Overcoming Judgement

Leave a reply

Overcoming Judgement

GUEST POST from Mike Shipulski

Judging results when things are different than our expectations.

If you don’t like being judged, stop judging yourself.

No one can judge you without your consent, even you.

If someone judges you, that’s about them.

People’s judgment of you is none of your business.

When you see a friend judging themselves, give them a hug. A virtual one will do.

Judging someone means you want them to be different than they are.

If someone gives you a gift and you don’t accept it, it’s still theirs. Judgment is like that.

If you’re afraid of being judged for trying something new, be afraid, and try it anyway.

Judgment is objective evidence of disapproval if you accept it.

Judging someone won’t change their behavior, other than make them angry.

When you see a friend being judged, give them a hug (in a social distance way.)

When someone judges you, don’t worry. In ten years, no one will remember.

When someone tries to judge you, let them try.

If you do your best, why do you think it’s okay to judge yourself about the outcome?

If you don’t do your best, don’t judge. Ask why.

Judgment can debilitate, but only if you let it.

Image credit: Unsplash

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

It’s Easy to Say No to Customers

1 Reply

It's Easy to Say No to Customers

GUEST POST from Shep Hyken

If a customer asks you to do something you haven’t done before, “No” is an easy answer. Why? Because …

“We don’t do that.”

“We’ve never done that.”

“We don’t carry that product.”

“That’s not our policy.”

And more reasons – or excuses – like these.

Recently, I was the keynote speaker at a conference, and the CEO, who spoke just before me, teed up my presentation perfectly when he talked about going the extra mile. His approach to this concept was realistic. He said, “No one will be able to go the extra mile every time.” He emphasized that unless the customer has some kind of emergency, the extra mile is often something small—something we typically don’t do.

Customers can be our best source of innovation and opportunity. If we survey our customers and ask for feedback, we may find ways to improve our products and services. Or sometimes, they will come right out and ask for something out of the ordinary. It’s easy to ignore feedback or say “No, “when someone suggests something we’ve never done before. But what if we looked beyond the words and thought, “What if,” instead of, “That is something we don’t do.”?

Years ago, I wrote an article about the Anti-No Zone. The premise was employees at a restaurant were trained to find ways to say “Yes.” If you want to dig deeper into this idea, check out my article about Cameron Mitchell, a very successful restaurateur who authored a book titled Yes Is the Answer! What’s the Question? And I wrote another article featuring Christine Trippi on How to Say YES – Every Time.

All of these articles are about avoiding the word no. At the same time, it’s unrealistic to say yes to every request; however, maybe we can say “No” without really saying “No.” Instead, you can offer alternative solutions that, while not what the customer is asking for, will still make them happy.

So, going the extra mile is more than a customer service strategy. And it’s more than avoiding the word no. It is a mindset that customers will appreciate. At the same time, it’s recognizing that anything that you might say no to at first is a possibility to innovate and grow.

So, the next time you are about to say “No” to a customer or an employee, catch yourself and before you answer, and think, “If I could say yes, what would that look like?” Practice the mindset of not just going the extra mile but being proactive about finding ways to do so.

Image Credits: Pexels, Shep Hyken

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Artificial Intelligence is a No-Brainer

Leave a reply

Why innovation management needs co-intelligence

Artificial Intelligence is a No-Brainer

GUEST POST from John Bessant

Long fuse, big bang. A great descriptor which Andrew Hargadon uses to describe the way some major innovations arrive and have impact. For a long time they exist but we hardly notice them, they are confined to limited application, there are constraints on what the technology can do and so on. But suddenly, almost as if by magic they move center stage and seem to have impact everywhere we look.

Which is pretty much the story we now face with the wonderful world of AI. While there is plenty of debate about labels — artificial intelligence, machine learning, different models and approaches — the result is the same. Everywhere we look there is AI — and it’s already having an impact.

More than that; the pace of innovation within the world of AI is breath-taking, even by today’s rapid product cycle standards. We’ve become used to seeing major shifts in things like mobile phones, change happening on a cycle measured in months. But AI announcements of a breakthrough nature seem to happen with weekly frequency.

That’s also reflected in the extent of use — from the ‘early days’ (only last year!) of hearing about Chat GPT and other models we’ve now reached a situation where estimates suggest that millions of people are experimenting with them. Chat GPT has grown from a handful of people to over 200 million in less than a year; it added its first million subscribers within five days of launch! Similar figures show massive and rapid take -up of competing products like Anthropic’s Claude and Google’s Gemini, etc. It’s pretty clear that there’s a high-paced ‘arms race’ going on and it’s drawing in all the big players.

This rapid rate of adoption is being led by an even faster proliferation on the supply side, with many new players entering the market , especially in niche fields. As with the apps market there’s a huge number of players jumping on the bandwagon, and significant growth in the open source availability of models. And many models now allow for users to create their own custom versions — mini-GPTs’ and ‘Co-pilots’ which they can deploy for highly specific needs.

Not surprisingly estimates suggest that the growth potential in the market for AI technologies is vast, amounting to around 200 billion U.S. dollars in 2023 and expected to grow to over 1.8 trillion U.S. dollars by 2030.

Growth in Artificial Intelligence

There’s another important aspect to this growth. As Ethan Mollick suggests in his excellent book ‘Co-intelligence’, everything that we see AI doing today is the product of a far-from-perfect version of the technology; in very short time, given the rate of growth so far, we can expect much more power, integration and multi-modality.

