Category Archives: Digital Transformation

Why Are Transformations So Hard to Manage?

Why Are Transformations So Hard to Manage?

GUEST POST from Drs. Dean Anderson and Linda Ackerman Anderson

Knowing which type of change your organization is undergoing is critical to your success. Three types exist, and each requires different change strategies, plans and degrees of employee engagement. A very common reason for failure in transformational change is leaders inadvertently using approaches that do not fit the type of change they are leading. Is this happening in your organization?

The three types of change occurring in organizations today are:

  1. Developmental
  2. Transitional
  3. Transformational

Traditional project management and change management effectively support developmental and transitional change, but they are woefully insufficient for transformational change. You will need to understand the type of change you are in to know whether typical project or change management approaches can work for you.

Developmental Change

Developmental change is the simplest type of change: it improves what you are currently doing rather than creates something new. Improving existing skills, processes, methods, performance standards, or conditions can all be developmental changes. Specific examples include increasing sales or quality, interpersonal communication training, simple work process improvements, team development, and problem-solving efforts.

Transitional Change

Transitional change replaces “what is” with something completely new. This requires designing and implementing a “new state.” The organization simultaneously must dismantle and emotionally let go of the old way of operating while the new state is being put into place. This “transitional” phase can be project managed and effectively supported with traditional change management tools. Examples include reorganizations, simple mergers or acquisitions, creation of new products or services that replace old ones, and IT implementations that do not radically impact people’s work or require a significant shift in culture or behavior to be effective.

Two variables define transitional change: (1) you can determine your destination in detail before you begin, and can, therefore, “manage” your transition, and (2) people are largely impacted only at the levels of skills and actions, not the more personal levels of mindset, behavior and culture.

Transformational Change

Transformation, however, is far more challenging for two distinct reasons. First, the future state is unknown when you begin, and is determined through trial and error as new information is gathered. This makes it impossible to “manage” transformation with pre-determined, time-bound and linear project plans. You can have an over-arching change strategy, but the actual change process literally must “emerge” as you go. This means that your executives, managers and frontline workers alike must operate in the unknown—that scary, unpredictable place where stress skyrockets and emotions run high.

Second, the future state is so radically different than the current state that the people and culture must change to implement it successfully. New mindsets and behaviors are required. In fact, often leaders and workers must shift their worldviews to even invent the required new future, let alone operate it effectively.

Without these “inner” shifts of mindset and culture, the “external” implementation of new structures, systems, processes or technology do not produce their intended ROI. For example, many large IT implementations fail because they require a mindset and culture change that does not occur, i.e., the new systems require people to share information across strongly held boundaries or put the needs of the enterprise over their own turf agendas. Without these radical changes in attitude and behavior, people do not use the technology as designed and the change fails to deliver its ROI.

Implications for the Workforce

Because transformation impacts people so personally, you must get them involved in it to garner their support; and the earlier in the process of formulating your transformation strategy the better! Employee resistance is always in direct proportion to the degree to which people are kept in the dark and out of the change process. Here are some options for employee engagement.

Get staff engaged in building your case for change and determining the vision for the new state. Consider using large group meeting technologies, which can involve hundreds of people simultaneously in short periods of time.

Consider putting a wider representation of people on your change leadership team. Provide mindset, behavior, and change skill development to all employees. Use employee groups to identify your customers’ requirements for your transformation, and to benchmark what “best-in-class” organizations are doing in your industry. Ask employee groups to input to enterprise-wide changes that impact them, and give them the authority to design the local changes for improving their work (they know it best.) Then before implementation, get them involved in doing an impact analysis of your design to ensure that it is feasible and won’t overwhelm your organization beyond what it can handle.

When you engage your employees in these ways before implementation, you minimize resistance. Use such strategies to support your change efforts, especially if they are transformational.

