An Innovation Lesson From The Rolling Stones

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An Innovation Lesson From The Rolling Stones

GUEST POST from Robyn Bolton

If you’re like most people, you’ve faced disappointment. Maybe the love of your life didn’t return your affection, you didn’t get into your dream college, or you were passed over for promotion.  It hurts.  And sometimes, that hurt lingers for a long time.

Until one day, something happens, and you realize your disappointment was a gift.  You meet the true love of your life while attending college at your fallback school, and years later, when you get passed over for promotion, the two of you quit your jobs, pursue your dreams, and live happily ever after. Or something like that.

We all experience disappointment.  We also all get to choose whether we stay there, lamenting the loss of what coulda shoulda woulda been, or we can persevere, putting one foot in front of the other and playing The Rolling Stones on repeat:

“You can’t always get what you want

But if you try sometimes, well, you might just find

You get what you need”

That’s life.

That’s also innovation.

As innovators, especially leaders of innovators, we rarely get what we want.  But we always get what we need (whether we like it or not)

We want to know. 
We need to be comfortable not knowing.

Most of us want to know the answer because if we know the answer, there is no risk. There is no chance of being wrong, embarrassed, judged, or punished.  But if there is no risk, there is no growth, expansion, or discovery.

Innovation is something new that creates value. If you know everything, you can’t innovate.

As innovators, we need to be comfortable not knowing.  When we admit to ourselves that we don’t know something, we open our minds to new information, new perspectives, and new opportunities. When we say we don’t know, we give others permission to be curious, learn, and create. 

We want the creative genius and billion-dollar idea. 
We need the team and the steady stream of big ideas.

We want to believe that one person blessed with sufficient time, money, and genius can change the world.  Some people like to believe they are that person, and most of us think we can hire that person, and when we do find that person and give them the resources they need, they will give us the billion-dollar idea that transforms our company, disrupts the industry, and change the world.

Innovation isn’t magic.  Innovation is team work.

We need other people to help us see what we can’t and do what we struggle to do.  The idea-person needs the optimizer to bring her idea to life, and the optimizer needs the idea-person so he has a starting point.  We need lots of ideas because most won’t work, but we don’t know which ones those are, so we prototype, experiment, assess, and refine our way to the ones that will succeed.   

We want to be special.
We need to be equal.

We want to work on the latest and most cutting-edge technology and discuss it using terms that no one outside of Innovation understands. We want our work to be on stage, oohed and aahed over on analyst calls, and talked about with envy and reverence in every meeting. We want to be the cool kids, strutting around our super hip offices in our hoodies and flip-flops or calling into the meeting from Burning Man. 

Innovation isn’t about you.  It’s about serving others.

As innovators, we create value by solving problems.  But we can’t do it alone.  We need experienced operators who can quickly spot design flaws and propose modifications.  We need accountants and attorneys who instantly see risks and help you navigate around them.  We need people to help us bring our ideas to life, but that won’t happen if we act like we’re different or better.  Just as we work in service to our customers, we must also work in service to our colleagues by working with them, listening, compromising, and offering help.

What about you?
What do you want?
What are you learning you need?

Image Credit: Unsplash

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AI and the Productivity Paradox

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AI and the Productivity Paradox

GUEST POST from Greg Satell

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

Productivity growth would take off in the late 1990s, but then mysteriously drop again during the mid-aughts. At each juncture, experts would debate whether digital technology produced real value or if it was all merely a mirage. The debate would continue even as industry after industry was disrupted.

Today, that debate is over, but a new one is likely to begin over artificial intelligence. Much like in the early 1970s, we have increasing investment in a new technology, diminished productivity growth and “experts” predicting massive worker displacement . Yet now we have history and experience to guide us and can avoid making the same mistakes.

You Can’t Manage (Or Evaluate) What You Can’t Measure

The productivity paradox dumbfounded economists because it violated a basic principle of how a free market economy is supposed to work. If profit seeking businesses continue to make substantial investments, you expect to see a return. Yet with IT investment in the 70s and 80s, firms continued to increase their investment with negligible measurable benefit.

A paper by researchers at the University of Sheffield sheds some light on what happened. First, productivity measures were largely developed for an industrial economy, not an information economy. Second, the value of those investments, while substantial, were a small portion of total capital investment. Third, the aggregate productivity numbers didn’t reflect differences in management performance.

Consider a widget company in the 1970s that invested in IT to improve service so that it could ship out products in less time. That would improve its competitive position and increase customer satisfaction, but it wouldn’t produce any more widgets. So, from an economic point of view, it wouldn’t be a productive investment. Rival firms might then invest in similar systems to stay competitive but, again, widget production would stay flat.

So firms weren’t investing in IT to increase productivity, but to stay competitive. Perhaps even more importantly, investment in digital technology in the 70s and 80s was focused on supporting existing business models. It wasn’t until the late 90s that we began to see significant new business models being created.

