Category Archives: Open Innovation

3 Ways to View Your Innovation Basket

(including one that makes Radical Innovation easy)

GUEST POST from Robyn Bolton

You are a rolling stone, and that means you gather no moss! You read the September issue of HBR (and maybe last week’s article), tossed out your innovation portfolio, and wove yourself an innovation basket to “differentiate the concept from finance and avoid the mistake of treating projects like financial securities, where the goal is usually to maximize returns through diversification [and instead] remember that innovation projects are creative acts.”

Then you explained this to your CFO and received side-eye so devastating it would make Sophie Loren proud.

The reality is that the innovation projects you’re working on are investments, and because they’re risky, diversification is the best way to maximize the returns your company needs.

But it’s not the only way we should communicate, evaluate, and treat them.

Different innovation basket views for different customers

When compiling an innovation basket, the highest priority is having a single source of truth. If people in the organization disagree on what is in and out of the basket, how you measure and manage the portfolio doesn’t matter.

But a single source of truth doesn’t mean you can’t look at that truth from multiple angles.

Having multiple views showing the whole basket while being customized to address each of your internal customer’s Jobs to be Done will turbocharge your ability to get support and resources.

The CFO: What returns will we get and when?

The classic core/adjacent/transformationa l portfolio is your answer. By examining each project based on where to play (markets and customers) and how to win (offerings, profit models, key resources and activities), you can quickly assess each project’s relative riskiness, potential return, time to ROI, and resource requirements.

The CEO: How does this support and accelerate our strategic priorities?

This is where the new innovation basket is most helpful. By starting with the company’s strategic goals and asking, “What needs to change to achieve our strategy?” leadership teams immediately align innovation goals with corporate strategic priorities. When projects and investments are placed at the intersection of the goal they support, and the mechanism of value creation (e.g., product, process, brand), the CEO can quickly see how investments align with strategic priorities and actively engage in reallocation decisions.

You: Will any of these ever see the light of day?

As much as you hope the answer is “Yes!”, you know the answer is “Some. Maybe. Hopefully.” You also know that the “some” that survive might not be the biggest or the best of the basket. They’ll be the most palatable.

Ignoring that fact won’t make it untrue. Instead, acknowledge it and use it to expand stakeholders’ palates.

Start by articulating your organization’s identity, the answers to “who we are” and “what we do.”

Then place each innovation in one of three buckets based on its fit with the organization’s identity:

Identity-enhancing innovations that enhance or strengthen the identity
Identity-stretching innovations that “do not fit with the core of an organization’s identity, but are related enough that if the scope of organizational identity were expanded, the innovation would fit.”
Identity-challenging innovations that are “in direct conflict with the existing organizational identity.”

It probably won’t surprise you that identity-enhancing innovations are far more likely to receive internal support than identity-challenging innovations. But what may surprise you is that core, adjacent, and transformational innovations can all be identity-enhancing.

For example, Luxxotica and Bausch & Lomb are both in the vision correction industry (eyeglasses and contact lenses, respectively) but have very different identities. Luxxotica views itself as “an eyewear company,” while Bausch & Lomb sees itself as an “eye health company” (apologies for the puns).

When laser-vision correction surgery became widely available, Bausch & Lomb was an early investor because, while the technology would be considered a breakthrough innovation, it was also identity-enhancing. A decade later, Bausch & Lomb’s surgical solutions and ophthalmic pharmaceuticals businesses account for 38% of the company’s revenue and one-third of the growth.

One basket. Multiple Views. All the Answers.

Words are powerful, and using a new one, especially in writing, can change your behavior and brain. But calling a portfolio a basket won’t change the results of your innovation efforts. To do that, you need to understand why you have a basket and look at it in all the ways required to maximize creativity, measure results, and avoid stakeholder side-eye.

Image Credit: Pixabay

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Why You Should Care About Service Design

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GUEST POST from Robyn Bolton

What if a tool had the power to delight your customers, cut your costs, increase your bottom line, and maybe double your stock price? You’d use it, right?

That’s precisely the power and impact of Service Design and service blueprints. Yet very few people, especially in the US, know, understand, or use them. Including me.

Thankfully, Leala Abbott, a strategist and researcher at the intersection of experience, innovation, and digital transformation and a lecturer at Parsons School of Design, clued me in.

What is Service Design?

RB: Hi, Leala, thanks for taking the time to talk with me today.

LA: My pleasure! I’m excited about this topic. I’ve managed teams with service designers, and I’ve always been impressed by the magical way they brought together experience strategy, UX, and operations.

RB: I felt the same way after you explained it to me. Before we get too geeked up about the topic, let’s go back to the beginning and define “service.”

LA: Service is something that helps someone accomplish a goal. As a result, every business needs service design because every business is in the service industry.

RB: I’ll be honest, I got a little agitated when I read that because that’s how I define “solution.” But then I saw your illustration explaining that service design moves us from seeing and problem-solving isolated moments to seeing an integrated process. And that’s when it clicked.

LA: That illustration is from Lou Downe’s talk Design in Government Impact for All . Service Design helps us identify what customers want and how to deliver those services effectively by bringing together all the pieces within the organization. It moves us away from fragmented experiences created by different departments and teams within the same company to an integrated process that enables customers to achieve their goals.

Why You Need It

RB: It seems so obvious when you say it. Yet so often, the innovation team spends all their time focused on the customer only to develop the perfect solution that, when they toss it over the wall for colleagues to make, they’re told it’s not possible, and everything stops. Why aren’t we always considering both sides?

LA: One reason, I think, is people don’t want to add one more person to the team. Over the past two decades, the number of individuals required to build something has grown exponentially. It used to be that one person could build your whole website, but now you need user experience designers, researchers, product managers, and more. I think it’s just overwhelming for people to add another individual to the mix. We believe we have all the tools to fix the problem, so we don’t want to add another voice, even if that voice explains the huge disconnect between everything built and their operational failures.