Image credit: Pixabay

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

Top 10 Human-Centered Change & Innovation Articles of July 2022Drum 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 July’s ten most popular innovation posts:

  1. What Latest Research Reveals About Innovation Management Software — by Jesse Nieminen
  2. Top Five Reasons Customers Don’t Return — by Shep Hyken
  3. Five Myths That Kill Change and Transformation — by Greg Satell
  4. How the Customer in 9C Saved Continental Airlines from Bankruptcy — by Howard Tiersky
  5. Changing Your Innovator’s DNA — by Arlen Meyers, M.D.
  6. Why Stupid Questions Are Important to Innovation — by Greg Satell
  7. We Must Rethink the Future of Technology — by Greg Satell
  8. Creating Employee Connection Innovations in the HR, People & Culture Space — by Chris Rollins
  9. Sickcare AI Field Notes — by Arlen Meyers, M.D.
  10. Cultivate Innovation by Managing with Empathy — by Douglas Ferguson

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

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:

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

What will it take to create a national medical records system?

What will it take to create a national medical records system?

GUEST POST from Arlen Meyers, M.D.

Almost every person that has experienced the US sickcare system has been frustrated by the lack of data interoperability. We are all paying the costs, now pegged at $4.1T. About $1T of the tab is waste.

Here is the case for data interoperability.

Larry Ellison, the CEO of Oracle, is the latest person who says he wants his company to fix that.

Like those that preceded him, he will face:

  1. Stakeholders that don’t play nice with each other
  2. An enormous cost
  3. Trying to create a VAST business model
  4. Inconsistent technical standards
  5. Competition
  6. The lack of a national patient unique identifier system
  7. Privacy and confidentiality issues
  8. A highly regulated system for patients sharing their data
  9. End user resistance to dissemination and implementation
  10. Cybersecurity
  11. Connecting the kaleidoscope of the disparate elements of the US sickcare system of systems, like the VA, safety net hospitals, rural hospitals, academic centers and DOD facilities
  12. Combining financial data with clinical data
  13. Combining research data with clinical care data
  14. Varying levels of data maturity in the system
  15. Accessing data that is created outside of traditional medical service facilities
  16. The growth of retail sickcare and sicktech companies
  17. Harnessing data from the internet of medical things
  18. Integrating artificial intelligence to not only achieve the quintuple aim, but also create shareholder value that will conflict with one another
  19. Winning the “cloud wars”
  20. The lack of trust and growing sickcare technoskepticism
  21. The Cerner VA implentation FUBAR halo effects.
  22. Changing the EMR “SHIT” -single most hated information technology- to a whole product solution
  23. Accessing unstructured data on social media sites
  24. Governance of the enterprise
  25. Regulatory oversight of software as a medical device and digital therapeutics
  26. Low levels of sickcare professional and patient data literacy
  27. Barriers to international data sharing in a era of pandemics and required rapid response
  28. Fax facts
  29. Push back from patients who want to be paid for their data
  30. Decentralized clinical trial data issues
  31. DEI
  32. Leaderpreneurship skills
  33. UI/UX Will he eliminate passwords?

Wouldn’t it be nice if Sickcare USA, Inc. could provide you with the same experience as your bank ATM system?

Is Larry really the smartest person or just in the wrong room?

Image Credit: Pixabay

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Five Myths That Kill Change and Transformation

Five Myths That Kill Change and Transformation

GUEST POST from Greg Satell

I first became interested in transformation in the fall of 2004. I was managing a leading news organization in Kyiv, Ukraine when the Orange Revolution broke out. It was an amazing thing to witness and experience. Seemingly overnight, a habitually dormant populace suddenly rose up and demanded change.

One of the things that struck me at the time is how no one really knew what was going on or what would happen next—not the journalists I spoke to in the newsroom every day, not the other business leaders and certainly not the political leaders. Anyone with any conventional form of power seemed to have completely lost their ability to shape events.

That’s what started me on my 15 year-long journey to understand how transformation works that led to my book, Cascades. What I found was that many traditional notions about change management are not only wrong, but they can also actually kill a transformational effort even before it really starts. Here are five myths that you need to avoid if you want to bring change about.

Myth #1: You Need to Get Off to a Fast Start

Traditionally, managers launching a new initiative have aimed to start big. They work to gain approval for a sizable budget as a sign of institutional commitment, recruit high-profile executives, arrange a big “kick-off” meeting and look to move fast, gain scale and generate some quick wins. All of this is designed to create a sense of urgency and inevitability.