The Greatest Value Comes From New Business Models—Not Cost Savings

Things began to change when firms began to see the possibilities to shift their approach. As Josh Sutton, CEO of Agorai, an AI marketplace, explained to me, “The businesses that won in the digital age weren’t necessarily the ones who implemented systems the best, but those who took a ‘digital first’ mindset to imagine completely new business models.”

He gives the example of the entertainment industry. Sure, digital technology revolutionized distribution, but merely putting your programming online is of limited value. The ones who are winning are reimagining storytelling and optimizing the experience for binge watching. That’s the real paradigm shift.

“One of the things that digital technology did was to focus companies on their customers,” Sutton continues. “When switching costs are greatly reduced, you have to make sure your customers are being really well served. Because so much friction was taken out of the system, value shifted to who could create the best experience.”

So while many companies today are attempting to leverage AI to provide similar service more cheaply, the really smart players are exploring how AI can empower employees to provide a much better service or even to imagine something that never existed before. “AI will make it possible to put powerful intelligence tools in the hands of consumers, so that businesses can become collaborators and trusted advisors, rather than mere service providers,” Sutton says.

It Takes An Ecosystem To Drive Impact

Another aspect of digital technology in the 1970s and 80s was that it was largely made up of standalone systems. You could buy, say, a mainframe from IBM to automate back office systems or, later, Macintoshes or a PCs with some basic software to sit on employees desks, but that did little more than automate basic clerical tasks.

However, value creation began to explode in the mid-90s when the industry shifted from systems to ecosystems. Open source software, such as Apache and Linux, helped democratize development. Application developers began offering industry and process specific software and a whole cadre of systems integrators arose to design integrated systems for their customers.

We can see a similar process unfolding today in AI, as the industry shifts from one-size-fits-all systems like IBM’s Watson to a modular ecosystem of firms that provide data, hardware, software and applications. As the quality and specificity of the tools continues to increase, we can expect the impact of AI to increase as well.

In 1987, Robert Solow quipped that, “ You can see the computer age everywhere but in the productivity statistics,” and we’re at a similar point today. AI permeates our phones, smart speakers in our homes and, increasingly, the systems we use at work. However, we’ve yet to see a measurable economic impact from the technology. Much like in the 70s and 80s, productivity growth remains depressed. But the technology is still in its infancy.

We’re Just Getting Started

One of the most salient, but least discussed aspects of artificial intelligence is that it’s not an inherently digital technology. Applications like voice recognition and machine vision are, in fact, inherently analog. The fact that we use digital technology to execute machine learning algorithms is actually often a bottleneck.

Yet we can expect that to change over the next decade as new computing architectures, such as quantum computers and neuromorphic chips, rise to the fore. As these more powerful technologies replace silicon chips computing in ones and zeroes, value will shift from bits to atoms and artificial intelligence will be applied to the physical world.

“The digital technology revolutionized business processes, so it shouldn’t be a surprise that cognitive technologies are starting from the same place, but that’s not where they will end up. The real potential is driving processes that we can’t manage well today, such as in synthetic biology, materials science and other things in the physical world,” Agorai’s Sutton told me.

In 1987, when Solow made his famous quip, there was no consumer Internet, no World Wide Web and no social media. Artificial intelligence was largely science fiction. We’re at a similar point today, at the beginning of a new era. There’s still so much we don’t yet see, for the simple reason that so much has yet to happen.

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

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Curiosity and Collaboration in the Escape Room Adventure Playground

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Curiosity and Collaboration in the Escape Room Adventure Playground

GUEST POST from Leo Chan

When’s the last time you felt curious? When’s the last time you fully immersed yourself in curiosity?

For me, it was this past weekend, during my escape room experience at Escape Games Canada. 

It’s only my second time with escape rooms. My first wasn’t positive. I actually really disliked it.

In reflection, I believe it was because I was too in my head and didn’t lean into curiousity enough back then. I didn’t know what to do. I stood around, confused and overwhelmed. So I watched my team while I stood there helpless.

This time, I was ready to jump in. I chose to let my curiosity lead. 

We were led into a very small room and after an intro sequence, the mission begun. During the intro, I looked around the room curiously. I noticed a small lantern-like light with an electrical symbol. Adjacent to it was an empty cavern with a power socket.

When the mission started, everyone stood wondering what to do.

💡The immediate next step was intuitive for me. I grabbed the lantern-like light, unplugged it and put into the adjacent power socket.

The door opened and we were onto the next part of the mission. “Cool! What’s next?” I thought.

The entire escape room experience was a fun exercise of curiousity and I found it delightful. I went into each room with lots of curiosity, wondering “What if I…? What happens if…?” I pushed buttons, pulled things, rotated, twisted objects, examined items, looked for patterns. It was thoroughly enjoyable.

