Category Archives: Leadership

You Must Accept That People Are Irrational

You Must Accept That People Are Irrational

GUEST POST from Greg Satell

For decades, economists have been obsessed with the idea of “enlightened self-interest,” building elaborate models based on the assumption that people make rational choices. Business and political leaders have used these models to shape competitive strategies, compensation, tax policies and social services among other things.

It’s clear that the real world is far more complex than that. Consider the prisoner’s dilemma, a famous thought experiment in which individuals acting in their self-interest make everyone worse off. In a wide array of real world and experimental contexts, people will cooperate for the greater good rather than pursue pure self-interest.

We are wired to cooperate as well as to compete. Identity and dignity will guide our actions even more than the prospect for loss or gain. While business schools have trained generations of managers to assume that they can optimize results by designing incentives, the truth is that leaders that can forge a sense of shared identity and purpose have the advantage.

Overcoming The Prisoner’s Dilemma

John von Neumann was a frustrated poker player. Despite having one of the best mathematical minds in history that could probably calculate the odds better than anyone on earth, he couldn’t tell whether other players were bluffing or not. It was his failure at poker that led him to create game theory, which calculates the strategies of other players.

As the field developed, it was expanded to include cooperative games in which players could choose to collaborate and even form coalitions with each other. That led researchers at RAND to create the prisoner’s dilemma, in which two suspects are being interrogated separately and each offered a reduced sentence to confess.

Prisoner's Dilemma

Here’s how it works: If both prisoners cooperate with each other and neither confesses, they each get one year in prison on a lesser charge. If one confesses, he gets off scot-free, while his partner gets 5 years. If they both rat each other out, then they get three years each—collectively the worst outcome of all.

Notice how from a rational viewpoint, the best strategy is to defect. No matter what one guy does, the other one is better off ratting him out. If both pursue self-interest, they are made worse off. It’s a frustrating problem. Game theorists call it a Nash equilibrium—one in which nobody can improve their position by unilateral move. In theory, you’re basically stuck.

Yet in a wide variety of real-world contexts, ranging from the survival strategies of guppies to military alliances, cooperation is credibly maintained. In fact, there are a number of strategies that have proved successful in overcoming the prisoner’s dilemma. One, called tit-for-tat, relies on credible punishments for defections. Even more effective, however, is building a culture of shared purpose and trust.

Kin Selection And Identity

Evolutionary psychology is a field very similar to game theory. It employs mathematical models to explain what types of behaviors provide the best evolutionary outcomes. At first, this may seem like the utilitarian approach that economists have long-employed, but when you combine genetics with natural selection, you get some surprising answers.

Consider the concept of kin selection. From a purely selfish point of view, there is no reason for a mother to sacrifice herself for her child. However, from an evolutionary point of view, it makes perfect sense for parents to put their kids first. Groups who favor children are more likely to grow and outperform groups who don’t.

This is what Richard Dawkins meant when he called genes selfish. If we look at things from our genes’ point of view, it makes perfect sense for them to want us to sacrifice ourselves for children, who are more likely to be able to propagate our genes than we are. The effect would logically also apply to others, such as cousins, that likely carry our genes.

Researchers have also applied the concept of kin selection to other forms of identity that don’t involve genes, but ideas (also known as memes) in examples such as patriotism. When it comes to people or ideas we see as an important part of our identity, we tend to take a much more expansive view of our interests than traditional economic models would predict.

Cultures of Dignity

It’s not just identity that figures into our decisions, but dignity as well. Consider the ultimatum game. One player is given a dollar and needs to propose how to split it with another player. If the offer is accepted, both players get the agreed upon shares. If it is not accepted, neither player gets anything.

If people acted purely rationally, offers as low as a penny would be routinely accepted. After all, a penny is better than nothing. Yet decades of experiments across different cultures show that most people do not accept a penny. In fact, offers of less than 30 cents are routinely rejected as unfair because they offend people’s dignity and sense of self.

Results from ultimatum game are not uniform, but vary in different cultures and more recent research suggests why. In a study in which a similar public goods game was played it was found that cooperative—as well as punitive—behavior is contagious, spreading through three degrees of interactions, even between people who haven’t had any direct contact.

Whether we know it or not, we are constantly building ecosystems of norms that reward and punish behavior according to expectations. If we see the culture we are operating in as trusting and generous, we are much more likely to act collaboratively. However, if we see our environment as cutthroat and greedy, we’ll tend to model that behavior in the same way.

Forging Shared Identity And Shared Purpose

In an earlier age, organizations were far more hierarchical. Power rested at the top. Information flowed up, orders went down, work got done and people got paid. Incentives seemed to work. You could pay more and get more. Yet in today’s marketplace, that’s no longer tenable because the work we need done is increasingly non-routine.

That means we need people to do more than merely carry out tasks, they need to put all of their passion and creativity into their work to perform at a high-level. They need to collaborate effectively in teams and take pride in the impact their efforts produce. To achieve that at an organizational level, leaders need to shift their mindsets.

As David Burkus explained in his TED Talk, humans are prosocial. They are vastly more likely to perform when they understand and identify with who their work benefits than when they are given financial incentives or fed some grandiose vision. Evolutionary psychologists have long established that altruism is deeply embedded in our sense of tribe.

