Curiosity and Collaboration in the Escape Room Adventure Playground

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 todayIs 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

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

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

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

(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

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

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

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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Customer Wants and Needs Not the Same

Customer Wants and Needs Not the Same

GUEST POST from Shep Hyken

Many years ago, I walked into an Ace Hardware store to find a new hinge for a swinging door. When I showed the salesperson my broken hinge, he asked if I was open to a suggestion. He sold me a better hinge that was less expensive. Who could argue with that? I had no idea that years later, I would write about this example in one of my books, Amaze Every Customer Every Time.

After that, I noticed when salespeople were more helpful than “salesy.” And guess what happens when they practice helpful behavior versus typical sales behavior? They make the sale.

Another example of this “helpful” level of service happened at B&H Photo. I had made a list of equipment I would buy to upgrade my studio so I could create better virtual keynote speeches for my clients. I was getting ready to spend more than $20,000 on equipment. The woman helping me asked me several questions and made some suggestions. She said I was overspending and didn’t need all the gear I thought I did. Her recommendations saved me more than $12,000!

The same thing happened at one of my favorite music stores, Eddie’s Guitar, where I’ve purchased some beautiful-sounding guitars over the years. I had my sights on a jazz guitar that I thought was the best for my budget. Nate, the owner, and Granville, the salesperson, said almost in unison, “You don’t want that. What you want is this one.” It was the same price, yet it sounded so much better.

What I love about these examples is that the focus was on selling me the best. Saving money was a nice perk, but even if they suggested higher-priced items, if they could prove it was more about what I needed versus what I thought I needed, I’d buy. They asked the right questions to understand my needs and made the appropriate suggestions for what was in my best interest. Consider what happened:

  1. They were interested. They asked questions to understand what I needed.
  2. They demonstrated expertise that led to appropriate suggestions.
  3. Money was less important than the customer’s long-term happiness. In these examples, the salespeople cared as much – maybe more – about me than the sale. The result, by the way, is that I’ve been back many times to both stores.
  4. Trust was created. When the salespeople proved they were helping more than selling, they won me over. And by the way, selling with service is a great sales strategy!

The result of these experiences is everything I speak and write about. It doesn’t matter if it’s sales, customer support, or anything else in the customer’s journey. Create an experience that makes them say, “I’ll be back!”

Image Credits: Shep Hyken, Pixabay

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The Hard Problem of Consciousness is Not That Hard

The Hard Problem of Consciousness is Not That Hard

GUEST POST from Geoffrey A. Moore

We human beings like to believe we are special—and we are, but not as special as we might like to think. One manifestation of our need to be exceptional is the way we privilege our experience of consciousness. This has led to a raft of philosophizing which can be organized around David Chalmers’ formulation of “the hard problem.”

In case this is a new phrase for you, here is some context from our friends at Wikipedia:

“… even when we have explained the performance of all the cognitive and behavioral functions in the vicinity of experience—perceptual discrimination, categorization, internal access, verbal report—there may still remain a further unanswered question: Why is the performance of these functions accompanied by experience?”

— David Chalmers, Facing up to the problem of consciousness

The problem of consciousness, Chalmers argues, is two problems: the easy problems and the hard problem. The easy problems may include how sensory systems work, how such data is processed in the brain, how that data influences behavior or verbal reports, the neural basis of thought and emotion, and so on. The hard problem is the problem of why and how those processes are accompanied by experience.3 It may further include the question of why these processes are accompanied by that particular experience rather than another experience.

The key word here is experience. It emerges out of cognitive processes, but it is not completely reducible to them. For anyone who has read much in the field of complexity, this should not come as a surprise. All complex systems share the phenomenon of higher orders of organization emerging out of lower orders, as seen in the frequently used example of how cells, tissues, organs, and organisms all interrelate. Experience is just the next level.

The notion that explaining experience is a hard problem comes from locating it at the wrong level of emergence. Materialists place it too low—they argue it is reducible to physical phenomena, which is simply another way of denying that emergence is a meaningful construct. Shakespeare is reducible to quantum effects? Good luck with that.

Most people’s problems with explaining experience, on the other hand, is that they place it too high. They want to use their own personal experience as a grounding point. The problem is that our personal experience of consciousness is deeply inflected by our immersion in language, but it is clear that experience precedes language acquisition, as we see in our infants as well as our pets. Philosophers call such experiences qualia, and they attribute all sorts of ineluctable and mysterious qualities to them. But there is a much better way to understand what qualia really are—namely, the pre-linguistic mind’s predecessor to ideas. That is, they are representations of reality that confer strategic advantage to the organism that can host and act upon them.

Experience in this context is the ability to detect, attend to, learn from, and respond to signals from our environment, whether they be externally or internally generated. Experiences are what we remember. That is why they are so important to us.