The all-singing, dancing and doing pretty much anything else version of AI we can imagine isn’t far off. Speculation about when AGI — artificial general intelligence — will arrive is still just that — speculative — but the direction of travel is clear.

Not that the impact is seen as entirely positive. Whilst there have been impressive breakthroughs, using AI to help understand and innovate in fields as diverse as healthcare , distribution and education these are matched by growing concern about, for example, privacy and data security, deep-fake abuse and significant employment effects.

With its demonstrable potential for undertaking a wide range of tasks AI certainly poses a threat to the quality and quantity of a wide range of jobs — and at the limit could eliminate them entirely. And where earlier generations of technological automation impacted simple manual operations or basic tasks AI has the capacity to undertake many complex operations — often doing so faster and more effectively than humans.

AI models like Chat GPT can now routinely pass difficult exams for law or medical school, they can interpret complex data sets and spot patterns better than their human counterparts and they can quickly combine and analyze complex data to arrive at decisions which may often be better quality than those made by even experienced practitioners. Not surprisingly the policy discussion around this potential impact has proliferated at a similarly fast rate, echoing growing public concern about the darker side of AI.

But is it inevitable going to be a case of replacement, with human beings shunted to the side-lines? No-one is sure and it is still early days. We’ve had technological revolutions before — think back fifty years to when we first felt the early shock waves of what was to become the ‘microelectronics revolution’. Newspaper headlines and media programs with provocative titles like ‘Now the chips are down’ prompted frenzied discussion and policy planning for a future world staffed by robots and automated to the point where most activity would be undertaken by automated systems, overseen by one man and a dog. The role of the dog being to act as security guard, the role of the man being confined to feeding the dog.

Automation Man and Dog

This didn’t materialize; as many commentators pointed out at the time and as history has shown there were shifts and job changes but there was also compensating creation of new roles and tasks for which new skills were needed. Change yes — but not always in the negative direction and with growing potential for improving the content and quality of remaining and new jobs.

So if history is any guide then there are some grounds for optimism. Certainly we should be exploring and anticipating and particularly trying to match skills and capacity building to likely future needs.

Not least in the area of innovation management. What impact is AI having — and what might the future hold? It’s certainly implicated in a major shift right across the innovation space in terms of its application. If we take a simple ‘innovation compass’ to map these developments we can find plenty of examples:

Exploring Innovation Space

Innovation in terms of what we offer the world — our products and services — here AI already has a strong presence in everything from toys through intelligent and interactive services on our phones through to advanced weapon systems

And it’s the same story if we look at process innovation — changes in the ways we create and deliver whatever it is we offer. AI is embedded in automated and self-optimizing control systems for a huge range of tasks from mining, through manufacturing and out to service delivery.

Position innovation is another dimension where we innovate in opening up new or under-served markets, and changing the stories we tell to existing ones. AI has been a key enabler here, helping spot emerging trends, providing detailed market analysis and underpinning so many of the platform businesses which effectively handle the connection between multi-sided markets. Think Amazon, Uber, Alibaba or AirBnB and imagine them without the support of AI.

And innovation is possible through rethinking the whole approach to what we do, coming up with new business models. Rethinking the underlying value and how it might be delivered — think Spotify, Netflix and many others replacing the way we consume and enjoy our entertainment. Once again AI step forward as a key enabler.

AI is already a 360 degree solution looking for problems to attach to. Importantly this isn’t just in the commercial world; the power of AI is also being harnessed to enable social innovation in many different ways.

But perhaps the real question is not about AI-enabled innovations but one of how it affects innovators — and the organizations employing them? By now we know that innovation isn’t some magical force that strikes blindly in the light bulb moment. It’s a process which can be organized and managed so that we are able to repeat the trick. And after over 100 years of research and documenting hard-won experience we know the kind of things we need to put in place — how to manage innovation. It’s reached the point where we can codify it into an international standard — ISO 56001- and use this as a template to check out the ways in which we build and operate our innovation management systems.

So how will AI affect this — and, more to the point, how is it already doing so? Let’s take our helicopter and look down on where and how AI playing a role in the key areas of innovation management systems.

Typically the ‘front end’ of innovation involves various kinds of search activity, picking up strong and weak signals about needs and opportunities for change. And this kind of exploration and forecasting is something which AI has already shown itself to be very good at — whether in the search for new protein forms or the generation of ideas for consumer products.

Frank Piller’s research team published an excellent piece last year describing their exploration of this aspect of innovation. They looked at the potential which AI offered and tested their predictions out by tasking Chat GPT with a number of prompts based on the needs of a fictitious outdoor activities company. They had it monitoring and picking up on trends, scraping online communities for early warning signals about new consumer themes and, crucially, actually doing idea generation to come up with new product concepts. Their results mimic many other studies which suggest that AI is very good at this — in fact, as Mollick reports, it often does the job better than humans.

Of course finding opportunities is only the start of the innovation process; a key next stage is some kind of strategic selection. Out of all the possibilities of what we could do, what are we going to do and why? Limited resources mean we have to make choices — and the evidence is that AI is pretty helpful here too. It can explore and compare alternatives, make better bets and build more viable business models to take emerging value propositions forward. (At least in the test case where it competed against MBA students…!)