RB: Speaking of operational failures, one of the most surprising things about Service Design is that it almost always results in cost savings. That’s not something most people think about when they hear “design.”

LA: The significant impact on the bottom line is one of the most persuasive aspects of service design. It shifts the focus from pretty pictures to the actual cost implications. Bringing in the operational side of the business is crucial. Building a great customer journey and experience is important, but it’s also important to tie it back to lost revenue and increased cost to serve

Proof It Works

LA: One of the most compelling cases I recently read was about Autodesk’s transition to SaaS, they brought in a service design company called Future Proof. Autodesk wanted to transition from a software licensing model to a software-as-a-service model. It’s a significant transition not just in terms of the business model and pricing but also in how it affects customers.

If you’re a customer of Autodesk, you used to pay a one-time fee for your software, but now you are paying based on users and services. Budgeting becomes messy. The costs are no longer simple and predictable. Plus, it raises lots of questions about the transition, cost predictability, control over access, managing subscriptions, and flexibility. Notice that these issues are about people managing their money and increasing costs. These are the areas where service design can truly help.

Future Proof conducted customer interviews, analyzed each stage of the customer journey, looked at pricing models and renewal protocols, and performed usability studies. When they audited support ticket data for the top five common customer issues, they realized that if Autodesk didn’t change their model, the cost of running software for every customer would increase by 40%, and profit margins would decrease by 15% to 20%.

Autodesk made the change, revenue increased significantly, and their stock price doubled. Service design allows for this kind of analysis and consideration of operational costs.

How to Learn More

RB: Wow, not many things can deliver better service, happier customers, and doubling a stock price. Solid proof that companies, and innovation teams in particular, need to get smart on service design. We’ve talked a lot about the What and Why of Service Design. How can people learn more about the How?

LA: Lou Downe’s book is a great place to start Good Services: How to Design Services That Work. So is Woo, Wow, and Win: Service Design, Strategy, and the Art of Customer Delight by Thomas A Stewart and Patricia O’Connell. I also recommend people check out The Service Design Network for tools and case studies and TheyDo, which helps companies visualize and manage their service design.

Image Credit: Pixabay

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Leaders Avoid Doing This One Thing

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GUEST POST from Robyn Bolton

Being a leader isn’t easy. You must BE accountable, compassionate, confident, curious, empathetic, focused, service-driven, and many other things. You must DO many things, including build relationships, communicate clearly, constantly learn, create accountability, develop people, inspire hope and trust, provide stability, and think critically. But if you’re not doing this one thing, none of the other things matter.

Show up.

It seems obvious, but you’ll be surprised how many “leaders” struggle with this.

Especially when they’re tasked with managing both operations and innovation.

It’s easy to show up to lead operations.

When you have experience and confidence, know likely cause and effect, and can predict with relative certainty what will happen next, it’s easy to show up. You’re less likely to be wrong, which means you face less risk to your reputation, current role, and career prospects.

When it’s time to be a leader in the core business, you don’t think twice about showing up. It’s your job. If you don’t, the business, your career, and your reputation suffer. So, you show up, make decisions, and lead the team out of the unexpected.

It’s hard to show up to lead innovation.

When you are doing something new, facing more unknowns than knowns, and can’t guarantee an outcome, let alone success, showing up is scary. No one will blame you if you’re not there because you’re focused on the core business and its known risks and rewards. If you “lead from the back” (i.e., abdicate your responsibility to lead), you can claim that the team, your peers, or the company are not ready to do what it takes.

When it’s time to be a leader in innovation, there is always something in the core business that is more urgent, more important, and more demanding of your time and attention. Innovation may be your job, but the company rewards you for delivering the core business, so of course, you think twice.

Show up anyway

There’s a reason people use the term “incubation” to describe the early days of the innovation process. To incubate means to “cause or aid the development of” but that’s the 2^nd definition. The 1^st definition is “to sit on so as to hatch by the warmth of the body.”

You can’t incubate if you don’t show up.

Show up to the meeting or call, even if something else feels more urgent. Nine times out of ten, it can wait half an hour. If it can’t, reschedule the meeting to the next day (or the first day after the crisis) and tell your team why. Don’t say, “I don’t have time,” own your choice and explain, “This isn’t a priority at the moment because….”

Show up when the team is actively learning and learn along with them. Attend a customer interview, join the read-out at the end of an ideation session, and observe people using your (or competitive) solutions. Ask questions, engage in experiments, and welcome the experiences that will inform your decisions.

Show up when people question what the innovation team is doing and why. Especially when they complain that those resources could be put to better use in the core business. Explain that the innovation resources are investments in the company’s future, paving the way for success in an industry and market that is changing faster than ever.

You can’t lead if you don’t show up.

Early in my career, a boss said, “A leader without followers is just a person wandering lost.” Your followers can’t follow you if they can’t find you.

After all, “80% of success is showing up.”

Image credit: Pixabay

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A Top-Down Open Innovation Approach

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A Top-Down Open Innovation Approach

GUEST POST from Geoffrey A. Moore

For high-tech in much of the 20 century, when start-up capital was scarce and the need for it was great, innovation began at the core and migrated to the edge. Today we have the reverse. Start-up capital is plentiful, the need for it is modest, and innovation is thriving at the edge and moving reluctantly to the core, fearful of the inertia it will encounter once it gets there.

Yet if innovations are going to scale, they must leverage the core-edge dynamic in both directions. That means, in addition to enabling innovation from the bottom up—something today’s start-up enterprises are having great success in doing—we must also be able to manage it from the top down, from the core out, from the acquiring-sponsoring enterprise to acquired-innovating start-up. Here success is not so widespread, but there is a fix for that.