Now, as language-enabled humans, we verbalize these experiences constantly, which is what leads us to locate them higher up in the order of emergence, after language itself has emerged. Of course, we do have experiences with language directly—lots of them. But we need to acknowledge that our identity as experiencers is not dependent upon, indeed precedes our acquisition of, language capability.

With this framework in mind, let’s revisit some of the formulations of the hard problem to see if we can’t nip them in the bud.

  • The hard problem of consciousness is the problem of explaining why and how we have qualia or phenomenal experiences. Our explanation is that qualia are mental abstractions of phenomenal experiences that, when remembered and acted upon, confer strategic advantage to organisms under conditions of natural and sexual selection. Prior to the emergence of brains, “remembering and acting upon” is a function of chemical signals activating organisms to alter their behavior and, over time, to privilege tendencies that reinforce survival. Once brain emerges, chemical signaling is supplemented by electrical signaling to the same ends. There is no magic here, only a change of medium.
  • Annaka Harris poses the hard problem as the question of “how experience arise[s] out of non-sentient matter.” The answer to this question is, “level by level.” First sentience has to emerge from non-sentience. That happens with the emergence of life at the cellular level. Then sentience has to spread beyond the cell. That happens when chemical signaling enables cellular communication. Then sentience has to speed up to enable mobile life. That happens when electrical signaling enabled by nerves supplements chemical signaling enabled by circulatory systems. Then signaling has to complexify into meta-signaling, the aggregation of signals into qualia, remembered as experiences. Again, no miracles required.
  • Others, such as Daniel Dennett and Patricia Churchland believe that the hard problem is really more of a collection of easy problems, and will be solved through further analysis of the brain and behavior. If so, it will be through the lens of emergence, not through the mechanics of reductive materialism.
  • Consciousness is an ambiguous term. It can be used to mean self-consciousness, awareness, the state of being awake, and so on. Chalmers uses Thomas Nagel’s definition of consciousness: the feeling of what it is like to be something. Consciousness, in this sense, is synonymous with experience. Now we are in the language-inflected zone where we are going to get consciousness wrong because we are entangling it in levels of emergence that come later. Specifically, to experience anything as like anything else is not possible without the intervention of language. That is, likeness is not a qualia, it is a language-enabled idea. Thus, when Thomas Nagel famously asked, “What is it like to be a bat?” he is posing a question that has meaning only for humans, never for bats.

Going back to the first sentence above, self-consciousness is another concept that has been language-inflected in that only human beings have selves. Selves, in other words, are creations of language. More specifically, our selves are characters embedded in narratives, and use both the narratives and the character profiles to organize our lives. This is a completely language-dependent undertaking and thus not available to pets or infants. Our infants are self-sentient, but it is not until the little darlings learn language, hear stories, then hear stories about themselves, that they become conscious of their own selves as separate and distinct from other selves.

On the other hand, if we use the definitions of consciousness as synonymous with awareness or being awake, then we are exactly at the right level because both those capabilities are the symptoms of, and thus synonymous with, the emergence of consciousness.

  • Chalmers argues that experience is more than the sum of its parts. In other words, experience is irreducible. Yes, but let’s not be mysterious here. Experience emerges from the sum of its parts, just like any other layer of reality emergences from its component elements. To say something is irreducible does not mean that it is unexplainable.
  • Wolfgang Fasching argues that the hard problem is not about qualia, but about pure what-it-is-like-ness of experience in Nagel’s sense, about the very givenness of any phenomenal contents itself:

Today there is a strong tendency to simply equate consciousness with qualia. Yet there is clearly something not quite right about this. The “itchiness of itches” and the “hurtfulness of pain” are qualities we are conscious of. So, philosophy of mind tends to treat consciousness as if it consisted simply of the contents of consciousness (the phenomenal qualities), while it really is precisely consciousness of contents, the very givenness of whatever is subjectively given. And therefore, the problem of consciousness does not pertain so much to some alleged “mysterious, nonpublic objects”, i.e. objects that seem to be only “visible” to the respective subject, but rather to the nature of “seeing” itself (and in today’s philosophy of mind astonishingly little is said about the latter).

Once again, we are melding consciousness and language together when, to be accurate, we must continue to keep them separate. In this case, the dangerous phrase is “the nature of seeing.” There is nothing mysterious about seeing in the non-metaphorical sense, but that is not how the word is being used here. Instead, “seeing” is standing for “understanding” or “getting” or “grokking” (if you are nerdy enough to know Robert Heinlein’s Stranger in a Strange Land). Now, I think it is reasonable to assert that animals “grok” if by that we mean that they can reliably respond to environmental signals with strategic behaviors. But anything more than that requires the intervention of language, and that ends up locating consciousness per se at the wrong level of emergence.

OK, that’s enough from me. I don’t think I’ve exhausted the topic, so let me close by saying…

That’s what I think, what do you think?

Image Credit: Pixabay

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