Category Archives: Digital Transformation

Transformation Insights

Future Always Wins

“The most damaging phrase in the language is, ‘We’ve always done it this way!”
~ Grace Murray Hopper

GUEST POST from Bruce Fairley

Nearly a century ago in 1923, General Motors made an evolutionary leap in car design with the chemical expertise of Dupont. Debuting the new Duco paint technology, they introduced consumers to a range of car colors, thus giving the Second Industrial Revolution more variety. This was antithetical to rival Henry Ford’s ‘keep it plain to make it rain’ approach. One car – one color was his contribution to humanity. But the robotic consistency that made Ford a legend also became his Achilles heel as glamor and luxury disrupted the auto business and he was dragged kicking and screaming into the future.

When people say ‘it’s lonely at the top’ – it’s not. It’s crowded with competition. In today’s Fourth Industrial Revolution – or Industry 4.0 – leaders that have the courage to change are able to do what some titans haven’t been able to do.

Pivot. Quickly.

Technological leaps have now advanced to an accelerated rate unprecedented in human history. Change is no longer a left curve surprise, but rather a constant evolution that offers both potentially great reward – and great risk. If growth doesn’t drive change – danger will. Visionary leaders navigate today’s ‘wild west’ landscape with an intelligent team approach. One that re-aligns technology to serve business goals rather than other way around.

But this is not a solo mission. Evolution thrives in collaboration, whether it’s upending an industry or upleveling a medium sized firm into a scalable trajectory. Optimizing the tech-business relationship takes multiple points of expertise and objective study. Where technology currently serves – and where it’s poised to strike is a critical question at the heart of any digital transformation worth undertaking. This may not be obvious at first glance. A previously valuable ‘built to last’ feature may now be hindering ‘built to evolve’ capabilities.

That is one reason why C-Suite leaders often turn to digital transformation firms such as The Narrative Group to fix the gap between their current technological resources and their ambitions. Just as GM partnered with Dupont to dazzle consumers nearly a hundred years ago, corporations that wish to present their best offer to the world need a similar confluence of five positive elements:

Collaboration Between Complementary Influencers
Creative and Analytical Engagement
Smart Use of Technology
Human Powered Learnability

And most importantly … The Willingness to Change Because the future always wins.

When I founded The Narrative Group, it was partly in response to this need for collaboration that I saw as critical to a corporation’s evolution. Going a step beyond ‘consulting’ to helping construct a corporation’s best future allows me to contribute to the safeguarding of that future for the many people that rely on a corporation’s healthy bottom line to build their own lives. Human potential is measured not only in outcome but also the way in which that outcome is achieved. Effective collaboration requires three key pillars that support an evolutionary leap:

Trust between the internal leadership team and the digital transformation firm hired to consult.

Transparency in the process from first contact through recommendations.

Trajectory in implementing recommendations in a way that maximizes the potential benefits.

This is part of a larger conversation that I enjoy having with clients and within my own team. I will elaborate on some of these points in future posts, but for now I hope I’ve sparked some reflection about the strength of character great leaders exhibit when they choose to master change rather than be blindsided by it.

If you’re a C-Suite leader that would like to discuss your corporation’s Industry 4.0 evolution and how to advance towards a best future outcome that aligns with your vision, reach out at:

connect@narrative-group.com

Looking forward to continuing the conversation…

Image Credit: The Narrative Group

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Taking Personal Responsibility – Seeing Self as Cause

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Taking Personal Responsibility – Seeing Self as Cause

GUEST POST from Janet Sernack

In our last two blogs on Taking Personal Responsibility, we stated that when people aren’t taking personal responsibility, they cannot be accountable, they will fail in their jobs, and their teams, and fail to grow as individuals and as leaders. Taking personal responsibility is an especially crucial capability to develop self-awareness and self-regulation skills in the decade of both disruption and transformation. It all starts with seeing self as the cause of what happens to us, rather than baling it on the effects events and problems have on us! Where people can learn to recognize the structures at play in their lives and change them so that they can create what they really want to create in their lives, teams, or organizations.

In the last two blogs, we shared a range of tips for shifting people’s location, by creating a line of choice, to help them shift from being below the line and blaming others for their reactive response, to getting above the line quickly. Through shifting their language from “you, they and them” to “I, we and us” and bravely disrupting and calling out people when they do slip below the line. How doing this allows people to also systemically shift across the maturity continuum, from dependence to independence and ultimately towards interdependence.

In a recent newsletter Otto Scharmer, from the Presencing Institute states “Between action and non-action there is a place. A portal into the unknown. But what are we each called to contribute to the vision of the emerging future? Perhaps these times are simply doorways into the heart of the storm, a necessary journey through the cycles of time required to create change”.

Creating the place – the sacred pause

When I made a significant career change from a design and marketing management consultant to becoming a corporate trainer, one of the core principles I was expected to teach to senior corporate managers and leaders was taking personal responsibility.

Little knowing, that at the end of the workshop, going back to my hotel room and beating myself up, for all of the “wrongs” in the delivery of the learning program, was totally out of integrity with this core principle.

Realising that when people say – those that teach need to learn, I had mistakenly thought that I had to take responsibility for enacting the small imperfections I had delivered during the day, by berating myself, making myself “wrong” and through below the line self-depreciation!

Where I perfectly acted out the harmful process of self-blame, rather than rationally assessing the impact of each small imperfection, shifting to being above the line where I could intentionally apply the sacred pause:

Hit my pause button to get present, accept my emotional state,
Connect with what really happened to unpack the reality of the situation and eliminate my distortions around it,
Check-in and acknowledge how I was truly feeling about what happened,
Acknowledge some of the many things that I had done really well,
Ask myself what is the outcome/result I want for participants next program?
Ask myself what can I really learn from this situation?
Consciously choose what to do differently the next time I ran the program.

I still often find myself struggling with creating the Sacred Space between Stimulus and Response and have noticed in my global coaching practice, that many of my well-intentioned clients struggle with this too.

The impact of the last two and a half years of working at home, alone, online, with minimal social interactions and contact, has caused many of them to languish in their reactivity, and for some of them, into drowning in a very full emotional boat, rather than riding the wave of disruptive change.

