Category Archives: Digital Transformation

People Drive the World-Technology as a Co-Pilot via Center of Human Compassion

GUEST POST from Teresa Spangler

People at the Center – Technology as a Co-Pilot

Are people at the center of your innovation and new product plans? Have we made people the center of all things digital? Are human’s and our environment the center of the new world entering the 4th Industrial Revolution? When innovation is during groundbreaking disruptive inventions or whether innovation is iterating into new products… what is placed at the center of your strategies? What are the reasons for these new inventions?

So much is at stake, as the world turns to being driven by AI, humanoids, rockets’ red glare searching for new lands to inhabit, games and more games feeding our brains with virtual excitement and stimulation, devices galore on our bodies, in our hands, in our homes helping us navigate our every move and in many ways directing us on how to think. The acceleration of digital permeating our lives is mind boggling. The news we are fed, seemingly unbiased, the product advertisements that sneak into our feeds, the connections via too many social and work-related networks that appear all too promising and friendly too is overwhelming. Technology is encompassing our lives!

The Power of Technology

Don’t get me wrong, I love technology for all the positive it contributes to the world. Technology is allowing individuals to create! To create and earn! To take control of their lives and build meaningful endeavors. The creation of TIME and SPACE to live how we to live has been a major outcome of

1. technology but also 2. the pandemic.

Let’s explore the creator economy which has experienced an explosion of late. As referenced in the Forbes article, The Biggest Trends For 2022 In Creator Economy And Web3, by Maren Thomas Bannon, Today, the total size of the creator economy is estimated to be over $100 billion and 50 million people worldwide consider themselves creators. Creators will continue to bulge out of the global fabric as individuals seek to augment their incomes or escape the confines or rigged corporate cultures. Technology is enabling creators no doubt!

Technology is also allowing forward acting organizations to scale growth at unprecedented speeds. Let’s look at a recent survey conducted by Accenture

Curious about the effects of the pandemic, we completed a second round of research in early 2021 and discovered the following:

Technology Leaders have moved even further ahead of the pack and have been growing at 5x the rate of Laggards on average in the past three years.
Among the “Others” there is a group of organizations—18% of the entire sample—that has been able to break previous performance barriers—the Leapfroggers.

Let’s look at a recent survey conducted by Accenture

Curious about the effects of the pandemic, we completed a second round of research in early 2021 and discovered the following:

Technology Leaders have moved even further ahead of the pack and have been growing at 5x the rate of Laggards on average in the past three years.
Among the “Others” there is a group of organizations—18% of the entire sample—that has been able to break previous performance barriers—the Leapfroggers.

Of course, so much technology is doing good things for the world. 3-D printing is emerging at the center of homelessness. As reported in the #NYTIMES, this tiny village in Mexico is housing homeless people. The homes were built using an oversized 3-D printer.

Another example positive outcomes of technology is the emergence of over-the-counter hearing devices. Fortune Business Insights estimates the global hearing aids market is projected to grow from $6.67 billion in 2021 to $11.02 billion by 2028 at a CAGR of 7.4% in forecast period, 2021-2028.

These devices, until this year, were regulated to being sold by medical professionals at, for the majority of population in need, very high prices $2000 to $5000+ per hearing aid. Yes typically you need two. But recent innovations in ear buds and bluetooth are allowing other technology companies into the game! Take Bose for example, the FDA recently approved Bose SoundControl Hearing Aids to be purchased on their website for $895/pair. No need for a hearing professional. This significantly changes the playing field and opens the doors for so many that have put off purchases (of these not covered by insurance by the way) devices.

Entertainment & leisure travel is going to a whole new level with the help of technology. It’s wonderful that anyone with connectivity and travel the world and explore via Virtual Reality. Here are 52 places you can explore in the comfort of your home shared by NY Times. Many of us attended conferences and events over the past two years virtually. We’ll see an exponential growth in virtual reality experiences in the coming year.

So why am I talking about creating a Center for Human Compassion if so much good is really coming out of technology? Because many of the outcomes are also unrealized and not anticipated or at least publicized to prepare people. It is essential for companies, technologists, and product teams to consider the consequences of new technologies. Not as an afterthought but at the forethought, from inception of ideas we must ask what are the downsides? How will people be affected? What could happen?

The quote below is taken from the World Economic Forum report, Positive AI Economic Futures

machines will be able to do most tasks better than humans. Given these sorts of predictions, it is important to think about the possible consequences of AI for the future of work and to prepare for different scenarios. Continued progress in these technologies could have disruptive effects: from further exacerbating recent trends in inequality to denying more and more people their sense of purpose and fulfillment in life, given that work is much more than just a source of income.

WeForum brings 150 thought leaders together to share thoughts on how we create an AI world we want. For all of AI’s good, there are potentials for negative outcomes.

Let’s take the military’s fight again hobbyists and drones. In the recent article from WSJ, The Military’s New Challenge: Defeating Cheap Hobbyist Drones, how much energy was placed on Human Compassion if drone technologies, IoT and AI got in the wrong hands?

The U.S. is racing to combat an ostensibly modest foe: hobbyist drones that cost a few hundred dollars and can be rigged with explosives. @WSJ

I feel certain there was some consideration but not enough to draw out possible negative impacts and how to mitigate them before they could even start. Did we really put people at the center of what is possible with drone technologies? What do you think?

This is no easy task. We know what is good for us can turn to bad for us when in the wrong hands, or if it’s not moderated to healthy limits. How do we help facilitate a more compassionate relationship with technology and put people at the center?

Here are four strategies to ensure you are keeping people at the center of your innovation, new products and technology development efforts.

Create a Center of Human Compassion, or People Centered Technology Consortium, or what ever you wish to brand your initiative. Select trusted advisors from external (customers, partners…) and a select group of internal stake holders to join your collaborative to gather input, feedback and push back!
Discuss with your trusted group very early on. Gamify initiatives around gathering what ifs! Anticipating the worst you will plan better for the best! (leaving the hope out)
Build a continuous feedback loop. It is important that insights and scenarios are revisited and rehashed over and over again.
Join other consortiums and get involved with AI and tech for good initiatives. If you can’t find ones you feel are of value to you and your company, start one!

Mantra for the year: #lucky2022 but not without work and placing people front and center of plans will good fortune and luck come for the masses.

As always, reach out if you have ideas you’d like to share or questions you’d like to discuss!

