Category Archives: Innovation

Practical Applications of AI for Human-Centered Innovation

Beyond the Hype

Practical Applications of AI for Human-Centered Innovation

GUEST POST from Chateau G Pato

The air is thick with the buzz of Artificial Intelligence. From Davos to daily headlines, the conversation often oscillates between utopian dreams and dystopian fears. As a thought leader focused on human-centered change and innovation, my perspective cuts through this noise: AI is not just a technology; it is a powerful amplifier of human capability, especially when applied with empathy and a deep understanding of human needs. The true innovation isn’t in what AI can do, but in how it enables humans to do more, better, and more humanely.

Too many organizations are chasing AI for the sake of AI, hoping to find a magic bullet for efficiency. This misses the point entirely. The most transformative applications of AI in innovation are those that don’t replace humans, but rather augment their unique strengths — creativity, empathy, critical thinking, and ethical judgment. This article explores practical, human-centered applications of AI that move beyond the hype to deliver tangible value by putting people at the core of the AI-driven innovation process. It’s about designing a future where humanity remains in the loop, guiding and benefiting from intelligent systems.

AI as an Empathy Amplifier: Deepening Understanding

Human-centered innovation begins with deep empathy for users, customers, and employees. Traditionally, gathering and synthesizing this understanding has been a labor-intensive, often qualitative, process. AI is revolutionizing this by giving innovators superpowers in understanding human context:

  • Sentiment Analysis for Voice of Customer (VoC): AI can process vast quantities of unstructured feedback — customer reviews, social media comments, call center transcripts — to identify emerging pain points, unspoken desires, and critical satisfaction drivers, often in real-time. This provides a granular, data-driven understanding of user sentiment that human analysts alone could never achieve at scale, leading to faster, more targeted product improvements.
  • Personalized Journeys & Predictive Needs: By analyzing behavioral data, AI can predict individual user needs and preferences, allowing for hyper-personalized product recommendations, customized learning paths, or proactive support. This moves from reactive service to anticipatory human care, boosting customer loyalty and reducing friction.
  • Contextualizing Employee Experience (EX): AI can analyze internal communications, HR feedback, and engagement surveys to identify patterns of burnout, identify skill gaps, or flag cultural friction points, allowing leaders to intervene with targeted, human-centric solutions that improve employee well-being and productivity. This directly impacts talent retention and operational efficiency.

“The best AI applications don’t automate human intuition; they liberate it, freeing us to focus on the ‘why’ and ‘how’ of human experience. This is AI as a partner, not a replacement.” — Braden Kelley


Case Study 1: AI-Powered User Research at Adobe

The Challenge:

Adobe, with its vast suite of creative tools, faces the constant challenge of understanding the diverse, evolving needs of millions of users — from professional designers to casual creators. Traditional user research (surveys, interviews, focus groups) is time-consuming and expensive, making it difficult to keep pace with rapid product development cycles and emerging user behaviors.

The AI-Powered Human-Centered Solution:

Adobe developed internal AI tools that leverage natural language processing (NLP) to analyze immense volumes of unstructured user feedback from forums, support tickets, app store reviews, and in-app telemetry. These AI systems identify recurring themes, emerging feature requests, and points of friction with remarkable speed and accuracy. Instead of replacing human researchers, the AI acts as an an ‘insight engine,’ highlighting critical areas for human qualitative investigation. Researchers then use these AI-generated insights to conduct more focused, empathetic interviews and design targeted usability tests, ensuring human intelligence remains in the loop for crucial interpretation and validation.

The Innovation Impact:

This approach drastically accelerates the ideation and validation phases of Adobe’s product development, translating directly into faster time-to-market for new features. It allows human designers to spend less time sifting through data and more time synthesizing insights, collaborating on creative solutions, and directly interacting with users on the most impactful issues. Products are developed with a deeper, faster, and more scalable understanding of user pain points and desires, leading to higher adoption, stronger user loyalty, and ultimately, increased revenue.


AI as a Creativity & Productivity Partner: Amplifying Output

Beyond empathy, AI is fundamentally transforming how human innovators generate ideas, prototype solutions, and execute complex projects, not by replacing creative thought, but by amplifying it while maintaining human oversight.

  • Generative AI for Ideation & Concepting: Large Language Models (LLMs) can act as powerful brainstorming partners, generating hundreds of diverse ideas, marketing slogans, or design concepts from a simple prompt. This allows human creatives to explore a broader solution space faster, finding novel angles they might have missed, thereby reducing ideation cycle time and boosting innovation output.
  • Automated Prototyping & Simulation: AI can rapidly generate low-fidelity prototypes from design specifications, simulate user interactions, or even predict the performance of a physical product before it’s built. This drastically reduces the time and cost of the early innovation cycle, making experimentation more accessible and leading to significant R&D savings.
  • Intelligent Task Automation (Beyond RPA): While Robotic Process Automation (RPA) handles repetitive tasks, AI goes further. It can intelligently automate the contextual parts of a job, managing schedules, prioritizing communications, or summarizing complex documents, freeing human workers for higher-value, creative problem-solving. This leads to increased employee satisfaction and higher strategic output.

Case Study 2: Spotify’s AI-Driven Music Discovery & Creator Tools

The Challenge:

Spotify’s core challenge is matching millions of users with tens of millions of songs, constantly evolving tastes, and emerging artists. Simultaneously, they need to empower artists to find their audience and create efficiently in a crowded market. Traditional human curation alone couldn’t scale to this complexity.

The AI-Powered Human-Centered Solution:

Spotify uses a sophisticated AI engine to power its personalized recommendation algorithms (Discover Weekly, Daily Mixes). This AI doesn’t just match songs; it understands context — mood, activity, time of day, and even the subtle social signals of listening. This frees human curators to focus on high-level thematic curation, editorial playlists, and breaking new artists, rather than sifting through endless catalogs. More recently, Spotify is also exploring AI tools for artists, assisting with everything from mastering tracks to suggesting optimal release times based on audience analytics, always with human creators retaining final creative control.