Research shows when you satisfy your curiosity, your brain rewards you with a flood of dopamine. That’s why curious people are happy people.

Each new step of the escape room was another opportunity to exercise more curiousity. What would happen next? What would we be required to do? 

In addition to this curiousity extravaganza, I also loved that this escape room required real collaboration.

In one room, I noticed there were two joysticks and a button on one side of the room. On the other side of the room, there was a viewfinder (like a periscope).

I was curious about this and thought the two were linked together so I told my wife, “hey, go over to the viewfinder and tell me if anything changes when I move these joysticks around.” 

My curiosity was right. She said “Yes! It moves what I’m seeing!” We then proceeded to work together to figure out the puzzle.

In another room, we had to work together as a trio to solve a puzzle. We each stood in three parts of the room, interacting with the material and dialoging about what we were seeing and then using that as an input to the piece we were responsible for. Our collaboration leveraged our diverse perspectives and experiences. Some people needed to use math (thank goodness that wasn’t me), memorization, cartography, pattern recognition and other skills.

We couldn’t have achieved our mission without collaborating, it was literally impossible. We leaned into our diverse perspectives and experiences; it was wonderful!

As we left the escape room, I couldn’t help but thinking that I went through an immersive, innovation masterclass because the experience highlighted two very important innovation mindsets: curiosity & collaboration.

🌱Mindset #1: Curiosity is essential for innovation. It leads you to see new things, go down new paths and try new things. Walt Disney once said: 

“We keep moving forward, opening new doors, and trying new things, because we are curious and curiosity keeps leading us down new paths.” 

The problem with curiosity is that it’s become a buzzword. We tell people to “just be curious.” We’ve fallen prey to the belief that people are either curious or not curious. And the sad reality is, many adults have lost their curiosity. They’ve lost their child-like wonder. What if you could reinvigorate curiousity? What if you could learn how to be curious once again? It’s possible. 

🌱Mindset #2: Collaboration drives innovation. True collaboration allows us to see new perspectives, gain insights and reach unexpected outcomes. Walter Isaacson, author of The Innovators says this: 

Innovation comes from teams more than lightbulb moments of lone geniuses.

Collaboration is more mindset than skillset and most of us think we’re better collaborators than we really are. If you’ve experienced working in functional silos, a lack of communication, a lack of knowing what’s going on in other teams, you’ve experienced a lack of collaboration. A lack of collaboration roots in a lack of belief in the true power of collaboration. In order to move the needle on collaboration, you need to shift people’s mindsets on collaboration.

At the end of the escape room experience, my wife asked, “How did you know what to do? (It was her first ever escape room experience). I exclaimed, “It’s easy! I was curious!”

🪄Curiosity is powerful. In a 2019 research study, researchers discovered that a single-unit increase in curiosity on a seven-point scale was associated with 34% greater creativity.

🚀 Right now, I want you reflect on the following two prompts:

  1. How will you stimulate your curiosity today? Is there a topic you’ve been curious to learn more about? Maybe it’s a topic, hobby or interest of yours. Some popular topics these days include: Generative AI & ChatGPT. Once you’ve identified an area of curiosity, go and learn about it. Explore it and enjoy the process. I’m giving you permission right now to go and do this. After you’re done, come back and share your experiences with me!
  2. Who could you collaborate with on something you’re working on? It doesn’t matter if it’s a small or big thing. Invite them into your work and get their perspective. You’ll gain fresh insights and new ideas from them. Pro tip: Find someone you NORMALLY wouldn’t ask. Be surprised by what they share with you.

🌱Both curiosity and the collaborative mindset can be taught and nurtured. If you want to know how and bring this to your team, please reach out! I’d be happy to help.

Image credit: Leo Chan

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The Secrets of Seeing What’s Missing

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The Secrets of Seeing What's Missing

GUEST POST from Mike Shipulski

With one eye open and the other closed, you have no depth perception. With two eyes open, you see in three dimensions. This ability to see in three dimensions is possible because each eye sees from a unique perspective. The brain knits together the two unique perspectives so you can see the world as it is. Or, as your brain thinks it is, at least.

And the same can be said for an organization. When everyone sees things from a single perspective, the organization has no depth perception. But with at least two perspectives, the organization can better see things as they are. The problem is we’re not taught to see from unique perspectives.

With most presentations, the material is delivered from a single perspective with the intention of helping everyone see from that singular perspective. Because there’s no depth to the presentation, it looks the same whether you look at it with one eye or two. But with some training, you can learn how to see depth even when it has purposely been scraped away.

And it’s the same with reports, proposals, and plans. They are usually written from a single perspective with the objective of helping everyone reach a single conclusion. But with some practice, you can learn to see what’s missing to better see things as they are.