The simple truth is that we can no longer coerce people to do what we want with Rube Goldberg-like structures of carrots and sticks, but must inspire people to want what we want. Humans are not purely rational beings, responding to stimuli as if they were vending machines that spit out desired behaviors when the right buttons are pushed, but are motivated by identity and dignity more than anything else.

Leadership is not an algorithm, but a practice of creating meaning through relationships of trust in the context of a shared purpose.

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

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The Need for Organizational Learning

The Need for Organizational Learning

GUEST POST from Mike Shipulski

The people within companies have development plans so they can learn new things and become more effective. There are two types of development plans – one that builds on strengths and another that shore up shortcomings. And for both types, the most important step is to acknowledge it’s important to improve. Before a plan can be created to improve on a strength, there must be recognition that something good can come from the improvement. And before there can be a plan to improve on a shortcoming, there must be recognition that there’s something missing and it needs to be improved.

And thanks to Human Resources, the whole process is ritualized. The sequence is defined, the timing is defined and the tools are defined. Everyone knows when it will happen, how it will happen and, most importantly, that it will happen. In that way, everyone knows it’s important to learn new skills for the betterment of all.

Organizational learning is altogether different and more difficult. With personal learning, it’s clear who must do the learning (the person). But with organizational learning, it’s unclear who must learn because the organization, as a whole, must learn. But we can’t really see the need for organizational learning because we get trapped in trying to fix the symptoms. Team A has a problem, so let’s fix Team A. Or, Team B has a problem, so let’s fix Team B. But those are symptoms. Real organizational learning comes when we recognize problematic themes shared by all the teams. Real organization learning comes when we realize these problems don’t result from doing things wrong, rather, they are a natural byproduct of how the company goes about its work.

The difficulty with organizational learning is not fixing the thematic problems. The difficulty is recognizing the thematic problems. When all the processes are followed and all the best practices are used, yet the same problematic symptoms arise, the problem is inherent in the foundational processes and practices. Yet, these are the processes and practices responsible for past success. It’s difficult for company leaders recognize and declare that the things that made the company successful are now the things that are holding the company back. But that’s the organizational learning that must happen.

What worked last time will work next time, as long as the competitive landscape remains constant. But when the landscape changes, what worked last time doesn’t work anymore. And this, I think, is how recipes responsible for past success can, over time, begin to show cracks and create these systematic problems that are so difficult to see.

The best way I know to recognize the need for organizational learning is to recognize changes in the competitive landscape. Once these changes are recognized, thought experiments can be run to evaluate potential impacts on how the company does business. Now that the landscape changed like this, it could stress our business model like that. Now that our competitors provide new services like this, it could create a gap in our capabilities like that.

Organizational learning occurs when the right leaders feel the problems. Fight the urge to fix the problems. Instead, create the causes and conditions for the right leaders to recognize they have a real problem on their hands.

Image credit: 1 of 950+ FREE quote slides available at http://misterinnovation.com

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How Incumbents Can React to Disruption

How Incumbents Can React to Disruption

GUEST POST from Geoffrey A. Moore

Think back a couple of years and imagine …

You are Jim Farley at Ford, with Tesla banging at the door. You are Bob Iger at Disney with Netflix pounding on the gates. You are Pat Gelsinger at Intel with Nvidia invading your turf. You are virtually every CEO in retail with Amazon Prime wreaking havoc on your customer base. So, what are you supposed to do now?

The answer I give in Zone to Win is that you have to activate the Transformation Zone. This is true, but it is a bit like saying, you have to climb a mountain. It begs the question, How?

There are five key questions executives facing potential disruption must ask:

1. When?

If you go too soon, your investors will lose patience with you and desert the ship. If you go too late, your customers will realize you’re never really going to get there, so they too, reluctantly, will depart. Basically, everybody gets that a transformation takes more than one year, and no one will give you three, so by default, when the window of opportunity to catch the next wave looks like it will close within the next two years, that’s when you want to pull the ripcord.

2. What does transformation really mean?

It means you are going to break your established financial performance covenants with your investors and drastically reduce your normal investment in your established product lines in order to throw your full weight behind launching yourself into the emerging fray. The biggest mistake executives can make at this point is to play down the severity of these actions. Believe me, they are going to show, if not this quarter, then soon, and when they do, if you have not prepared the way, your entire ecosystem of investors, partners, customers, and employees are going to feel betrayed.

3. What can you say to mitigate the consequences?

Simply put, tell the truth. The category is being disrupted. If we are to serve our customers, we need to transition our business to the new technology. This is our number one priority, we have clear milestones to measure our progress, and we plan to share this information in our earnings calls. In the meantime, we continue to support our core business and to work with our customers and partners to address their current needs as well as their future roadmaps.

4. What is the immediate goal?

The immediate goal is to neutralize the threat by getting “good enough, fast enough.” It is not to leapfrog the disruptor. It is not to break any new ground. Rather, it is simply to get included in the category as a fast follower, and by so doing to secure the continuing support of the customer base and partner ecosystem. The good news here is that customers and partners do not want to switch vendors if they can avoid it. If you show you are making decent progress against your stated milestones, most will give you the benefit of the doubt. Once you have gotten your next-generation offerings to a credible state, you can assess your opportunities to differentiate long-term—but not before.