The Innovation Impact:

The AI system allows Spotify to deliver a highly personalized and human-feeling music discovery experience at an unimaginable scale, directly driving user engagement and subscriber retention. For artists, AI acts as a creative assistant and market intelligence tool, allowing them to focus on making music while gaining insights into audience behavior and optimizing their reach. This symbiotic relationship between human creativity and AI efficiency is a hallmark of human-centered innovation, resulting in a stronger platform ecosystem for both consumers and creators.

The future of innovation isn’t about AI replacing humans; it’s about AI elevating humanity. By focusing on how AI can amplify empathy, foster creativity, and liberate us from mundane tasks, we can build a future where technology truly serves people. This requires a commitment to responsible AI development — ensuring fairness, transparency, and human oversight. The challenge for leaders is not just to adopt AI, but to design its integration with a human-centered lens, ensuring it empowers, rather than diminishes, the human spirit of innovation, and delivers measurable value across the organization.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Unsplash

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A Letter to Innovation Santa

Ten Essentials for an Innovator’s Christmas List

A Letter to Innovation Santa

GUEST POST from John Bessant

Christmas, as my 6-year old never tires of reminding me, is coming. Never mind that technically it’s a month away and forget the efforts I make, Scrooge-like, not to allow any trace of the season to cross our threshold until at least 1st December. She excitedly points out that everywhere — the TV and online adverts, the shop decorations, even some of our early bird neighbors with their flashing light displays — everywhere the signals are unmistakable. ‘It’s nearly here!’

Which prompts her to write lists, long and getting longer, of gift ideas in case Santa is short of the relevant information about this year’s must-have items without which a six-year old’s world can never be complete. I feel like King Canute, water lapping around my ankles as I desperately try to stem the tide, inevitability fast approaching on my horizon.

In a desperate attempt to distract myself from these seasonal waves I began thinking about the kind of list I might put together for a would-be innovating organization. Assuming there was an innovation equivalent of the old gentleman at the North Pole what might he be working on with his elves right now? What are his stock-pickers pulling off the warehouse shelves and loading up on the sleigh? What might be on the must-have list for an innovation Christmas?

Turns out to be a useful exercise in choice editing. Just like my daughter, my early lists grew and grew like Topsy, sprawling over several pages. And containing lots of items in the ‘Motherhood and apple pie’ class — things which were unarguably ‘good’ for innovation but a bit vague in how they might actually be implemented. ‘Make innovation happen every day in every way’ or ‘Put innovation at the heart of everything you do’, or ‘Keep reinventing the organization’ kind of thing — nice sentiments but not exactly helpful.

Back to the drawing board, trying to focus on things which not only represent important elements but also have some specific tools to help put them into practice. So here’s the result. If you’re looking for inspiration for your seasonal innovation shopping here’s a few ideas that might help. (And if you believe in an Innovation Santa they might be useful items to add to the ‘what I’d really like’ list you’re about to send up the chimney)

First the wrapping paper.

Innovation matters. If we don’t change what we offer the world (our products and services) and the ways we create and deliver them (our processes) then there’s a good chance that we won’t survive long in today’s turbulent market-place. The issue isn’t about whether or not to innovate but how?

The good news is that we’ve learned a lot about this challenge; whilst innovation still remains a risky business there are some key insights which can help stack the deck in our favour. Over a hundred years of research consistently shows that successful innovators

1. Manage innovation as a process.

Innovation isn’t like the cartoon moment with a light bulb flashing on above someone’s head. It’s a journey, involving key steps (search, select, implement) to create value from ideas. Anyone might get lucky once but in order to repeat the innovation trick we need a process for managing this; it doesn’t have to be bureaucratic, but it does have to be systematic. So, to help you work with this one there are plenty of frameworks which you can adapt, checklists to make sure you’ve got a system for innovation — you could do a lot worse than start with the framework which the ISO launched this year for an Innovation Management Standard …

2. Explore all the innovation space available.

There are many different ways to innovate, from changing our offering, updating our processes, exploring new market contexts and even switching our underlying business model. It’s a little like an innovation compass and the challenge is to make sure we explore the full 360 degrees of opportunity. Once again there are plenty of tools to help with this — try looking at Doblin’s ten types of innovation, play with the 4Ps innovation compass or explore Blue Ocean thinking

3. Have an innovation strategy

A clear roadmap of where and how innovation will take the business forward. It’s easy to wave the flag and shout about how important innovation is; serious players think through their strategy for dealing with it, share the roadmap and make sure that people buy into it. And there are plenty of stocking fillers here to help with strategic positioning and analysis, from good old PEST and SWOT through to more thorough future scanning, scenarios and road mapping and discovery-driven planning.

4. Pay attention to the small stuff.

Although radical changes are the ones which hit the headlines the underlying economic evidence is clear; most innovation, most of the time, is about doing what we do a little better. Incremental innovation of this kind adds up and has the additional advantage that it is much lower in risk, advancing slowly along well-known frontiers. This is where the lean toolkit becomes a must-have — whether it’s tools like fishbones and process maps for continuous improvement of processes or value analysis and product feature maps for our offerings.

5. Mobilize the mainstream.

Many organizations have specialists who are given the responsibility for innovation — a bit like James Bond, they have the ‘license to innovate’. But every human being comes fitted with the standard equipment to enable us to be creative, finding solutions to problems and coming up with new ideas. Smart innovators mobilize this creativity across the entire organization. And there’s a rich toolbox to help with this one, from simple variants on the humble suggestion scheme to powerful collaboration platforms to ensure voices get heard, ideas get shared and collective intelligence puts its weight behind the big strategic challenges facing the organization.

6. Make connections.

Innovation has always been a multi-player game rather than a solo act and these days the talk is all about ‘open innovation’. Simply put, in a world rich in knowledge even the largest organization has to recognize that ‘not all the smart people work for us’. The game has shifted from one where knowledge creation and ownership is key to one where managing knowledge flow is the critical ingredient. The good news for smaller firms is that this levels the playing field; you don’t have to have all the resources for innovation as long as you know where they are and how to connect to them. By now some version of ‘open innovation’ should be at the heart of your strategy and there are plenty of tools and frameworks to help you work out what connections you need and how to build them. It might also be worth looking at your absorptive capacity — how well placed are you to take advantage of all the rich knowledge that’s out there, making sure you don’t get a kind of ‘knowledge indigestion’ as a result of gorging yourself on everything that’s on offer!