That may work for a conventional project, but for something that’s truly transformational, it’s a sure path to failure. Starting off with a big bang will often provoke fear and resistance among those who aren’t yet on board. Real, lasting change always starts with small groups, loosely connected, united by a shared purpose.

A much more effective strategy is to start with a keystone change that represents a concrete and tangible goal, involves multiple stakeholders and paves the way for future change. That’s how you build credibility and momentum. While the impact of that early keystone change might be limited, a small, but meaningful, initiative can show what’s possible.

For example, when the global data giant Experian sought to transform itself into a cloud-based enterprise, it started with internal API’s that had limited effect on its business. Yet those early achievements spurred on a full digital transformation. In much the same way, when Wyeth Pharmaceuticals began its shift to lean manufacturing, it started with a single process at a single plant. That led toa 25% reduction of costs across the entire firm.

Myth #2: You Need to Demand Early Commitment

Another thing that leaders often do is demand early commitment to a transformational initiative. They point out a new direction and they want everybody to get on board—or else. Any lingering questions or doubts are considered to be tantamount to disloyalty and are not tolerated.

This is silly. If an initiative really is transformational, then by definition it’s very different than what the rank and file have come to accept. If people don’t have any questions or doubts, then that means they never really believed in the organization before the transformation. They were just keeping their heads down and playing along.

Rather than demanding commitment, smart transformation initiatives start out as voluntary. By allowing people to opt-in, you are much more likely to get people who are truly enthusiastic and want things to work. That will make things much easier than wasting a lot of time and energy trying to convince people that change is a good thing.

Smart, devoted people should have questions. Certainly, you wouldn’t want people to change direction on a dime and have absolutely no doubts. At least in the beginning, you want to allow people to self-select. That’s how you ensure that people are genuinely enthusiastic and engaged, rather than just playing lip service to the idea.

Myth #3: You Have to Have a Unique Value Proposition and Differentiate Yourself

Because traditional change management programs rely so much on persuasion, they tend to borrow a lot from marketing. So the first step they often take is to differentiate the change they seek from the status quo by formulating a unique value proposition. This is almost always a mistake.

It is difference that makes people uncomfortable with change in the first place, so presenting unfamiliar concepts is a sure way to heighten resistance. Rather than focusing on differentiation, what you want to do is present change in the context of shared values.

For example, many organizations today are trying to adopt agile development techniques. Unfortunately, evangelists often start by promoting the Agile Manifesto, because that’s what makes them passionate about the idea in the first place. Yet for people outside the Agile community, the Agile Manifesto can seem strange, or even threatening.

If you want to attract people to your cause, you need to focus on shared values to create a comfortable entry point. In the case of Agile development, while most people are unfamiliar with the concepts in the Agile Manifesto, everybody understands the value of better-quality projects done faster & cheaper. As Darrell Rigby and his co-authors explain in Doing Agile Right, Agile, at its core, is really about becoming a high-performance organization.

Myth #4: You Have to Engage Your Fiercest Critics

One of the things we’re most frequently asked about in our workshops is how to persuade those who are dead set against change. The underlying assumption is that if you can come up with the right communication strategy or rhetorical flourish, anybody can be convinced of anything. That’s clearly not the case. Nobody is that clever or charming.

The truth is that if an idea is important and has real potential for impact, there will always be people who will hate it and work to undermine it in ways that are dishonest, deceptive and underhanded. You will not convince them, and you shouldn’t even try. You will just be wasting time and energy.

What you can do, however, is listen. The arguments your opposition uses will clue you in to the shared values that can bring people over to your side. For example, for a long-time people who opposed LGBTQ rights emphasized that they were defending families. It is no accident that gay marriage, with its emphasis on committed relationships and raising happy families, became the vehicle to drive the movement forward.

In a similar vein, those who oppose diversity and inclusion initiatives often do so on the grounds of performance (while strongly proclaiming that they support fairness). Yet the vast preponderance of the evidence shows that diversity improves performance. By making that case, you are tapping in a value that even your opposition has highlighted as important.