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Future Trends in Innovation Metrics and Analytics

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Future Trends in Innovation Metrics and Analytics

GUEST POST from Art Inteligencia

For decades, organizations have grappled with the elusive challenge of measuring innovation. Traditional metrics—R&D spend, patent counts, or revenue from new products—have offered a rearview mirror perspective, telling us what happened, but rarely why, or what to do next. As a human-centered change and innovation thought leader, I’ve seen firsthand that this limited view often stifles true innovation, pushing teams towards incremental improvements rather than bold, transformative leaps. The future of innovation demands a radical shift in how we measure, analyze, and, crucially, understand its underlying human dynamics.

We are moving beyond simple outputs to a more holistic, predictive, and human-centric approach to innovation analytics. This evolution is driven by the increasing complexity of global markets, the imperative for continuous adaptation, and the undeniable recognition that innovation is ultimately a human endeavor, fueled by curiosity, collaboration, and psychological safety.

The Inadequacy of Yesterday’s Metrics

Relying solely on lagging indicators like “percentage of revenue from new products” can be profoundly misleading. It reveals past success but offers scant insight into the health of your current innovation pipeline or the evolving capabilities of your teams. Patent counts, while indicative of intellectual property generation, do not inherently correlate with market impact or customer value. These metrics often inadvertently encourage a focus on quantity over quality, and a siloed view of innovation as a departmental function rather than an overarching organizational capability.

The inherent challenge is that innovation is fundamentally messy, non-linear, and often unpredictable. Attempting to force it into neat, quantitative boxes inevitably overlooks the rich, qualitative data that truly propels breakthrough ideas.

Pivotal Future Trends in Innovation Metrics and Analytics

1. From Lagging to Leading Indicators: Measuring Potential

The future of innovation measurement lies in rigorously assessing the inputs and processes that *predict* future innovation success. This includes vital metrics around:

Experimentation Velocity: How swiftly are new ideas being prototyped, tested, and iterated upon? This reflects learning speed.
Psychological Safety Scores: Are employees genuinely comfortable taking calculated risks, openly sharing failures, and constructively challenging existing assumptions without fear?
Cross-Functional Collaboration Index: How effectively are diverse teams collaborating and exchanging knowledge on new initiatives and challenging problems?
Idea Generation & Diversity: The sheer volume and strategic breadth of new ideas being submitted and actively explored across the entire organization.

2. Qualitative & Behavioral Analytics: Unearthing the “Why”

Beyond raw numerical data, organizations will increasingly leverage rich qualitative insights to deeply understand user behavior, emotional responses, and the true problem-solving effectiveness of their innovations. This sophisticated approach involves:

User Journey Analytics: Meticulously mapping emotional highs and lows, identifying points of friction, and recognizing moments of profound delight throughout the user experience.
Sentiment Analysis: Analyzing unstructured feedback from customer reviews, social media discussions, and internal communications to accurately gauge perception and emotional resonance.
Observed Behavior: Direct, empathetic observation of how users naturally interact with prototypes and finished products, leading to the discovery of unspoken needs and intuitive design opportunities.

3. Ecosystem & Network Metrics: Beyond Organizational Walls

True innovation rarely flourishes in isolation. Future metrics will critically assess the health, vibrancy, and effectiveness of external partnerships, open innovation initiatives, and dynamic internal knowledge networks:

Partnership Value Index: Quantifying the strategic value, collaborative output, and mutual benefit derived from external alliances and collaborations.
Knowledge Sharing Flow: Measuring the velocity, impact, and reach of knowledge transfer both within and outside the traditional boundaries of the organization.
Community Engagement: Tracking active participation and meaningful contribution within open innovation platforms or customer co-creation initiatives.

4. Impact-Oriented Metrics: Holistic Value Creation

Innovation is no longer solely about financial returns. Organizations are increasingly accountable for broader societal and environmental impacts. Future metrics will profoundly reflect this critical shift:

Social & Environmental Impact Scores: Quantifying tangible contributions to sustainability, community well-being, or ethical practices, beyond mere compliance.
Customer Lifetime Value (CLV) from Innovation: Measuring precisely how new offerings enhance long-term customer relationships and loyalty, not just initial sales.
Employee Well-being & Engagement from Innovation: Assessing how innovation initiatives contribute to a positive, empowering, and thriving internal culture.

5. AI and Advanced Analytics: The Intelligent Layer

The sheer volume, velocity, and complexity of these new, diverse data points necessitate sophisticated analytical capabilities. AI and machine learning will move far beyond simple dashboards to provide truly predictive and actionable insights:

Predictive Modeling: Accurately forecasting the likelihood of innovation success based on the interplay of various leading indicators.
Pattern Recognition: Identifying subtle, non-obvious correlations and emerging trends between vast, diverse data sets that human analysts might easily miss.
Automated Anomaly Detection: Instantly flagging unexpected drops in collaboration, experimentation, or sentiment, signaling potential issues or emerging opportunities early.

Transformative Case Studies in Advanced Innovation Measurement

Case Study 1: “The Experimentation Engine” at a Global Consumer Goods Company

A large consumer goods company, historically characterized by slow innovation cycles, strategically shifted its primary focus from post-launch product revenue to experimentation velocity and rapid learning cycles. They implemented a sophisticated digital platform to meticulously track every experiment, ranging from minor packaging tweaks to entirely novel product concepts.

Metrics in Action: Instead of relying on traditional annual reviews of product P&Ls, teams were rigorously measured on:

The total number of experiments initiated per quarter.
The average time to complete an experiment (from initial hypothesis formulation to validated learning).
The number of “failed” experiments that, crucially, yielded significant, actionable insights.
The degree of cross-functional participation in experiment design and subsequent analysis.

Outcome:

Within a mere 18 months, the company witnessed an astonishing 300% increase in the number of experiments run annually. While many of these experiments “failed” in their initial hypothesis, the speed of learning accelerated dramatically across the organization. This profound shift led to a remarkable 25% reduction in time-to-market for successful new products and a significant increase in the hit rate of subsequent innovations, as insights gleaned from rapid failures directly informed more successful ventures. The organizational culture fundamentally transformed from risk-averse to a dynamic “fail fast, learn faster” ethos.