7. Build an innovative organization.

Companies like 3M and Google are famous for giving their staff time and space to explore and experiment, not just because they are generous employers trying to attract and retain talented employees. What they’re really doing is actively trying to recreate the entrepreneurial spirit which began their businesses. They believe that embedding that spirit in ‘the way we do things round here’ gives them a real long-term edge — everyone is an entrepreneur. But they also know that creating that kind of climate needs work — on the physical layout (to make sure people have the chance to creatively collide) on time (to allow ideas to emerge and incubate), on support and space (to provide fertile environments for creativity) and on their approach to ‘failure’ (not punishing people when things don’t work but encouraging an experimental learning approach). Maybe take a look at some of the tools available to help you assess how much of a creative climate you have — and focus on what you might usefully work on to develop it further.

8. Co-create with users.

Learning from markets has always been important but customers aren’t passive, they can also be a rich source of ideas for innovation. Finding ways to tap into user innovation not only generates more diverse ideas, it also helps create a partnership with the marketplace which improves adoption of innovation. People will use things, work with processes, feel a sense of ‘ownership’ if they’ve been involved in the innovation process. And the good news here is that we have plenty of tools and frameworks to help — starting with design thinking and embracing approaches like lead user methods

9. Accept failure

Innovation is omelet territory and the odd broken egg is an important part. The key is to learn from failures and use the information to build and strengthen capability for the future. That’s been the big lesson coming out of the whole lean -start-up’ model for developing new ventures and it sits just as well inside established organizations who make use of agile approaches. Once again there are plenty of tools which capture this ‘build-measure-learn — pivot’ approach which builds on ‘intelligent failure’ …

10. Build dynamic capability.

Innovation involves a moving target — constant changes in technologies, markets, competition, regulation and a host of other variables. Successful innovators build on the above principles, but they also keep checking and updating their innovation management capabilities, learning new tricks and discarding old ones which no longer work. Innovation model innovation. Having a commitment to structured and constructively critical reflection is a key to this ‘metacognition’ approach — and there are plenty of helpful frameworks to enable and support that process. Check out the Innovation Fitness Test as an example …

One last seasonal thought. Innovation, like a puppy, is for life, not just for Christmas. It’s something we need to think about all year round. So, it might be worth recycling your Christmas innovation list into something you could use as a set of New Year resolutions …

You can find a podcast version of this here

If you’d like more songs, stories and other resources on the innovation theme, check out my website here, or listen to my podcast here, and if you’d like to learn with me take a look at my online course here

Image credit: Pixabay

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Nominations Closed – Top 40 Innovation Bloggers of 2022

Nominations Closed for the Top 40 Innovation Bloggers of 2022Human-Centered Change and Innovation loves making innovation insights accessible for the greater good, because we truly believe that the better our organizations get at delivering value to their stakeholders the less waste of natural resources and human resources there will be.

As a result, we are eternally grateful to all of you out there who take the time to create and share great innovation articles, presentations, white papers, and videos with Braden Kelley and the Human-Centered Change and Innovation team. As a small thank you to those of you who follow along, we like to make a list of the Top 40 Innovation Bloggers available each year!

Our lists from the ten previous years have been tremendously popular, including:

Top 40 Innovation Bloggers of 2015
Top 40 Innovation Bloggers of 2016
Top 40 Innovation Bloggers of 2017
Top 40 Innovation Bloggers of 2018
Top 40 Innovation Bloggers of 2019
Top 40 Innovation Bloggers of 2020
Top 40 Innovation Bloggers of 2021

Do you just have someone that you like to read that writes about innovation, or some of the important adjacencies – trends, consumer psychology, change, leadership, strategy, behavioral economics, collaboration, or design thinking?

Human-Centered Change and Innovation is now looking for the Top 40 Innovation Bloggers of 2022.

The deadline for submitting nominations is December 24, 2022 at midnight GMT.

You can submit a nomination either of these two ways:

  1. Sending us the name of the blogger and the url of their blog by @reply on twitter to @innovate
  2. Sending the name of the blogger and the url of their blog and your e-mail address using our contact form

(Note: HUGE bonus points for being a contributing author)

So, think about who you like to read and let us know by midnight GMT on December 24, 2022.

We will then compile a voting list of all the nominations, and publish it on December 25, 2022.

Voting will then be open from December 25, 2022 – January 1, 2023 via comments and twitter @replies to @innovate.

The ranking will be done by me with influence from votes and nominations. The quality and quantity of contributions by an author to this web site will be a contributing factor.

Contact me with writing samples if you’d like to publish your articles on our platform!

The official Top 40 Innovation Bloggers of 2022 will then be announced on here in early January 2023.

We’re curious to see who you think is worth reading!

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Building a Foresight Muscle

Integrating Futures Thinking into Your Strategy

Building a Foresight Muscle - Integrating Futures Thinking into Your Strategy

GUEST POST from Chateau G Pato

In the world of human-centered change and innovation, we often talk about agility—the ability to react quickly. But agility alone is no longer enough. The pace of disruption, from Generative AI to climate instability, has made the classic five-year strategic plan feel like an exercise in nostalgia. What companies need now is foresight: the systematic discipline of scanning the horizon for potential threats and opportunities to prepare for a range of plausible futures, not just the one we wish for.

Foresight is not about predicting the future; it’s about creating a more resilient present. It’s the innovation discipline that bridges the gap between today’s operational demands and tomorrow’s existential risks. If your strategy is only built on what happened last quarter, you are driving your organization by looking solely in the rearview mirror. To survive and thrive in the Age of Perpetual Disruption, organizations must move from being reactive to being pre-emptive by integrating futures thinking directly into their core strategic planning process. This requires building a dedicated “Foresight Muscle.”