Innovation Process John Bessant

And then we are in the world of implementation, the long and winding road to converting our value proposition into something which will actually work and be wanted. Today’s agile innovation involves a cycle of testing, trial and error learning, gradually pivoting and homing in on what works and building from that. And once again AI is good at this — not least because it’s at the heart of how it does what it does. There’s a clue in the label — machine learning is all about deploying different learning and improvement strategies. AI can carry out fast experiments and focus in, it can simulate markets and bring to bear many of the adoption influences as probabilistic variables which it can work with.

Of course launching a successful version of a value proposition converted to a viable solution is still only half the innovation journey. To have impact we need to scale — but here again AI is likely to change the game. Much of the scaling journey involves understanding and configuring your solution to match the high variability across populations and accelerate diffusion. We know a lot about what influences this (not least thanks to the extensive work of Everett Rogers) and AI has particular capabilities in making sense of the preferences and predilections of populations through studying big datasets. It’s record in persuasion in fields like election campaigning suggests it has the capacity to enhance our ability to influence the innovation adoption decision process.

Scaling also involves complementary assets — the ‘who else?’ and ‘what else?’ which we need to have impact at scale. We need to assemble value networks, ecosystems of co-operating stakeholders — but to do this we need to be able to make connections. Specifically finding potential partners, forming relationships and getting the whole system to perform with emergent properties, where the whole is greater than the sum of the parts.

And here too AI has an growing track record in enabling recombinant innovation, cross-linking, connecting and making sense of patterns, even if we humans can’t always see them.

So far, so disturbing — at least if you are a practicing innovation manager looking over your shoulder at the AI competition rapidly catching up. But what about the bigger picture, the idea of developing and executing an innovation strategy? Here our concern is with the long-term, managing the process of accumulating competencies and capabilities to create long term competitiveness in volatile and unpredictable markets?

It involves being able to imagine and explore different options and make decisions based on the best use of resources and the likely fit with a future world. Which is, once again, the kind of thing which AI has shown itself to be good at. It’s moved a long way from playing chess and winning by brute calculating force. Now it can beat world champions at complex games of strategy like Go and win poker tournaments, bluffing with the best of them to sweep the pot.

Artificial Intelligence Poker Player

So what are we left with? In many ways it takes us right back to basics. We’ve survived as a species on the back of our imaginations — we’re not big or fast, or able to fly, but we are able to think. And our creativity has helped us devise and share tools and techniques, to innovate our way out of trouble. Importantly we’ve learned to do this collectively — shared creativity is a key part of the puzzle.

We’ve seen this throughout history; the recent response to the Covid-19 pandemic provides yet another illustration. In the face of crisis we can work together and innovate radically. It’s something we see in the humanitarian innovation world and in many other crisis contexts. Innovation benefits from more minds on the job.

So one way forward is not to wring our hands and say that the game is over and we should step back and let the AI take over. Rather it points towards us finding ways of working with it — as Mollick’s book title suggests, learning to treat it as a ‘co-intelligence’. Different, certainly but often in in complementary ways. Diversity has always mattered in innovation teams — so maybe by recruiting AI to our team we amplify that effect. There’s enough to do in meeting the challenge of managing innovation against a background of uncertainty; it makes sense to take advantage of all the help we can get.

AI may seem to point to a direction in which our role becomes superfluous — the ‘no-brain needed’ option. But we’re also seeing real possibilities for it to become an effective partner in the process.

And subscribe to my (free) newsletter here

You can find my podcast here and my videos here

And if you’d like to learn with me take a look at my online course here

Image credits: Dall-E via Microsoft CoPilot, John Bessant

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Do Nothing More Often

2 Replies

Do Nothing More Often

GUEST POST from Robyn Bolton

“What do you plan to do on vacation?” my friend asked.

“Nothing…”

Long silence

“…And it will be amazing.”

We live in a world that confuses activity with achievement so I should not have been surprised that the idea of deliberately doing nothing stunned my friend into silence.

After all, when people say, “I wish I had nothing to do” they usually mean “I wish I could choose what I do with my time.” And, when they do have the opportunity to choose, very few choose to do nothing.

Why does the idea of doing nothing make us so uncomfortable?

To put it bluntly, busy-ness is a status symbol.

In their paper, “Conspicuous Consumption of Time: When Busyness and Lack of Leisure Time Become a Status Symbol,” professors Silvia Bellezza (Columbia Business School), Neeru Paharia (Georgetown University), and Anat Keinan (Harvard University), wrote that people’s desire to be perceived as time-starved is

“driven by the perceptions that a busy person possesses desired human capital characteristics (competence, ambition) and is scarce and in demand on the job market.”

We didn’t always believe this.

For most of human history, we’ve had a pretty balanced view of the need for both work and leisure. Aristotle argued that virtue was obtainable through contemplation, not through endless activity. Most major religions call for a day of rest and reflection. Even 19th-century moral debates, as recorded by historian EO Thompson, recognized the value of hard work AND the importance of rest.

So what happened?

While it’s easy to say that we have to work more because of the demands of our jobs, the data says otherwise. In fact, according to a working paper by Jonathan Gershuny, a time-expert based on the UK, actual time spent at work has not increased since the 1960s.

The actual reason may be that we want to work more. According to economist Robert Frank, those who identify as workaholics believe that:

“building wealth…is a creative process, and the closest thing they have to fun.”

We choose to spend time working because Work — “the job itself, the psychic benefits of accumulating money, the pursuit of status, and the ability to afford the many expensive enrichments of an upper-class lifestyle” according to an article in The Atlantic — is what we find most fulfilling.