Case Study 2: “The Collaborative Ecosystem” at a Public Sector Innovation Lab

A pioneering government innovation lab, specifically tasked with solving complex societal challenges, quickly recognized that traditional metrics like “number of programs launched” were woefully insufficient. Their strategic focus pivoted to rigorously measuring the health, vibrancy, and tangible impact of their collaborative ecosystem.

Metrics in Action: They meticulously developed and tracked a suite of metrics centered around:

The diversity of stakeholders actively engaged per project (e.g., direct citizen involvement, NGOs, private sector partners, academic institutions).
The frequency and depth of impactful knowledge exchange across various network nodes and partner organizations.
Quantifiable social impact indicators (e.g., measurable reduction in specific social issues, demonstrable increase in citizen participation) directly attributable to collaborative initiatives.
The total number of truly cross-sector solutions co-created and successfully scaled for broader impact.

Outcome:

By proactively prioritizing these comprehensive ecosystem metrics, the lab underwent a profound transformation, evolving from a previously siloed entity into a dynamic central hub for public sector innovation. They experienced an impressive 50% increase in unique cross-sector partnerships within just two years. More significantly, the quality, scalability, and long-term sustainability of the solutions they developed improved dramatically, leading to measurable positive impacts on critical areas like urban planning and public health initiatives. This powerfully demonstrated that fostering a vibrant, interconnected innovation ecosystem is, in itself, a profoundly powerful metric of success.

Embracing the New Innovation Analytics Paradigm

The fundamental shift to these future-forward innovation metrics requires far more than just new dashboards; it demands a profound cultural transformation across the organization. Leaders must champion a mindset that deeply values continuous learning over elusive perfection, fosters open collaboration over internal competition, and prioritizes holistic impact over narrow financial gains. Investing in the right enabling tools—from sophisticated advanced analytics platforms to robust, intuitive collaboration software—is undeniably crucial, but the true, lasting transformation lies in empowering every team and individual to deeply understand and proactively act upon these richer, more insightful data points.

By courageously embracing these emerging trends, organizations can transcend merely tracking past performance to actively and intelligently shaping their innovative future. It’s about meticulously creating a dynamic, responsive system that not only precisely identifies breakthrough opportunities but also cultivates the essential human potential and collaborative spirit necessary to truly realize them. The future of innovation measurement is not just coming—it’s here, and it’s far more intelligent, comprehensive, and profoundly human-centered than anything we’ve ever witnessed before. 📈💡

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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Reaching Beyond the Limits of Innovation and Transformation

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Reaching Beyond the Limits of Innovation and Transformation Recently on Episode #873 of the Marketer of the Day podcast, I had the opportunity to sit down with Robert Plank, have a great conversation, and chat about a number of different topics. Here is a quick excerpt:

“When it comes to innovation, timing is a huge factor. Going in too soon or too late can both cost you lots of money. Innovation isn’t all about creativity and value-creation, it is also about the services that you provide around your new idea and helping people understand how your idea can be of value to their lives. But how can we know if our innovative ideas can really affect people’s lives?”

Click the play button to listen to the podcast right here, right now:

Here is Robert Plank in his own words describing what the Marketer of the Day podcast is all about:

The Marketer of the Day Podcast interviews entrepreneurs who have been through “the struggle.”

They’ve experienced the headaches of repeat failure, trial-and-error, scaling, delegating, course-correcting, and getting their online businesses to succeed beyond their wildest dreams… and want to help you get to where you need to go.

Or visit Robert’s site here for additional information and all of the ways to subscribe to his podcast:

https://www.robertplank.com/873-innovation-change-customer-braden-kelley/

Four Lessons Learned from the Digital Revolution

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Four Lessons Learned from the Digital Revolution

GUEST POST from Greg Satell

When Steve Jobs was trying to lure John Sculley from Pepsi to Apple in 1982, he asked him, “Do you want to sell sugar water for the rest of your life, or do you want to come with me and change the world?” The ploy worked and Sculley became the first major CEO of a conventional company to join a hot Silicon Valley startup.

It seems so quaint today, in the midst of a global pandemic, that a young entrepreneur selling what was essentially a glorified word processor thought he was changing the world. The truth is that the digital revolution, despite all the hype, has been something of a disappointment. Certainly it failed to usher in the “new economy” that many expected.

Yet what is also becoming clear is that the shortcomings have less to do with the technology itself, in fact the Covid-19 crisis has shown just how amazingly useful digital technology can be, than with ourselves. We expected technology and markets to do all the work for us. Today, as we embark on a new era of innovation, we need to reflect on what we have learned.

1. We Live In a World of Atoms, Not Bits

In 1996, as the dotcom boom was heating up, the economist W. Brian Arthur published an article in Harvard Business Review that signaled a massive shift in how we view the economy. While traditionally markets are made up of firms that faced diminishing returns, Arthur explained that information-based businesses can enjoy increasing returns.

More specifically, Arthur spelled out that if a business had high up-front costs, network effects and the ability to lock in customers it could enjoy increasing returns. That, in turn, would mean that information-based businesses would compete in winner-take-all markets, management would need to become less hierarchical and that investing heavily to win market share early could become a winning strategy.

Arthur’s article was, in many ways, prescient and before long investors were committing enormous amounts of money to companies without real businesses in the hopes that just a few of these bets would hit it big. In 2011, Marc Andreesen predicted that software would eat the world.

He was wrong. As the recent debacle at WeWork, as well as massive devaluations at firms like Uber, Lyft, and Peloton, shows that there is a limit to increasing returns for the simple reason that we live in a world of atoms, not bits. Even today, information and communication technologies make up only 6% of GDP in OECD countries. Obviously, most of our fate rests with the other 94%.

The Covid-19 crisis bears this out. Sure, being able to binge watch on Netflix and attend meetings on Zoom is enormously helpful, but to solve the crisis we need a vaccine. To do that, digital technology isn’t enough. We need to combine it with synthetic biology to make a real world impact.

2. Businesses Do Not Self Regulate

The case Steve Jobs made to John Sculley was predicated on the assumption that digital technology was fundamentally different from the sugar-water sellers of the world. The Silicon Valley ethos (or conceit as the case may be), was that while traditional businesses were motivated purely by greed, technology businesses answered to a higher calling.

This was no accident. As Arthur pointed out in his 1996 article, while atom-based businesses thrived on predictability and control, knowledge-based businesses facing winner-take-all markets are constantly in search of the “next big thing.” So teams that could operate like mission-oriented “commando units” on a holy quest would have a competitive advantage.