The Foresight Cycle: From Weak Signals to Strategy

Futures thinking is a cyclical, human-driven process designed to challenge organizational rigidity. The goal is to develop a portfolio of possibilities, often called Scenarios, which force decision-makers to ask, “What if our core assumptions are completely wrong?”

The Three Pillars of Futures Integration:

  • 1. Horizon Scanning (The Data Intake): Systematically monitor technological, economic, political, environmental, and social (T.E.P.E.S.) trends. This moves beyond standard market research to actively seek out weak signals—small, seemingly insignificant anomalies (a niche patent, a fringe academic paper, a micro-community trend) that could compound into massive shifts a decade from now.
  • 2. Scenario Planning (The Cognitive Workout): Develop 3–5 alternative, equally plausible future narratives. These scenarios should not include the “default” future. By immersing executive teams in these plausible worlds, you create experiential learning that reduces the likelihood of future shock.
  • 3. Backcasting (The Strategic Link): Once a desired future state (the most advantageous scenario) is identified, work backward to determine the required actions, milestones, and investments needed today to make that future a reality. This translates abstract foresight into concrete innovation roadmaps.

“Prediction is cheap. Preparation is invaluable. Foresight is the difference between surviving a crisis and capitalizing on a discontinuity.” — Roger Spitz


Case Study 1: Shell and the Power of Scenario Planning

The Challenge:

As early as the 1970s, Royal Dutch Shell, a colossal, capital-intensive energy company, faced immense geopolitical and economic volatility that threatened its long-term stability. Relying on single-point forecasts (predicting one oil price, one political outcome) was a recipe for disaster.

The Foresight Solution:

Shell pioneered the use of Scenario Planning. They developed narratives, such as “The World of Scarcity” and “The World of Abundance,” that explored radical changes in oil supply, regulatory environments, and environmental constraints. Critically, their team was ready when the 1973 oil crisis hit. While other companies were paralyzed by the unexpected shock, Shell was able to quickly recognize the unfolding events as fitting one of their pre-prepared scenarios (The Scarcity World). Because they had already debated the implications of this future, they were able to act decisively while their competitors stalled.

The Strategic Impact:

Shell used foresight not to predict when the crisis would occur, but to train its management to think the unthinkable. This cognitive agility allowed them to reposition assets, secure long-term contracts, and emerge from the crisis significantly stronger than their peers. Their sustained use of scenarios for over four decades demonstrates the power of embedding foresight as a permanent strategic function, not a one-off project.


Case Study 2: Nokia and the Warning Signs Missed

The Challenge:

In the early 2000s, Nokia was the unchallenged king of the mobile phone market. They had internal foresight teams and research labs that were highly aware of the future potential of both touch-screen technology and high-speed data networks (3G/4G). They saw the weak signals of the coming smartphone revolution.

The Failure to Integrate:

Nokia did not lack information; they lacked the organizational fortitude to integrate that information into their core strategy. Their foresight was too isolated. The operational business units, focused on maintaining existing profit margins from hardware, actively resisted internal investment in high-risk, unproven smartphone operating systems (like the future Symbian alternatives). The existing organizational structure and mental models acted as a powerful innovation antibody, rejecting the uncomfortable future presented by their own foresight team.

The Strategic Impact:

When the iPhone launched, it was not a surprise to Nokia’s foresight specialists, but it was a disruptive crisis to the rest of the company because the necessary internal strategic shifts had never been made. This case is a profound lesson: Foresight must be fused with budget allocation and decision-making authority. Having a beautiful set of scenarios is worthless if the organization is incapable of acting on the challenging insights they reveal. Nokia’s demise underscores that strategy without integrated foresight is a slow form of corporate suicide.


Building Your Foresight Muscle: A Human-Centered Approach

Integrating futures thinking is fundamentally a human-centered change effort. It requires challenging biases, fostering intellectual humility, and creating a safe space for counter-narratives. The ultimate human benefit is reduced crisis-induced stress and a shift toward more creative, strategic work. Braden Kelley’s FutureHacking methodology is a great set of tools to leverage if you don’t already have your own toolkit – or to supplement it. Here are three exercises to strengthen your foresight:

  • Challenge Confirmation Bias: Design scenario workshops that actively seek out the data that contradicts your most cherished beliefs. Use diverse teams to reduce the echo chamber effect.
  • Democratize Scanning: Don’t limit horizon scanning to an elite team. Train employees across all levels and geographies — especially customer-facing roles—to recognize and report weak signals. This makes foresight a collective intelligence exercise.
  • Measure Impact, Not Accuracy: Don’t grade your foresight team on whether their prediction came true. Measure their success on whether the scenarios they created led to better, more robust strategic decisions today (e.g., diversifying a supply chain, launching an experimental business unit).

The greatest risk in strategic planning is not being wrong; it’s being rigid. By building a robust foresight muscle — by systematically scanning, scripting scenarios, and backcasting your innovation agenda — you transform your organization from a passive observer of change into an active shaper of its own destiny. Start small, but start now. The future is already signaling its presence; are you listening?

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Pixabay

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What is a Chief Innovation Officer?

What is a Chief Innovation Officer?

GUEST POST from Art Inteligencia

The Chief Innovation Officer is a relatively new position, but one that is gaining traction in many organizations. It is a role that is becoming increasingly important as businesses become more focused on pushing the boundaries of their industries and developing new products and services.

The Chief Innovation Officer is typically responsible for developing innovative strategies and leading the organization’s efforts to identify and implement new ideas and technologies. This person is tasked with creating a culture of innovation that encourages collaboration, experimentation, and risk-taking, while also ensuring that the organization remains competitive and current in the marketplace.

The Chief Innovation Officer generally works closely with the executive team and other leaders within the organization to ensure that the innovation process is well-defined and aligned with the organization’s overall goals and objectives. This person is often responsible for developing and executing an innovation strategy, which may include identifying and testing new ideas, products, services, and processes in order to develop new value for the organization.