Being the creative cause

In our work at ImagineNation, whether we help people, leaders and teams adapt, innovate and grow through disruption, their ability to develop true self-awareness and be above the line is often the most valuable and fundamental skill set they develop.

It then enables us to make the distinction that creating is completely different from reacting or responding to the circumstances people find themselves in by applying the sacred pause.

When people shift towards seeing self as the cause they are able to create and co-create what they want in their lives, teams or organization by learning to create by creating, starting with asking the question:

What result do you want to create in your life?
What is the reality of your current situation?

This creates a state of tension, it is this tension that seeks resolution.

In his ground-breaking book The Path of Least Resistance Robert Fritz, goes on to describe and rank these desired results as “Fundamental Choices, Primary Choices, and Secondary Choices.”

Because there is one thing that we can all do right and is totally in our control – is to shift towards seeing self as the cause and make a set of conscious choices, with open hearts, minds, and wills, as to how we think, feel and choose to act.

“We are the creative force of our life, and through our own decisions rather than our conditions, if we carefully learn to do certain things, we can accomplish those goals.”

We all have the options and choices in taking responsibility, empowering ourselves and others to be imaginative and creative, and using the range of rapid changes, ongoing disruption, uncertainty, and the adverse pandemic consequences, as levers for shifting and controlling, the way we think, feel.

Benefits of seeing self as the cause and being above the line

Applying the sacred pause to make change choices in how we act – and being brave and bold in shifting across the maturity continuum, will help us to cultivate the creativity, interdependence, and systemic thinking we all need right now because it:

Helps people self-regulate their reactive emotional responses, be more open-hearted and emotionally agile, and helps develop psychologically safe work environments where people can collaborate and experiment, and fail without the fear of retribution or punishment.
Enables people to be more open-minded, imaginative, and curious and creates a safe space for continuous learning, maximizing diversity and inclusion, and proactive intentional change and transformation.
Promotes ownership of a problem or challenging situation and helps develop constructive and creative responses to problems and an ability to take intelligent actions.
Gives people an opportunity to impact positively on others and build empowered trusted and collaborative relationships.
Enables entrepreneurs and innovators to invent creative solutions and drive successful innovative outcomes.
Building the foundations for accountability, where people focus their locus of control on what they promise to deliver, enables them to be intrinsically motivated, and take smart risks on negotiating outcomes that they can be counted on for delivering.

Tips for seeing self as the cause and operating above the line

Taking personal responsibility and seeing self as the cause involves:

Acknowledging that “I/we had a role or contributed in some way, to the fact that this has not worked out the way “I/we wanted.”
Clarifying the outcome or result in you want from a specific situation or a problem.
Seeking alternatives and options for making intelligent choices and actions, and using the language of “I/we can” and “I/we will” to achieve the outcome.
Replacing avoiding, being cynical and argumentative, blaming, shaming, controlling, and complaining with courageous, compassionate, and creative language and acts of intention.
People become victors who operate from “self as cause” where they are empowered to be the creative forces in their own lives by making fundamental, primary, and secondary change choices.
Trust your inner knowing and deep wisdom that everything has a specific and definable cause and that each and every one of us has the freedom to choose how to respond to it.

Back to leadership basics

As Stephen Covey says, people need to deeply and honestly say “I am what I am today because of the choices I made yesterday” because it’s not what happens to us, it’s our reactive response to what happens that hurts us.

Being willing to step back, retreat, and reflect on the gap between the results you want, and the results you are getting all starts with stepping inward, backward, and forwards, using the sacred pause, to ask:

What happened? What were the key driving forces behind it?

How am I/we truly feeling about it?

What was my/our role in causing this situation, or result?

What can I/we learn from it?

What is the result/outcome I want to create in the future?

What can I/we then do to create it?

As a corporate trainer, consultant and coach, I found out the hard way that developing the self-awareness and self-regulation skills in taking personal responsibility and seeing self as the cause is the basis of the personal power and freedom that is so important to me, and almost everyone else I am currently interacting with.

It’s the foundation for transcending paralysis, overwhelm, and stuck-ness and activating our sense of agency to transform society and ourselves.

This is the third and final blog in a series of blogs on the theme of taking responsibility – going back to leadership basics. Read the previous two here:

Find out about our learning products and tools, including The Coach for Innovators, Leaders, and Teams Certified Program, a collaborative, intimate, and deeply personalized innovation coaching and learning program, supported by a global group of peers over 9-weeks, starting Tuesday, October 18, 2022. It is a blended and transformational change and learning program that will give you a deep understanding of the language, principles, and applications of an ecosystem focus, human-centric approach, and emergent structure (Theory U) to innovation, and upskill people and teams and develop their future fitness, within your unique context.

Image credit: Pixabay

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What Makes Digital Health Clinical Trials Different?

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What Makes Digital Health Clinical Trials Different?

GUEST POST from Arlen Meyers, M.D.

For digital health entrepreneurs, unless your intended use puts you in the FDA category of a medical device, you don’t need to show that your product is safe and effective, let alone cost-effective. In most cases, rather, you need to demonstrate to investors that it can quickly scale and make money and the sooner the better. Too bad. You would think that whether you have to or not that prudent sick care business practices would mean creating a product that does what you say it will do. That’s why only a handful of the hundreds of thousands of digital health apps are clinically valid.

However, most sick care digipreneurs avoid costly, risky trials because they are afraid of possible negative results that could be the death blow of their company, like many early stage biotech or device companies that wake up to see their valuations plummet due to a failed trial.

Digital health regulation is changing rapidly as the FDA tries to keep up with the pace of change and new products and services. On FDA regulation, the rule—for now, at least—is clear: Any device that is “intended for use in the diagnosis of disease of other conditions, or in the cure, mitigation, treatment, or prevention of disease” requires FDA approval, Curtis said. This goes for devices meant for humans and animals, as the FDA regulates both.

The emergence of digital therapeutics, the incorporation of AI and the adoption of remote sensing is challenging us how to demonstrate safety and efficacy, if not cost-efffectiveness.