It’s not that I like working, I just don’t like wasting time.

We tend to equate doing nothing with laziness, apathy, a poor work ethic, and a host of other personality flaws and social ills. But what if that’s not true.

What if, in the process of doing nothing, we are as productive as when we do something?

Science is increasingly showing this to be the case.

Multiple fMRI studies have revealed the existence of the default mode network (DMN), a large-scale brain network that is most active when we’re day-dreaming. Researchers at the University of Southern California argue that

“downtime is, in fact, essential to mental processes that affirm our identities, develop our understanding of human behavior and instill an internal code of ethics — processes that depend on the DMN.”

The results of harnessing the power of your DMN are immense:

More creativity. The research discussed in Scientific American suggests that DMN is more active in creative people. For example, according to Psychology Today:

  • The most recorded song of all time, “Yesterday” by The Beatles, was ‘heard’ by Paul McCartney as he was waking up one morning. The melody was fully formed in his mind, and he went straight to the piano in his bedroom to find the chords to go with it, and later found words to fit the melody.
  • Mozart described how his musical ideas ‘flow best and most abundantly.’ when he was alone ‘traveling in a carriage or walking after a good meal, or during the night when I cannot sleep… Whence and how they come, I know not, nor can I force them.’
  • Tchaikovsky described how the idea for a composition usually came ‘suddenly and unexpectedly… It takes root with extraordinary force and rapidity, shoots up through the earth, puts forth branches and leaves, and finally blossoms.’

More productivity. According to an essay in The New York Times, “Idleness is not just a vacation, an indulgence or a vice; it is as indispensable to the brain as vitamin D is to the body, and deprived of it we suffer a mental affliction as disfiguring as rickets. The space and quiet that idleness provides is a necessary condition for standing back from life and seeing it whole, for making unexpected connections and waiting for the wild summer lightning strikes of inspiration — it is, paradoxically, necessary to getting any work done.”

Less burnout. Regardless of how many hours you work, consider this: researchers have found that it takes 25 minutes to recover from a phone call or an e-mail. On average, we are interrupted every 11 minutes which means that we can never catch up, we’re always behind.

That feeling of always being behind leads to burn-out which the World Health Organization officially recognized as a medical condition defined as a “syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed” and manifests with the following symptoms:

  • Feelings of energy depletion or exhaustion
  • Increased mental distance from one’s job, or feelings of negativism or cynicism related to one’s job
  • Reduced professional efficacy

Doing nothing, quieting our minds and not focusing on any particular task, can actually help reset our bodies systems, quieting the release of stress chemicals, slowing our heart rates, and improving our mental and physical energy

Better health. Multiple studies indicate that idleness “produces many health benefits including, but not limited to, reduced heart rate, better digestion, improvements in mood, and a boost in overall emotional well-being — which, of course, affects everything on a biochemical and physiological level, thereby serving as a major deciding factor on whether or not we fall ill, and/or remain ill. Mental downtime also replenishes glucose and oxygen levels in the brain, and allows our brains to process and file things, which leaves us feeling more rested and clear-headed, promotes a stronger sense of self-confidence, and…more willing to we trust change.”

Fine, you convinced me. How can I do nothing?

There are the usual suspects — vacations, meditation, and physical exercise — but, if you’re anything like me, the thought of even finding 5 minutes to listen to a meditation app is so overwhelming that I never even start.

An easier place to start, in my experience, is in intentionally working nothing into the moments that are already “free.” Here are three of my favorite ways to work a bit of nothing into my day.

Make the Snooze button work for you. When my alarm goes off, I instinctively hit the Snooze button because, I claim, it is my first and possibly only victory of the day. It’s also a great way to get 9 minutes of thoughtful quiet nothingness in which I can take a few deep breaths, scan my body for any aches and pains, and make sure that I’m calm and my mind is quiet when I get out of bed.

Stare out the window. I always place my computer next to a window so that I can stare out the window for a few minutes throughout the day and people think I’m thinking deep thoughts. Which I am. Subconsciously. Lest anyone accuse me of being lazy or unproductive while I watch the clouds roll by, I simply point them to research that shows “that individuals who took five to ten minute breaks from work to do nothing a few times a day displayed an approximately 50% increase in their ability to think clearly and creatively, thus rendering their work far more productive.

Bring the beach to you. Research from a variety of places, from the UK Census to The Journal of Coastal Zone Management, indicate that our brains and bodies benefit from time at the beach. But, if you can’t go to the beach, there are lots of ways to bring the beach to you. Perhaps the simplest is to bring more blue into your environment. Most people associate blue with feelings of calm and peace and a study published in the American Association for the Advancement of Science found that the color blue can boost creativity. Even putting a picture of a beach (or your own personal happy place) on your desk or computer screen can trigger your brain to slow down, relax, and possibly trigger your DMN.

With so many benefits, isn’t it time you started doing more nothing?

Image credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Four Hidden Secrets of Innovation

1 Reply

Four Hidden Secrets of Innovation

GUEST POST from Greg Satell

Every enterprise needs to innovate. It doesn’t matter whether you are a profit-seeking business, a nonprofit organization or a government entity, the simple truth is that every business model fails eventually, because things change over time. We have to manage not for stability, but for disruption or face irrelevance.