Geoffrey Moore Return on Innovation

In the core-edge dynamic, the job of the core acquiring institution is not to innovate—it is to get a return on innovation from wherever it is sourced. This could be an internal skunk works project, a major R&D project, a tuck-in acquisition, or a merger with another mature enterprise. The challenge is not, in other words, to bring innovation into existence but rather to capitalize on it in a meaningful way. That is what the pie chart above is all about.

The key claims of this model are 1) that there are three ways to get a positive return from an innovation investment and 2) that they are mutually exclusive. (There are also at least five ways to get a negative return which we will get to in a moment.)

The winning returns can come from:

Differentiation. To win here you must create an offer that dramatically outperforms its competitive set on at least one vector of innovation. You are playing for competitive separation, looking for a 10X result on at least one chosen vector, either in product performance, customer delight, or operational savings. This sort of thing creates the highest return on innovation possible. Think Apple iPad over any prior tablet (or arguably any tablet since).
Neutralization. To win here you must catch up to a competitor’s innovation sufficiently to get your offer back in the hunt. This means getting to “good enough” as quickly as possible. Here you are playing for speed—how fast can you get back in the game. Think Google Android catching up to (and then overtaking) the Apple iPhone.
Optimization. To win here you produce essentially the same offer on a better, faster, cheaper basis. Basically, you are extracting resources from an established effort in order to hit a new price-point, repurpose them for innovation elsewhere or simply taking to the bottom line. Here you are playing neither for separation nor for speed but rather for money. Think Nokia’s long history of success with feature phones.

The critical thing to note about these three sources of return is that they are at odds with one another. If you are going to get maximum separation, you cannot tell exactly when that will occur, so you cannot play for speed. Conversely, if you are playing for speed, you must suppress any impulse to go beyond a “good enough” standard. But in both cases you are willing to spend extra money to achieve your primary goal, be that separation or speed. That puts both approaches at odds with optimization, where the goal is to extract cost from the system.

The net of this is that top-down management of innovation requires leaders to charter their innovation teams with one—and only one—of these objectives. Where you have multiple needs, you need multiple teams. To understand why, let’s turn to look at how innovation investments fail to pay off.

There are at least five ways this can happen, as follows:

The innovation doesn’t work. Ouch. But that is the price of playing innovation poker. In fact, if you have no failed experiments, you probably are not taking enough risk.
The differentiation doesn’t go far enough. Yes, you create something different, but it is a far cry from a 10X separation, and so the market accepts it as good but does not grant you any competitive advantage for it. Basically, you just spent your R&D budget and have nothing to pay you back for it. HP and Dell have both suffered here greatly in recent years.
The neutralization doesn’t go fast enough. The team got caught up in out-doing the competition rather than simply getting to good enough. The problem is, the market will not pay you any return on improvements beyond good enough, so all you have done here is waste time, which is the one thing you cannot afford to waste when your product is out of the game. Nokia was a prime offender here with respect to its tardy response to the iPhone challenge.
The optimization doesn’t go deep enough. Basically, you optimize around the edges and do not attack any of the sacred cows (typically meaning you do not touch either engineering or sales). The gains are minimal, and the bottlenecks that are holding you back are still deeply in place. Ginny Rometti made a version of this point in one of IBM’s earnings calls, but so could every other Tech 50 CEO in any given quarter. This is a really big problem because tech has never been good at optimization.
The innovation project blended two or more goals. The problem here is that either the differentiation goal slowed you down or the neutralization goal dumbed you down or the optimization goal tied you down. One way or another, you went down.

So the net here is simple. Managing innovation is a different discipline from innovating per se. It is all about controlling the charter, targeting one and only one kind of return, and then focusing the team solely on that set of outcomes. It isn’t all that cool. It is just very, very important.

That’s what I think. What do you think?

Image Credit: Pexels

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How to Make Navigating Ambiguity a Super Power

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GUEST POST from Robyn Bolton

You are a leader. The boss. The person in charge.

That means you know the answer to every question, make the right decision when faced with every choice, and act confidently when others are uncertain. Right?

(Insert uproarious laughter here).

Of course not. But you act like you do because you’re the leader, the boss, the person in charge.

You are not alone. We’re all doing it.

We act like we have the answers because we’ve been told that’s what leaders do. We act like we made the right decision because that’s what leaders do in a volatile, uncertain, complex, and ambiguous (VUCA) world where we must work quickly and flexibly while doing more with less.

But what if we didn’t?

What if we stopped pretending to have the answer or know the right choice? What if we acknowledged the ambiguity of a situation, explored its options and interpretations for just a short while, and then decided?

We’d make more informed choices. We’d be more creative and innovative. We’d inspire others.

So why do we keep pretending?

Ambiguity: Yea! Meh. Have you lost your mind?!?

Stanford’s d.School calls the ability to navigate ambiguity “the super ability” because it’s necessary for problem-finding and problem-solving. Ambiguity “involves recognizing and stewing in the discomfort of not knowing, leveraging and embracing parallel possibilities, and resolving or emerging from ambiguity as needed.”

Navigating ambiguity is essential in a VUCA world, but not all want to. They found that people tend to do one of three things when faced with ambiguity:

Endure ambiguity as “a moment of time that comes before a solution and is antagonistic to the objective – it must be conquered to reach the goal.”
Engage ambiguity as “an off-road adventure; an alternate path to a goal. It might be rewarding and helpful or dangerous and detrimental. Its value is a chosen gamble. Exhilaration and exhaustion are equally expected.”
Embrace ambiguity as “oceanic and ever-present. Exploration is a challenge and an opportunity. The longer you spend in it, the more likely you are to discover something new. Every direction is a possibility. Navigation isn’t simple. It requires practice and patience.

Students tend to enter the program with a resignation that ambiguity must be endured. They leave embracing it because they learn how to navigate it.

You can too.

In fact, as a leader in a VUCA world, you and your team need to.