5. In what ways do we act differently?

This is laid out in detail in the chapter on the Transformation Zone in Zone to Win. The main thing is that supporting the transformation effort is the number one priority for everyone in the enterprise every day until you have reached and passed the tipping point. Anyone who is resisting or retarding the effort needs to be counseled to change or asked to leave. That said, most people will still spend most of their time doing what they were doing before. It is just that if anyone on the transformation initiative asks anyone else for help, the person asked should do everything they can to provide that help ASAP. Executive staff meetings make the transformation initiative the number one item on the agenda for the duration of the initiative, the goal being at each session to assess current progress, remove any roadblocks, and do whatever possible to further accelerate the effort.

Conclusion

The net of all of the above is transformation is a bit like major surgery. There is a known playbook, and if you follow it, there is every reason to expect a successful outcome. But woe to anyone who gets distracted along the way or who gives up in discouragement halfway through. There is no halfway house with transformations—you’re either a caterpillar or a butterfly, there’s nothing salvageable in between.

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

Image Credit: Slashgear.com

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Learning Business and Life Lessons from Monkeys

Learning Business and Life Lessons from Monkeys

GUEST POST from Greg Satell

Franz Kafka was especially skeptical about parables. “Many complain that the words of the wise are always merely parables and of no use in daily life,” he wrote. “When the sage says: ‘Go over,’ he does not mean that we should cross to some actual place… he means some fabulous yonder…that he cannot designate more precisely, and therefore cannot help us here in the very least.

Business pundits, on the other hand, tend to favor parables, probably because telling simple stories allows for the opportunity to seem both folksy and wise at the same time. When Warren Buffet says “Only when the tide goes out do you discover who’s been swimming naked,” it doesn’t sound so much like an admonishment.

Over the years I’ve noticed that some of the best business parables involve monkeys. I’m not sure why that is, but I think it has something to do with taking intelligence out of the equation. We’re often prone to imagining ourselves as the clever hero of our own story and we neglect simple truths. That may be why monkey parables have so much to teach us.

1. Build The #MonkeyFirst

When I work with executives, they often have a breakthrough idea they are excited about. They begin to tell me what a great opportunity it is and how they are perfectly positioned to capitalize on it. However, when I begin to dig a little deeper it appears that there is some major barrier to making it happen. When I try to ask about it, they just shut down.

One reason that this happens is that there is a fundamental tension between innovation and operations. Operational executives tend to focus on identifying clear benchmarks to track progress. That’s fine for a typical project, but when you are trying to do something truly new and different, you have to directly confront the unknown.

At Google X, the tech giant’s “moonshot factory,” the mantra is #MonkeyFirst. The idea is that if you want to get a monkey to recite Shakespeare on a pedestal, you start by training the monkey, not building the pedestal, because training the monkey is the hard part. Anyone can build a pedestal.

The problem is that most people start with the pedestal, because it’s what they know and by building it, they can show early progress against a timeline. Unfortunately, building a pedestal gets you nowhere. Unless you can actually train the monkey, working on the pedestal is wasted effort.

The moral: Make sure you address the crux of the problem and don’t waste time with peripheral issues.

2. Don’t Get Taken In By Coin Flipping Monkeys

We live in a world that worships accomplishment. Sports stars who have never worked in an office are paid large fees to speak to corporate audiences. Billionaires who have never walked a beat speak out on how to fight crime (even as they invest in gun manufacturers). Others like to espouse views on education, although they have never taught a class.

Many say that you can’t argue with success, but consider this thought experiment: Put a million monkeys in a coin flipping contest. The winners in each round win a dollar and the losers drop out. After twenty rounds, there will only be two monkeys left, each winning $262,144. The vast majority of the other monkeys leave with merely pocket change.

How much would you pay the winning monkeys to speak at your corporate event? Would you invite them to advise your company? Sit on your board? Would you be interested in their views about how to raise your children, invest your savings or make career choices? Would you try to replicate their coin-flipping success? (Maybe it’s all in the wrist).

The truth is that chance and luck play a much bigger part in success than we like to admit. Einstein, for example, became the most famous scientist of the 20th century not just because of his discoveries but also due to an unlikely coincidence. True accomplishment is difficult to evaluate, so we look for signals of success to guide our judgments.

The moral: Next time you judge someone, either by their success or lack thereof, ask yourself whether you are judging actual accomplishment or telltale signs of successful coin flipping. It’s harder to tell the difference than you’d think.

3. The Infinite Monkey Theorem

There is an old thought experiment called the Infinite Monkey Theorem, which is eerily disturbing. The basic idea is that if there were an infinite amount of monkeys pecking away on an infinite amount of keyboards they would, in time, produce the complete works of Shakespeare, Tolstoy and every other literary masterpiece.

It’s a perplexing thought because we humans pride ourselves on our ability to recognize and evaluate patterns. The idea that something we value so highly could be randomly generated is extremely unsettling. Yet there is an entire branch of mathematics, called Ramsey Theory, devoted to the study of how order emerges from random sets of data.

While the infinite monkey theorem is, of course, theoretical, technology is forcing us to confront the very real dilemma’s it presents. For example, music scholar and composer David Cope has been able to create algorithms that produce original works of music that are so good even experts can’t tell they are computer generated. So what is the value of human input?