There is no shortage of advice for how to go about it. In fact, there is far too much advice. Design thinkers will tell you to focus on the end user, but Harvard’s Clayton Christensen says that listening too much to customers is how good business fail. Then there’s open innovation, lean startups and on and on it goes.

The truth is that there is no one path to innovation. Everybody has to find their own way. Just because someone had success with one strategy, doesn’t mean that it’s right for the problem you need to solve. So the best advice is to gather as many tools for your toolbox as you can. Here are four things about innovation you rarely hear, but are crucially important.

1. Your Success Often Works Against You

For the most part, managers aren’t responsible for innovation, but as the name implies, to manage operations. That involves hiring and empowering strong employees, optimizing practices and processes and reducing errors and mistakes. You’re generally not trying to build a better mousetrap, you are trying to run things smoothly and efficiently.

It’s easy for someone to stand up on stage at a conference and paint operational managers as dimwits with their heads in the sand, but the truth is that managing a quality operation is a very tough job and requires a lot of talent, dedication and skill. So unless you’ve actually done the job, don’t be too quick to judge.

However, managers do need to realize that there is a fundamental tradeoff between innovation and optimizing operations. Running efficient operations requires standardization and control to yield predictable outcomes. Innovation, on the other hand requires experimentation. You need to try a lot of new things, most of which are going to fail.

That’s why success so often leads to failure. What makes you successful in one competitive environment will likely be a hindrance when things change. So you need to work to find a healthy balance between squeezing everything you can out of the present, while still leaving room to create and build for the future.

2. Don’t Look For A Large Addressable Market, Look For A Hair-On-Fire Use Case

Good operational managers learn to identify large addressable markets. Bigger markets help you scale your business, drive revenues and allow you invest back into operations to create more efficiency. Greater efficiencies lead to fatter profit margins, which allow you to invest even more on improvements, creating a virtuous cycle.

Yet when you are trying something to do something truly new and different, trying to scale too fast can kill your business even before it’s really gotten started. A truly revolutionary product is unpredictable because, by its very nature, it’s not well understood. Charging boldly into the unknown is a sure way to run into unanticipated problems that are expensive to fix at scale.

A better strategy is to identify a hair on fire use case — someone who needs a problem fixed so badly that they are willing to overlook the inevitable glitches. They will help you identify shortcomings early and correct them. Once you get things ironed out, you can begin to scale for more ordinary use cases.

For example, developing a self-driving car is a risky proposition with a dizzying amount of variables you can’t account for. However, a remote mine in Western Australia, where drivers are scarce and traffic nonexistent, is an ideal place to test and improve the technology. In a similar vein, Google Glass failed utterly as a mass product, but is getting a second life as an industrial tool. Sometimes it’s better to build for the few than the many.

3. Start With The Monkey First

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 big barrier to making it happen. When I try to ask about that, they just shut down.

Make no mistake. Innovation isn’t about ideas, it’s about solving problems. The truth is that nobody cares about what ideas you have, they care about the problems you can solve for them. The reason that most people can’t innovate isn’t because they don’t have ideas, but because they lack the perseverance needed to stick with a really tough problem until it’s cracked.

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.

4. The Next Big Thing Always Starts Out Looking Like Nothing At All

When Alexander Fleming first published his discovery of penicillin, no one really noticed. When Xerox executives first got a look at the Alto — the machine that would become the model for the Macintosh seven years later — they didn’t see what the big deal was. When Jim Allison first showed pharmaceutical executives his idea for cancer immunotherapy, not one would invest in it.

We always think that when we see the next big thing it will be obvious, but the truth is that it always starts out looking like nothing at all. The problem is that when something truly has the power to change the world, the world isn’t ready for it yet. It needs to build advocacy, gain traction among a particular industry or field and combine with other innovations before it can make an impact.

But no one ever tells you that. We are conditioned to think that someone like Steve Jobs or Elon Musk just stands up on stage, announces that the world has changed and everybody just goes along. It never really happens that way because innovation is never a single event. It is a long process of discovery, engineering and transformation that usually takes about 30 years to fully complete.

Don’t worry about people stealing your ideas,” said the computing pioneer Howard Aiken. “If your ideas are any good, you’ll have to ram them down people’s throats” and never were truer words spoken. Great innovators aren’t just people with ideas, they are people who are willing to stick it out, take the shots from people who ridicule them and, eventually, if they are lucky, they really do change the world.

— Article courtesy of the Digital Tonto blog and previously appeared on Inc.com
— Image credits: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.






Career Development at Its Best

Leave a reply

Career Development at Its Best

GUEST POST from Geoffrey A. Moore

A colleague recently forwarded me an article about upskilling one’s team. I am on board with the first part—innovating from within—but I am not comfortable with the concept of “upskilling.” Here’s why.

Upskilling implies that the challenges you face lend themselves to known skilled responses. Combined with the idea of training, it also implies that you have that skills knowledge already in-house and simply need to transfer it to a new cohort. I can see both of these ideas being applicable to technical work, but I don’t think they reflect the realities of knowledge work. There, instead, I think we need to substitute learning for training and experience for upskilling.

Whereas training puts the responsibility for a successful outcome on the trainer, learning puts it on the learner. In the world of knowledge work, that’s where it has to sit. We need to develop ourselves—no one else can do it for us. But we need experience to do so, and this is where managers can have a big impact. It is not the training we give our teams but rather the assignments we entrust to them that let them build new muscles.