For example, there’s been an explosion in the number and variety of digital apps purporting to address behavioral health issues, but a recent study published in Nature Digital Medicine casts doubts on their backing by legitimate scientific research. Based on the literature review conducted by the researchers, only 14 percent of apps described design or development that was based on real-world evidence.

One commentary to a recently published article on digital health trials noted that “The pipeline of digital health studies appears to be promising,” noted the researchers, but they also underscored that the small sample sizes in many studies “could limit their ability to yield a high level of evidence, demonstrate value, or motivate stakeholder adoption.”

Digital health technologies hold great promise to solve some of the biggest problems in our healthcare system, including achieving higher quality, lower cost, and greater access to care. a better doctor and patient experience and efficiencies in business processes. In the January 2019 issue of Health Affairs, reported that scant evidence exists demonstrating the clinical impact of twenty top-funded digital health companies. These companies tended not to study the clinical effectiveness of their products in terms of key healthcare metrics like patient outcomes, cost, and access to care.

They found 104 peer-reviewed published studies on the products or services of these companies. The majority of the studies were from three companies. Nine companies had no peer-reviewed publications. Only 28% of the studies targeted patients with high-burden, high-cost conditions or risk factors. Healthy volunteers were the most commonly studied population. Further, 15% of all studies assessed the product’s “clinical effectiveness” and only eight studies assessed clinical effectiveness in a high-cost, high-burden population. The eight clinical effectiveness studies measured impact in terms of patient outcomes, while no studies measured impact in terms of cost or access to care. There were no clinical effectiveness studies in heart disease, COPD, mental health conditions, hyperglycemia, or low back pain. Studies that did not assess clinical effectiveness may have intended to validate the product against a gold standard measurement or report feasibility of use.

This is of particular interest given the incredible amount of funding, interest, and hype in digital health. Although these companies were only a small portion of total digital health companies, they were a large portion of total private funding and had the most resources to demonstrate impact. Further, since “digital health” currently encompasses myriad technology types and approaches, these findings have broad implications.

From text messages to mobile apps, digital health devices are becoming increasingly important in clinical trials for their ability to streamline trials, lower site burden, and improve the patient experience. However, manufacturers must consider the safety, reliability, and convenience of these devices in order to effectively implement them into medical device trials. The digital components of these medical device trials must adhere to the same rigorous regulatory standards as the device itself, which can pose significant hurdles for some sponsors. Those hurdles include:

Usability and Accuracy. Sponsors must be able to determine that a device is providing the desired endpoint values in a trial. The metric should be accurate and presented in a usable format.
Safety. The manufacturer should be able to provide highly secure methods for transmitting data between the digital health device and the analysis site.
Convenience. The manufacturer should be able to provide logistical support to decrease the site and subject burden. They should also be able to provide full documentation of engineering verification for the devices.
Ease of Use. It is important to consider how the patient will interact with the device. It needs to be an appropriate size and weight, and it should allow the patient to move and behave in the same way he or she normally would.
Reliability. To maintain data continuity, the device should have a battery life sufficient to allow it to collect data for long periods of time with minimal glitches.

In another study of digital health apps for COVID 19, apps were evaluated using the Systems Wide Analysis of mobile health-related technologies (SWAT) tool in line with the NHS Digital Assessment Questionnaire and were given a score for each category (usability, functionality, ethical values, security and privacy, user-perceived value, design, and content) by two independent assessors.

A recent review concluded that “Safety of apps is an emerging public health issue. The available evidence shows that apps pose clinical risks to consumers. Involvement of consumers, regulators, and healthcare professionals in development and testing can improve quality. Additionally, mandatory reporting of safety concerns is needed to improve outcomes.”

The concept of a “digital clinical trial” involves leveraging digital technology to improve participant access, engagement, trial-related measurements, and/or interventions, enable concealed randomized intervention allocation, and has the potential to transform clinical trials and to lower their cost. In April 2019, the US National Institutes of Health (NIH) and the National Science Foundation (NSF) held a workshop bringing together experts in clinical trials, digital technology, and digital analytics to discuss strategies to implement the use of digital technologies in clinical trials while considering potential challenges. This position paper builds on this workshop to describe the current state of the art for digital clinical trials including (1) defining and outlining the composition and elements of digital trials; (2) describing recruitment and retention using digital technology; (3) outlining data collection elements including mobile health, wearable technologies, application programming interfaces (APIs), digital transmission of data, and consideration of regulatory oversight and guidance for data security, privacy, and remotely provided informed consent; (4) elucidating digital analytics and data science approaches leveraging artificial intelligence and machine learning algorithms; and (5) setting future priorities and strategies that should be addressed to successfully harness digital methods and the myriad benefits of such technologies for clinical research.

But, when it comes to human subject pilots and trials, there are several glaring differences of digital health trials compared to drug and device trials:

Intellectual property concerns are usually lower in digital trials
Digital trials need to be done faster because the markets change so quickly and the barriers to entry are lower
IRBs set up to protect patients in drug and device trials are not comfortable with digital health trials
We are still trying to define the ethics of data science
Cybersafety is as important as patient safety
Digital health clinical trial ecosystems are primitive compared to drug and device trial ecosystems although both have recruitment and completion challenges
Data trials need mostly patient data, not the physical presence of patients
HIPAA rules get in the way
Lack of interoperability and getting data from non-traditional hospital based HIT systems skews the data and , consequently, the results
Funding sources for conducting digital health trials are scarce. Investors don’t fund research projects. They fund product development and marketing. Here are some ideas on how to convince your CFO to pilot, test and integrate your IT solution.

The FDA has stated their position when it comes to the regulation of mobile medical apps.

Digital health has evolved because:

Interoperability is improving
Sick care is turning into health care
The medical business model is changing
Costs continue to spiral out of control
The recognition by digipreneurs and investors that sick care is ripe for digitization
Patient and provider frustration with a lousy experience
Cheap mobile and internet technologies
Regulatory, IP and reimbursement changes
The breakdown of barriers to diffusion and implementation
Digital heath ecosystems

An international consortium of medical experts has introduced the first official standards for clinical trials that involve artificial intelligence. The move comes at a time when hype around medical AI is at a peak, with inflated and unverified claims about the effectiveness of certain tools threatening to undermine people’s trust in AI overall.