The moral: Much like the coin flipping contest, the infinite monkey theorem makes us confront what we value and why. What is the difference between things human produced and identical works that are computer generated? Are Tolstoy’s words what give his stories meaning? Or is it the intent of the author and the fact that a human was trying to say something important?

Imagining Monkeys All Around Us

G. H. Hardy, widely considered a genius, wrote that “For any serious purpose, intelligence is a very minor gift.” What he meant was that even in purely intellectual pursuits, such as his field of number theory, there are things that are far more important. It was, undoubtedly, intellectual humility that led Hardy to Ramanujuan, perhaps his greatest discovery of all.

Imagining ourselves to be heroes of our own story can rob us of the humility we need to succeed and prosper. Mistaking ourselves for geniuses can often get us into trouble. People who think they’re playing it smart tend to make silly mistakes, both because they expect to see things that others don’t and because they fail to look for and recognize trouble signs.

Parables about monkeys can be useful because nobody expects them to be geniuses, which demands that we ask ourselves hard questions. Are we doing the important work, or the easiest tasks to show progress on? If monkeys flipping coins can simulate professional success, what do we really celebrate? If monkeys tapping randomly on typewriters can create masterworks, what is the value of human agency?

The truth is that humans are prone to be foolish. We are unable, outside a few limited areas of expertise, to make basic distinctions in matters of importance. So we look for signals of prosperity, intelligence, shared purpose and other things we value to make judgments about what information we should trust. Imagining monkeys around us helps us to be more careful.

Sometimes the biggest obstacle between where we are now and the fabulous yonder we seek is just the few feet in front of us.

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

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7 Things Leaders Need to Know About Team AI Usage

7 Things Leaders Need to Know About Team AI Usage

GUEST POST from David Burkus

Leaders, we need to talk about intelligence.

By now you’ve–hopefully–started to take it as seriously as many leaders of industry have been. Either way you look at artificial intelligence, good or bad, it is here to stay. And so we need to start thinking of answers for several questions at the intersection of leadership and AI.

How can it be used effectively, not just to cut costs but to supercharge productivity? How can we use artificial intelligence to supplement our solid foundational leadership? Where should we NOT be using artificial intelligence?

It’s still early in the new world of artificial intelligence in the workplace. A lot of companies are delaying hiring, some are already cutting teams to embrace the optimistic promises AI will bring. But I don’t think we should be all in…yet.

I do know one thing to be true: Leaders using AI will quickly outpace leaders who don’t. And it’s important you get equipped, and in the right way.

Artificial intelligence will make good managers better, but not mediocre bosses better

They say a great actor can bring a C+ movie script up to a B+ or even an A if they are really good. But if a C+ actor is given a C+ script, then it’s going be a C+ movie. The same goes for artificial intelligence and leadership. You need to be a great leader before you start implementing artificial intelligence. AI will not bump up a mediocre manager and turn them into a great leader. It’s not some miracle machine. The truth is you need to have your foundations as a manager be solid first. AI is a good supplement for already successful managers.

Don’t use artificial intelligence to monitor

Often the first temptation of leaders experimenting with AI is to find a productivity AI tool out there, plug it into their IT systems, and start virtually looking over their team’s shoulders to monitor output. There are already dozens of stories…horror stories…of companies doing just that. And it’s not a good look, and deeply hurts morale.

If you need a technology tool to ensure your people are actually working when they say they are, you screwed up a long time ago—back during the hiring process.

And the current research on this isn’t in artificial intelligence’s favor. If AI is used to “collect and analyze data about workers,” then eight out of ten workers say AI use on them would definitely or probably make them feel inappropriately watched. In addition, about a one third of the public does not think AI would lead to equitable evaluations. A majority also agrees this would lead to the information collected about workers being misused (66%).

Artificial intelligence is good at turning anything and everything into a metric. Time is an easy metric. Number of sales calls is an easy metric. Messages on slack is an easy metric. How often you move your mouse is an easy, and terrifying, metric. But just because you have easy numbers to pull on your team doesn’t mean they are the right metrics to be pulling.

Leadership is really about people, not the metrics. How you solicit and give feedback is important. How you support and grow individual employees is important. Inspiring your team and being transparent is important. If you monitor your team endlessly, and your team knows that you’re outsourcing the process of harvesting that data with artificial intelligence, it creates distance between you and them.

And that ultimately works against you in the long run. People don’t like leaders who seem far from them and far from…reality.

Become fluent in artificial intelligence, or risk getting lost in translation

There’s some interesting data from Deloitte on AI that came out in Spring 2024. Organizations reporting “very high” Generative AI expertise expect to change their talent strategies even faster, with 32 percent already making changes. According to their findings, a lot of companies are redesigning work processes and changing workflows to integrate AI at different points.

You’re probably already experiencing this with Google, Microsoft and others integrating artificial intelligence into their core products like email and chats.

Another big focus is going to be on AI fluency. Deloitte found that 47 percent of respondents are dedicating time towards it. The leadership who gets educated on AI early, and keeps training consistently on as it develops, will be the best equipped to shepherd their teams going forward. It’s inevitable that career paths and job descriptions are going to evolve. It’s up to you to stay current.