How to Embrace (or at least Engage) Ambiguity

When you want to learn something new, the library is one of the best places to start. In this case, the Library of Ambiguity – an incredible collection of the resources, tools, and activities that professors at Stanford’s d.School use to help their students build this super ability.

It’s easy to get overwhelmed by the number of resources, so here are three that I recommend:

Design Project Scoping Guide

What it is: A guide for selecting, framing, and communicating the intentions of a design project
When to use it: When you are defining an innovation project and need to align on scope, goals, and priorities
Why I like it: The guide offers excellent examples of helpful and unhelpful scoping documents.

Learning Zone Reflection Tool

What it is: A tool to help individuals better understand the tolerance of ambiguity, especially their comfort, learning, and panic zones
When to use it: Stanford used this as a reflection tool at the end of an introductory course, BUT I would use it at the start of the project as a leadership alignment and team-building tool:
- Leadership alignment – Ask individual decision-makers to identify their comfort, learning, and panic zones for each element of the Project Scoping Guide (problem to be solved, target customer, context, goals, and priorities), then synthesize the results. As a group, highlight areas of agreement and resolve areas of difference.
- Team-building – At the start of the project, ask individual team members to complete the worksheet as it applies to both the project scope and the process. Individuals share their worksheets and, as a group, identify areas of shared comfort and develop ways to help each other through areas of learning or panic.
Why I like it: Very similar to the Project Playground concept I use with project teams to define the scope and set constraints, it can be used individually to build empathy and support amongst team members.

Team Dashboards

What it is: A tool to build trust and confidence amongst a team working through an ambiguous effort
When to use it: At regular pre-defined intervals during a project (e.g., every team check-in, at the end of each Sprint, once a month)
What I like about it:
- Individuals complete it BEFORE the meeting, so the session focuses on discussing the dashboard, not completing it
- The dashboard focuses on the usual business things (progress against responsibilities, the biggest challenge, next steps) and the “softer” elements that tend to have the most significant impact on team experience and productivity (mood, biggest accomplishment, team balance between talking and doing)

Learn It. Do It.

The world isn’t going to get simpler, clearer, or slower. It’s on you as a leader to learn how to deal with it. When to slow it down and explore and when to speed it up and act. No one is born knowing. We all learn along the way. The Library will help. No ambiguity about that!

Image credit: Pexels

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10 Military Innovation Moments

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GUEST POST from Robyn Bolton

Innovation is something different that creates value. Sometimes it’s big, new to the world, world-changing things. Sometimes it’s a slight tweak to make things easier, faster, cheaper or better.

Sometimes, it’s both.

It’s no secret that the military and NASA are birthplaces of incredible inventions (something new) and innovations (something different that creates value). Most people know that Velcro, nylon, and powdered drinks (Tang!) originated at Nasa, and that Jeep, GPS, and the internet come to us from the military.

But did you know that these 10 everyday innovations have their origin in the military?

1. Duct Tape

Invented in 1942 to seal ammo boxes with something that could resist water and dirt while also being fast and easy to remove so soldiers could quickly access ammunition when they needed it. Originally, it was made by applying a rubber-based adhesive to duck cloth, a plain and tightly woven cotton fabric, and has evolved over the years to be used for everything from repairing equipment on the moon to purses.

2. Synthetic Rubber Tires

Speaking of rubber, prior to WWII, most rubber was harvested from trees in South America and shipped to southern Asia where the majority of rubber products were produced. When the Axis powers cut-off access to Asia, the US military turned to Firestone, Goodyear, and Standard Oil to create a replacement substance. The recipe they created is still used today.

3. Silly Putty

Like most inventions, there were a lot of failed experiments before the right synthetic rubber recipe was found. Silly Putty is the result of one of those experiments. A scientist at GE developed the strange substance but quickly shelved it after it became clear that it had no useful military application. Years later, GER execs started showing off the novelty item at cocktail parties, an advertising exec in attendance saw its commercial potential and bought the manufacturing rights, packaged it into eggs and sold it as a toy. 350 million eggs later, we’re still playing with it.

4. Superglue

The result of another failed experiment, Superglue came onto the market in 1958 and has stuck around ever since (sorry, that pun was intended). Military scientists were testing materials to use as clear plastic rifle sights and created an incredibly durable but impossibly sticky substance called cyanoacrylate. Nine years later it was being sold commercially as Superglue and eventually did make its way into military use during the Vietnam War as a way to immediately stop bleeding from wounds.

5. Feminine Hygiene Pads

Image Credit: Museum of American History

Before Superglue was used to stop bleeding, bandages woven with cellulose were used on the battlefields and hospitals. Seeing how effective the bandages were at holding blood and the convenience of having so many on hand, US and British WW1 nurses began using them as sanitary napkins and bandage makers adapted and expanded their post-War product lines to accommodate.

6. Undershirts

Image Credit: Foto-ianniello/Getty Images

While people have been wearing undergarments for centuries, the undershirt as we know it — a t-shaped, cotton, crewneck — didn’t come into being until the early twentieth century. Manufactured and sold by the Cooper Underwear Co., it caught the Navy’s eye as a more convenient and practical option than the current button-up shirts. In 1905, it became part of the official Navy uniform and the origin of the term “crewneck.”

7. Aerosol Big Spray

Soldiers fighting in the Pacific theater of WWII had a lot to worry about, so they were eager to cross mosquitos and malaria off that list. In response, the Department of Defense teamed up with the Department of Agriculture to find a way to deliver insecticide as a fine mist. The first aerosol “bug bomb” was patented in 1941 and, thanks to the development of a cheaper plastic aerosol valve, became commercially available to civilians in 1949.

8. Canned Food

Image Credit: Pacific Paratrooper — WordPress.com

While it’s not surprising that canned foods were originally created for the military, it may surprise you to learn that it was Napoleon’s armies that first used the concept. In response to the French Government’s offer of a large cash reward for anyone who could find a way to preserve large quantities of food, an inventor discovered that food cooked inside a jar wouldn’t spoil unless the seal leaked, or the container was broken. But glass jars are heavy and fragile, so innovation continued until WW1 when metal cans replaced the glass jars.