When you see what’s missing, you see things in stereo vision.

Here are some tips to help you see what’s missing. Try them out next time you watch a presentation or read a report, proposal, or plan.

When you see a WHAT, look for the missing WHY on the top and HOW on the bottom. Often, at least one slice of bread is missing from the why-what-how sandwich.

When you see a HOW, look for the missing WHO and WHEN. Usually, the bread or meat is missing from the how-who-when sandwich.

Here’s a rule to live by: Without finishing there can be no starting.

When you see a long list of new projects, tasks, or initiatives that will start next year, look for the missing list of activities that would have to stop in order for the new ones to start.

When you see lots of starting, you’ll see a lot of missing finishing.

When you see a proposal to demonstrate something for the first time or an initial pilot, look for the missing resources for the “then what” work. After the prototype is successful, then what? After the pilot is successful, then what? Look for the missing “then what” resources needed to scale the work. It won’t be there.

When you see a plan that requires new capabilities, look for the missing training plan that must be completed before the new work can be done well. And look for the missing budget that won’t be used to pay for the training plan that won’t happen.

When you see an increased output from a system, look for the missing investment needed to make it happen, the missing lead time to get approval for the missing investment, and the missing lead time to put things in place in time to achieve the increased output that won’t be realized.

When you see a completion date, look for the missing breakdown of the work content that wasn’t used to arbitrarily set the completion date that won’t be met.

When you see a cost reduction goal, look for the missing resources that won’t be freed up from other projects to do the cost reduction work that won’t get done.

It’s difficult to see what’s missing. I hope you find these tips helpful.

Image credit: Pixabay

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AI Actually Leads to Increased Customer Experience Employment

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AI Actually Leads to Increased Customer Experience Employment

GUEST POST from Shep Hyken

That title is a bold statement in a world where AI, ChatGPT and other technologies are doing many tasks that employees have typically performed. Sometimes, the technologies perform even better.

Earlier this year, Goldman Sachs economists predicted that generative AI tools could impact 300 million full-time jobs worldwide, which could lead to a significant disruption in the job market. That is a lot of jobs, but it’s important to note that the word used was “disrupt,” not “eliminate.” According to Statista, there are approximately 3.32 billion workers in the world. At first, one might think that 300 million is just 10% of the 3.32 billion workers on the planet, but consider some of these jobs fall under the labor category and won’t be impacted at the level other jobs are.

While it may appear to be doom and gloom for many employees, I have a rosier outlook. I’m not so naïve to think AI won’t eliminate any jobs. Of course, there will be some elimination, but perhaps we should be more focused on the word “displacement” when discussing AI’s impact. If you look at trends in business, it’s very typical that as one product becomes obsolete, another product resurfaces and replaces lost jobs. For example, the vinyl record industry lost out to 8-track tapes, which were eventually replaced by cassette tapes, followed by CDs, which now are being replaced by streaming services. In the music industry, the jobs shifted to new products, or people found similar work in other industries.

As new technologies like AI and ChatGPT increase in capability, employees must be flexible, learn new skills and be willing to go where the jobs are available. One of the big areas of concern is the customer service and support world.

Almost everyone has experienced a digital self-service customer support tool like a chatbot or interactive voice response system. My annual customer experience research found that just 31% of customers prefer using these self-service digital customer support solutions. The phone still continues to be the No. 1 preferred method of communication.

I had the opportunity to collaborate with Capterra on its recent CX survey to understand how companies are investing in technology that drives a better customer experience. The Capterra 2023 CX Investments Survey was conducted in June 2023 to explore CX strategies and investment decisions at U.S. businesses with 5,000 or fewer employees with respondents being decision-makers at the manager level. When we asked about the impact AI has on increasing or decreasing CX staff, here’s what we found:

  • 63% of companies have increased staff.
  • 28% indicate no change.
  • Just 9% of have reduced staff as a result of AI.

With all the hyperbole surrounding the elimination of jobs in the customer support world, only 9% of companies have reduced staff, far from eliminating all staff. In fact, the majority of companies increased staff. What AI and other technologies are doing in the customer support world is taking care of lower-level questions and problems that simply require automated responses, allowing agents to focus on bigger, more complicated issues.

As an example, it was in the 1990s when airlines started selling tickets online. Before that, the only way to purchase a ticket was to call and make a reservation or go to the airport. In just a few years, almost all airlines were going digital. The customer service agents, also known as reservationists, feared for their jobs. While the shift to passengers booking their own tickets reduced the demand for traditional travel and reservation agents, new jobs were created in the airline industry. More employees were needed to manage and maintain online booking platforms and to support passengers with problems or more complicated travel itineraries. Furthermore, the convenience and accessibility of online reservations made air travel more accessible to more people, allowing airlines to expand their operations, and in turn, hire more customer service agents and other employees important to the overall passenger experience.