You NEED to know what the technology is, how it’s being used, and how it’s helping those you’re serving. Be it clients, customers, the public–whomever. Saying you just typed some words into a text box and out came some more words….is not a good answer. Or a good look for you. You sound like you’re treating it like magic, when it’s actually just code.

Turn your conversations and meetings into a database

Middle managers spend a lot of time, arguably too much time, sending progress reports up the chain to the C-Suite and marching orders down to the individual contributors at the bottom. And there’s a fair amount of investigating to find out where things really stand, and time can be spent having to meet multiple people to get all the correct and current information. This is a time slog.

Meanwhile, there are dozens of AI tools now that just take notes. Notes from meetings. Notes from calls. They take the transcript and pair it down to the key takeaways, action items, attendance –a full brief for your records.

So, instead of asking someone to take notes during a meeting or having all your notes in the chat only to evaporate once the zoom call ends, you have a searchable document that you can reference, build on, and keep track of. New hires can use the database to catch up, and senior leaders can get a quick read of the progress and where everything stands.

Use AI/Chat bots to offload small, clerical questions

Here’s a situation: You run a small team and maybe you have a few new hires. You’re going to get a bunch of clerical questions from them over their first 90 days. That’s normal. That’s how it’s supposed to be. Onboarding takes time. “Who’s the point person for this? What’s so and so’s email from HR? What’s the policy for remote days at the company?”

Here’s where artificial intelligence can be really useful. Depending on the sort of chat platform you use– Slack, Teams, whatever, you could make a simple chat bot that you upload a full archive of the company’s policies and your own team norms, clerical details– everything new hires will probably ask you about. So, when those quick questions, quick stop-and-chats happen, the chat-bot can take care of that.

This shouldn’t subtract your time with your new hires. This just subtracts the lower stakes conversations. Now, you have more time for the high-level conversations with them. More coaching. More mentorship. More progression towards team goals. It might sound simple but…that’s because it is.

Use AI as an audience for decisions before taking them public

Being in a leadership role requires making decisive decisions. You include feedback and perspectives from your team as much as possible. Do the research. Talk to people. But then comes the actual decision making. And that is often just you, alone, with your thoughts.

Instead of making your pros and cons list, one practical thing to try is inputting proposed decisions or actions in an AI tool and then asking for all the counterpoints and possible outcomes.

You could even scale this out to your whole team. Ideally, teams should be leveraging task-focused conflict in team discussions to spark new and better ideas. But conflict can be tricky. So, what if AI is always the devil’s advocate? As your team is generating or discussing ideas, you can be feeding those ideas into an AI tool and asking it for counterpoints or how competitors might respond.

Don’t let it make the decision for you but do let it help guide you to possible solutions.

Get the legal clearance before going too deep

One last disclaimer: check with your human resources or your senior leadership, your informational technology (IT) people—or honestly, all of them—to know the boundaries you can work within when using AI tools.

Many of the tools out there are free and still in beta mode or come with a small fee. And most of the larger AI companies are taking whatever data you input and using it to better refine their product. Your company may have rules on the books about data privacy. Certainly, if you work in legal, healthcare, or government services, you’re dealing with sensitive data that may be protected.

Get clear answers before using any AI tools. Until someone above you with authority gives you the OK, you should probably just play with the tools on your own time with your own personal projects.

Conclusion

Artificial intelligence is just getting started in the workplace. And it’s all playing out in real time. If you’re a manager starting to get your hands dirty with these new tools, acknowledge to your team that this is all a work in progress and the norms around AI are likely to evolve. Be sure to keep the playing field level with your team. Practice that transparency, onboard everyone to the tools you’re using and that they can use and see where this takes you. Remember, AI, at its best, is here to enhance our human capabilities, not replace them.

AI will never take the place of a great boss…. but it might be better than being managed by a bad one.

Image credit: David Burkus

Originally published at https://davidburkus.com on September 9, 2024.

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An Industrial Call-To-Arms for the Environment

An Industrial Call-To-Arms for the Environment

GUEST POST from Mike Shipulski

What is your obligation to improve the health of our planet?

For the CEO – Look around. Look at Europe. Look at China’s plans. Look at the startups. I know you want to achieve your growth objectives, but if you don’t take seriously the race toward cleaner products and services, you’ll go out of business. You can see this as a problem or an opportunity. Bury your head or put on your track shoes and run! It’s your choice.

Look at the oceans. Look at the landfills. Look at the rise in global temperatures. Just look. This isn’t about ROI, this is about survival. Growth objectives aside, no one will buy things when they are struggling to survive in an uncertain future. Your same old dirty products won’t cut it anymore. So, what are you going to do?

For an example of a path forward, look to the companies in the oil business. Their recipe is clear. They’ve got to use their large but ever-diminishing profits to buy themselves into technologies and industries that will ultimately eat their core business. Though the timing is uncertain, it’s certain that improvements in cleaner technologies will demand they make the change.

Whatever you do, don’t wait. You don’t have much time. Cleaner technologies are getting better every day. It’s time to start.