9. Microwave

RadaRange on the Nuclear Ship NS Savannah

This is another one that you probably would have guessed has its origins in the military but may be surprised by its actual origin story. The term “microwave” refers to an adaptation of radar technology that creates electromagnetic waves on a tiny scale and passes those micro-waves through food, vibrating it, and heating it quickly. The original microwaves made their debut in 1946 on ships but it took another 20 years to get the small and affordable enough to be commercially viable.

10. Wristwatches

Watches first appeared on the scene in the 15th century but they didn’t become reliable or accurate until the late 1700s. However, up until the early 20th century, wristwatches were primarily worn as jewelry by women and men used pocket watches. During its military campaigns in the late 1880s, the British Army began using wristwatches as a way to synchronize maneuvers without alerting the enemy to their plans. And the rest, as they say, is history.

So, there you have it. 10 everyday innovations brought to us civilians by the military. Some, like synthetic rubber, started as intentional inventions (something new) and quickly became innovations (something new that creates value). Some, like superglue and silly putty, are “failed” experiments that became innovations. And some, like undershorts and feminine products, are pure innovations (value-creating adaptations of pre-existing products to serve different users and users).

Sources: USA Today, Pocket-lint.com, and Mic.com

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The Pitfalls of Crowdsourcing

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How to Overcome Them to Spur Innovation

The Pitfalls of Crowdsourcing: How to Overcome Them to Spur Innovation

GUEST POST from Diana Porumboiu

There is a lot of buzz around open collaboration as a driver for innovation. Studies, academia, research, and the myriad of examples from companies are boasting about the amazing results brought by ideas from external parties. A study shows that 85% of the top global brands have used crowdsourcing during the last decade.

But is crowdsourcing truly effective to spur innovation? Even though its popularity increased so much, there’s also plenty of evidence that dispute its effectiveness.

As tempting as it is to fall into the trap of the latest trends in innovation methods, it’s not wise to jump headfirst. So, we decided to write this article and show you the hard facts of crowdsourcing, which will help you decide if this is something your organization can benefit from.

For this, we’ll explain the pitfalls of crowdsourcing and provide practical tips on how to overcome them. To put things in perspective, let’s start with the broader picture, of what crowdsourcing is, or isn’t.

What is crowdsourcing?

As the word indicates, crowdsourcing is all about leveraging the power of the crowds. If you’ve been reading our blog, or worked with innovation topics before, you might think that we are actually referring to open innovation. Not quite. Indeed, the two terms are oftentimes used interchangeably, and the concepts are similar.

But it’s best to make the difference between the two, because setting on the right terminology will also help you better communicate your innovation initiatives to your organization, and to external stakeholders too.

Basically, both crowdsourcing and open innovation refer to engaging external individuals to participate in the innovation process by suggesting ideas and solutions to a specific topic.

Crowdsourcing is the practice of obtaining ideas, solutions, or services from a large, sometimes undefined group of people through an open call. It is a process that leverages the collective intelligence and creativity of a crowd to solve problems, generate new ideas, or carry out tasks.

On the other hand, open innovation includes many other activities that involve people outside the initial working group (open data, scouting, trend research, idea management, etc.). If you want to learn more about the topic, our blog provides vast resources on open innovation which you can find here.

Now, while open innovation, as the name states, is specifically done to generate more innovation, crowdsourcing is used in other contexts too. Methods like crowd labor, crowdfunding, or crowd curation can be valuable if you need to outsource routine and well-defined tasks, manual work or fund your project. These can, in fact, be part of an innovation strategy, but they are not specifically targeting innovation.

That’s where crowdsourcing for innovation comes into play, and what we’ll focus on next.

The pitfalls of crowdsourcing

While crowdsourcing can be an effective way to generate ideas, solve problems, and engage with a community, unless it is properly planned, executed, and managed, it can come up short.

Let’s take a closer look at each of these pitfalls.

Risk management:

There are many risks that come with open collaboration, and some of the most cited are intellectual property and data privacy. Organizations are apprehensive about exposing themselves to the large public and weary about potential conflicts that could arise from ownership, and copyright as well as exposure to competitors.

So, when considering crowdsourcing as part of your innovation strategy, you should weigh the risks associated with it.

There are four main things to keep in mind when it comes to legal risks associated with crowdsourcing:

Existing patents and patents protection for technical solutions
- Trademarks applicable when sourcing new product names, logos or brands
Design of the visual appearance of new products
Copyrights for any original texts

That’s why it’s best to have clearly pre-defined contractual terms, NDAs and confidentiality agreements that deal with intellectual property ownership and data protection. So, make sure to establish clear ownership and copyright guidelines upfront.

This can include requiring contributors to agree to terms and conditions that grant the sponsoring organization the right to use and modify the contributions. Providing clear attribution and recognition for contributors can also help to avoid disputes over ownership. Rewarding participation doesn’t just help with motivation and engagement, but it can also mitigate the legal risks.

Crowd management:

The success of your crowdsourcing initiative hinges on the participation of individuals who provide ideas. However, many crowdsourcing projects fall short due to low engagement levels, inadequate idea generation, or low quality.

These issues may arise because contributors don’t recognize the significance of their contributions, lack motivation, misunderstand project requirements, or are unaware of the initiative.

Because crowdsourcing initiatives require a lot of time, effort and specific skills it’s best to delegate the project to someone who is not involved in everyday innovation activities (if you have those already in place).

Even so, crowdsourcing should still be aligned with the overall innovation and strategic goals, and therefore managed as part of existing processes.

To ensure crowdsourcing runs smoothly, contributors are engaged, decide on the roles and responsibilities for managing the process and ensure that there is adequate support for contributors.