The airline example is similar to many other industries. Undoubtedly, AI eliminates some jobs, especially those requiring low cognitive skills, but it also creates new jobs due to the need for people to develop, maintain and improve new technologies. And consider that new industries will be discovered and developed because of more advanced technologies. They will need workers.

The point of all this goes back to the title of this article. AI will not eliminate jobs—but it will change the job market. Just as some people see a glass of water as half-full or half-empty, you can decide if AI will create scary or exciting times.

This article was originally published on Forbes.com

Image Credits: Shep Hyken

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Measuring Employee Engagement Accurately

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Measuring Employee Engagement Accurately

GUEST POST from David Burkus

Employee engagement has been a hot topic for several decades. And for good reason. Business teams with highly engaged employees have a 59 percent lower turnover rate than those with less engaged staff. Highly engaged teams are 17 percent more productive. Engaged teams receive 10 percent higher customer reviews. And yes, businesses with engaged employees have higher profit margins than non-engaged competitors.

But getting employees to feel engaged is no small feat. Even how to measure employee engagement can be a difficult question to answer for many leaders. But there are good reasons to try. Measuring employee engagement helps identify cultural strengths for the organization. Done well measuring employee engagement builds trust through the company. And measuring employee engagement helps understand and respond to potential trends, both in the organization and across the industry.

In this article, we’ll outline how to measure employee engagement through the most commonly used method and offer the strengths and weaknesses of each method.

Surveys

The first method used to measure employee engagement is surveys. And this is also the most commonly used method as well—mostly for commercial reasons. After the Gallup Organization launched their original Q12 survey of engagement, dozens of competing companies with competing surveys sprung up all promising a different and better way to measure employee engagement. Most of these surveys present a series of statements and ask participants to rate how much they agree or disagree on a 5- or 7-point “Likert” scale. Some include a few open-ended questions as well.

The biggest strength of the survey method is that it scales easily. For an organization with hundreds or thousands of employees, emailing out a survey invitation and letting the system do the rest of the work saves a lot of time. In addition, surveys allow for objective comparisons between teams and divisions, or between the company and an industry benchmark. But while the comparisons may be objective, the data itself may not be. That’s the biggest weakness of surveys, they most often rely on self-reported data. And as a result, those taking the survey may not be completely honest, either because they want to feel more engaged or because they don’t trust the survey to be truly anonymous.

Proxies

The second method used to measure employee engagement is proxies—meaning other metrics that serve as a proxy for engagement. Because we know that employee engagement correlates to other measurements, we can assume a certain level of engagement based off those measurements. For example, productivity has a strong correlation to employee engagement when looking at teams or entire organizations. So, if productivity is high, it’s safe to assume employee engagement isn’t low. Likewise, absenteeism and turnover tend to rise as employee engagement falls, so changes over time on those metrics point to changes over time in engagement. (And comparisons between engagement in departments/teams can sometimes be made based on these proxies.)

The big strength of proxies is that they’re usually measurements that are already being captured. Larger organizations are already tracking productivity, turnover, and more and so the data are already there. The weaknesses of proxy measurements, however, are that they’re not a perfect correlation. It’s possible to be productive but not engaged, and there are often other reasons certain roles have higher turnover than others beyond employee engagement. In addition, some of these proxies are lagging indicators—if turnover is increasing than engagement has already fallen—and so they don’t provide leaders a chance to respond as fast.

Interviews

The third method used to measure employee engagement is interviews. And this method is the least common one but it’s growing in usage. Sometimes these are called “stay” interviews, in contrast to the exit interviews that are common practice in organizations. The idea is to regularly interview employees who are staying about how the company (and leaders) are doing and how things could be improved. While the questions used should provide some structure, the open-ended nature allows leaders to discover potentially unknown areas for improvement.

The biggest strength of stay interviews is that they’re a useful method for team leaders who may not have senior leader support for measuring engagement. Conducting stay interviews with ones’ team doesn’t require senior leadership approval or data from Human Resources. So, it’s available to leaders at all levels. And while that’s true, the weakness of stay interviews is that they’re hard to scale. Training thousands of managers on conducting a stay interview isn’t as easy as emailing out a survey. Moreover, because different managers would conduct these interviews differently, cross-comparison would be subject to bias. Stay interviews are a powerful way to measure engagement on a team, but they’re most potent when they’re used by managers who truly want the feedback their team provides (and not merely because they were told to conduct interviews).

Conclusion

While all three methods are a way to measure employee engagement, it’s not enough to merely measure. We measure things so we can improve them. So once the measurement is done, leaders need to have a plan in place make progress. That plan should include sharing out the results of the measurement and sharing the lessons learned from analyzing those results. In addition, leaders should share what changes are planned based on those lessons. And while it doesn’t need to be shared, it’s worth thinking ahead of time how the effects of those changes will be themselves be measured.