Myth #5: Transformation Is Either Top-Down or Bottom-Up

There has been a long running debate about whether change should be top-down or bottom-up. Some say that true change can only take hold if it comes from the top and is pushed through the entire organization. Others argue that you must first get buy-in from the rank-and-file before any real change can take place.

That is a false choice. For any given idea or initiative, you are likely to find both support and resistance at every level of the organization. You don’t start a movement for change by specifying who belongs and who doesn’t, you need to go out and identify your Apostles wherever you can find them.

The truth is that transformation isn’t top-down or bottom-up but moves from side-to-side. Change never happens all at once and can’t simply be willed into existence. It can only take place when people truly internalize and embrace it. The best way to do that is to empower those who already believe in change to bring in those around them.

And that reveals what is probably the most important myth of all, that creating change takes special personal qualities. One of the things that amazed me in my research was how ordinary even legendary change leaders were at the beginning (as a young lawyer, Gandhi was too shy to speak up in court). What made them different is what they learned along the way.

Transformation is always a journey, never a particular destination. So, the most important thing you can do to bring change about is simply to get started. If not now, when? If not you, who?

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

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TODAY ONLY – Change Planning Toolkit – Fourth of July Special

TODAY ONLY - Change Planning Toolkit - Fourth of July SpecialHappy Fourth of July!

For all of my American friends in celebration of Independence Day, I have a special offer for you.

If you live in the United States of America, TODAY ONLY, if you purchase a copy of:

The Change Planning Toolkit from the Human-Centered Change methodology …

You can get one of the two following deals if you are one of the first ten (10) people to purchase the deal and ENTER A UNITED STATES MAILING ADDRESS:

OPTION ONE: Free copy of Charting Change (a $49.99 value) when you buy a $99.99 one-year Change Planning Toolkit license (a $1,200 value)

OPTION TWO: Save 40% and get a free copy of Charting Change (a $49.99 value) when you buy a $999.99 Change Planning Toolkit lifetime license (a $120,000 value) and use coupon code lifetime4th

Thank you to all of our servicemen and servicewomen for protecting our freedom, and to everyone else please keep your fingers and toes safe with any celebration fireworks, and …

Keep innovating!

We Must Rethink the Future of Technology

We Must Rethink the Future of Technology

GUEST POST from Greg Satell

The industrial revolution of the 18th century was a major turning point. Steam power, along with other advances in areas like machine tools and chemistry transformed industry from the work of craftsmen and physical labor to that of managing machines. For the first time in world history, living standards grew consistently.

Yet during the 20th century, all of that technology needed to be rethought. Steam engines gave way to electric motors and internal combustion engines. The green revolution and antibiotics transformed agriculture and medicine. In the latter part of the century digital technology created a new economy based on information.

Today, we are on the brink of a new era of innovation in which we will need to rethink technology once again. Much like a century ago, we are developing new, far more powerful technologies that will change how we organize work, identify problems and collaborate to solve them. We will have to change how we compete and even redefine prosperity itself.

The End of the Digital Revolution

Over the past few decades, digital technology has become almost synonymous with innovation. Every few years, a new generation of chips would come out that was better, faster and cheaper than the previous one. This opened up new possibilities that engineers and entrepreneurs could exploit to create new products that would disrupt entire industries.

Yet there are only so many transistors you can cram onto a silicon wafer and digital computing is nearing its theoretical limits. We have just a few generations of advancements left before the digital revolution grinds to a halt. There will be some clever workarounds to stretch the technology a bit further, but we’re basically at the end of the digital era.

That’s not necessarily a bad thing. In many ways, the digital revolution has been a huge disappointment. Except for a relatively brief period in the late nineties and early aughts, the rise of digital technology has been marked by diminished productivity growth and rising inequality. Studies have also shown that some technologies, such as social media, worsen mental health.

Perhaps even more importantly, the end of the digital era will usher in a new age of heterogeneous computing in which we apply different computing architectures to specific tasks. Some of these architectures will be digital, but others, such as quantum and neuromorphic computing, will not be.

The New Convergence

In the 90s, media convergence seemed like a futuristic concept. We consumed information through separate and distinct channels, such as print, radio and TV. The idea that all media would merge into one digital channel just felt unnatural. Many informed analysts at the time doubted that it would ever actually happen.