Also, to reach the right people, and as many as possible, you should design effective campaigns that encourage participation.

To ensure quality control establish clear guidelines and criteria for contributions. This can include specific requirements for content, format, and presentation, as well as screening and review processes to filter out low-quality or irrelevant contributions.

Using a platform that allows for peer-review or voting can also help to separate the wheat from the chaff. This what can also facilitate evaluation, which we’ll explore next in more detail.

Idea evaluation:

Evaluating ideas is one of the most complex and challenging aspects of idea management, particularly when it comes to crowdsourcing initiatives where you have a significant number of ideas to sift through and assess.

First, it can be time-consuming and overwhelming to select the ideas to develop.
Second, ideas and perspectives might differ so there will be inconsistency and biases in the evaluation process.
Third, there is a tendency to pick the familiar over the distant ones.
And last, there is also the issue of the quality and level of detail of ideas varying widely, making it difficult to determine which ideas are truly innovative and valuable.

With all these challenges, you could overlook potentially great ideas. What’s more, in a crowdsourcing environment, there is often limited interaction between the idea generators and the evaluators, which can make it challenging to provide feedback and refine the ideas further.

To mitigate this, you need a methodical framework for evaluating ideas. You can learn everything about idea evaluation from this article.

In short, to create an evaluation process that works for you, it’s best to decide on a set of criteria that can help you sift through the ideas. For example, Viima’s evaluation tool gives you the flexibility to choose your own metrics and then analyze and make decisions based on those criteria, without the hassle of going through each of every idea individually.

To have a clearer understanding of how this works in practice, try out the crowdsourcing board template. We set it up so you can easily and safely start collecting ideas from outside the organization.

But remember that even with the best tool, before opening up the organization to the crowds, you will still have to work out your internal process and how that fits into the bigger picture, which takes us to the next point.

Process integration:

Poorly designed or executed processes can lead to low-quality submissions or misunderstandings about the goals of the initiative. A study suggests that besides the issue of managing crowds, organizations also fail to create a process around it.

This is a trap in which many organizations fall. Unless you build a process and plan that goes beyond the first steps of the crowdsourcing initiative, you might waste a lot of time and distract internal teams from using the time and resources on actually executing the strategy.

So, first thing first is to ask yourself if crowdsourcing will serve a bigger purpose. If so, how will it be part of your internal processes and what resources it will require? Crowdsourcing shouldn’t impede internal practices and processes. It should align with the overall strategy and provide value for the organization.

Crowdsourcing shouldn’t impede internal practices and processes. It should align with the overall strategy and provide value for the organization.

Although we have discussed a number of potential pitfalls of crowdsourcing, it’s important to recognize that these issues are often complex and multifaceted. As such, there is rarely a single reason for failure.

To provide a more comprehensive understanding of crowdsourcing, we will next look at some examples of both failed and successful initiatives.

When crowdsourcing goes wrong

1. Pepsi Refresh

In 2010, Pepsi launched “Pepsi Refresh”, a crowdsourcing initiative that invited people to submit their ideas for projects that could benefit their communities, with the winning ideas receiving funding from Pepsi.

While the initiative generated significant attention, it was ultimately considered a failure. Even though in terms of reach and visibility the campaign was a great success, the goal of increasing sale was missed. In fact, “Pepsi Refresh” did the opposite, losing the parent company some $350m.

One reason was the lack of alignment between the initiative and Pepsi’s core brand message. While Pepsi had traditionally focused on promoting its products, the Refresh Project shifted the company’s focus to community engagement and social responsibility.

Another issue with the Refresh Project was the complexity of the submission and voting processes. There were also concerns about transparency and fairness in the voting process. Some critics suggested that the system was easily manipulated, allowing certain ideas to receive more votes than they deserved, while others were unfairly overlooked.

This outcome highlights the importance of ensuring alignment with business strategy and values, as well as the big role played by transparency.

2. Nokia’s “IdeasProject”

Nokia’s “IdeasProject” was a crowdsourcing initiative launched in 2008 to gather ideas from customers and the public for the company’s product development. While the initiative generated significant interest and engagement from users, it ultimately failed to produce significant results, and was eventually discontinued.

One reason for the failure of the IdeasProject was a lack of follow-through and implementation of the ideas generated. While thousands of ideas were submitted and discussed on the platform, few were actually developed or brought to market by Nokia. This led to disillusionment and disengagement among users, who felt that their contributions were not valued or taken seriously.

Another issue was the lack of clear communication and marketing of the IdeasProject. Many customers and potential contributors were not aware of the initiative or did not understand its purpose, which limited the overall reach and impact of the platform.

3. Yahoo’s “Assignments”

In 2007, Yahoo launched “Assignments,” a platform aimed to leverage the collective intelligence of its users to generate high-quality content. The initiative allowed users to submit original content, including articles, photos, and videos, which other users could rate and review. Yahoo planned to use the best-rated content to enhance its news and information websites.

Yahoo failed to create a strong community around the initiative, which made it difficult to generate high-quality content. Furthermore, there were concerns about copyright violations, as some of the content submitted by users was copyrighted material.

Because the platform was plagued with issues, including a lack of quality control over articles submitted and disputes over payments to writers, the platform was eventually shut down in 2012.

When crowdsourcing goes right

Despite the challenges associated with crowdsourcing, we should acknowledge that there is still potential for success, and not all crowdsourcing efforts are doomed to fail.

1. Linux

Linux is a popular open-source operating system that was developed through a crowdsourcing initiative. The project was started by Linus Torvalds in 1991, who was a computer science student at the University of Helsinki in Finland. Torvalds wanted to create a free and open operating system that could be used by anyone, and he enlisted the help of other developers from around the world to contribute to the project.