The Chief Innovation Officer is also responsible for ensuring that the organization has the necessary resources to bring new ideas to life. This includes assembling the right teams, managing budgets, and developing partnerships and collaborations. Additionally, this position is often responsible for staying abreast of industry trends and changes in order to best position the organization for success.

Ultimately, the Chief Innovation Officer is responsible for helping the organization stay ahead of the competition and remain competitive in the market. This person is a leader who is passionate about innovation and brings a unique perspective to the table. They are an invaluable asset to any organization that is looking to create and maintain a culture of innovation and stay ahead of the curve.

To read more about Chief Innovation Officers, see these other articles:

  1. Hiring the Right Chief Innovation Officer — by Braden Kelley
  2. Birth of the Part-Time Chief Innovation Officer — by Braden Kelley
  3. Are You Hanging Your Chief Innovation Officer Out to Dry? — by Teresa Spangler
  4. Death of the Chief Innovation Officer — by Braden Kelley

Extra Extra: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pexels

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3 Steps to Find the Horse’s A** In Your Company (and Create Space for Innovation)

3 Steps to Find the Horse's A** In Your Company (and Create Space for Innovation)

GUEST POST from Robyn Bolton

Innovation thrives within constraints.

Constraints create the need for questions, creative thinking, and experiments.

But as real as constraints are and as helpful as they can be, don’t simply accept them. Instead, question them, push on them, and explore around them.

But first, find the horse’s a**

How Ancient Rome influenced the design of the Space Shuttle

In 1974, Thiokol, an aerospace and chemical manufacturing company, won the contract to build the solid rocket boosters (SRBs) for the Space Shuttle. The SRBs were to be built in a factory in Utah and transported to the launch site via train.

The train route ran through a mountain tunnel that was just barely wider than the tracks.

The standard width of railroad tracks (distance between the rails or the railroad gauge) in the US is 4 feet, 8.5 inches which means that Thiokol’s engineers needed to design SRBs that could fit through a tunnel that was slightly wider than 4 feet 8.5 inches.

4 feet 8.5 inches wide is a constraint. But where did such an oddly specific constraint come from?

The designers and builders of America’s first railroads were the same people and companies that built England’s tramways. Using the existing tramways tools and equipment to build railroads was more efficient and cost-effective, so railroads ended up with the same gauge as tramways – 4 feet 8.5 inches.

The designers and builders of England’s tramways were the same businesses that, for centuries, built wagons. Wanting to use their existing tools and equipment (it was more efficient and cost-effective, after all), the wagon builders built tramways with the exact distance between the rails as wagons had between wheels – 4 feet 8.5 inches.

Wagon wheels were 4 feet 8.5 inches apart to fit into the well-worn grooves in most old European roads. The Romans built those roads, and Roman chariots made those grooves, and a horses pulled those chariots, and the width of a horses was, you guessed it, 4 feet 8.5 inches.

To recap – the width of a horses’ a** (approximately 4 feet 8.5 inches) determined the distance between wheels on the Roman chariots that wore grooves into ancient roads. Those grooves ultimately dictated the width of wagon wheels, tramways, railroad ties, a mountain tunnel, and the Space Shuttle’s SRBs.

How to find the horse’s a**

When you understand the origin of a constraint, aka find the horse’s a**, it’s easier to find ways around it or to accept and work with it. You can also suddenly understand and even anticipate people’s reactions when you challenge the constraints.

Here’s how you do it – when someone offers a constraint:

  1. Thank them for being honest with you and for helping you work more efficiently
  2. Find the horse’s a** by asking questions to understand the constraint – why it exists, what it protects, the risk of ignoring it, who enforces it, and what happened to the last person who challenged it.
  3. Find your degrees of freedom by paying attention to their answers and how they give them. Do they roll their eyes in knowing exasperation? Shrug their shoulders in resignation? Become animated and dogmatic, agitated that someone would question something so obvious?

How to use the horse’s a** to innovate

You must do all three steps because stopping short of step 3 stops creativity in its tracks.

If you stop after Step 1 (which most people do), you only know the constraint, and you’ll probably be tempted to take it as fixed. But maybe it’s not. Perhaps it’s just a habit or heuristic waiting to be challenged.

If you do all three steps, however, you learn tons of information about the constraint, how people feel about it, and the data and evidence that could nudge or even eliminate it.

At the very least, you’ll understand the horse’s a** driving your company’s decisions.

Image credit: Pixabay

Endnotes:

  1. To be very clear, the origin of the constraint is the horse’s a**. The person telling you about the constraint is NOT the horse’s a**.
  2. The truth is never as simple as the story and railroads used to come in different gauges. For a deeper dive into this “more true than not” story (and an alternative theory that it was the North’s triumph in the Civil War that influenced the design of the SRBs, click here

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Preserving Ecosystems as an Innovation Superpower

Lessons from Picasso and David Attenborough

Preserving Ecosystems as an Innovation Superpower

GUEST POST from Pete Foley

We probably all agree that the conservation of our natural world is important. Sharing the planet with other species is not only ethically and emotionally the right thing to do to, but it’s also enlightened self-interest. A healthy ecosystem helps equilibrate and stabilize our climate, while the potential of the largely untapped biochemical reservoir of the natural world has enormous potential for pharmaceuticals, medicine and hence long-term human survival.

Today I’m going to propose yet another reason why conservation is in our best interest. And not just the preservation of individual species, but also the maintenance of the complex, interactive ecosystems in which individual species exist.

Biomimicry: Nature is not only a resource for pharmaceuticals, but also an almost infinite resource for innovation that transcends virtually every field we can, or will imagine. This is not a new idea. Biomimicry, the concept of mimicking natures’ solutions to a broad range of problems, was first coined by Janine Benyus in 1997. But humans have intuitively looked to nature to help solve problems throughout history. Silk production in ancient bio-technology that co-opts the silk worm, while much of early human habitations were based on caves, a natural phenomenon. More recently, Velcro, wind turbines, and elements of bullet train design have all been attributed to innovation inspired by nature.