Assigning an inexperienced person to a new challenge is always a risk—for them, for their manager, and for the customer of the work to be done. Unfortunately, without risk, there is no learning. There is no risk-free way to learn. So the manager’s goal is to create opportunity while mitigating risk.

One of the best means for so doing is assigning people the role of the Single Accountable Leader (SAL). The need for a SAL arises in any cross-functional initiative where hierarchy of authority is replaced by team collaboration. Just as a football team needs a quarterback to run a play that involves 11 people collaborating toward one outcome, so does a cross-functional initiative need a single accountable leader to be the focus of decision-making as the team adapts to unfolding events. This person need not be an expert. They need to be vigilant. They need to stay on top of things. They need to inquire and inspect, to detect when the effort is going off course, to focus the team on redirecting it, to get counsel from their mentors, and to escalate issues that are beyond their ability to address. Most of all, they need to care.

When people care, they learn. They go the extra mile. They bring out the best in others. And in so doing, they build the new muscle that will qualify them for a larger role in the enterprise. This to me is career development at its best. The SAL assignment is the most precious gift that managers and mentors can bestow upon their charges. I hope you can take advantage of it.

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

Image Credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.






Do You Bring Your Whole Self to Work?

1 Reply

Do You Bring Your Whole Self to Work?

GUEST POST from Mike Shipulski

Do you bring your whole self to work? If not, how do you feel about that?

When you demonstrate your unique goodness and it’s met with “You don’t fit in.” they may say they want you to fit in, but, really, that’s objective evidence that they need your unique goodness.

Witches were burned at the stake because their special powers frightened people.

If it’s a good idea, don’t block it because people call it heresy.

The Universe doesn’t care if it’s heresy, as long as it’s a good idea.

The Universe doesn’t discriminate against witches.

If you’re a plumber that fixes pipes and fixes potholes, they’ll expect you to fix pipes and fill potholes.

Sometimes you’ve got to withhold the solution If you want the organizational learning to happen.

If you fill all the potholes, the company never learns that someone’s not doing their job.

A plumber who fixes pipes and fills potholes should be paid more than a plumber that just fixes pipes.

When no one listens to reason, the only thing left to do is let the wheels fall off.

And if you really care about the long-term success of the company, you’ll let them fall off.

If you see things differently, you’re obligated to say so, even if you’re wrong.

When you speak truth to Power, does Power thank you or kick you?

If after speaking unsayable truth to Power, they kick you, that says a lot about Power.

When you’re satisfied with what you have, striving-based motivation tactics have no power.

It’s easy to mentor down into the organization, but it takes a special person to mentor uphill.

Never do your boss’s job.

When successful thinking becomes geriatric, it’s time for hospice.

Successful business models change only after they become unsuccessful.

Change happens only after exhausting all other possibilities. And it takes special people to make it happen.

If you ‘re afraid and hold back because you’re concerned about being burned at the stake, you should put your magic wand in your pocket, jump on your broom (or vacuum cleaner), and find another job.

Image credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.






AI Can Help Attract, Retain and Grow Customer Relationships

Leave a reply

AI Can Help Attract, Retain and Grow Customer Relationships

GUEST POST from Shep Hyken

How do you know what your customers want if they don’t tell you? It’s more than sending surveys and interpreting data. Joe Tyrrell is the CEO of Medallia, a company that helps its customers tailor experiences through “intelligent personalization” and automation. I had a chance to interview him on Amazing Business Radio and he shared how smart companies are using AI to build and retain customer relationships. Below are some of his comments followed by my commentary:

  • The generative AI momentum is so widespread that 85% of executives say the technology will be interacting directly with customers in the next two years. AI has been around for longer than most people realize. When a customer is on a website that makes suggestions, when they interact with a chatbot or get the best answers to frequently asked questions, they are interacting with AI-infused technology, whether they know it or not.
  • While most executives want to use AI, they don’t know how they want to use it, the value it will bring and the problems it will solve. In other words, they know they want to use it, but don’t know how (yet). Tyrrell says, “Most organizations don’t know how they are going to use AI responsibly and ethically, and how they will use it in a way that doesn’t introduce unintended consequences, and even worse, unintended bias.” There needs to be quality control and oversight to ensure that AI is meeting the goals and intentions of the company or brand.
  • Generative AI is different than traditional AI. According to Tyrrell, the nature of generative AI is to, “Give me something in real time while I’m interacting with it.” In other words, it’s not just finding answers. It’s communicating with me, almost like human-to-human. When you ask it to clarify a point, it knows exactly how to respond. This is quite different from a traditional search bar on a website—or even a Google search.
  • AI’s capability to personalize the customer experience will be the focus of the next two years. Based on the comment about how AI technology currently interacts with customers, I asked Tyrrell to be more specific about how AI will be used. His answer was focused on personalization. The data we extract from multiple sources will allow for personalization like never before. According to Tyrrell, 82% of consumers say a personalized experience will influence which brand they end up purchasing from in at least half of all shopping situations. The question isn’t whether a company should personalize the customer experience. It is what happens if they don’t.
  • Personalization isn’t about being seen as a consumer, but as a person. That’s the goal of personalization. Medallia’s North Star, which guides all its decisions and investments, is its mission to personalize every customer experience. What makes this a challenge is the word every. If customers experience this one time but the next time the brand acts as if they don’t recognize them, all the work from the previous visit along with the credibility built with the customer is eroded.
  • The next frontier of AI is interpreting social feedback. Tyrrell is excited about Medallia’s future focus. “Surveys may validate information,” says Tyrrell, “but it is often what’s not said that can be just as important, if not even more so.” Tyrrell talked about Medallia’s capability to look everywhere, outside of surveys and social media comments, reviews and ratings, where customers traditionally express themselves. There is behavioral feedback, which Tyrrell refers to as social feedback, not to be confused with social media feedback. Technology can track customer behavior on a website. What pages do they spend the most time on? How do they use the mouse to navigate the page? Tyrell says, “Wherever people are expressing themselves, we capture the information, aggregate it, translate it, interpret it, correlate it and then deliver insights back to our customers.” This isn’t about communicating with customers about customer support issues. It’s mining data to understand customers and make products and experiences better.