For Marketing – Look at the upstarts. Look at the powerful companies in adjacent markets who will soon be your direct competitors. Look at your stodgy, unprofitable competitors who are now sufficiently desperate to try anything. Their next marketing push will be built on the bedrock of an improved planet. They’ll be almost as good as you in the traditional areas of productivity and quality and they’ll blow your doors off with their meaner and greener products. Customers will choose green over brown. And they’ll look for real improvements that make the planet smile. The time for green-washing is past. That trick is out of gas.

You need to help customers with new jobs to be done. They care about their environment. They care about their carbon footprint. They care about clean water. And they care about recycling and reuse. It’s real. They care. Now it’s up to you to help them make progress in these areas. It will be a tough road to convince your company that things need to change, but that’s why you’re in Marketing.

You’re already behind. It’s time to start. And it’s up to you to lead the charge.

For Manufacturing – Look at your Value Stream Maps (VSMs). Assign a carbon footprint to each link in the chain. And do the same with water consumption. Assess each process step for carbon and water and rank them worst to best. For the worst, run carbon kaizens and improve the carbon footprint. And run water kaizens for the thirstiest processes.

And look again at your VSMs, and look more broadly. Look back into the supply chain, rank for carbon and water and improve the ones that need the treatment. And teach your suppliers how to do it. And look forward into your distribution channels and improve or eliminate the worst actors. And then propose to Marketing that you teach your customers how to use VSMs to clean up their act. And challenge Engineering to change the design to eliminate the remaining bad actors.

You’ve made good progress with your value streams. Now it’s time to help others make the progress that must be made. As subject matter experts, it’s your time to shine. And, please, start now.

For Engineering – Look at your products. Look at how they’re used. Look at how they’re delivered. Look at how they’re made. Look at how they’re recycled. Sure, your products provide good functionality, but throughout their life cycle they also create carbon dioxide and consume water. And you’re the only ones that can design out the environmental impact.

Learn how to do a Life Cycle Assessment (LCA). Learn which elements of the product create the largest problems. For all the parts that make up the product, sort them worst to best to prioritize the design work. It’s time for radical part count reduction. Try to design out half the parts. It’s possible. And the payoff is staggering. What’s the carbon footprint of a part that was designed out of the product?

Or, to make a more radical improvement, consider an Innovation Burst Event (IBE) to make a fundamental change in the way your products/services impact the environment. With this approach, your innovation work, by definition, will make the planet smile.

It’s time to be open-minded. Ask Manufacturing for the worst processes (including supply chain and distribution) and try to design them out. Design out the part, or change the material, or change the design to enable a friendlier process. Manufacturing can only improve a bad process, but you can design them out altogether. There’s power in that, but with power comes responsibility.

And it’s time for you to take responsibility.

For Everyone in Industry – Regardless of your company, your country or your political affiliation, we can all agree that all our lives get better as the health of our planet improves. And everyone can agree that cleaner air is better. And everyone can agree it’s the same for our water – cleaner is better. And that’s a whole lot of agreement.

As industry leaders, I challenge you to build on that common ground. As industry leaders, I challenge you to improve our planet one product at a time and one process at a time. And as industry leaders, I challenge you to help each other. There’s no competitive disadvantage when you help a company outside your industry. And there’s no shame in learning from companies outside your industry. And it’s good for the planet and profits. There’s nothing in the away. It’s time to start.

As an industry leader, if you want to make a difference in the health of our planet, drop a comment.

Image credit: Pixabay

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Three Steps from Stuck to Success

Managing Uncertainty

Three Steps from Stuck to Success

GUEST POST from Robyn Bolton

When a project is stuck and your team is trying to manage uncertainty, what do you hear most often:

  1. “We’re so afraid of making the wrong decision that we don’t make any decisions.”
  2. “We don’t have time to explore a bunch of stuff. We need to make decisions and go.”
  3. “The problem is so multi-faceted, and everything affects everything else that we don’t know where to start.”

I’ve heard all three this week, each spoken by teams leads who cared deeply about their projects and teams.

Differentiating between risk and uncertainty and accepting that uncertainty would never go away, just change focus helped relieve their overwhelm and self-doubt.

But without a way to resolve the fear, time-pressure, and complexity, the project would stay stuck with little change of progressing to success.

Turn Uncertainty Into an Asset

It’s a truism in the field of innovation that you must fall in love with the problem, not the solution. Falling in love with the problem ensures that you remain focused on creating value and agnostic about the solution.

While this sounds great and logically makes sense, most struggle to do it. As a result, it takes incredible strength and leadership to wrestle with the problem long enough to find a solution.

Uncertainty requires the same strength and leadership because the only way out of it is through it. And, research shows, the process of getting through it, turns it into an asset.

Three Steps to Turn Uncertainty Into an Asset

Research in the music and pharmaceutical industries reveals that teams that embraced uncertainty engaged in three specific practices:

  1. Embrace It: Start by acknowledging the uncertainty and that things will change, go wrong, and maybe even fail. Then stay open to surprise and unpredictability, delving into the unknown “by being playful, explorative, and purposefully engaging in ventures with indeterminate outcome.”
  2. Fix It: Especially when dealing with Unknowable Uncertainty, which occurs when more info supports several different meanings rather than pointing to one conclusion, teams that succeed make provisional decisions to “fix” an uncertain dimension so they can move forward while also documenting the rationale for the fix, setting a date to revisit it, and criteria for changing it.
  3. Ignore It: It’s impossible to embrace every uncertainty at once and unwise to fix too many uncertainties at the same time. As a result, some uncertainties, you just need to ignore. Successful teams adopt “strategic ignorance” “not primarily for purposes of avoiding responsibility [but to] allow postponing decisions until better ideas emerge during the collaborative process.