Collaboratively developed guidelines for the privacy, content, security, design and operability of mobile health (mHealth) apps have been released. Compliance with the guidelines can provide a level of assurance that an app delivers value to patients, physicians and other users.

The guidelines were developed by Xcertia, a nonprofit founded by the AMA and other major health and technology organizations. They address concerns that have hindered the use of mHealth apps. Fears that an app may expose personal health information, that its content is inaccurate or that its functionality is limited have slowed adoption of mHealth digital health tools.

These advances are permeating all aspects of clinical research but the recent acceleration of decentralised and hybrid clinical trials (DCTs) illustrates how far reaching digitalisation is becoming. Patient-centricity has been driving the decentralisation of clinical trials for some time but the rapid emergence of the COVID-19 pandemic required the pharmaceutical industry to pivot operations and accelerate its DCT programmes. This response required a corresponding ramp-up in mobile technology, data management and AI.

AI can provide insight into protocol complexity and contribute to protocol designs better adapted to DCTs, including the creation of virtual control arms. The intelligent use of data to include historical data as well as the data collected during a clinical trial can optimise the number and diversity of patients needed to reach the desired endpoints and give the patients who do participate a higher value experience.

Until and unless we address ongoing digital health clinical trial issues , sick care digipreneurs will have little or no incentive to conduct digital health clinical trials using precious startup funds. Instead, they will continue to sell snake oil and lots of folks will buy it. Maybe you should sleep on it.

Image Credit: Pixabay

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The Future of User Research in a Digital-First Landscape

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The Future of User Research in a Digital-First Landscape

GUEST POST from Chateau G Pato

In an era where digital experiences define customer interactions and influence business growth, understanding user needs is more critical than ever. As organizations pivot towards a digital-first strategy, the methods and tools for user research must evolve to keep pace with changing expectations and technologies.

Embracing Digital Ethnography

Traditional user research methods like face-to-face interviews and focus groups often fall short in a global digital economy where interactions occur online. Digital ethnography, leveraging tools such as social media listening and online behavioral data, allows researchers to gain profound insights with greater reach and efficiency. By observing digital behaviors in real-time, researchers can access authentic user interactions without the bias that often accompanies direct questioning.

Case Study 1: Netflix

Innovating with Cultural Analytics

Netflix has fine-tuned its user research process to align with its digital-first model. By employing digital ethnography techniques, Netflix tracks viewing habits and preferences through an intricate web of data analytics. This deep dive into cultural analytics not only helps Netflix in curating personalized content but also in identifying potential content trends across different regions.

Understanding the cultural context of their growing global audience, Netflix successfully predicted the popularity of shows like “Squid Game,” a South Korean series that became a worldwide sensation. By analyzing regional viewing patterns and social media buzz, Netflix tapped into a cultural wave before it crested, ultimately driving subscriptions and engagement globally.

Leveraging AI and Machine Learning

Innovations in AI and machine learning have unlocked new possibilities for user research, enabling researchers to process vast amounts of data with precision. These technologies can predict trends, discern patterns, and generate meaningful insights that were previously out of reach. AI-powered tools can analyze user feedback, identify sentiment, and highlight areas where digital interfaces may require enhancement.

Case Study 2: Spotify

AI-Driven Personalization

Spotify’s use of AI and machine learning for user research stands as a beacon of innovation. The company utilizes AI algorithms to analyze user listening behaviors, preferences, and feedback, enabling it to create highly personalized experiences. Playlists such as “Discover Weekly” use these insights to cater to individual tastes, promoting user satisfaction and retention.

Spotify’s approach to user research showcases the power of AI in transforming raw data into actionable insights that not only understand current user preferences but also anticipate future needs. By continuously refining their models, Spotify remains at the forefront of delivering user-centric digital products.

Integrating Qualitative and Quantitative Methods

While digital tools offer quantitative insights at scale, the importance of qualitative research remains undiminished. Combining both approaches provides a comprehensive understanding of user needs, motivations, and potential pain points. Digital tools can help in identifying broad trends, but qualitative methods are essential in uncovering the ‘why’ behind these patterns.

Organizations that build a culture of innovation prioritize the integration of diverse research methodologies, ensuring they cater to the complete user journey from multiple angles.

The Road Ahead

The future of user research in a digital-first landscape is rich with potential. By embracing emerging technologies and methodologies, organizations can create richer, more empathetic user experiences that resonate deeply with their audiences. The continual evolution and integration of advanced tools and human-centric approaches will shape how we understand and engage with users in a world increasingly defined by digital interactions.

As we stand on the precipice of this exciting future, the opportunity lies in our ability to remain curious, adaptable, and thoughtful about the role user research plays in crafting experiences that are not only effective but transformative.

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.

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Remote Work Revolution is Rethinking Employee Experience

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Remote Work Revolution is Rethinking Employee Experience

GUEST POST from Art Inteligencia

In the not-so-distant past, remote work was often seen as an occasional luxury. Fast forward to today, and it has become a significant, often preferable, reality for millions of employees worldwide. This shift—accelerated by global events and technological advancement—has brought about a remote work revolution that demands a fresh perspective on the employee experience. As organizations rethink their strategies, it’s crucial to center human needs in the design and implementation of remote work policies.

The New Paradigm

The traditional work environment has been significantly disrupted, leading to newfound flexibility and autonomy. But as appealing as remote work is, it also introduces challenges that can impact an employee’s sense of belonging, job satisfaction, and productivity. To address these, companies must foster transparent communication, promote work-life balance, and create spaces for social interaction—physically or virtually.

“Remote work is not just about working from a different location, but rather creating a dynamic ecosystem that can adapt to an employee’s personal and professional needs.”
Braden Kelley

Case Study 1: TechVision

Background

TechVision, a rapidly-growing software firm, recognized early the potential drawbacks of remote work. It understood that despite the liberating nature of flexible work schedules, employees might feel isolated and overlooked in a virtual environment.