Tyrrell’s insights emphasize the opportunities for AI to support the relationship a company or brand has with its customers. The future of customer engagement will be about an experience that creates customer connection. Even though technology is driving the experience, customers appreciate being known and recognized when they return. Tyrrell and I joked about the theme song from the TV sitcom Cheers, which debuted in 1982 and lasted 11 seasons. But it really isn’t a joke at all. It’s what customers want, and it’s so simple. As the song title suggests, customers want to go to a place Where Everybody Knows Your Name.

Image Credits: Unsplash

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.






Creating Effective Digital Teams

1 Reply

Creating Effective Digital Teams

GUEST POST from Howard Tiersky

Creating digital products is a multi-disciplinary process, blending creativity, engineering, strategy, customer support, legal regulations and more. How to structure their teams is a major challenge faced by large enterprises and global brands undergoing a digital transformation. Specifically, they need to answer the following three questions:

  1. What’s the optimal way to organize the necessary roles and responsibilities?
  2. Which part of the organization should own each capability?
  3. How do we get everyone working together?

The optimal structure for digital teams varies across different organizations. At FROM, we use a base framework that identifies fifteen key roles or competencies that are part of creating and operating most digital properties. Those roles are divided into three conceptual teams: the Digital Business Team, the Digital Technology Team, and the Extended Business Team.

The Digital Business Team

  1. Digital Business Vision Owner: The Business Vision Owner defines the key business measures and objectives for the digital property, including target market segments and their objectives. This “visioneer” makes final decisions on product direction.
  2. Product Management: Product Management owns the product on a day-to-day basis, and liaises with other areas to make sure the digital value proposition is realized. They’re responsible for commissioning and reviewing customer research to develop and maintain the product roadmap in terms of the business vision and can prioritize the backlog of changes and improvements.
  3. Program Management: Distinct from the Product Manager, the Program Manager is responsible for owning the long-term plan to achieve the product roadmap, including budgets and resource allocations, and for maintaining the release schedule.
  4. User Interface/User Experience: UI/UX is responsible for the overall look and feel of the digital product. They develop and maintain UI standards to be used as the product is developed, are involved in user testing, and QA new releases.
  5. Content Development: Content Development creates non-campaign and non-marketing or editorial content for the site, including articles, instructions, and FAQ or helps content. Their job is to create content that’s easy to understand and consistent with the brand or voice of the product or site.

The Digital Technology Team

  1. Front End Development: Front End Development selects frameworks and defines front-end coding standards for any technologies that will be used. They’re also responsible for writing code that will execute in the browser, such as HTML, HTML5, JavaScript, and mobile code (e.g., Objective-C.) Front End Development drives requirements for back-end development teams, to ensure the full user experience can be implemented.
  2. Back End Development: Back End Development manages core enterprise systems, including inventory, financial, and CRM. They’re responsible for exposing, as web services, the capabilities that are needed for front-end development. They’re responsible for developing and enforcing standards to protect the integrity of those enterprise systems, as well as reviewing requests for and implementing new capabilities.
  3. Data: Data develops and maintains enterprise and digital specific data models, managing data, and creating and maintaining plans for data management and warehousing. They monitor the health of databases, expose services for data access, and manage data architecture.
  4. Infrastructure: Infrastructure maintains the physical hardware used for applications and data. They maintain disaster and business continuity programs and monitor the scalability and reliability of the physical infrastructure. They also monitor and proactively manage the security of the infrastructure environment.
  5. Quality Assurance: Quality Assurance creates and maintains QA standards for code in production, develops automated and manual test scripts, and executes any integration, browser, or performance testing scenarios. They also monitor site metrics to identify problems proactively. (It should be noted that, though you want dedicated QA professionals on your team, QA is everyone’s responsibility!)

The Extended Business Team

  1. Marketing: Marketing is responsible for some key digital operations. They develop offers and campaigns to drive traffic. They manage email lists and execution and manage and maintain the CRM system.
  2. Product and Pricing: Product and Pricing responsibility can vary, depending on industry and type of digital property. When appropriate, they develop, license or merchandise anything sold on the site. They set pricing and drive requirements for aligning digital features with any new products based on those product’s parameters.
  3. Operations: Operations is responsible for fulfillment of the value proposition. For commerce sites, for example, this includes picking, packing and shipping orders. For something like a digital video aggregation site, responsibilities include finding, vetting and uploading new video content.
  4. Business Development: Business Development is focused on creating partnerships that increase traffic and sales, or find new streams of revenue.
  5. Customer Support: Customer support is responsible for maintaining knowledge of digital platforms, policies, and known issues and solutions. They assist customers with problems and questions and track customer interactions to report on trends and satisfaction levels.