Yet today, we can use a single device to listen to music, watch videos, read articles and even publish our own documents. In fact, we do these things so naturally we rarely stop to think how strange the concept once seemed. The Millennial generation doesn’t even remember the earlier era of fragmented media.

Today, we’re entering a new age of convergence in which computation powers the physical, as well as the virtual world. We’re beginning to see massive revolutions in areas like materials science and synthetic biology that will reshape massive industries such as energy, healthcare and manufacturing.

The impact of this new convergence is likely to far surpass anything that happened during the digital revolution. The truth is that we still eat, wear and live in the physical world, so innovating with atoms is far more valuable than doing so with bits.

Rethinking Prosperity

It’s a strange anachronism that we still evaluate prosperity in terms of GDP. The measure, developed by Simon Kuznets in 1934, became widely adopted after the Bretton Woods Conference a decade later. It is basically a remnant of the industrial economy, but even back then Kuznets commented, “the welfare of a nation can scarcely be inferred from a measure of national income.”

To understand why GDP is problematic, think about a smartphone, which incorporates many technologies, such as a camera, a video player, a web browser a GPS navigator and more. Peter Diamandis has estimated that a typical smartphone today incorporates applications that were worth $900,000 when they were first introduced.

So, you can see the potential for smartphones to massively deflate GDP. First of all, the price of the smartphone itself, which is just a small fraction of what the technology in it would have once cost. Then there is the fact that we save fuel by not getting lost, rarely pay to get pictures developed and often watch media for free. All of this reduces GDP, but makes us better off.

There are better ways to measure prosperity. The UN has proposed a measure that incorporates 9 indicators, the OECD has developed an alternative approach that aggregates 11 metrics, UK Prime Minister David Cameron has promoted a well-being index and even the small city of Somerville, MA has a happiness project.

Yet still, we seem to prefer GDP because it’s simple, not because its accurate. If we continue to increase GDP, but our air and water are more polluted, our children less educated and less healthy and we face heightened levels of anxiety and depression, then what have we really gained?

Empowering Humans to Design Work for Machines

Today, we face enormous challenges. Climate change threatens to pose enormous costs on our children and grandchildren. Hyperpartisanship, in many ways driven by social media, has created social strife, legislative inertia and has helped fuel the rise of authoritarian populism. Income inequality, at its highest levels since the 1920s, threatens to rip shreds in the social fabric.

Research shows that there is an increasing divide between workers who perform routine tasks and those who perform non-routine tasks. Routine tasks are easily automated. Non-routine tasks are not, but can be greatly augmented by intelligent systems. It is through this augmentation that we can best create value in the new century.

The future will be built by humans collaborating with other humans to design work for machines. That is how we will create the advanced materials, the miracle cures and new sources of clean energy that will save the planet. Yet if we remain mired in an industrial mindset, we will find it difficult to harness the new technological convergence to solve the problems we need to.

To succeed in the 21st century, we need to rethink our economy and our technology and begin to ask better questions. How does a particular technology empower people to solve problems? How does it improve lives? In what ways does it need to be constrained to limit adverse effects through economic externalities?

As our technology becomes almost unimaginably powerful, these questions will only become more important. We have the power to shape the world we want to live in. Whether we have the will remains to be seen.

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

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

Top 10 Human-Centered Change & Innovation Articles of June 2022Drum 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. We also publish a weekly Top 5 as part of our FREE email newsletter. Did your favorite make the cut?