Initiatives and Outcomes

To combat these challenges, TechVision introduced several initiatives:

Virtual Lounges: These digital meeting rooms are always open, encouraging employees to drop in for casual chats. This fosters a sense of community and reduces feelings of isolation.
Flexible Working Hours: Acknowledging diverse personal schedules, TechVision allows employees to define their own working hours, provided they meet deliverable deadlines.
Monthly Home Office Stipend: Understanding that an efficient home workspace is crucial, the company provides a stipend for employees to enhance their home office setup.

As a result, TechVision noticed a 20% increase in employee satisfaction and a 15% boost in productivity, proving that a thoughtful approach to remote work could yield significant benefits.

Case Study 2: GlobalInnovate

Background

GlobalInnovate, a multinational design firm, faced the challenge of maintaining creativity and collaboration in a remote setup. Vital brainstorming sessions had to transition from the boardroom to the online space, sometimes losing the dynamic energy critical to innovation.

Initiatives and Outcomes

GlobalInnovate employed the following strategies:

Virtual Reality Collaboration Tools: By adopting VR meeting platforms, the firm recreated the spatial dynamics of an in-person meeting, fostering more natural interactions.
Regular Creative Jams: These unstructured sessions are dedicated purely to creative exploration, allowing teams to ideate freely without the pressure of immediate deliverables.
Global Work Sprints: Employees from different time zones collaborate intensively on projects for a week, followed by a comprehensive review and reflection process.

These approaches have sustained GlobalInnovate’s creative output, with the firm reporting a 30% rise in innovative solutions proposed by their teams over a six-month period.

Conclusion

The remote work revolution isn’t merely a shift in location; it’s a transformation in how we perceive and execute work itself. Organizations, by re-imagining the employee experience to ensure connectivity, flexibility, and creativity, can turn the challenges of remote work into opportunities for growth and innovation. As we move forward, it’s imperative that we continue to pioneer strategies that place human experience at the forefront of the remote work landscape.

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.

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Rethinking Agility for the Post-Digital Age

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Rethinking Agility for the Post-Digital Age

GUEST POST from Greg Satell

For the past 50 years, innovation has largely been driven by our ability to cram more transistors onto a silicon wafer. That’s what’s allowed us to double the power of our technology every two years or so and led to the continuous flow of new products and services streaming out of innovative organizations.

Perhaps not surprisingly, over the past few decades agility has become a defining competitive attribute. Because the fundamentals of digital technology have been so well understood, much of the value has shifted to applications and things like design and user experience. Yet that will change in the years ahead.

Over the next few decades we will struggle to adapt to a post-digital age and we will need to rethink old notions about agility. To win in this new era of innovation we will have to do far more than just move fast and break things. Rather, we will have to manage four profound shifts in the basis of competition that will challenge some of our most deeply held notions.

Shift 1: From Transistor-Based Computers to New Computing Architectures

In 1965, Intel’s Gordon Moore published a paper that established predicted Moore’s Law, the continuous doubling of transistors that can fit on an integrated circuit. With a constant stream of chips that were not only more powerful, but cheaper, successful firms would rapidly prototype and iterate to speed new applications to market.

Yet now Moore’s Law is ending. Despite the amazing ingenuity of engineers, the simple reality is that every technology eventually hits theoretical limits. The undeniable fact is that atoms are only so small and the speed of light is only so fast and that limits what we can do with transistors. To advance further, we will simply have to find a different way to compute things.

The two most promising candidates are quantum computing and neuromorphic chips, both of which are vastly different from digital computing, utilizing different logic and require different computer languages and algorithmic approaches than classical computers. The transition to these architectures won’t be seamless.

We will also use these architectures in much different ways. Quantum computers will be able to handle almost incomprehensible complexity, generating computing spaces larger than the number of atoms in the known universe. Neuromorphic chips are potentially millions of times more efficient than conventional chips and are much more effective with continuous streams of data, so may be well suited for edge computing and tasks like machine vision.

Shift 2: From Bits to Atoms

The 20th century saw two major waves of innovation. The first, dominated by electricity and internal combustion, revolutionized how we could manipulate the physical world. The second, driven by quantum physics, microbial science and computing, transformed how we could work with the microscopic and the virtual.

The past few decades have been dominated by the digital revolution and it seems like things have been moving very fast, but looks can be deceiving. If you walked into an average 1950s era household, you would see much that you would recognize, including home appliances, a TV and an automobile. On the other hand, if you had to live in a 1900’s era home, with no running water or electricity, you would struggle to survive.

The next era will combine aspects of both waves, essentially using bits to drive atoms. We’re building vast databases of genes and materials, cataloging highly specific aspects of the physical world. We are also using powerful machine learning algorithms to analyze these vast droves of data and derive insights. The revolution underway is so profound that it’s reshaping the scientific method.

In the years to come, new computing architectures are likely to accelerate this process. Simulating chemistry is one of the first applications being explored for quantum computers, which will help us build larger and more detailed databases. Neuromorphic technology will allow us to shift from the cloud to the edge, enabling factories to get much smarter.

The way we interface with the physical world is changing as well. New techniques such as CRISPR helps us edit genes at will. There is also an emerging revolution in materials science that will transform areas like energy and manufacturing. These trends are still somewhat nascent, but have truly transformative potential.

Shift 3: From Rapid Iteration to Exploration

Over the past 30 years, we’ve had the luxury of working with technologies we understand extremely well. Every generation of microchips opened vast new possibilities, but worked exactly the same way as the last generation, creating minimal switching costs. The main challenge was to design applications.

So it shouldn’t be surprising that rapid iteration emerged as a key strategy. When you understand the fundamental technology that underlies a product or service, you can move quickly, trying out nearly endless permutations until you arrive at an optimized solution. That’s often far more effective than a planned, deliberate approach.

Over the next decade or two, however, the challenge will be to advance technology that we don’t understand well at all. As noted above, quantum and neuromorphic computing are still in their nascent stages. Improvements in genomics and materials science are redefining the boundaries of those fields. There are also ethical issues involved with artificial intelligence and genomics that will require us to tread carefully.