How these teams and the roles within them fit together varies from company to company. However, it’s good practice to review this model to see, first, if you have these key roles represented in your organization. Then, make sure to create well-defined responsibilities and processes, and finally, look at how they function together, to see if they’re organized in the most effective manner. If your Digital Business, Digital Technology, and Extended Business teams are in sync, all your projects will benefit.

This article originally appeared on the Howard Tiersky blog
Image Credits: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.






These Forgotten Customers Are Key to Your Success

Leave a reply

These Forgotten Customers Are Key to Your Success

GUEST POST from Robyn Bolton

“There is only one boss. The customer.” – Sam Walton

With all the buzz around human-centered design, customer-centric businesses, and external-facing organizations, corporate America is (finally) waking up to the importance and value of creating things that people actually want and that solve people’s problems.

Teams of innovators, ethnographers, socialists, researchers, and consultants scurry about gathering customer insights, soliciting customer feedback, and generating reports that can be funneled back to R&D, innovation, and product development teams to inform the development of the Next Big Thing.

While this is all important work, amidst all of this activity, one customer is consistently overlooked. And it is this customer that often decides the fate of the Next Big Thing

There is only one first customer. Your boss.

Let’s start with what a customer is:

“The recipient of a good, service, product, or idea obtained from a seller, vendor, or supplier via a financial transaction or exchange for money or some other valuable consideration.

Yes, you should spend a lot of time getting to know the people outside your company who will eventually be asked to exchange money for the good, product, or service you are creating.

You also need to spend time getting to know the people inside your organization who you are currently asking to exchange money (give you a budget) or some other valuable consideration (time, people, permission) for your idea and its development.

And you need convince them that “a financial transaction” is worth it because, if you don’t they can and will spend their money elsewhere.

Your boss is a tough customer

No matter what type of company you are in — from a company of 10 to a company of 10,000 — you are faced with limited resources. A dollar spent in one place means a dollar not spent in another place. A person allocated to one team means one less person on another team.

Managers have to make resources allocation trade-offs all the time but are often moving pieces between functions and teams where they know the ROI of additional investments. This situation changes dramatically when a manager must decide whether to invest resources into a new and uncertain venture or to invest in the core, and much more certain, business.

Convincing your boss to buy your idea, especially if that idea is a new venture, is tough because you’re asking your boss to buy (or invest in) something with an uncertain ROI rather than buy (or invest in) something with a more certain ROI. But you can be successful if you understand your boss.

Your boss can be understood (and their decisions anticipated)

First, get comfortable with the fact that your boss is a human being. And, just like other human beings, your boss makes lots of decisions, believes that these decisions are based on logic and reason, and actually bases most decisions more on emotion and instinct.

As frustrating as this may be when you are at the receiving end of these decisions, take comfort in the fact that you can actually use the tools you use to understand external customers to understand, and even anticipate, your boss’ decisions.

Here’s how:

  1. What is the current business situation? While this is usually an easy question to answer, it can be hard to anticipate what impact it will have on your boss’ willingness to invest. Just as most people are hesitant to invest in something new when the current business environment is poor, many people are equally hesitant to invest when business is booming. This is usually because investments in the core business are generating more than usual upside and that’s great for your boss and/or there is no urgency to do anything new because people assume the good times will go on forever (news flash: they wont’). So while you can’t anticipate what impact the answer to this question will have on your odds of securing investment, you do need to know the context within which you are asking.
  2. What is your boss being asked to deliver? How is she measured and rewarded? Is your boss expected to deliver revenue increases? She’ll be drawn to new ideas that increase revenue. Cost savings? Then pitch ways to improve efficiency. How much time does she have to deliver results? If she needs to show results quarterly, you have to generate results quickly. If she has a year to show improvement, you have a longer runway to show results.
  3. What is your boss’ reputation? Does she like it? Humans are hard-wired to be social creatures so, whether we admit it or not, we really care how other people see us. What is your boss’ reputation — is she known for being a steady hand that consistently delivers or a renegade willing to rock the boat and take risks? And how does she feel about her reputation? Does she like it or does she see herself differently? If you have a boss that likes being seen as reliable and a defender of the status quo, you’re going to have a much harder time selling your new idea than if you boss is seen (or wants to be seen) as the next Steve Jobs.

With the answers to these questions, you can figure out the likelihood that your boss will buy your idea. If you boss is managing a business that is struggling, is expected to increase revenue after years of decreases, and is happy to be known as someone who always delivers, it’s unlikely she’ll be willing to invest resources in a new and unproven idea. But if your boss is managing a struggling business, is expected to develop new revenue streams that will replace the old ones, and enjoys a reputation as a someone who challenges the status quo, odds are she’ll support a reasonably well-thought out proposal for initial investment in a new venture.

Bottom Line

Before you get the opportunity to sell a new product or service to external customers, you need to sell your idea to internal customers…your boss. Take the time to understand you boss, the things that motivate her and the issues and challenges that she faces. Then, just as you create a product or service to solve your external customers’ problems, you can create a pitch that shows your boss how your idea solves her challenges.

Approach your boss as you would a customer and you’re likely to get the support you need. Forget that your boss is your first customer and you may never get the chance to pitch to the ones you’ve spent so much time studying.

Image credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.