Done well, these measurements and the resulting plans will create an environment where everyone can do their best work ever.

Image credit: Pixabay

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3 Ways to View Your Innovation Basket

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(including one that makes Radical Innovation easy)

3 Ways to View Your Innovation Basket

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/transformational 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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Avoid These Four Myths While Networking Your Organization

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Avoid These Four Myths While Networking Your Organization

GUEST POST from Greg Satell

In an age of disruption, everyone has to adapt eventually. However, the typical organization is ill-suited to change direction. Managers spend years—and sometimes decades—working to optimize their operations to deliver specific outcomes and that can make an organization rigid in the face of a change in the basis of competition.

So it shouldn’t be surprising that the idea of a networked organizations have come into vogue. While hierarchies tend to be rigid, networks are highly adaptable and almost infinitely scalable. Unfortunately, popular organizational schemes such as matrixed management and Holacracy have had mixed results, at best.

The truth is that networks have little to do with an organization chart and much more to do with how informal connections form in your organization, especially among lower-level employees. In fact, coming up with a complex scheme is likely to do little more than cause a lot of needless confusion. Here are the myths you need to avoid.

Myth #1: You Need To Restructure Your Organization

In the early 20th century, the great sociologist Max Weber noted that the sweeping industrialization taking place would lead to a change in how organizations operated. As cottage industries were replaced by large enterprises, leadership would have to become less traditional and focused on charismatic leaders and more organized and rational.

He also foresaw that jobs would need to be broken down into small, specific tasks and be governed by a system of hierarchy, authority and responsibility. This would require a more formal mode of organization—a bureaucracy—in which roles and responsibilities were clearly defined. Later, executives such as Alfred Sloan at General Motors perfected the model.

Most enterprises are still set up this way because it remains the most efficient way to organize tasks. It aligns authority with accountability and optimizes information flow. Everybody knows where they stand and what they are responsible for. Organizational restructures are painful and time consuming because they disrupt and undermine the normal workflow.

In fact, reorganizations can backfire if they cut informal ties that don’t show up on the organization chart. So a better path is to facilitate informal ties so that people can coordinate work that falls in between organizational boundaries. In his book One Mission, McChrystal Group President Chris Fussell calls this a “hybrid organization.”

Myth #2 You Have To Break Down Silos

In 2005, researchers at Northwestern University took on the age old question: “What makes a hit on Broadway.” They looked at all the normal stuff you would imagine to influence success, such as the production budget, the marketing budget and the track record of the director. What they found, however, was surprising.

As it turns out, the most important factor was how the informal networks of the cast and crew were structured. If nobody had ever worked together before, results were poor, but if too many people had previously worked together, results also suffered. It was in the middle range, where there was both familiarity and disruption, that produced the best results.

Notice how the study doesn’t mention anything about the formal organization of the cast and crew. Broadway productions tend to have very basic structures, with a director leading the creative team, a producer managing the business side and others heading up things like music, choreography and so on. That makes it easy for a cast and crew to set up, because everyone knows their place.

The truth is that silos exist because they are centers of capability. Actors work with actors. Set designers work with set designers and so on. So instead of trying to break down silos, you need to start thinking about how to connect them. In the case of the Broadways plays, that was done through previous working relationships, but there are other ways to achieve the same goal.

Myth #3: You Need To Identify Influentials, Hubs And Bridges

In Malcolm Gladwell’s breakaway bestseller The Tipping Point, he wrote “The success of any kind of social epidemic is heavily dependent on the involvement of people with a particular and rare set of social gifts,” which he called “The Law of the Few.” Before long, it seemed like everybody from marketers to organizational theorists were looking to identify a mysterious group of people called “influentials.”

Yet as I explain in Cascades, decades of empirical evidence shows that influentials are a myth. While it is true that some people are more influential than others, their influence is highly contextual and not significant enough to go to the trouble of identifying them. Also, a study that analyzed the emails of 60,000 people found that information does not need rely on hubs or bridges.

With that said, there are a number of ways to network your organization by optimizing organizational platforms for connection. For example, Facebook’s Engineering Bootcamp found that “bootcampers tend to form bonds with their classmates who joined near the same time and those bonds persist even after each has joined different teams.”

One of my favorite examples of how even small tweaks can improve connectivity is a project done at a bank’s call center. When it was found that a third of variation in productivity could be attributed to informal communication outside of meetings, the bank arranged for groups to go on coffee break together, increasing productivity by as much as 20% while improving employee satisfaction at the same time.

Myth #4: Networks Don’t Need Leadership

Perhaps the most damaging myth about networks is that they don’t need strong leadership. Many observers have postulated that because technology allows people to connect with greater efficiency, leaders are no longer critical to organizing work. The reality is that nothing can be further from the truth.