The project’s success is attributed to its collaborative and decentralized development model, which fosters innovation and customization, as well as a strong community of passionate and supportive developers. Moreover, Linux’s technical merits, such as stability, security, and flexibility, make it a popular choice for a diverse range of applications, from web servers and supercomputers to smartphones and home appliances.

2. Ford

The “Make it Driveable” crowdsourcing campaign by Ford was launched in 2018 to gather ideas and solutions for making vehicles more accessible to people with disabilities. The campaign invited individuals and organizations to submit their ideas for features or modifications that would make driving and traveling in a car easier for people with disabilities.

The campaign engaged a diverse range of people and organizations, including disability advocates, engineers, and designers, in the co-creation process who generated a broad range of innovative ideas and solutions.

The “Make it Driveable” campaign showcased Ford’s innovation and leadership in the automotive industry, demonstrating the potential for crowdsourcing to drive meaningful change and create value for both the company and its stakeholders.

3. Lego

As mentioned above, Lego’s crowdsourcing platform, Lego Ideas has been running successfully since 2008. The platform allows Lego fans to submit their own designs for new Lego sets, and the community votes on their favorite designs. The Lego Ideas platform has been hugely successful, with several of the winning designs becoming popular and highly sought-after sets.

For Lego, crowdsourcing is a cost-effective approach to supplement its in-house capabilities and expand their line of products. Even more, because of the voting system they can assess whether a product idea has potential and demand among its customers.

For participants, Lego Ideas provides a valuable platform to share and contribute to the company’s mission of inspiring future builders. Users can gain recognition from their peers for their ideas and benefit financially if their product is successfully released to the market.

These are just a few examples which show how crowdsourcing can be applied successfully, as long as it’s in line with the company’s core values and goals, and it’s built on a framework that enables systematic use of the ideas from outside the organization.

But as previous examples have shown, crowdsourcing can also go wrong even for the most successful organizations. These examples can hopefully help you make a more informed decision, and inspire in the way you approach crowdsourcing, or open collaboration in general.

To recap, you need alignment between your crowdsourcing initiatives and the overarching strategy, integration with internal processes, a framework that enables idea management, evaluation and development and last but not least, an effective campaign to gather the crowds around your organization.

How to start crowdsourcing

First thing first. Does crowdsourcing align with your current strategic plans? If it does, the first step is to develop a clear plan for using crowdsourcing effectively.

If you are not sure which way to go, as a first step in choosing your approach, you can find inspiration in this chart from Deloitte, which shows a variety of crowdsourcing activities that cater for different needs.

Viima Crowdsourcing 1

Depending on your strategy, industry, and your company profile, you will probably know what type of crowdsourcing is most appropriate for your organization.

This will help you decide on other factors such as the type of contributions you are after, the resources required, and the audience you will target.

Viima Crowdsourcing 2

1. Define your goals and set boundaries

The first step is to set clear goals for your crowdsourcing campaign. What do you want to achieve: is it brand awareness, ideas for improving products or customer satisfaction?

Decide on a set of metrics that will help you evaluate the success of the campaign and measure its impact. This will help you adjust as needed but also set realistic targets about the outcomes you think are possible. If you’re set to get disruptive or completely novel ideas that require technical knowledge and complex solutions, you have to carefully consider whom you want to target with the campaign.

2. Define the target audience and the engagement mechanisms

This step is essential for the success of your crowdsourcing. Without the right participants, you won’t have enough relevant ideas.

Think about who would have the most knowledge and expertise in this area and who would be most interested in providing their ideas and insights. Consider demographics such as age, occupation, location, and interests.

Depending on the goals you set or the types of ideas you are after, you will need different audiences. Sometimes there might be more generic ones, while in other cases you will want specific people with knowledge of the topic or interest in the field. On the other hand, sometimes it is more beneficial to have a diverse audience that can bring new and fresh ideas.

Once you have identified your target audience, you need to develop engagement mechanisms that will motivate them to participate in your crowdsourcing campaign.

Engagement mechanisms refer to the various ways in which you can interact with your target audience and encourage them to contribute their ideas. These mechanisms may include online platforms, social media channels, email campaigns, targeted advertising, events, and rewards or incentives.

It’s important to remember that engagement mechanisms should be designed specifically for the target audience.

3. Decide on a platform to support your activities

Once you have decided on the goals, determined the target audience, and the engaging mechanisms, you should next look for a platform that can cater to all your needs.

The platform should act as a transparent communication and exchange forum for participants. It should be easily accessible and simple to use, but also flexible enough to allow different use cases.

As mentioned above, many crowdsourcing failures are related to the inability of organizations to manage and integrate the initiative in their existing processes. Providing feedback and encouraging ongoing participation are also other important elements to consider when scouting for a crowdsourcing tool.

To get an idea of what open innovation platforms are out there and how they can be used for crowdsourcing, you can read this Guide to Open Innovation Platforms: How to Unlock the Power of Collaboration.

The selection criteria should consider factors such as accessibility to the target audience, the ability to integrate relevant engagement mechanisms to promote ongoing participation, and the capability to distribute incentives after the completion of activities.

4. Pilot and iterate

Consider starting with a pilot initiative to test the approach before scaling up.

No matter how well you prepare for something new, like crowdsourcing might be for some, you will most likely stumble a couple of times. And that’s completely fine.

No amount of research and shortlisting will give you the full scope of how it works in practice for your organization. That’s why it’s important to pilot on a smaller scale. And once you’re happy with the pilot results you are ready to scale up.

Doing pilots allows you to test the platform, check for compatibility with the platform, and test your plan and ways of working.

If you are not sure about the first step, get started with a platform and see how it would work in practice internally. Some vendors offer free user-based versions, like us here at Viima, and some have demos or other free trials.

Additionally, piloting may also help evaluate if you’re searching via the wrong criteria (of if your goals are misguided), or if your ways of working or processes are wrong for what you want to achieve. Also, consider using feedback from participants to iterate and refine the initiative over time.