Companies like Google who vowed to not “be evil,” could attract exactly the type of technology “commandos” that Arthur described. They would, as Mark Zuckerberg has put it, “move fast and break things,” but would also be more likely to hit on that unpredictable piece of code that would lead to massively increasing returns.

Unfortunately, as we have seen, businesses do not self-regulate. Knowledge-based businesses like Google and Facebook have proven to be every bit as greedy as their atom-based brethren. Privacy legislation, such as GDPR, is a good first step, but we will need far more than that, especially as we move into post-digital technologies that are far more powerful.

Still, we’re not powerless. Consider the work of Stop Hate For Profit, a broad coalition that includes the Anti-Defamation League and the NAACP, which has led to an advertiser boycott of Facebook. We can demand that corporations behave how we want them to, not just what the market will bear.

3. As Our Technology Becomes More Powerful, Ethics Matter More Than Ever

Over the past several years some of the sense of wonder and possibility surrounding digital technology gave way to no small amount of fear and loathing. Scandals like the one involving Facebook and Cambridge Analytica not only alerted us to how our privacy is being violated, but also to how our democracy has been put at risk.

Yet privacy breaches are just the beginning of our problems. Consider artificial intelligence, which exposes us to a number of ethical challenges, ranging from inherent bias to life and death ethical dilemmas such as the trolley problem. It is imperative that we learn to create algorithms that are auditable, explainable and transparent.

Or consider CRISPR, the gene editing technology, available for just a few hundred dollars, that vastly accelerates our ability to alter DNA. It has the potential to cure terrible diseases such as cancer and Multiple Sclerosis, but also raises troubling issues such as biohacking and designer babies. Worried about some hacker cooking up a harmful computer virus, what about a terrorist cooking up a real virus?

That’s just the start. As quantum and neuromorphic computing become commercially available, most likely within a decade or so, our technology will become exponentially more powerful and the risks will increase accordingly. Clearly, we can no longer just “move fast and break things,” or we’re bound to break something important.

4. We Need a New Way to Evaluate Success

By some measures, we’ve been doing fairly well over the past ten years. GDP has hovered around the historical growth rate of 2.3%. Job growth has been consistent and solid. The stock market has been strong, reflecting robust corporate profits. It has, in fact, been the longest US economic expansion on record.

Yet those figures were masking some very troubling signs, even before the pandemic. Life expectancy in the US has been declining, largely due to drug overdoses, alcohol abuse and suicides. Consumer debt hit record highs in 2019 and bankruptcy rates were already rising. Food insecurity has been an epidemic on college campuses for years.

So, while top-line economic figures painted a rosy picture there was rising evidence that something troubling is afoot. The Business Roundtable partly acknowledged this fact with its statement discarding the notion that creating shareholder value is the sole purpose of a business. There are also a number of initiatives designed to replace GDP with broader measures.

The truth is that our well-being can’t be reduced to and reduced to a few tidy metrics and we need more meaning in our lives than more likes on social media. Probably the most important thing that the digital revolution has to teach us is that technology should serve people and not the other way around. If we really want to change the world for the better, that’s what we need to keep in mind.

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

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Top 10 Human-Centered Change & Innovation Articles of August 2022

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Top 10 Human-Centered Change & Innovation Articles of August 2022 Drum roll please…

At the beginning of each month we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are August’s ten most popular innovation posts:

Why Amazon Wants to Sell You Robots — by Shep Hyken

Now is the Time to Design Cost Out of Our Products — by Mike Shipulski

How Consensus Kills Innovation — by Greg Satell

The Four Secrets of Innovation Implementation — by Shilpi Kumar

Reset and Reconnect in a Chaotic World — by Janet Sernack

This 9-Box Grid Can Help Grow Your Best Future Talent — by Soren Kaplan

‘Fail Fast’ is BS. Do This Instead — by Robyn Bolton

The Power of Stopping — by Mike Shipulski

The Battle Against the Half-Life of Learning — by Douglas Ferguson

The Phoenix Checklist – Strategies for Innovation and Regeneration — by Teresa Spangler

BONUS – Here are five more strong articles published in July that continue to resonate with people:

Is Digital Different? — by John Bessant

Marriott’s Approach to Customer Service — by Shep Hyken

Empathy: The Currency of Human Connection and Innovation — by Soren Kaplan

Four Keys to Decision Making Every Leader Should Know — by Greg Satell

Is Percy an Innovation or Another Attack on America’s Poor? — by Braden Kelley

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last two years:

Top 40 Innovation Bloggers of 2020

Top 40 Innovation Bloggers of 2021

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Driving the Next Era of Growth: Leveraging Data to Innovate

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Driving the Next Era of Growth: Leveraging Data to Innovate

GUEST POST from Teresa Spangler

“50% of US executives and 39% of European executives said budget constraints were the primary hurdle in turning Big Data into a profitable business asset. Rounding out the top 5 challenges were data security concerns, integration challenges, lack of technical expertise, and proliferation of data silos.” (Capgemini)

“The biggest challenges companies face when implementing Big Data are budget constraints” (Capgemini)

Data analytics is continuously evolving as AI and machine learning applications get faster and smarter. The benefits that may be gained by analyzing massive data sets identifying in seconds patterns, signals, and relationships between nonaligned and aligned areas is intoxicating for savvy companies seeking to innovate. We recognize that companies can make faster and better decisions with strong analytic teams interpreting the findings. Look at what information-driven analytics has done already in cool improvements around us. There are so many good examples of this. Take transportation systems, the use of information analytics to course vehicles round congested areas in actual time is one simple example. Another, that literally may have saved the restaurant industry during the pandemic, is meals delivery services which depend on data collected to forecast demand on menu items, key order times, navigation around cities and streets not to mentioned detailed knowledge individual’s meal preferences. Data helped to optimize driving routes for more efficient delivers.

As data analytics becomes more sophisticated, we might anticipate revolutionary disruptions. However, economists report spending greater funds per capita on research, yet there is a significant decline in rate of successful innovation output. One motive for this could be that we are mistakenly focusing an excessive amount of on R&D instead of on innovation output which takes exceptional justification, funding, and resources. What does data analytics have to do with innovation? Everything! Research is crucial but just one part of a puzzle for developing new products and services. Today, innovation requires a sophistication in data analytics interpretation. There’s also a need for the curiosity, for human evaluation and a bit of intuition and intelligence. Companies need an astute cleverness like no other time in history and an ingenious approach to taking research and turning it into something new and worthwhile. The process must be diligent, but it must also be agile. Too frequently, organizations get bogged down within the details of research and improvement, without truly questioning outside the boundaries of a container process. As a result, we have delays in the process often stalling out for lack of resource allocations. Even worse, companies not focusing on deep understanding of their data may misinterpret the analytics leaving more to chance that to solid pathways.