And Biomimicry, together with related areas such as biomechanics and bio-utilization taps into the fundamental core of what the front end of innovation is all about. Dig deep into virtually any innovation, and we’ll find it has been stolen from another source. For example, early computers reapplied punch cards from tapestry looms. The Beatles stole and blended liberally from the blues, skiffle, music hall, reggae and numerous other sources. ‘Uberization’ has created a multitude of new business from AirBNB to nanny, housecleaning or food prep services. Medical suturing was directly ‘stolen’ from embroidery, the Dyson vacuum from a sawmill, oral care calcium deposition technology was reapplied from laundry detergents, etc., etc..

Picasso – Great Artists Steal! This is also the creative process espoused by Pablo Picasso when he said ‘good artists borrow, great artists steal’. He ‘stole’ elements of African sculpture and blended them with ideas from contemporaries such as Cézanne to create analytical cubism. In so doing he combined existing knowledge in new ways that created a revolutionary and emergent form of art – one that asked the viewer to engage with a painting in a whole new way. Innovation incarnate!

Ecosystems as an Innovation Resource: The biological world is the biggest potential source of potential innovative ideas we have at our disposal anywhere.  Hence it is an intuitive place to go looking for ideas to solve our biggest innovation challenges. But despite many people trying to leverage this potential goldmine, including myself, it’s never really achieved its full potential. For sure, there are a few great examples, such as Velcro, bullet train flow dynamics or sharkskin surfaces. But given how long we’ve been playing in this sandbox, there are far too few successes. And of those, far too many are based on hindsight, as opposed to using nature to solve a specific challenge. Just look at virtually any article on biomimicry, and the same few success stories show up year after year.

The Resource/Source Paradox. One issue that helps explain this is that the natural world is an almost infinite repository of information. That potential creates a challenging signal to noise’ search problem. The result is enormous potential, but coupled with almost inevitably high failure rates, as we struggle to find the most useful insights

Innovation is More than Ideation: Another challenge is that innovation is not just about ideas or invention; it’s about turning those ideas into practice. In the case of biomimicry, that is particularly hard, as the technical challenge of converting natural technology into viable commercial technologies is hampered because nature works on fundamentally different design principles, and uses very different materials to us. Evolution builds at a nano scale, is highly context dependent, and is result rather than theory led. Materials are usually organic; often water based, and are grown rather than manufactured.  Very different to most conventional human engineering.

Tipping Point: But the good news is that materials science, technology, 3D printing and computational and data processing power, together with nascent AI are evolving at such a fast rate that I’m optimistic that we will soon reach a tipping point that will make search and translation of natural innovations considerably easier than today. Self-learning systems should be able to more easily replicate natural information processing, and 3D printing and nano structures should be able to better mimic the physical constructs of natural systems. AI, or at least massively increased computing power should make it easier for us to both ask the right questions and search large, complex databases.

Conservation as an Innovation Superpower: And that brings me back to conservation as an innovation superpower. If we don’t protect our natural environment, we’ll have a lot less to search, and a lot less to mimic. And that applies to ecosystems as well as individual species. Take the animal or plant out of its natural environment, and it becomes far more difficult to untangle how or why it has evolved in a certain way.

Evolution is the ultimate exploiter of serendipity. It does not have to understand why something works, it simply runs experiments until it stumbles on solutions that do, and natural selection picks the winner(s). That leads to some surprisingly sophisticated innovation. For example, we are only just starting to understand the quantum effects used in avian navigation and photosynthesis. Migratory birds don’t have deep knowledge of quantum mechanics; the beauty of evolution is that they don’t need to. The benefit to us is that we can potentially tap into sophisticated innovation at the leading edge of our theoretical knowledge, provided we know how to define problems, where to look and have sufficient knowledge to decipher it and reduce it to practice. The bad news is that we don’t know what we don’t know. Evolution tapped into quantum mechanics millennia before we knew what it was, so who knows what other innovations lie waiting to be discovered as our knowledge catches up with the nature – the ultimate experimenter.

Ecosystems Matter: But a species without the context of its ecosystem is at best half the story. Nature has solved flight, deep-water exploration, carbon sequestration, renewable energy, high and low temperature resilience and so many more challenges. And it has also done so with 100% utilization and recycling on a systems basis. But most of the underlying innovations solve very specific problems, and so require deep understanding of context.

The Zebra Conundrum: Take the zebra as an example. I was recently watching a David Attenborough documentary about zebras. As a tasty prey animal surrounded by highly efficient predators such as lions, leopards, cheetahs and hyenas, the zebra is an evolutionary puzzle. Why has it evolved a high contrast coat that grabs attention and makes it visible from miles away? High contrast is a fundamental visual cue that means even if a predator is not particularly hungry; it is pretty much compelled to take notice of the hapless zebra. But despite this, the zebra has done pretty well, and the planes of Africa are scattered with this very successful animal. The explanation for this has understandably been the topic of much conjecture and research, and to this day remains somewhat controversial. But more and more, the explanation is narrowing onto a surprisingly obvious culprit; the tsetse fly. When we think of the dangers to a large mammal, we automatically think of large predators. But while zebras undoubtedly prefer to avoid being eaten by lions, diseases associated with tsetse fly bites kill more of them. That means that avoiding tsetse flies likely creates stronger evolutionary pressure than avoiding lions, and that is proving to be a promising explanation for the zebras coat. Far less flies land on or bite animals with stripes.  Exactly why that is remains debatable, and theories range from disrupting the flies vision when landing, to creating mini weather fronts due to differential heating or cooling from the stripes. But whatever the mechanism ultimately turns out to be, stripes stop flies. It appears that the obvious big predators were not the answer after all.

Context Matters: But without deep understanding of the context in which the zebra evolved, this would have been very difficult to unravel. Even if we’d conserved zebras in zoos, finding the tsetse fly connection without the context of the complex African savannah would be quite challenging. It’s all too easy to enthusiastically chase an obvious cause of a problem, and so miss the real one, and our confirmation bias routinely amplifies this.

