underrated and that moving fast can sometimes bog you down.
The Luxury Of Stability
Mark Zuckerberg had the luxury of being disruptive because he was working in a mature, stable environment. His “Hacker Way” letter showed a bias for action over deliberation in the form of “shipping code,” because he had little else to worry about. Facebook could be built fast, because it was built on top of technology that was slowly developed over decades.
The origins of modern computing are complex, with breakthroughs in multiple fields eventually converging into a single technology. Alan Turing and Claude Shannon provided much of the theoretical basis for digital computing in the 1930s and 40s. Yet the vacuum tube technology at the time only allowed for big, clunky machines that were very limited.
A hardware breakthrough came in 1948, when John Bardeen, William Shockley and Walter Brattain invented the transistor, followed by Jack Kilby and Robert Noyce’s development of the integrated circuit in the late 1960s. The first computers were connected to the Internet a decade later and, a generation after that, Tim Berners-Lee invented the World Wide Web.
All of this happened very slowly but, by the time Mark Zuckerberg became aware of it all, it was just part of the landscape. Much like older generations grew up with the Interstate Highway System and took for granted that they could ride freely on it, Millennial hackers grew up in a period of technological, not to mention political, stability.
The Dangers Of Disruption
Mark Zuckerberg founded Facebook with a bold idea. “We believe that a more open world is a better world because people with more information can make better decisions and have a greater impact,” he wrote. That vision was central to how he built the company and its products. He believed that enabling broader and more efficient communication would foster a deeper and more complete understanding.
Yet the world looks much different when your vantage point is a technology company in Menlo Park, California then it does from, say, a dacha outside Moscow. If you are an aging authoritarian who is somewhat frustrated by your place in the world rather than a young, hubristic entrepreneur, you may take a dimmer view on things.
For many, if not most, people on earth, the world is often a dark and dangerous place and the best defense is often to go on offense. From that vantage point, an open information system is less an opportunity to promote better understanding and more of a vulnerability you can leverage to exploit your enemy.
In fact, the House of Representatives Committee on Intelligence found that agents of the Russian government used the open nature of Facebook and other social media outlets to spread misinformation and sow discord. That’s the problem with moving fast and breaking things. If you’re not careful, you inevitably end up breaking something important.
This principle will become even more important in the years ahead as the potential for serious disruption increases markedly.
The Four Disruptive Shifts Of The Next Decade
While the era that shaped millennials like Mark Zuckerberg was mostly stable, the next decade is likely to be one of the most turbulent in history, with massive shifts in demography, resources, technology and migration. Each one of these has the potential to be destabilizing, the confluence of all four courts disaster and demands that we tread carefully.
Consider the demographic shift caused by the Millennials and Gen Z’ers coming of age. The last time we had a similar generational transition was with the Baby Boomers in the 1960s, which saw more than its share of social and political strife. The shift in values that will take place over the next ten years or so is likely to be similar in scale and scope.
Yet that’s just the start. We will also be shifting in resources from fossil fuels to renewables, in technology from bits to atoms and in migration globally from south to north and from rural to urban areas. The last time we had so many important structural changes going on at once it was the 1920s and that, as we should remember, did not turn out well.
It’s probably no accident that today, much like a century ago, we seem to yearn for “a return to normalcy.” The past two decades have been exhausting, with global terrorism, a massive financial meltdown and now a pandemic fraying our nerves and heightening our sense of vulnerability.
Still, I can’t help feeling that the lessons of the recent past can serve us well in creating a better future.
We Need To Rededicate Ourselves Tackling Grand Challenges
In Daniel Kahneman’s book, Thinking, Fast and Slow, he explained that we have two modes of thinking. The first is fast and intuitive. The second is slow and deliberative. His point wasn’t that one was better than the other, but that both have their purpose and we need to learn how to use both effectively. In many ways, the two go hand-in-hand.
One thing that is often overlooked is that to think fast effectively often takes years of preparation. Certain professions, such as surgeons and pilots, train for years to hone their instincts so that they will be able to react quickly and appropriately in an emergency. In many ways, you can’t think fast without first having thought slow.
Innovation is the same way. We were able to develop coronavirus vaccines in record time because of the years of slow, painstaking work by Katalin Karikó and others like her, much like how Mark Zuckerberg was able to “move fast and break things” because of the decades of breakthroughs it took to develop the technology that he “hacked.”
Today, as the digital era is ending, we need to rededicate ourselves to innovating slow. Just as our investment in things like the human genome project has returned hundreds of times what we put into it, our investment in the grand challenges of the future will enable countless new (hopefully more modest) Zuckerbergs to wax poetic about “hacker culture.”
Innovation is never a single event. It is a process of discovery, engineering and transformation and those things never happen in one place or at one time. That’s why we need to innovate fast and slow, build healthy collaborations and set our sights a bit higher.
Intrapreneurs are employees trying to act like entrepreneurs, i.e. pursuing opportunity in their organizations with scarce resources with the goal of creating user defined value through the deployment of innovation. Many run into a brick wall.
Remember, it is easier to ask for forgiveness than for permission.
Do any job that needs to make your project work, regardless of your job description.
Come to work each day willing to be fired.
Recruit a strong team.
Ask for advice before resources.
Forget pride of authorship, spread credit wisely
When you bend the rules, keep the best interests of the company and its customers in mind.
Honor your sponsors
Underpromise and overdeliver
Be true to your goals, but realistic about ways to achieve them.
We’ve heard #1 a lot and it has become part of the lore of intrapreneurship and organizational behavior. But, is it really a good idea? It depends, and here are some reasons why:
Every organization, hospital and university has a culture of risk. Some cut you some slack. Some don’t.
It depends on the risk involved. Andrew Gove of Intel advised to ask for foregiveness, but don’t drill holes below the water line.
Sometimes, it ‘s better to keep what you are doing secret so as not to expose your idea too soon to the organizational immune system or people who are out to torpedo your success.
It takes a while to get your idea ready for prime time and validate assumptions. Better to fail early and off the radar than flop big.
Getting the resources you need will require imagination and political savvy. Sometimes that requires stealth and cunning.
Most organizations have archaic systems for prioritizing innovation or a new product portfolio. Asking for permission just puts you in dysfunctional queue.
Better to deliver your idea with as much value added as possible.
You are not the only one with the responsibility of moving your idea forward. Think about your team members and sponsors who have their necks out too.
One swallow does not a summer make. Even if you roll out a successful idea, people are going to want to know what you have done for them lately. Better to have a pipeline of products in development before launch. Platforms are more attractive than products.
Building sustainability takes time and is sometimes done better off the radar. Once you have a successful internal venture, people will come to you to take credit.
There are two kinds of innovators. Permission seekers start with the rules, create ecosystems that conform to them, create business models that are new or different and that foster innovation. Forgiveness seekers, do the same, but in reverse. They use technologies that have reached a coherence tipping point to create business models and ecosystems and then drive to change the rules to allow them to scale.
There is a lot to recommend stealth innovation. Beware of making too much noise and make it low impact at the beginning. Don’t use words, like “center”, “institute” or “innovation” that are likely to mobilize hostiles with competing interests. Practice digipreneur guerilla tactics. Watch out for snipers.
Arming yourself with anti-radar technology is usually a smart move. However, if you get shot down over enemy territory it might be hard to find you and you will be placing your search and rescue team members in jeopardy. Think twice before flying over hostile territory without a survival plan.
Sign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.