So in the future, we will need to put greater emphasis on exploration to understand these new technologies and how they relate to our businesses. Instead of looking to disrupt markets, we will need to pursue grand challenges to solve fundamental problems. Most of all, it’s imperative to start early. By the time many of these technologies hit their stride, it will be too late to catch up.

Shift 4. From Hyper Competition to Mass Collaboration

The competitive environment we’ve become used to has been relatively simple. For each particular industry, there have been distinct ecosystems based on established fields of expertise. Competing firms raced to transform fairly undifferentiated inputs into highly differentiated products and services. You needed to move fast to get an edge.

This new era, on the other hand, will be one of mass collaboration in which government partners with academia and industry to explore new technologies in the pre competitive phase. For example, the Joint Center for Energy Storage Research combines the work of five national labs, a dozen or so academic institutions and hundreds of companies to develop advance batteries. Covid has redefined how scientists collaborate across institutional barriers.

Or consider the Manufacturing Institutes set up under the Obama administration. Focusing on everything from advanced fabrics to biopharmaceuticals, these allow companies to collaborate with government labs and top academics to develop the next generation of technologies. They also operate dozens of testing facilities to help bring new products to market faster.

I’ve visited some of these facilities and have had the opportunity to talk with executives from participating companies. What struck me was how palpable the excitement about the possibilities of this new era was. Agility for them didn’t mean learning to run faster down a chosen course, but to widen and deepen connections throughout a technological ecosystem.

Over the past few decades, we have largely been moving faster and faster down a predetermined path. Over the next few decades, however, we’ll increasingly need to explore multiple domains at once and combine them into something that produces value. We’ll need to learn how to go slower to deliver much larger impacts.

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

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Four Key Attributes of Transformational Leaders

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Four Key Attributes of Transformational Leaders

GUEST POST from Greg Satell

Change isn’t what it used to be. Where earlier generations had leaders like Gandhi, King and Mandela, today’s change efforts seem rudderless. Movements like #Occupy, Black Lives Matter and #MeToo hold marches replete with strident calls for change, but they never seem to get anywhere. Lots of sound and fury, signifying nothing.

Many believe that if only these movements had more charismatic leaders or more inspiring oratory they would be able to gain more traction. Others say that society has become too corrupt and our politics too coarse to make change happen. They want to blow the system up, not work within it.

The truth is that leadership has little to do with fancy speeches or clever slogans. The notion that today’s call for change face greater opposition than the British Raj, Jim Crow or Apartheid is simply laughable. In researching my book, Cascades, however, I found that, despite important differences, transformational leaders had these four things in common.

1. They Work To Make A Difference, Not Just Make A Point

When the #Occupy Wall Street movement broke out in 2011, it inspired millions with its rallying call,, “We are the 99%.” Yet soon it became clear that all was not well. As New York Times columnist Joe Nocera noted, the group “had plenty of grievances, aimed mainly at the ‘oppressive” power of corporations,’ but “never got beyond their own slogans.” It soon fizzled out, a massive waste of time.

Making lots of noise and achieving little seems to be a common theme among the failed revolutions of today. All too often they believe that the righteousness of their cause, along with some clever memes on social media, will win the day. It won’t. Real change requires real work. You have to want to make a difference, not just make a point

It’s not just young activists who make this mistake. Corporate bigwigs often fall into the same trap. They seek to “disrupt” without any real affirmative plan for change. In Lights Out, Wall Street Journal reporters Thomas Gryta and Ted Mann chronicle how General Electric CEO Jerrfey Immelt tried mightily to gin up the stock price and project an innovative image, but did little to create actual value.

For transformative leaders, making a difference is the real point. Thurgood Marshall, to take just one example, spent decades working in relative obscurity, not to mention facing significant danger, before he triumphed in Brown vs. Board of Education. If we are to achieve anything of significance, we need to think less about disruption and more about tackling grand challenges.

2. They Lead With Values

Today, we regard Nelson Mandela as an almost saintly figure, but it wasn’t always that way. In fact, throughout his career as an activist, he was accused of being a communist, an anarchist and worse. When confronted with these accusations, however, he always pointed out that no one had to guess what he believed in, because it was written down in the Freedom Charter in 1955.

Being explicit about values helped to signal to external stakeholders, such as international institutions, that the anti-Aparthied activists shared common values with them. In fact, although the Freedom Charter was a truly revolutionary document, its call for things like equal rights and equal protection would be considered unremarkable in most societies.

After Apartheid fell and Mandela rose to power, the values spelled out in the Freedom Charter became important constraints. To uphold the stated principle that “all should be equal under the law,” his government couldn’t oppress whites. His reconciliation efforts are a big part of the reason he is so revered today.

Values are just as powerful in a corporate context for many of the same reasons. In Lou Gerstner’s IBM turnaround in the 1990s, for example, he not only put forth serving customers as an important value, he also made it clear that he was willing to forego revenue on every sale to make good on it. His willingness to incur costs showed his values were more than lip service.

Make no mistake. Every significant change comes with costs and being explicit about values makes it clear what costs you are willing to incur. Far too many would-be change leaders fail to be explicit about their values because they don’t want to be constrained in any way. It’s much easier to spout slogans like “Disrupt” or “Innovate or Die” than to think seriously about what change will cost you and others.

3. They Shape Networks

The March on Washington was a defining moment for the civil rights movement and for America. So it shouldn’t be surprising that those seeking change today, such as Black Lives Matter and the modern women’s movement, try to emulate that earlier success with marches of their own. These efforts consistently fail to achieve anything real and, in fact, often do significant damage when they spin out of control.

The truth is that the civil rights movement didn’t become powerful because it held the March on Washington. In fact, it was very much the opposite. The March on Washington was held because the civil rights movements had already become powerful. It wasn’t an opening shot, but part of the end game, the culmination of decades of painstaking work of not just Martin Luther King Jr., but a broad array of leaders.