This practice is iterative, often leading to new knowledge, re-examined fixes, and fresh uncertainties. It sounds overwhelming but the teams that are explicit and intentional about what they’re embracing, fixing, and ignoring are not only more likely to be successful, but they also tend to move faster.

Put It Into Practice

Let’s return to NatureComp, a pharmaceutical company developing natural treatments for heart disease.

Throughout the drug development process, they oscillated between addressing What, Who, How, and Where Uncertainties. They did that by changing whether they embraced, fixed, or ignored each type of uncertainty at a given point:

As you can see, they embraced only one type of uncertainty to ensure focus and rapid progress. To avoid the fear of making mistakes, they fixed uncertainties throughout the process and returned to them as more information came available, either changing or reaffirming the fix. Ignoring uncertainties helped relieve feelings of being overwhelmed because the team had a plan and timeframe for when they would shift from ignoring to embracing or fixing.

Uncertainty is Dynamic – You Need to Be Dynamic, Too

You’ll never eliminate uncertainty. It’s too dynamic to every fully resolve. But by dynamically embracing, fixing, and ignore it in all its dimensions, you can accelerate your path to success.

Image credit: Pexels

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Identity is Crucial to Change

Identity is Crucial to Change

GUEST POST from Greg Satell

In an age of disruption, the only viable strategy is to adapt. Today, we are undergoing major shifts in technology, resources, migration and demography that will demand that we make changes in how we think and what we do. The last time we saw this much change afoot was during the 1920s and that didn’t end well. The stakes are high.

In a recent speech, the EU’s High Representative for Foreign Affairs and Security Policy Josep Borrell highlighted the need for Europe to change and adapt to shifts in the geopolitical climate. He also pointed out that change involves far more than interests and incentives, carrots and sticks, but even more importantly, identity.

“Remember this sentence,” he said. “’It is the identity, stupid.’ It is no longer the economy, it is the identity.” What he meant was that human beings build attachments to things they identify with and, when those are threatened, they are apt to behave in a visceral, reactive and violent way. That’s why change and identity are always inextricably intertwined.

“We can’t define the change we want to pursue until we define who we want to be.” — Greg Satell

The Making Of A Dominant Model

Traditional models come to us with such great authority that we seldom realize that they too once were revolutionary. We are so often told how Einstein is revered for showing that Newton’s mechanics were flawed it is easy to forget that Newton himself was a radical insurgent, who rewrote the laws of nature and ushered in a new era.

Still, once a model becomes established, few question it. We go to school, train for a career and hone our craft. We make great efforts to learn basic principles and gain credentials when we show that we have grasped them. As we strive to become masters of our craft we find that as our proficiency increases, so does our success and status.

The models we use become more than mere tools to get things done, but intrinsic to our identity. Back in the nineteenth century, the miasma theory, the notion that bad air caused disease, was predominant in medicine. Doctors not only relied on it to do their job, they took great pride in their mastery of it. They would discuss its nuances and implications with colleagues, signaling their membership in a tribe as they did.

In the 1840s, when a young doctor named Ignaz Semmelweis showed that doctors could prevent infections by washing their hands, many in the medical establishment were scandalized. First, the suggestion that they, as men of prominence, could spread something as dirty as disease was insulting. Even more damaging, however, was the suggestion that their professional identity was, at least in part, based on a mistake.

Things didn’t turn out well for Semmelweis. He railed against the establishment, but to no avail. He would eventually die in an insane asylum, ironically of an infection he contracted under care, and the questions he raised about the prevailing miasma paradigm went unanswered.

A Gathering Storm Of Accumulating Evidence

We all know that for every rule, there are exceptions and anomalies that can’t be explained. As the statistician George Box put it, “all models are wrong, but some are useful.” The miasma theory, while it seems absurd today, was useful in its own way. Long before we had technology to study bacteria, smells could alert us to their presence in unsanitary conditions.

But Semmelweis’s hand-washing regime threatened doctors’ view of themselves and their role. Doctors were men of prominence, who saw disease emanating from the smells of the lower classes. This was more than a theory. It was an attachment to a particular view of the world and their place in it, which is one reason why Semmelweis experienced such backlash.

Yet he raised important questions and, at least in some circles, doubts about the miasma theory continued to grow. In 1854, about a decade after Semmelweis instituted hand washing, a cholera epidemic broke out in London and a miasma theory skeptic named John Snow was able to trace the source of the infection to a single water pump.

Yet once again, the establishment could not accept evidence that contradicted its prevailing theory. William Farr, a prominent medical statistician, questioned Snow’s findings. Besides, Snow couldn’t explain how the water pump was making people sick, only that it seemed to be the source of some pathogen. Farr, not Snow, won the day.

Later it would turn out that a septic pit had been dug too close to the pump and the water had been contaminated with fecal matter. But for the moment, while doubts began to grow about the miasma theory, it remained the dominant model and countless people would die every year because of it.