The fact is that it is small groups, loosely connected, but united by a shared purpose that drive change. While individuals can form loosely connected small groups, they can rarely form a shared purpose by themselves. So the function of leadership these days is less to plan and direct action than it is to empower and inspire belief.

So perhaps the biggest shift is not one of tactics, but of mindset. In traditional hierarchies, information flows up through the organization and orders flow down. That helps leaders maintain control, but it also makes the organization slow to adapt and vulnerable to disruption.

Leaders need to learn how to facilitate information flow through horizontal connections so people lower down in the organization can act on it without waiting for approval. That’s where shared purpose comes in. Without a common purpose and shared values, pushing decision making down will only result in chaos. It’s much easier to get people to do what you want if they already want what you want.

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

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How to Defeat Corporate Antibodies

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A Guide to Beating Resistance

How to Defeat Corporate Antibodies

GUEST POST from Stefan Lindegaard

Imagine yourself as the CEO of a mid-sized organization that’s struggling to grow and adapt to the ever-changing business landscape. You decide that it’s time for a significant transformation, which will involve new partnerships, revamped processes, and a shift in the company’s culture.

Despite the potential benefits, the proposed changes are met with strong resistance from within the organization. Corporate antibodies, individuals who fight against innovation and maintain the status quo, are now the biggest challenge to overcome.

In this guide, we’ll walk you through a story that illustrates the impact of corporate antibodies on organizational development and explores the role of organizational culture, leadership, and employee engagement in fostering a supportive environment for change.

A Tale of Two Teams

In our fictional organization, there are two departments that perfectly illustrate the impact of corporate antibodies on organizational development: the marketing team, led by an open-minded and forward-thinking manager named Susan, and the finance department, led by a risk-averse and conservative manager named Mark.

Susan’s marketing team is known for embracing new ideas and encouraging collaboration. She has created a culture where employees are motivated to share ideas, challenge assumptions, and learn from failures. On the other hand, Mark’s finance team resists any proposed changes and defends the status quo. Mark is wary of any initiatives that could disrupt the stability of his department and is often skeptical of suggestions coming from outside his team.

The Power of Culture

One day, during a company-wide meeting, the CEO announces a new partnership with a cutting-edge technology company to streamline processes, reduce costs, and drive innovation across the organization.

Susan’s marketing team quickly embraces the idea, eager to explore the opportunities this partnership could bring. They begin brainstorming ways to integrate the new technology into their work and share their ideas with other teams.

In contrast, Mark’s finance team reacts with apprehension and skepticism. They question the need for such a drastic change and raise concerns about potential disruptions to their well-established processes. Mark himself is hesitant to support the initiative, fearing that it might expose weaknesses within his department and lead to a loss of control.

Detecting Corporate Antibodies

The stark difference between the two teams becomes apparent during meetings and discussions about the upcoming transformation. The finance team, led by Mark, expresses their resistance through statements like:

  • “We already tried something similar, and it didn’t work.”
  • “Our current process has worked fine for years; there’s no need to change.”
  • “If that were a good idea, we’d already have thought of it.”

Some individuals in the finance team genuinely believe they’re looking out for the company’s best interests, while others prioritize their personal interests or fear the potential consequences of change.

The Battle Begins

As the transformation moves into the incubation phase, the tensions between the two teams escalate. Susan’s marketing team starts working closely with the new technology partner, sharing their progress and achievements with the rest of the organization. They demonstrate the positive impact of the change initiative and inspire other departments to get on board.

Meanwhile, Mark’s finance team continues to resist the change, erecting roadblocks and questioning every decision made by the marketing team and the technology partner. Their relentless negativity creates a tense atmosphere and slows down the progress of the transformation.

The Turning Point

As the organization enters the Acceleration stage, the CEO recognizes the need to address the corporate antibodies that are hindering the company’s growth. She decides to implement the following strategies to manage resistance and foster a more supportive environment for change:

  1. Engage potential blockers: The CEO invites Mark and key members of his finance team to participate in decision-making processes, ensuring they feel valued and included. By involving them in shaping the transformation, she gradually turns some of the blockers into backers.
  2. Encourage open communication: The CEO fosters a culture where employees can voice their concerns and suggestions without fear of backlash. This allows the organization to identify and address potential issues early on, reducing the likelihood of resistance emerging later in the process.
  3. Provide support and resources: The CEO allocates resources to offer training and support to employees who need help navigating the change process. This alleviates anxieties and creates a more positive attitude towards the change initiatives.
  4. Celebrate successes: The CEO acknowledges the achievements of Susan’s marketing team and other departments that have embraced the change. Recognizing progress and milestones helps maintain morale and motivation while demonstrating the benefits of the transformation.
  5. Foster collaboration across departments: The CEO organizes cross-functional workshops and team-building activities that encourage employees from different departments to work together. This helps break down silos and promotes a greater understanding of the benefits of the change initiative across the organization.
  6. Appoint change champions: The CEO identifies key influencers within the organization who can help advocate for the change and address concerns from their peers. These change champions play a critical role in maintaining momentum and enthusiasm for the transformation.
  7. Establish a feedback loop: The CEO implements a system for collecting regular feedback from employees about the progress of the transformation. This allows the leadership team to monitor the effectiveness of their strategies, make necessary adjustments, and address any emerging concerns promptly.