General Stanley McChrystal took a similar approach in revamping the US Special Forces in Iraq to fight Al Qaeda. Realizing that a conventional approach would not be effective against an unconventional opponent, he declared that “it takes a network to defeat a network and shifted his “focus from moving pieces on the board to shaping the ecosystem.”

The truth is that it is networks of small groups, loosely connected but united by a shared purpose that drives transformational change. Effective leaders know that their role is to empower others by helping to connect people in order to achieve that purpose.

4. They Learn From Their Mistakes

One of the most surprising things I found in my research is how consistently early efforts failed. The first march on Washington, the Woman Suffrage Procession of 1913, quickly spiraled out of control. Gandhi’s first efforts to bring disobedience to India ended so horribly he would later call it his Himalayan miscalculation. Steve jobs, quite famously, was fired from Apple.

What made the difference wasn’t the mistakes they made, but how they learned from them. Alice Paul developed more innovative strategies, such as the Silent Sentinel protests, which were less vulnerable to disruption. Suffrage was won in 1919. Gandhi replaced widespread protests with the Salt March. Steve Jobs became more focused and built the World’s most valuable company.

Unfortunately, many of today’s activists don’t seem to have the same strategic flexibility. Once the #Occupy protesters went home, they never seemed to come up with an alternative approach. The riots at Ferguson were replaced, six years later, by the George Floyd riots. The modern women’s movement continues to march, with little to show for it.

None of this is to say that these causes are unworthy or that they are doomed to failure. What it does mean is that, if they are to succeed, they need to understand how revolutions fail and do something different. In an age of disruption, the only viable strategy is to adapt.

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

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Measuring Innovation Outcomes from Idea to Impact

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Measuring Innovation Outcomes from Idea to Impact

GUEST POST from Art Inteligencia

Innovation is the lifeblood of progress and business success. In a rapidly changing world, the ability to convert novel ideas into tangible results can define the trajectory of an organization. However, bridging the gap from idea inception to impactful outcomes requires more than inspiration. It demands a rigorous approach to measure, manage, and maximize the value of innovation activities.

The Innovation Measurement Conundrum

Innovation, by its nature, is nebulous and unpredictable, often challenging conventional methods of measurement. Traditional business metrics, heavily reliant on past performance, are insufficient for gauging future potential. Recognizing the unique challenges in measuring innovation outcomes, organizations must adopt a tailored assessment approach.

Five Key Dimensions of Innovation Measurement

Idea Generation: Evaluating the quantity and diversity of ideas generated.
Feasibility Assessment: Analyzing the technical and economic viability of ideas.
Development Efficiency: Monitoring the speed and cost-effectiveness of transforming ideas into products or services.
Market Impact: Measuring the uptake, market share, and customer satisfaction regarding the innovation.
Strategic Alignment: Ensuring innovations align with the long-term vision and goals of the organization.

Case Study 1: Tesla’s Electric Vehicle Revolution

Tesla exemplifies how transformative innovation can be methodically measured and interpreted to yield significant competitive advantages. At the heart of Tesla’s success is its rigorous approach to innovation management across various dimensions.

“Tesla’s focus was not just building faster cars but reimagining transportation itself.”

When Tesla embarked on its journey, the idea of electric vehicles (EVs) was met with skepticism. Yet, by leveraging an interlocking innovation strategy, Tesla was able to revolutionize the auto industry.

Key Measurements and Outcomes

Idea Generation: Tesla’s continuous emphasis on research and development, illustrated by its expansive patent portfolio, drove a stream of innovative ideas not just in vehicles but in energy solutions too.
Feasibility Assessment: The Gigafactory was fundamental to producing high-capacity batteries efficiently, rendering the idea of viable EVs more feasible.
Market Impact: As of recent years, Tesla dominates the electric vehicle market, achieving unprecedented valuations and market shares previously deemed unattainable for EVs.
Strategic Alignment: Every innovation, from the Roadster to the Cybertruck, aligns with the core mission of accelerating the world’s transition to sustainable energy.

Tesla’s structured approach to innovation allowed it to not only come up with groundbreaking ideas but also to meticulously track their progress toward strategic success.

Case Study 2: Starbucks’ Digital Transformation

Starbucks, a leader in retail coffee, faced the challenge of adapting to a digital age where customer engagement and convenience became paramount. The company’s innovation in digital engagement provides essential insights into measuring innovation outcomes.

“Transforming from a coffee company to a tech-enabled customer experience leader wasn’t just about the coffee; it was about the connection.”

Key Measurements and Outcomes

Idea Generation: Starbucks continuously invests in technology-centric solutions, driven by a dedicated tech innovation team exploring everything from AI to mobile payment systems.
Feasibility Assessment: A major move was the deployment of mobile order and pay systems after thorough feasibility studies assured integration with existing operations without disrupting service.
Development Efficiency: Swift deployment of these digital services was critical. This rapid rollout required strong cross-functional collaboration and efficient back-end processes.
Market Impact: The introduction of the Starbucks app significantly boosted customer engagement and sales, contributing to over $1 billion in mobile payment transactions in a single quarter.
Strategic Alignment: The innovations have consistently aligned with Starbucks’ strategy of enhancing customer convenience and personalization, reinforcing brand loyalty and market leadership.

Starbucks’ approach highlights the importance of aligning technological innovations with consumer expectations and long-term business strategy, ensuring that each innovation drives meaningful impact.

Conclusion: A Pathway to Impactful Innovation

These case studies illustrate that the key to transitioning from idea to impactful innovation lies in a structured and nuanced measurement strategy. Organizations must not only generate great ideas but also deploy tools and frameworks that evaluate and guide these innovations through various stages, aligning them with strategic imperatives. By focusing on the five dimensions of innovation measurement, businesses can demystify the process of innovation, ensuring its outcomes are both predictable and impactful.

As we journey into the future, the ability to measure innovation outcomes with precision will become a cornerstone of success, enabling companies to adapt, scale, and thrive in an ever-evolving landscape.