We often talk about protecting species, but if, as our technology evolves to more effectively ‘steal’ ideas from natural systems, from an innovation perspective alone, preserving context, in the form of complex ecosystems may likely turn out to be at least as important as preserving individual species. We don’t know what we don’t know, and often the surprisingly obvious and critical answer to a puzzle can only be determined by exploring a puzzle in its natural environment.

Enlightened Self-Interest. Could we use an analogy to the zebra to help control malaria? Could we steal avian navigation for gps? I have no idea, but I believe this makes pursuing conservation enlightened self-interest of the highest order. We want to save the environment for all sorts of reasons, but one of the most interesting is that one-day, some part of it could save us.

Image credit: Pixabay

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Guiding Principles for Human-Centered Innovation

The Ethical Compass

Guiding Principles for Human-Centered Innovation

GUEST POST from Chateau G Pato

We are living through the most rapid period of technological advancement in human history. From Generative AI to personalized genomics, the pace of creation is breathtaking. Yet, with great power comes the potential for profound unintended consequences. For too long, organizations have treated Ethics as a compliance hurdle — a check-the-box activity relegated to the legal department. As a human-centered change and innovation thought leader, I argue that this mindset is not only morally deficient but strategically suicidal. Ethics is the new operating system for innovation.

True Human-Centered Innovation demands that we look beyond commercial viability and technical feasibility. We must proactively engage with the third critical dimension: Ethical Desirability. When innovators fail to apply an Ethical Compass at the design stage, they risk building products that perpetuate societal bias, erode trust, and ultimately fail the people they were meant to serve. This failure translates directly into business risk: regulatory penalties, brand erosion, difficulty attracting mission-driven talent, and loss of consumer loyalty. The future of innovation is not about building things faster; it’s about building them better — with a deep, abiding commitment to human dignity, fairness, and long-term societal well-being.

The Four Guiding Principles of Ethical Innovation

To embed ethics directly into the innovation process, leaders must design around these four core principles:

  • 1. Proactive Transparency and Explainability: Be transparent about the system’s limitations and its potential impact. For AI, this means addressing the ‘black box’ problem — explaining how a decision was reached (explainability) and being clear when the output might be untrustworthy (e.g., admitting to the potential for a Generative AI ‘hallucination’). This builds trust, the most fragile asset in the digital age.
  • 2. Designing for Contestation and Recourse: Every automated system will make mistakes, especially when dealing with complex human data. Ethical design must anticipate these errors and provide clear, human-driven mechanisms for users to challenge decisions (contestation) and seek corrections or compensation (recourse). The digital experience must have an accessible, human-centered off-ramp.
  • 3. Privacy by Default (Data Minimization): The default setting for any new product or service must be the most protective of user data. Innovators must adopt the principle of data minimization — only collect the data absolutely necessary for the core functionality, and delete it when the purpose is served. This principle should extend to anonymizing or synthesizing data used for testing and training large models.
  • 4. Anticipating Dual-Use and Misapplication: Every powerful technology can be repurposed for malicious intent. Innovators must conduct mandatory “Red Team” exercises to model how their product — be it an AI model or a new biometric sensor — could be weaponized or misused, and build in preventative controls from the start. This proactive defense is critical to maintaining public safety and brand integrity.

“Ethical innovation is not about solving problems faster; it’s about building solutions that don’t create bigger, more complex human problems down the line.”


Case Study 1: Algorithmic Bias in Facial Recognition Systems

The Ethical Failure:

Early iterations of several commercially available facial recognition and AI systems were developed and tested using datasets that were overwhelmingly composed of lighter-skinned male faces. This homogenous training data resulted in systems that performed poorly — or failed entirely — when identifying women and people with darker skin tones.

The Innovation Impact:

The failure was not technical; it was an ethical and design failure. When these systems were deployed in law enforcement, hiring, or security contexts, they perpetuated systemic bias, leading to disproportionate errors, false accusations, and a deep erosion of trust among marginalized communities. The innovation became dangerous rather than helpful. The ensuing public backlash, moratoriums, and outright bans on the technology in some jurisdictions forced the entire industry to halt and recalibrate. This was a clear example where the lack of diversity in the input data (violating Principle 3) directly led to product failure and significant societal harm.


Case Study 2: The E-Scooter Phenomenon and Public Space

The Ethical Failure:

When ride-share e-scooters rapidly deployed in cities globally, the innovation focused purely on convenience and scaling. The developers failed to apply the Ethical Compass to the public space context. The design overlooked the needs of non-users — pedestrians, people with disabilities, and the elderly. Scooters were abandoned everywhere, creating physical obstacles, hazards, and clutter.

The Innovation Mandate:

While technically feasible and commercially popular, the lack of Anticipation of Misapplication (Principle 4) led to a massive negative social cost. Cities were forced to quickly step in with restrictive and punitive regulations to manage the chaos created by the unbridled deployment. The innovation was penalized for failing to be a responsible citizen of the urban environment. The ethical correction involved new technologies like integrated GPS tracking to enforce designated parking areas and mandatory end-of-ride photos, effectively embedding Contestation and Recourse (Principle 2) into the user-city relationship, but only after significant public frustration and regulatory intervention demonstrated the poor planning.


The Ethical Mandate: Making Compassion the Constraint

For innovation leaders, the Ethical Compass must be your primary constraint, just as budget and timeline are. This means actively hiring for ethical expertise, creating cross-functional Ethics Design Boards (EDBs) that include non-traditional stakeholders (e.g., anthropologists, ethicists, community advocates) for high-impact projects, and training every engineer, designer, and product manager to think like an ethicist.

The best innovations are those that successfully navigate not just the technological landscape, but the human landscape of values and consequences. When we prioritize human well-being over unbridled speed, we don’t just build better products — we build a better, more trustworthy future. Embrace ethics not as a brake pedal, but as the foundational gyroscope that keeps your innovation on course and your business resilient.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Pexels

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Fostering Inclusive Innovation Environments

Designing for Diversity

Fostering Inclusive Innovation Environments - Designing for Diversity

GUEST POST from Chateau G Pato

We live in an age where innovation is the ultimate currency of business survival. Yet, too many organizations pursue innovation using a narrow, homogenous lens. They gather teams of like-minded individuals, often with similar backgrounds and training, and wonder why their breakthroughs are incremental rather than disruptive. As a human-centered change and innovation thought leader, I argue that the most powerful, often untapped engine for exponential innovation is Diversity — specifically, the deliberate design of truly Inclusive Innovation Environments. Diversity is not a compliance metric; it is a profound competitive necessity, particularly in the creation of global products and AI systems.