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

  1. An Innovation Action Plan for the New CTO — by Steve Blank
  2. The Lost Tribe of Medicine — by Arlen Meyers, M.D.
  3. What Can Leaders Do to Have More Innovative Teams? — by Diana Porumboiu
  4. Transformation Insights — by Bruce Fairley
  5. Selling To Generation Z – This is What They Want — by Shep Hyken
  6. It is Easier to Change People than to Change People — by Annette Franz
  7. Leading a Culture of Innovation from Any Seat — by Patricia Salamone
  8. Harnessing the Dragons of your Imagination for Innovation — by Braden Kelley
  9. Successful Asynchronous Collaboration — by Douglas Ferguson
  10. Four Reasons the Big Quit Exists — by Braden Kelley

BONUS – Here are five more strong articles published in May:

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:

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

Transformation Insights – Part Two

Transformation Insights - Part Two

“The world needs stories and characters that unite us rather than tear us apart.”~ Gale Anne Hurd, Producer of Aliens and The Terminator

GUEST POST from Bruce Fairley

In my early years I was fortunate to spend some time on film sets. Unlike how the entertainment industry is portrayed in the Netflix series, The Movies that Made Us, I did not come to blows with any of my directors as Eddie Murphy apparently did with John Landis during the making of Coming to America. Nor did I witness an entire crew mutiny, as James Cameron did on Aliens. Instead, I often saw the same dynamic I’ve witnessed in the tech sector from the first moment I stepped off set and into I.T.

People coming together.

Skilled, diverse, passionate people hard at work fighting against miscommunication, technical issues, and time constraints – coming together to achieve something significant. I referred to this in my previous Transformation Insights post, The Future Always Wins as:

Collaboration Between Complementary Influencers.

This dynamic is as true of a film set as it is of a firm engaged in digital transformation. In both cases, expertise in various areas is required to create a successful whole, with C-Suite leaders in the corporate sphere tasked with providing the articulated vision at the helm. Of course, the success of any endeavor comes down to human-powered action and decision making at every level of execution. And while the challenges of a digital transformation project may not be as bone-breaking dangerous as the stunts in an action film, getting to greatness requires a similar fusion of mind and machine – of talent and technology.

If that sounds like The Terminator, consider that its box office success speaks to the fusion of mind and machine as an unstoppable trajectory – but those who deepen their humanity rather than succumb to machine rule are the heroes that triumph. This was mirrored in the making of the film, which was nearly shut down when the crew put down their tools. Addressing their humanity and acknowledging the value of their contribution changed the story from disaster to blockbuster.

Humans lead – technology serves. Not the other way around.

When that is reversed, dystopia ensues whether on screen or in the boardroom. Having witnessed many occasions in which technology was expediently obtained before its value to the user could be established, I am convinced we have lost the plot in telling a wider, corporate story. Technology was supposed to liberate not enslave. Instead, how many times have you attended a Zoom meeting or prepared weeks for a presentation only to discover the sound not working, the slide deck freezing, or even a hidden ‘on’ button? These may be simple examples, but they rob the intrepid hero of the corporate journey; the chance to shine and advance their creative talent much like the crew of Aliens putting down their tools. Now multiply that by the large scale digital transformation projects I’ve spearheaded, and it becomes clear how a broken axis between human-powered decision making and technology can break the bottom line.

Optimism and momentum towards a more positive, successful outcome hinges on more than technological expertise. It requires an understanding of the whole story – and how the team, tech, leadership, and consumers each play a role. The story you wish to tell about your corporate journey requires buy-in at every level of service – human and tech. Obstacles are not indictments, they are merely obstacles. But they do often require a third-party complementary collaborator that understands how to transform pitfalls into profits.

When I launched the Narrative Group I wanted to amplify the genius of C-Suite executives through the optimization of the business-tech relationship. Similarly to how I observed the inner workings of a set and how all the pieces had to fit together to create a screen success, I spent years observing digital transformation from the inside. Across continents and boardrooms, I learned, led, and transformed as well. This only increased my commitment to helping talented leaders tell their story successfully.

If you’re a C-Suite leader that would like to storyboard the trajectory of your corporate success, please feel free to reach out and continue the conversation at:

connect@narrative-group.com

Image Credit: The Narrative Group

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An Innovation Action Plan for the New CTO

Finding and Growing Innovation Islands Inside a Large Company

An Innovation Action Plan for the New CTO

GUEST POST from Steve Blank

How does a newly hired Chief Technology Officer (CTO) find and grow the islands of innovation inside a large company?

How not to waste your first six months as a new CTO thinking you’re making progress when the status quo is working to keep you at bay?