Conclusions

As you can see, just as there are good parts about crowdsourcing, there are also bad ones. There is no one size fits all solution when you want to innovate, and just like many other methods and tools, crowdsourcing can be a great enabler for innovation.

Regardless of the pitfalls and numerous failures from other companies, crowdsourcing can still be highly beneficial for your organization.

To summarize, let’s recap the positive aspects of using crowdsourcing for innovation and the main factors to consider to fully leverage its benefits.
First, for crowdsourcing to work well, it should make sense for the organization’s strategy and overall goals. Make a plan, assess the needs and the capabilities to manage a process like this. Because indeed, crowdsourcing should be designed as a process that complements, and doesn’t hinder other activities within the organization.

Second, make sure you choose the right platform from the get-go. For optimal results you should aim for something that is flexible enough that allows multiple uses, from external idea collection to managing the entire innovation process.

Lastly, don’t over-rely on technology either, because that is just a tool that helps you move forward and be more efficient. The true benefits come when you start building connections, nurture talent and find new approaches to solve problems.

Image credits: Viima, Pixabay

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Why Data-Based Decisions Will Lead You Straight to Hell

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Why Data-Based Decisions Will Lead You Straight to Hell

GUEST POST from Robyn Bolton

Many years ago, Clay Christensen visited his firm where I was a partner and told us a story*.

“I imagine the day I die and present myself at the entrance to Heaven,” he said. “The Lord will show me around, and the beauty and majesty will overcome me. Eventually, I will notice that there are no numbers or data in Heaven, and I will ask the Lord why that is.”

“Data lies,” the Lord will respond. “Nothing that lies can be in Heaven. So, if people want data, I tell them to go to Hell.”

We all chuckled at the punchline and at the strength of the language Clay used (if you ever met him, you know that he was an incredibly gentle and soft-spoken man, so using the phrase “go to Hell” was the equivalent of your parents unleashing a five-minute long expletive-laden rant).

“If you want data, go to Hell.”

Clay’s statement seems absolutely blasphemous, especially in a society that views quantitative data as the ultimate source of truth:

“In God we trust. All others bring data.” W. Edward Deming, founding Father of Total Quality Management (TQM)
“Above all else, show the data.” – Edward R. Tufte, a pioneer in the field of data visualization
“What gets measured gets managed” – Peter Drucker, father of modern management studies

But it’s not entirely wrong.

Quantitative Data’s blessing: A sense of safety

As humans, we crave certainty and safety. This was true millennia ago when we needed to know whether the rustling in the leaves was the wind or a hungry predator preparing to leap and tear us limb from lime. And it’s true today when we must make billion-dollar decisions about buying companies, launching products, and expanding into new geographies.

We rely on data about company valuation and cash flow, market size and growth, and competitor size and strategy to make big decisions, trusting that it is accurate and will continue to be true for the foreseeable future.

Quantitative Data’s curse: The past does not predict the future

As leaders navigating an increasingly VUCA world, we know we must prepare for multiple scenarios, operate with agility, and be willing to pivot when change happens.

Yet we rely on data that describes the past.

We can extrapolate it, build forecasts, and create models, but the data will never tell us with certainty what will happen in the future. It can’t even tell us the Why (drivers, causal mechanisms) behind the What it describes.

The Answer: And not Or

Quantitative data Is useful. It gives us the sense of safety we need to operate in a world of uncertainty and a starting point from which to imagine the future(s).

But, it is not enough to give the clarity or confidence we need to make decisions leading to future growth and lasting competitive advantage.

To make those decisions, we need quantitative data AND qualitative insights.

We need numbers and humans.

Qualitative Insight’s blessing: A view into the future

Humans are the source of data. Our beliefs, motivations, aspirations, and actions are tracked and measured, and turned into numbers that describe what we believed, wanted, and did in the past.

By understanding human beliefs, motivations, and aspirations (and capturing them as qualitative insights), we gain insight into why we believed, wanted, and did those things and, as a result, how those beliefs, motivations, aspirations, and actions could change and be changed. With these insights, we can develop strategies and plans to change or maintain beliefs and motivations and anticipate and prepare for events that could accelerate or hinder our goals. And yes, these insights can be quantified.

Qualitative Insight’s curse: We must be brave

When discussing the merit of pursuing or applying qualitative research, it’s not uncommon for someone to trot out the saying (erroneously attributed to Henry Ford), “If I asked people what they wanted, they would have said a horse that goes twice as fast and eats half as much.”

Pushing against that assertion requires you to be brave. To let go of your desire for certainty and safety, take a risk, and be intellectually brave.

Being brave is hard. Staying safe is easy. It’s rational. It’s what any reasonable person would do. But safe, rational, and reasonable people rarely change the world.

One more story

In 1980, McKinsey predicted that the worldwide market for cell phones would max out at 900,000 subscribers. They based this prediction on solid data, analyzed by some of the most intelligent people in business. The data and resulting recommendations made sense when presented to AT&T, McKinsey’s client.

Five years later, there were 340,213 subscribers, and McKinsey looked pretty smart. In 1990, there were 5.3 million subscribers, almost 6x McKinsey’s prediction. In 1994, there were 24.1M subscribers in the US alone (27x McKinsey’s global forecast), and AT&T was forced to pay $12.6B to acquire McCaw Cellular.

Should AT&T have told McKinsey to “go to Hell?” No.

Should AT&T have thanked McKinsey for going to (and through) Hell to get the data, then asked whether they swung by earth to talk to humans and understand their Jobs to be Done around communication? Yes.

Because, as Box founder Aaron Levie reminds us,

“Sizing the market for a disruptor based on an incumbent’s market is like sizing a car industry off how many horses there were in 1910.”

* Except for the last line, these probably (definitely) weren’t his exact words, but they are an accurate representation of what I remember him saying

Image Credit: Pixabay

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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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