With these additional strategies in place, the organization begins to witness significant progress in its transformation journey. The impact of the corporate antibodies is gradually diminished, and a culture of innovation and adaptability starts to flourish.

Monitoring Progress and Ensuring Long-term Success

The CEO understands the importance of monitoring progress and adjusting strategies as needed to ensure the long-term success of the transformation. To do this, she establishes a set of key performance indicators (KPIs) that help track the progress of the change initiatives and their impact on the organization. These KPIs may include employee engagement, cross-functional collaboration, efficiency gains, and financial performance.

Additionally, the CEO remains vigilant for signs of lingering resistance or the re-emergence of corporate antibodies. By maintaining open lines of communication and actively soliciting feedback from employees, she can quickly identify and address any issues that might hinder the organization’s development.

The conclusion is that identifying and tackling corporate antibodies is essential for successful organizational growth and transformation. By understanding the reasons behind their emergence and applying effective strategies to manage them, organizations can build a positive environment for change and promote long-lasting progress.

Emphasizing a strong organizational culture, good leadership, and employee engagement can help ensure your organization’s development efforts succeed, leading to a more resilient and adaptable business in a constantly changing world.

Image Credit: Stefan Lindegaard

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Our People Metrics Are Broken

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Our People Metrics Are Broken

GUEST POST from Mike Shipulski

We get what we measure and, generally, we measure what’s easy to measure and not what will build a bridge to the right behavior.

Timeframe. If we measure people on a daily pitch, we get behavior that is maximized over eight hours. If a job will take nine hours, it won’t get done because the output metrics would suffer. It’s like a hundred-meter sprint race where the stopwatch measures output at one hundred meters. The sprinter spends all her energy sprinting one hundred meters and then collapses. There’s no credit for running further than one hundred meters, so they don’t. Have you ever seen a hundred-meter race where someone ran two hundred meters?

Do you want to sprint one hundred meters five days a week? If so, I hope you only need to run five hundred meters. Do you want to run twenty-five miles per week? If so, you should slow down and run five miles per day for five days. You can check in every day to see if the team needs help and measure their miles on Friday afternoon. And if you want the team to run six miles a day, well, you probably have to allocate some time during the week so they can get stronger, improve their running stride, and do preventative maintenance on their sneakers. For several weeks prior to running six miles a day, you’ve got to restrict their running to four miles a day so they have time to train. In that way, your measurement timeframe is months, not days.

Over what timeframe do you measure your people? And, how do you feel about that?

Control Volume. If you have a fish tank, that’s the control volume (CV) for the fish. If you have two fish tanks, you two control volumes – control volume 1 (CV1) and control volume 2 (CV2). With two control volumes, you can optimize each control volume independently. If tank 1 holds red fish and tank 2 holds blue fish, based on the number of fish in the tanks, you put the right amount of fish food in tank 1 for the red fish and the right amount in tank 2 for the blue fish. The red fish of CV1 live their lives and make baby fish using the food you put in CV1. And to measure their progress, you count the number of red fish in CV1 (tank 1). And it’s the same for the blue fish in CV2.

With the two CVs, you can dial in the recipe to grow the most red fish and dial in a different recipe to grow blue fish. But what if you don’t have enough food for both tanks? If you give more food to the blue fish and starve the red fish, the red fish will get angry and make fewer baby fish. And they will be envious of the blue fish. And, likely, the blue fish will gloat. When CV1 gets fewer resources than CV2, the fish notice.

But what if you want to make purple fish? That would require red fish to jump into the blue tank and even more food to shift from CV1 to CV2. Now the red fish in CV1 are really pissed. And though the red fish moved to tank 2 do their best to make purple guppies with the blue fish, neither color know how to make purple fish. They were never given the tools, time, and training to do this new work. And instead of making purple guppies, usually, they eat each other.

We measure our teams over short timeframes and then we’re dissatisfied when they can’t run marathons. It’s time to look inside and decide what you want. Do you want short-term performance or long-term performance? And, no, you can’t have both from the same team.

And we measure our teams on the output of their control volumes and yet ask them to cooperate and coordinate across teams. That doesn’t work because any effort spent to help another control volume comes at the expense of your own. And the fish know this. And we don’t give them the tools, time, and training to work across control volumes. And the fish know this, too.

Image credit: Unsplash

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