I just had coffee with Anthony, a friend who was just hired as the Chief Technology Officer (CTO) of a large company (30,000+ people.) He previously cofounded several enterprise software startups, and his previous job was building a new innovation organization from scratch inside another large company. But this is the first time he was the CTO of a company this size.

Good News and Bad

His good news was that his new company provides essential services and regardless of how much they stumbled they were going to be in business for a long time. But the bad news was that the company wasn’t keeping up with new technologies and new competitors who were moving faster. And the fact that they were an essential service made the internal cultural obstacles for change and innovation that much harder.

We both laughed when he shared that the senior execs told him that all the existing processes and policies were working just fine. It was clear that at least two of the four divisions didn’t really want him there. Some groups think he’s going to muck with their empires. Some of the groups are dysfunctional. Some are, as he said, “world-class people and organizations for a world that no longer exists.”

So, the question we were pondering was, how do you quickly infiltrate a large, complex company of that size? How do you put wins on the board and get a coalition working? Perhaps by getting people to agree to common problems and strategies? And/or finding the existing organizational islands of innovation that were already delivering and help them scale?

The Journey Begins

In his first week the exec staff had pointed him to the existing corporate incubator. Anthony had long come to the same conclusion I had, that highly visible corporate incubators do a good job of shaping culture and getting great press, but most often their biggest products were demos that never get deployed to the field. Anthony concluded that the incubator in his new company was no exception. Successful organizations recognize that innovation isn’t a single activity (incubators, accelerators, hackathons); it is a strategically organized end-to-end process from idea to deployment.

In addition, he was already discovering that almost every division and function was building groups for innovation, incubation and technology scouting. Yet no one had a single road map for who was doing what across the enterprise. And more importantly it wasn’t clear which, if any, of those groups were actually continuously delivering products and services at high speed. His first job was to build a map of all those activities.

Innovation Heroes are Not Repeatable or Scalable

Over coffee Anthony offered that in a company this size he knew he would find “innovation heroes” – the individuals others in the company point to who single-handedly fought the system and got a new product, project or service delivered (see article here.) But if that was all his company had, his work was going to be much tougher than he thought, as innovation heroics as the sole source of deployment of new capabilities are a sign of a dysfunctional organization.

Anthony believed one of his roles as CTO was to:

  • Map and evaluate all the innovation, incubation and technology scouting activities
  • Help the company understand they need innovation and execution to occur simultaneously. (This is the concept of an ambidextrous organization (see this HBR article).)
  • Educate the company that innovation and execution have different processes, people, and culture. They need each other – and need to respect and depend on each other
  • Create an innovation pipeline – from problem to deployment – and get it adopted at scale

Anthony was hoping that somewhere three, four or five levels down the organization were the real centers of innovation, where existing departments/groups – not individuals – were already accelerating mission/delivering innovative products/services at high speed. His challenge was to find these islands of innovation and who was running them and understand if/how they:

  • Leveraged existing company competencies and assets
  • Understand if/how they co-opted/bypassed existing processes and procedures
  • Had a continuous customer discovery to create products that customers need and want
  • Figured out how to deliver with speed and urgency
  • And if they somehow had made this a repeatable process

If these groups existed, his job as CTO was to take their learning and:

  • Figure out what barriers the innovation groups were running into and help build innovation processes in parallel to those for execution
  • Use their work to create a common language and tools for innovation around rapid acceleration of existing mission and delivery
  • Make permanent delivering products and services at speed with a written innovation doctrine and policy
  • Instrument the process with metrics and diagnostics

Get Out of the Office

So, with another cup of coffee the question we were trying to answer was, how does a newly hired CTO find the real islands of innovation in a company his size?

A first place to start was with the innovation heroes/rebels. They often know where all the innovation bodies were buried. But Anthony’s insight was he needed to get out of his 8th floor office and spend time where his company’s products and services were being developed and delivered.

It was likely that most innovative groups were not simply talking about innovation, but were the ones who rapidly delivering innovative solutions to customer’s needs.

One Last Thing

As we were finishing my coffee Anthony said, “I’m going to let a few of the execs know I’m not out for turf because I only intend to be here for a few years.” I almost spit out the rest of my coffee. I asked how many years the division C-level staff has been at the company. “Some of them for decades” he replied. I pointed out that in a large organization saying you’re just “visiting” will set you up for failure, as the executives who have made the company their career will simply wait you out.