Breaking Through To A New Paradigm

In the early 1860s, as the Civil War was raging in the US, Louis Pasteur was researching wine-making in France. While studying the fermentation process, he discovered that microorganisms spoiled beverages such as beer and milk. He proposed that they be heated to temperatures between 60 and 100 degrees Celsius to avoid spoiling, a process that came to be called pasteurization

Pasteur guessed that the similar microorganisms made people sick which, in turn, led to the work of Robert Koch and Joseph Lister. Together they would establish the germ theory of disease. This work then led to not only better sanitary practices, but eventually to the work of Alexander Fleming, Howard Florey and Ernst Chain and development of antibiotics.

To break free of the miasma theory, doctors needed to change the way they saw themselves. The miasma theory had been around since Hippocrates. To forge a new path, they could no longer be the guardians of ancient wisdom, but evidence-based scientists, and that would require that everything about the field be transformed.

None of this occurred in a vacuum. In the late 19th century, a number of long-held truths, from Euclid’s Geometry to Aristotle’s logic, were being discarded, which would pave the way for strange new theories, such as Einstein’s relativity and Turing’s machine. To abandon these old ideas, which were considered gospel for thousands of years, was no doubt difficult. Yet it was what we needed to do to create the modern world.

Moving From Disruption to Resilience

Today, we stand on the precipice of a new paradigm. We’ve suffered through a global financial crisis, a pandemic and the most deadly conflict in Europe since World War II. The shifts in technology, resources, migration and demography are already underway. The strains and dangers of these shifts are already evident, yet the benefits are still to come.

To successfully navigate the decade ahead, we must make decisions not just about what we want, but who we want to be. Nowhere is this playing out more than in Ukraine right now, where the war being waged is almost solely about identity. Russians want to deny Ukrainian identity and to defy what they see as the US-led world order. Europeans need to take sides. So do the Chinese. Everyone needs to decide who they are and where they stand.

This is not only true in international affairs, but in every facet of society. Different eras make different demands. The generation that came of age after World War II needed to rebuild and they did so magnificently. Yet as things grew, inefficiencies mounted and the Boomer Generation became optimizers. The generations that came after worshiped disruption and renewal. These are, of course, gross generalizations, but the basic narrative holds true.

What should be clear is that where we go from here will depend on who we want to be. My hope is that we become protectors who seek to make the shift from disruption to resilience. We can no longer simply worship market and technological forces and leave our fates up to them as if they were gods. We need to make choices and the ones we make will be greatly influenced by how we see ourselves and our role.

As Josep Borrell so eloquently put it: It is the identity, stupid. It is no longer the economy, it is the identity.

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

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My Advice to Young Design Engineers

My Advice to Young Design Engineers

GUEST POST from Mike Shipulski

If your solution isn’t sold to a customer, you didn’t do your job. Find a friend in Marketing.

If your solution can’t be made by Manufacturing, you didn’t do your job. Find a friend in Manufacturing.

Reuse all you can, then be bold about trying one or two new things.

Broaden your horizons.

Before solving a problem, make sure you’re solving the right one.

Don’t add complexity. Instead, make it easy for your customers.

Learn the difference between renewable and non-renewable resources and learn how to design with the renewable ones.

Learn how to do a Life Cycle Assessment.

Learn to see functional coupling and design it out.

Be afraid but embrace uncertainty.

Learn how to communicate your ideas in simple ways. Jargon is a sign of weakness.

Before you can make sure you’re solving the right problem, you’ve got to know what problem you’re trying to solve.

Learn quickly by defining the tightest learning objective.

Don’t seek credit, seek solutions. Thrive, don’t strive.

Be afraid, and run toward the toughest problems.

Help people. That’s your job.

Image credit: 1 of 950+ FREE quote slides available at <a href=”http://misterinnovation.com” target=”_blank”>http://misterinnovation.com</a>

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Building a Learning Organization

Building a Learning Organization

GUEST POST from Stefan Lindegaard

Building a learning organization goes beyond adopting new methods or tools. At its core, it’s about fostering a culture where continuous growth, adaptability, and shared learning are prioritized at every level.

Creating this culture requires a top-down commitment led by leadership and management teams who embody a growth mindset, promote psychological safety, and actively engage in building a learning-focused environment.

Without this dedication, organizations miss a crucial opportunity to develop the capabilities essential for innovation and future-readiness.

Why is this important? Well, in today’s unpredictable and rapidly evolving landscape, a learning organization isn’t just a “nice-to-have” – it’s an imperative. While a company may excel in current operations, failing to invest in learning and adaptability poses significant risks to long-term success. Can any organization truly afford to ignore the need to shape its future?

Three Key Pillars

The foundation of a strong learning organization rests on three pillars:

  1. A growth mindset,
  2. psychological safety,
  3. and an unwavering commitment to fostering a culture of learning.

Leaders must first embody these values to inspire the entire organization to follow. It starts with self-reflection: How can leaders upgrade their mindset, skills, and tools to champion this change? How can they be supported in making it happen?

Only when leaders truly commit to this journey can we build a resilient organization where people and teams possess the adaptability, skills, and mindset needed to innovate, grow, and thrive.

Image Credit: Stefan Lindegaard

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