This article explores the complex process of measuring innovation outcomes through case studies of Tesla and Starbucks—two companies known for their transformative innovations. The article underscores the importance of a structured measurement approach that spans idea generation, feasibility assessment, development efficiency, market impact, and strategic alignment. The insights from these companies hope to inspire others to adopt comprehensive frameworks to transition from idea to impactful innovation.

Image credit: Pixabay

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Aligning Vision and Execution in Change Management

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Aligning Vision and Execution in Change Management

GUEST POST from Chateau G Pato

In the ever-evolving landscape of modern business, the ability to implement effective change management strategies stands as a crucial determinant of an organization’s success. At its core, change management is not just about overseeing transitions; it’s about crafting a vision for the future and ensuring that vision is executed in alignment with organizational goals. But alignment between vision and execution is easier said than done, requiring a meticulous blend of strategic foresight and operational ruthlessness. In this article, we explore how organizations can better align their vision and execution, using compelling case studies to illustrate key points.

The Importance of Alignment in Change Management

Imagine a symphony orchestra preparing for a performance without a conductor. Each musician may be skilled and dedicated, yet without someone to align individual performances, the result would be cacophonous rather than harmonious. Similarly, in organizations, an unaligned approach to change can lead to fragmented efforts, wasted resources, and unmet goals. Alignment ensures that every team member, resource, and process reflects the broader vision, fostering synergistic efforts toward common objectives.

Case Study 1: The Boeing 787 Dreamliner Project

Few change initiatives capture the imagination and exceed complexity like Boeing’s development of the 787 Dreamliner. The bold vision was to create an aircraft that would revolutionize air travel through unprecedented fuel efficiency and passenger comfort. However, the execution proved challenging and serves as a seminal example of the pitfalls of misalignment.

Initially, Boeing’s vision for the 787 was ambitious; they sought to integrate cutting-edge technology and materials, such as composite materials, at a scale never before attempted. The intention was to set new standards and transform the industry. However, execution faltered due to over-reliance on a global network of suppliers combined with the insufficient coordination and oversight mechanisms. Misalignment occurred because the vision did not translate effectively into the operational plans needed for execution. Substantial delays and cost overruns ensued, culminating in the project’s delay by three years and a multi-billion-dollar budget overrun.

The key takeaway from Boeing’s experience is the critical need for effective synchronization between strategic vision and operational execution. To achieve success, organizations must not only define an inspiring vision but also establish a practical roadmap to carry it out. This requires clear communication of roles, expectations, and timelines so that all stakeholders work cohesively towards the shared vision.

Case Study 2: Kotter’s Change Model at Google

Contrast Boeing’s struggles with Google’s relatively smooth adoption of Kotter’s change management model during the rollout of its internal Work-from-Anywhere (WFA) policy. In response to employee feedback and the changing dynamics of workplace flexibility post-pandemic, Google implemented a new telecommuting structure that adhered closely to an established change framework for seamless results.

Google began by communicating a strong vision—a future where work would cater more closely to the individual needs of employees while optimizing productivity. This vision was aligned from the top down, with Google’s leaders embodying the principles being communicated. Execution hinged upon methodical adherence to Kotter’s Change Management principles, including creating the urgency, forming a guiding coalition, and generating early wins to maintain momentum.

By leveraging these principles, Google ensured that all layers of management were engaged and empowered to drive change. Monitoring progress was integral; Google utilized both quantitative KPIs and qualitative employee feedback to iteratively refine and reinforce its approach. The result was a successful shift towards a flexible work model, with minimal disruption and positive employee feedback.

Strategies for Successful Alignment

Reflecting on both successes and setbacks, several strategies emerge for aligning vision and execution:

Clear Communication: Articulate the strategic vision in a way that resonates with every employee from the top levels of management to front-line workers. Use storytelling to connect emotionally with stakeholders.
Empowerment and Engagement: Ensure every team is empowered to make decisions within their domain, fostering a sense of ownership and accountability.
Agility and Adaptation: Build mechanisms for feedback and learning into your change process, allowing you to pivot swiftly when seniors identify mis-alignments or changing conditions.
Technology Leverage: Use technological solutions for tracking, coordinating, and reporting progress in real-time, providing visibility across all levels of the organization.
Leader Involvement: Ensure leaders are both champions of the vision and active participants in its execution, modeling the behaviors and mindsets desired.

Conclusion

Aligning vision and execution is not a one-time task but an ongoing, iterative process that requires diligence, communication, and genuine commitment from all organizational levels. As organizations navigate the complexities of the digital age, those that master this alignment will not just survive but thrive, setting new benchmarks in their industries. The case studies of Boeing and Google illustrate that while the road may be riddled with challenges, transformative success is achievable when vision and execution walk hand in hand.

Image credit: Pixabay

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Creating the World’s Best Change & Transformation Book

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The Perfect Change & Transformation Book On Friday I was speaking with my publisher Palgrave Macmillan (now part of Springer) about doing a second edition of Charting Change.

This means that my publisher is interested in having me create a new version of Charting Change that would include most, if not all, of the content contained in the first edition, while also adding thousands of words of new insights (plus new pictures and tools).

This causes me to ask you the following questions:

What human-centered change and transformation topics are missing from Charting Change?

What information would the perfect change & transformation book contain?

What tools do change management professionals and transformation leaders need to enjoy greater success in their jobs, projects, and programs?

Toolkit subscribers – which of my new tools should I highlight in the second edition that I didn’t introduce in the first edition?

Who do you think has something compelling to add to the conversation in an additional guest expert section in the book? And what is the topic you want to hear from them on?

Charting Change introduced my Human-Centered Change™ methodology and a suite of 50+ tools available for purchase (book buyers get access to 26 of the 50+ tools). That toolkit has since grown to a collection of 70+ tools available to toolkit subscribers.

Thank you so much to everyone who has supported the first edition thus far and also to my Human-Centered Change™ Toolkit subscribers.

I’m interested to hear in the comments below your thoughts on the questions above!
(or send me an email)

If you don’t already have a first edition copy of Charting Change, you can get one here:

https://www.amazon.com/dp/1137536950/
(support my sharing of free Human-Centered Change & Innovation tools and insights)

And don’t forget to download your Free Human-Centered Change Tools!

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