It’s worth saying, placing a greater emphasis on creativity and innovation is imperative vs. traditional research and improvement methods. As is deeply dissecting the data in your business. Where does all that data live? What are the hidden signals of the data, what types of converging uses (products/solutions) could you turn that data into?

We are in an era of new growth. Poll your customers! They are changing rapidly and challenged with keeping up with the speed of change but know they must. Where are they doubling down their efforts? How well do they understand their own data? What products and services are they developing, who are they collaborating with and a better question, why are you collaborating with them to innovate around their future needs? Are they investing in developing a more tech and analytic savvy organization? Better question, is your company?

As cliché as it is data is the new oil. Data will be producing its own data (it’s happening today) known as synthetic data. According to Gartner, “By 2025, synthetic data will reduce personal customer data collection, avoiding 70% of privacy violation sanctions.” This begs to question the emphasis companies are placing on developing the skills sets of the organization around analytics and data. And simply put, as oil has an expansive array of products and uses, we’re now in an era of inventing new energy sources to reduce even eliminate dependencies on oil. How might data fit into the effort to transform these dependencies? Data is essential for electric and autonomous vehicle development. Innovative companies are undertaking long tail efforts to drive the next generation of IoE (Internet of everything). Data is the fuel. Let’s explore four ways that organizations can use records analytics to power innovation and stay ahead of the competition.

Design new products that think for themselves: understanding data from a variety of sources may trigger new types of needs and possible new products that could be developed. For example: understanding water needs for new smart and innovative cities being designed takes enormous planning. A partner to Plazabridge Group, designs digital twin environments for the water sector. Cites like Singapore, Houston, Dubai, must anticipate the growing needs for water and plan design and building based on anticipated needs but also, they must plan for worst- and best-case scenarios. They must plan for leakage, or contamination or other possible scenarios that may impact water supplies. Digital twinning these environments is the most cost-effective way to simulate new innovative methods. Leveraging as much data as possible as well as generating newly created synthetic data cities can plan more economically, they can execute faster and prepare for events that may occur. Understanding these models around water, suppliers may produce products that help cities build these digital environments. Not just for water systems but for any part of businesses today; manufacturing, facilities management, construction…

Not all innovation has to be moonshot inventions. Simply identify unmet wishes of customers, consumers or the market creating engaging products and services. UBER goes from just carting us around leveraging an incredible inventive back in logistics infrastructure to launch UBER eats! Why not, the drivers are already out and about, the data collected indicates the most popular spots riders go to for coffee, lunch, dinner, drinks… UBER analysts have vast information on customer interests in turn turned from few riders during a pandemic to delivering food as an essential business during the pandemic. A pivot turns into a scalable source of augmented revenue as the shelter lifts and people get back to riding.

So much opportunity exists to improve customer engagement: records analytics can assist businesses to better understand their clients and their wishes. This expertise can then be used to improve customer service and support future-proofing your business.

Extend efficiency: data crunching algorithms, digital twinning, AR/VR simulations and access to remote experts will help corporations to streamline their operations, digitally transforming themselves for greater efficiency. This increased efficiency can lead to price savings, which can be reinvested in innovation.“90% of CEOs believe the digital economy will impact their industry, but less than 15% are executing on a digital strategy.”

— MIT Sloan and Capgemini. Seek out experts and industry mentors to help your organization make these shifts. We often fear what we cannot see, the beautiful thing about the digital world is you can build a virtual environment visualizing the unseen, and plan for all types of scenarios. A model we developed (not dependent on virtual or digital anything in fact) at Plazabridge Group is around the CIA’s The Phoenix Checklist. Strategies for Regenerating is our formula for going deep into understanding problems, future opportunities, needs, anticipating deeply the “What ifs” of every possible scenario. When done leveraging data and analytics the possibilities become endless.

Original Article

Image credits: Pixabay

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Process Keepers Hold the Keys to Change

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Process Keepers Hold the Keys to Change

GUEST POST from Mike Shipulski

If you want to improve the work, ask the people who do the work. They know the tools and templates. They know the ins and outs of the process. They know when and how to circumvent the process. And they know what will break if you try to change the process. And what breaks is the behavior of the people that use the process.

When a process changes, people’s behavior does not. Once people learn the process, they want to continue to work that way. It’s like their bodies know what to do without even thinking about it. But on the other hand, when a process doesn’t meet the need, people naturally modify their behavior to address the shortcomings of the process. And in this case, people’s behavior doesn’t match the process yet they standardize their behavior on circumventing the process. Both of these realities – people like to do what they did last time and people modify their behavior to address shortcomings of the process – make it difficult for people to change their behavior when the process changes.

When the process doesn’t work but the modified behavior does, change the process to match the modified behavior. When that’s not possible, ask the people why they modified their behavior and ask them to come up with a process that is respectful of their on-the-fly improvements and respectful of the company’s minimum requirements for their processes.

When the process doesn’t work but the people are following it anyway, ask them to come up with ways to improve the process and listen to their ideas. Then, run a pilot of their new process on the smallest scale and see what happens. If it makes things better, adopt the process on a larger scale and standardize on the new way to work. If it makes things worse, stop the pilot and try another improvement suggested by the team, again on a small scale. Repeat this process until the process performs satisfactorily.

When the people responsible for doing the work are given the opportunity to change their processes for the better, there’s a good chance the broader population that uses the process will ultimately align their behavior to the new process. But the change will not be immediate and there may be some backsliding. But, because the keepers of the process feel ownership of the new process and benefit from the change, they will continue to reinforce the new behavior until it becomes new behavior. And if it turns out the new process needs to be modified further, the keepers of the process will make those changes and slowly align the behavior to match the process.

When the new process is better than the old one, people will ultimately follow the new process. And the best way to make the new process better than the old one is to ask the people who do the work.