As he left, he looked at a bit more concerned than we started. “Looks like I have my work cut out for me.”

Lessons Learned

  1. Large companies often have divisions and functions with innovation, incubation and technology scouting all operating independently with no common language or tools
  2. Innovation heroics as the sole source of deployment of new capabilities are a sign of a dysfunctional organization
  3. Innovation isn’t a single activity (incubators, accelerators, hackathons); it is a strategically organized end-to-end process from idea to deployment
  4. Somewhere three, four or five levels down the organization are the real centers of innovation – accelerating mission/delivering innovative products/services at high speed
  5. The CTO’s job is to:
    • create a common process, language and tools for innovation
    • make them permanent with a written innovation doctrine and policy

  6. And don’t ever tell anyone you’re a “short timer”

This article originally appeared in Fast Company

Image credit: Unsplash

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Transforming Business Processes with Machine Learning

Transforming Business Processes with Machine Learning

GUEST POST from Chateau G Pato

In today’s rapidly evolving landscape, businesses depend on innovative solutions to remain competitive. One such transformative force is machine learning (ML), a subset of artificial intelligence (AI) that enables systems to learn and improve from experience without being explicitly programmed. By integrating machine learning into business processes, organizations can uncover insights, enhance decision making, and drive efficiencies. Let us delve into how machine learning is revolutionizing business operations through real-world examples.

Understanding Machine Learning

Machine learning algorithms build mathematical models based on sample data, known as training data, to make predictions or decisions without being explicitly programmed to perform the task. There are three primary types of machine learning:

  • Supervised learning: The model is trained on labeled data.
  • Unsupervised learning: The model works on unlabeled data to find hidden patterns.
  • Reinforcement learning: The model learns by receiving feedback from its environment.

Case Study 1: Optimizing Supply Chain Operations

Company: XYZ Manufacturing

XYZ Manufacturing, a global leader in consumer electronics, faced challenges with forecasting demand, managing inventory, and optimizing their supply chain. They turned to machine learning to address these issues.

By implementing supervised learning models, XYZ Manufacturing improved demand forecasting accuracy by 30%. These models analyzed historical sales data, market trends, and seasonality to predict future demand. As a result, the company reduced excess inventory and improved product availability.

Additionally, XYZ Manufacturing utilized unsupervised learning algorithms to optimize their logistics network. The algorithms identified patterns in transportation data, leading to more efficient routing that decreased shipping costs by 20% and reduced delivery times.

Case Study 2: Enhancing Customer Experience in Banking

Company: ABC Bank

ABC Bank, a leading financial institution, sought to improve its customer experience and service offerings. With the help of machine learning, they developed a personalized recommendation engine.

The bank utilized supervised learning to analyze customer transaction history, demographics, and preferences. This analysis enabled ABC Bank to offer tailor-made financial products and services to its customers, increasing cross-selling opportunities by 25% and enhancing customer satisfaction.

Furthermore, ABC Bank deployed reinforcement learning in its fraud detection systems. The model learned from various transaction patterns to detect anomalies and suspicious activities in real-time, reducing fraudulent transactions by 40%.

The Future of Machine Learning in Business

Machine learning is no longer a futuristic concept but a present-day reality driving substantial change across industries. As organizations continue to explore ML applications, we anticipate further advancements in process automation, intelligent decision-making, and personalized experiences.

However, it is crucial for leaders to adopt a human-centered approach when implementing machine learning. Ensuring transparency, addressing ethical considerations, and fostering continuous learning will empower businesses to harness the full potential of machine learning responsibly and sustainably.

Conclusion

Machine learning is transforming how businesses operate, creating opportunities to enhance efficiency, accuracy, and customer engagement. By learning from industry pioneers like XYZ Manufacturing and ABC Bank, organizations can navigate the complexities of machine learning adoption and unlock new avenues for growth and innovation.

As we embrace this technological revolution, let us remain committed to a vision where machine learning augments human creativity and intelligence, steering us toward a future brimming with possibilities.

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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