Diversity, in all its dimensions — cognitive, experiential, cultural, and demographic — brings a wider array of perspectives, mental models, and pain points to the problem-solving table. However, diversity without inclusion is merely a census count. Inclusion is the act of creating a climate where every individual feels psychologically safe to contribute their unique perspective, challenge the status quo, and bring their “whole self” to the work. When inclusion is fostered, diverse inputs lead directly to superior outputs: more robust testing of assumptions, earlier identification of blind spots (including dangerous algorithmic bias), and the creation of products and services that resonate across varied global markets with reduced risk of cultural failure.

The Three Pillars of Inclusive Innovation Design

To successfully shift from mandated diversity to organic, inclusive innovation, organizations must focus on three core design pillars:

  • 1. De-biasing the Problem Frame: Innovation often fails because the problem is defined too narrowly, based on the experience of the dominant group. Inclusive design mandates empathy research that actively seeks out and centers marginalized experiences. This involves techniques like “extreme user” interviews and mandatory cross-functional, diverse ideation teams to ensure the problem frame is broad enough to serve all potential customers, from rural users to global citizens.
  • 2. Formalizing Psychological Safety: Creative risk-taking—the heart of innovation—cannot happen in an environment where people fear speaking up or making mistakes. Psychological safety must be formalized through explicit team norms, such as Inclusion Nudges (behavioral prompts that encourage equitable participation), and leadership commitment that celebrates “informed iteration” (learning from failure) rather than punishing it. This is essential for encouraging honest critique of an idea, regardless of who proposed it.
  • 3. Designing for Cognitive Diversity (The “How”): Beyond demographics, true innovation power comes from blending different ways of thinking — analytic vs. intuitive, divergent vs. convergent, or specialists vs. generalists. Leaders must intentionally build teams that feature constructive abrasion, where diverse cognitive styles are encouraged to challenge one another respectfully, leading to solutions that are stress-tested from multiple angles before they hit the market.

“Diversity is being invited to the party. Inclusion is being asked to dance. But true innovation is having your song played, your moves celebrated, and the playlist changed because of your input.”


Case Study 1: Microsoft and the Accessible Controller

The Challenge:

Traditional gaming controllers, designed for two-handed dexterity, excluded millions of gamers with physical disabilities. The innovation problem was framed too narrowly, focusing only on the “average” user.

The Inclusive Innovation Solution:

Microsoft’s development of the Xbox Adaptive Controller was a masterclass in inclusive design. The project wasn’t led by a single internal R&D team; it was a deep collaboration with external organizations dedicated to accessibility and, critically, with users with various physical limitations who became co-designers. They focused on a modular design that could adapt to the user’s specific needs, not force the user to adapt to the technology.

The Innovation Impact:

By centering the experience of “extreme users,” Microsoft created a product that not only opened up the multi-billion-dollar gaming market to a previously excluded demographic but also established a new, modular standard for human-computer interaction. The innovation was driven by the empathy gained through actively including and listening to a traditionally marginalized user group, demonstrating that designing for the edge ultimately expands the core market and elevates the entire product category.


Case Study 2: IDEO and the Innovation of Bathroom Fixtures

The Challenge:

A client asked IDEO to redesign a commercial bathroom fixture — a seemingly mundane, mature product—for better user experience and efficiency. The initial team, composed mostly of male engineers, risked designing based on their own, limited perspective.

The Inclusive Innovation Solution:

IDEO deliberately staffed the project with a demographically and cognitively diverse team, crucially including women from various backgrounds. Through ethnographic research, the female team members immediately identified and centered a critical, overlooked pain point: women often use the bathroom differently (e.g., using sinks to adjust clothing or makeup, the height of mirrors relative to professional dress, etc.). This insight, which the male-centric team would have missed, allowed them to re-frame the problem from mere water efficiency to improving the entire grooming ecosystem.

The Innovation Impact:

The resulting fixtures and designs addressed a wider spectrum of needs, leading to innovations in mirror placement, shelf space utility, and overall ergonomics that provided superior value and differentiation. This simple staffing decision demonstrated that when a diverse team is empowered to challenge the existing artifact based on varied lived experiences, the resulting innovation is fundamentally deeper, more empathetic, and commercially stronger, reducing the risk of creating a product that only half the population truly values.


The Leadership Mandate: From Compliance to Creativity

Designing for diversity is the ultimate act of human-centered innovation. It requires a shift in leadership focus: from viewing diversity as a mandate to viewing it as a strategic accelerator of creativity. This means actively dismantling the homogeneous echo chambers that characterize too much of corporate decision-making.

Leaders must be accountable for the quality of inclusion, not just the quantity of diversity. By adhering to the three pillars — de-biasing the problem frame, formalizing psychological safety, and designing for cognitive diversity — organizations can unlock the full, immense creative power of their people. Innovation will not thrive in silence or uniformity. It requires the beautiful, constructive chaos of difference.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Pixabay

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If You Can Be One Thing – Be Effective

If You Can Be One Thing - Be Effective

GUEST POST from Mike Shipulski

If you’re asked to be faster, choose to be more effective. There’s nothing slower than being fast at something that doesn’t matter.

If you’re given a goal to be more productive, instead, improve effectiveness. There’s nothing less productive than making the wrong thing.

If you’re measured on efficiency, focus on effectiveness. Customers don’t care about your efficiency when you ship them the wrong product.

If you’re asked to improve quality, that’s good because quality is an important element of effectiveness.

If you’re asked to demonstrate more activity, focus on progress, which is activity done in an effective way.

If you’re asked to improve your team, ask them how they can be more effective and do that.

Regardless of the question, the answer is effectiveness.

Image credit: Unsplash

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