Image credit: Old Photo Profile

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Designing Your Organization for Transformation

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Designing Your Organization for Transformation

GUEST POST from Greg Satell

The March on Washington, in which Martin Luther King Jr. delivered his famous “I Have a Dream” speech, is one of the most iconic events in American history. So it shouldn’t be surprising that when anybody wants to drive change in the United States, they often begin with trying to duplicate that success.

Yet that’s a gross misunderstanding of why the march was successful. As I explain in Cascades, the civil rights movement didn’t become powerful because of the March on Washington, the March on Washington took place because the civil rights movement became powerful. It was part of the end game, not an opening shot.

Unfortunately, many corporate transformations make the same mistake. They try to drive change without preparing the ground first. So it shouldn’t be surprising that McKinsey has found that only about a quarter of transformational efforts succeed. Make no mistake, transformation is a journey, not a destination, and you start by preparing the ground first.

Start with a Keystone Change

Every successful transformation starts out with a vision, such as racial equality in the case of the civil rights movement. Yet to be inspiring, a vision needs to be aspirational, which means it is rarely achievable in any practical time frame. A good vision is more of a beacon than it is a landmark.

That’s probably why every successful transformation I found in my research first had to identify a keystone change which had a tangible and concrete objective, involved multiple stakeholders and paved the way for future change. In some cases, there are multiple keystone changes being pursued at once seeking to influence different institutions.

For example, King and his organization, the Southern Christian Leadership Conference (SCLC), mobilized southern blacks, largely through religious organizations, to influence the media and politicians. At the same time, through their work at the NAACP, Charles Hamilton Houston and Thurgood Marshall worked to influence the judicial system to eliminate segregation.

The same principle holds for corporate transformations. When Paul O’Neill set out to turnaround Alcoa in the 1980s, he started by improving workplace safety and, more recently, at Experian, when CIO Barry Libenson set out to move his company to the cloud, he started with internal APIs. In both cases, the stakeholders won over in achieving the keystone change also played a part in bringing about the larger vision.

Lead with Values

Throughout his career, Nelson Mandela was accused of being a communist, an anarchist and worse. Yet when confronted with these, he would always point out that nobody needed to guess what he believed, because it was all written down in the Freedom Charter way back in 1955. Those values signaled to everybody, both inside and outside of the anti-apartheid movement, what they were fighting for.

In a similar vein, when Lou Gerstner arrived at IBM in the early 90s, he saw that the once great company had lost sight of its values. For example, its salespeople were famous for dressing formally, but that was merely an early manifestation of a value. The original idea was to be close to customers and, since most of IBM’s early customers were bankers, salespeople dressed formally. Yet if customers were now wearing khakis, it was okay for IBM’ers to do so as well.

Another long held value at IBM was a competitive spirit, but IBM executives had started to compete with each other internally rather than working to beat the competition. So Gerstner worked to put a stop to the bickering, even firing some high-placed executives who were known for infighting. He made it clear, through personal conversations, emails and other channels that in the new IBM the customer would come first.

What’s important to remember about values is, if they are to be anything more than platitudes, you have to be willing to incur costs to live up to them. When Nelson Mandela rose to power, he couldn’t oppress white South Africans and live up to the values in the Freedom Charter. At IBM, Gerstner was willing to give up potential revenue on some sales to make his commitment to the customer credible.

Build a Network of Small Groups

With attendance at its weekend services exceeding 20,000, Rick Warren’s Saddleback Church is one of the largest congregations in the world. Yet much like the March on Washington, the mass of people obscures the networks that underlie the church and are the source of its power.

The heart of Saddleback Church is the prayer groups of six to eight people that meet each week, build strong ties and support each other in matters of faith, family and career. It is the loose connections between these small groups that give Saddleback its combination of massive reach and internal coherence, much like the networks of small groups convened in front of the Lincoln Memorial during the civil rights movement.

One of the key findings of my research into social and political movements is that they are driven by small groups, loosely connected, but united by a common purpose. Perhaps not surprisingly, research has also shown that the structure of networks plays a major role in organizational performance.

That’s why it’s so important to network your organization by building bonds that supersede formal relationships. Experian, for example has built a robust network of clubs, where employees can share a passion, such as bike riding and employee resource groups, that are more focused on identity. While these activities are unrelated to work, the company has found that it helps employees span boundaries in the organization and collaborate more effectively.

All too often, we try to break down silos to improve information flow. That’s almost aways a mistake. To drive a true transformation, you need to connect silos so that they can coordinate action.

Make the Shift from Hierarchies to Networks

In an earlier age, organizations were far more hierarchical. Power rested at the top. Orders went down, information flowed up and decisions we made by a select priesthood of vaunted executives. In today’s highly connected marketplace, that’s untenable. The world has become fast and hierarchies are simply too slow.

That’s especially true when it comes to transformation. It doesn’t matter if the order comes from the top. If the organization itself isn’t prepared, any significant transformation is unlikely to succeed. That’s why you need to lead with vision, establish a keystone change that involves multiple stakeholders and work deliberately to network your organization.

Yet perhaps most importantly, you need to understand that in a networked world, power no longer resides at the top of hierarchies, but emanates from the center of networks. You move to center by continually widening and deepening connections. That’s how you drive a true transformation.

None of this happens overnight. It takes some time. That’s why the desire for change is not nearly as important as the will to prepare for it.

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

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Successful Agile Transformations

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Case Studies

Successful Agile Transformations

GUEST POST from Art Inteligencia

In a world accelerating at an unprecedented pace, the very notion of how organizations function and deliver value is undergoing a seismic shift. For too long, “Agile” has been bandied about as a mere set of tools or a new project management methodology. But let me be clear: that’s missing the forest for the trees. True Agile transformation is a profoundly human transformation. It’s about dismantling rigid hierarchies, fostering a culture of trust and autonomy, and relentlessly focusing on delivering real value to real people – your customers and your employees.

Many organizations embark on Agile journeys, only to stumble. They hit the inevitable resistance to change, encounter leadership unwilling to cede control, or fail to truly embed the Agile mindset within their cultural DNA. Yet, amidst these challenges, beacons of success shine brightly. These are the organizations that understood that process is important, but people are paramount. They didn’t just *do* Agile; they *became* Agile, from the inside out. Let’s delve into a couple of illuminating case studies that highlight the power of successful, human-centered Agile transformations.

Case Study 1: ING – Banking on Agility and Empowerment

The Challenge: ING, a venerable multinational banking and financial services corporation, faced the classic dilemma of established giants: how to remain competitive and responsive against nimble fintech disruptors in a rapidly digitalizing market. Their traditional waterfall approaches and siloed departments were creating drag, hindering innovation and slowing their ability to deliver new digital products and services quickly. Customer expectations were evolving rapidly, and ING needed to catch up – fast.

The Human-Centered Agile Approach: ING didn’t merely adopt a framework; they engineered a radical organizational redesign centered on people. Drawing inspiration from Silicon Valley’s tech giants, they famously restructured their entire Dutch headquarters into a “tribe and squad” model. This wasn’t just a reshuffle; it was a profound cultural shift.

Empowered, End-to-End Ownership: They disbanded traditional functional departments, creating small, cross-functional “squads” (teams of 5-9 people) with complete, end-to-end responsibility for specific products or customer journeys. Each squad was given the autonomy to decide how they would achieve their objectives, fostering an incredible sense of ownership, accountability, and psychological safety. This was a direct investment in the human capital.
Relentless Customer-Centricity: The focus moved dramatically from internal processes to external customer value. Squads were organized explicitly around customer needs and journeys, ensuring every effort directly contributed to enhancing the customer experience. Continuous feedback loops, rapid prototyping, and extensive user testing became the norm, allowing ING to truly listen to its customers.
Leadership as Facilitators, Not Commanders: Senior leadership transformed from a command-and-control hierarchy to a servant leadership model. Their role became one of removing impediments, empowering teams, coaching, and fostering a culture where experimentation and learning from failure were not just tolerated, but encouraged. They invested heavily in comprehensive training and ongoing coaching for *all* employees, reinforcing the new mindset.

The Results: ING’s transformation is a benchmark for large-scale enterprise agility.

Dramatic Speed & Innovation: They significantly reduced time-to-market for new digital services, often by two-thirds. This agility fueled a surge in innovation, leading to a richer array of customer-facing products.
Enhanced Customer and Employee Experience: By placing customers at the heart of development, ING saw marked increases in customer satisfaction. Internally, employee engagement and morale soared as individuals felt more empowered, valued, and connected to the impact of their work.
Significant Cost Savings: Streamlined processes and increased efficiency led to substantial operational cost reductions.

Key Takeaways from ING:

Go Beyond Process: Agile is a cultural redesign. Real transformation requires fundamentally rethinking organizational structure and leadership roles.
Empower the Edge: Push decision-making authority to the teams closest to the work and the customer. Trust your people.
Leaders Must Serve: Leadership’s role shifts from directing to enabling and fostering a safe, experimental environment.

Case Study 2: Microsoft – Reigniting Innovation Through DevOps and Human Connection

The Challenge: For decades, Microsoft, an undeniable software behemoth, operated under deeply ingrained, lengthy waterfall development cycles. This led to notoriously slow response times to market shifts, often years-long product release cycles, and a growing disconnect between engineering teams and the rapidly evolving needs of their enterprise and consumer customers. As the industry pivoted to cloud computing and continuous delivery, Microsoft’s traditional pace became a critical liability. The scale of change required was staggering.

The Human-Centered Agile Approach: Microsoft’s revitalization, particularly within its Azure cloud services division, stands as a testament to the power of human-centered engineering transformation. It wasn’t just about adopting Scrum; it was about building a culture of rapid feedback and continuous improvement.

DevOps as a Cultural Bridge: A cornerstone was the widespread adoption of DevOps practices. This went far beyond automation; it was about fostering deep collaboration and communication between traditionally siloed development and operations teams. This human alignment created shared ownership for the entire software delivery lifecycle, leading to smoother, faster deployments and a significant reduction in blame-games.
Small, Autonomous Teams & Direct Customer Connection: They moved from massive, multi-year projects to smaller, highly focused, cross-functional engineering teams. Crucially, these teams were given significant autonomy and were pushed to establish direct, continuous feedback loops with customers. They regularly released minimal viable products (MVPs), gathered immediate user insights, and iterated. This direct connection gave engineers a palpable sense of purpose and impact.
Iterative Development and Continuous Delivery: The shift from infrequent, “big bang” releases to continuous integration and continuous delivery (CI/CD) meant delivering value incrementally, reducing risk, and allowing teams to adapt their products in real-time based on actual usage and feedback. This empowered teams to learn and adjust on the fly.
Leadership Modeling the Change: Under Satya Nadella’s leadership, there was a profound cultural pivot towards a “growth mindset.” Leadership actively participated in Agile ceremonies, openly discussed challenges, celebrated incremental successes, and championed transparency. This top-down commitment to vulnerability and learning reinforced the new ways of working and built trust across the organization.

The Results: Microsoft’s transformation is widely recognized for reigniting its innovation engine and solidifying its position as a cloud and software leader.

Exponential Release Acceleration: The release cadence for Azure, once measured in months or years, accelerated to daily or even hourly deployments for some services, allowing them to compete fiercely and effectively.
Superior Product Quality & Relevance: Continuous testing, integration, and rapid feedback loops led to higher quality products that were consistently more aligned with customer needs.
Elevated Employee Engagement: Engineers reported vastly improved morale, feeling more connected to the product, the customer, and the impact of their work. The ability to see their code deployed and used quickly was a massive motivator.
A Culture of Continuous Learning: Beyond metrics, Microsoft successfully instilled a culture of experimentation, embracing failure as a learning opportunity, and fostering a relentless drive for improvement across its vast engineering organization.

Key Takeaways from Microsoft:

DevOps is More Than Tools: It’s a cultural imperative that bridges development and operations for faster, higher-quality delivery.
Customer Proximity is Power: Direct and continuous customer feedback empowers teams and ensures relevance.
Leadership Must Lead By Example: A growth mindset, transparency, and active participation from the top are non-negotiable for large-scale change.

Image credit: Pexels

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Creating Accessible Digital Experiences

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Creating Accessible Digital Experiences

GUEST POST from Chateau G Pato

In the relentless pursuit of innovation, organizations often focus on speed, features, and market share. Yet, a fundamental aspect, one that unlocks true human potential and broadens market reach, is frequently overlooked: **accessibility**. For too long, accessibility has been relegated to a compliance checkbox, a burdensome requirement rather than a strategic advantage. I’m here to tell you that creating accessible digital experiences isn’t just about meeting mandates; it’s a profound strategic imperative, a catalyst for deeper customer engagement, enhanced brand loyalty, and genuine social impact. It’s about designing for humanity, not just for the “average” user, and in doing so, unlocking new avenues for growth and competitive differentiation.

The digital world, for all its promise of connectivity and information, can paradoxically create formidable barriers. For individuals with disabilities – visual, auditory, motor, cognitive – an inaccessible website, app, or software platform can be a fortress, not a gateway. When we design with accessibility in mind from the outset, we aren’t just accommodating a minority; we are improving the experience for everyone. Think about the universal design principles seen in the physical world: curb cuts, originally designed for wheelchairs, now benefiting parents with strollers, delivery drivers, and even skateboarders. The same principle applies in the digital realm, yielding universal benefits that improve usability and engagement for all.

The Irrefutable Business Case for Accessibility

Beyond the undeniable ethical responsibility, there’s an increasingly compelling business case for prioritizing accessibility. Leaders who grasp this are positioning their organizations for future success:

Expanded Market Reach: According to the World Health Organization, over one billion people, about 15% of the global population, experience some form of disability. This represents a significant, often underserved, market segment with substantial purchasing power – a market you’re currently missing if your experiences aren’t accessible.
Enhanced Usability for All: Features like clear navigation, high-contrast text, keyboard operability, and intuitive interfaces don’t just help those with disabilities; they enhance the experience for everyone. Consider a user accessing your app on a small screen in bright sunlight (requiring higher contrast) or a busy professional multitasking (benefiting from clear auditory cues and keyboard shortcuts).
Improved SEO & Performance: Many accessibility best practices, such as semantic HTML, proper heading structures, descriptive alt text for images, and well-structured content, directly contribute to better search engine optimization (SEO) and overall site performance. Google rewards well-structured, user-friendly content.
Reduced Legal Risk: Non-compliance with accessibility standards (like WCAG – Web Content Accessibility Guidelines, which are increasingly adopted globally) can lead to costly lawsuits, significant fines, and severe reputational damage. Proactive implementation is the most effective risk mitigation strategy.
Innovation & Brand Reputation: Companies that champion accessibility are seen as innovative, forward-thinking, and genuinely inclusive. This builds powerful brand loyalty, attracts top talent who value ethical practices, and fosters a culture of true innovation by pushing teams to think more creatively about problem-solving.

The Transformative Shift: From Compliance to Culture

The true breakthrough happens when accessibility transitions from a reactive checklist item mandated by legal teams to an ingrained, proactive part of an organization’s design, development, and content creation culture. This requires a human-centered approach, profound empathy, and a commitment to continuous learning and adaptation.

Embrace Inclusive Design Principles: Design for diversity from day one. Actively involve people with disabilities in the user research, design, and testing processes. Their lived experiences provide invaluable insights that no able-bodied designer can replicate.
Educate and Empower Teams: Provide comprehensive, ongoing training for designers, developers, product managers, quality assurance specialists, and content creators on accessibility standards (WCAG), assistive technologies, and inclusive design methodologies. Foster a shared understanding and collective responsibility.
Integrate Accessibility into Workflows: Make accessibility a standard, non-negotiable requirement in every sprint, every design review, every code commit, and every quality assurance check. It’s not an add-on or a post-launch fix; it’s integral to the definition of “done.”
Utilize Robust Tools & Testing: Leverage automated accessibility checkers for initial scans, but always complement this with manual testing using a variety of assistive technologies (e.g., popular screen readers like JAWS or NVDA, voice control software, keyboard-only navigation). Critically, conduct usability testing with actual users with diverse abilities.
Iterate and Improve Continuously: Accessibility is an ongoing journey, not a static destination. Establish feedback loops, monitor digital experience performance against accessibility metrics, and continuously iterate to enhance the user experience based on real-world usage and evolving standards.

Pioneering Inclusivity: Case Studies in Action

Case Study 1: Microsoft’s Cultural Transformation for Accessibility

Microsoft has undergone a remarkable journey, transforming accessibility from a secondary consideration to a core tenet of its mission: “to empower every person and every organization on the planet to achieve more.” This wasn’t merely about adding features; it was a profound cultural shift. They launched initiatives like the “AI for Accessibility” program, a $25 million five-year grant program leveraging AI to amplify human capabilities for people with disabilities, fostering external innovation. Internally, they’ve deeply integrated accessibility features into Windows, Office 365, and Xbox, from advanced Narrator screen reader improvements to live captions for Teams meetings and the groundbreaking Xbox Adaptive Controller, designed for gamers with limited mobility. This deep commitment extends to their hiring practices, ensuring diverse perspectives are inherent in product development teams, leading to more thoughtful, empathetic, and ultimately, more universally effective solutions.

Case Study 2: Starbucks’ Seamless Inclusive Digital Ordering

Starbucks, a global leader celebrated for its in-store customer experience, recognized the escalating importance of equally accessible digital channels. Their highly utilized mobile app, a primary touchpoint for millions of daily orders, became a focal point for significant accessibility enhancements. Collaborating closely with accessibility experts and, critically, with blind and low-vision users, they embarked on a comprehensive overhaul. This included vastly improving screen reader compatibility, optimizing color contrast ratios, and streamlining the entire navigation flow. The goal was to ensure users relying on assistive technologies could seamlessly browse menus, customize complex orders, apply loyalty points, and complete payments – functionalities absolutely crucial to the personalized Starbucks experience. This strategic investment not only significantly broadened their customer base, tapping into a previously underserved demographic, but also powerfully reinforced their brand image as a progressive, community-focused organization. The holistic improvements ultimately benefited all users by making the app inherently more intuitive, robust, and reliable, underscoring the universal dividends of inclusive design.

The Future is Undeniably Inclusive

As we race towards a future increasingly dominated by sophisticated digital interactions – from augmented reality to hyper-personalized AI and the metaverse – the imperative for accessibility only grows stronger. My perspective on human-centered innovation demands that we place empathy, usability, and inclusivity at the very core of our digital creation process. True innovation isn’t just about what technology can do; it’s about what it enables people to do, regardless of their diverse abilities. By embracing accessibility as a profound strategic advantage and embedding it as a cultural cornerstone, organizations can build not just better products and services, but fundamentally a better, more equitable, and more prosperous digital world for all.

The time for lip service is over. The time to act decisively is now. Let’s design a future where every digital door is truly open to everyone, creating value not just for shareholders, but for humanity.

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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