Monday, April 08, 2019

What I'ved learned so far about digital transformation and innovation

Lately I've been drinking from the firehose.  It seems every day there are new reports on digital transformation and innovation.  My good friend and collaborator Paul Hobcraft is constantly reviewing new reports and creating insights of his own, which inundate me with more information.

At the same time I've had the honor of chairing the Innovate Carolina conference, where the theme considered the interplay of innovation and digital transformation, and I'm teaching a class at NC State on digital transformation and innovation.  Well, teaching may be a strong word.  I have had the good fortune to attract a number of excellent speakers, from RIoT, IBM, RTI, NC State and others who know more about these emerging technologies than I could possibly know.

But through this I've learned a bit about both innovation and digital transformation.  Below I'm going to share a few things I've learned so far, and my sense of the implications.

Learnings so far:

  1. Innovation and digital transformation both impact efficiency; only innovation is about creating dramatically new stuff (so far).
    Most new technologies are first deployed to reduce costs or improve efficiencies.  In this way they demonstrate a rapid return on investment, so it's not surprising that many digital transformation initiatives are initially focused on efficiency gains and cost improvements.  So far digital transformation hasn't really addressed the question of transformative innovation - that is, innovating beyond the core.  I think there is great potential for digital transformation, especially big data and predictive analytics, to create new insights that lead to new innovations, but that seems to be still a few years away.
  2. Innovation and digital transformation both impact customer experience.
    Increasingly the focus within innovation is around design, human centered design and customer experience.  This focus is increasing because we need to provide more value to core products and because many innovations aren't centered around products but services and experiences.  It's interesting that a significant number of benefits from digital transformation are also focused on customer experience, whether this is based on smart bots on websites or more predictive data flow in an interaction.  Perhaps one of the best places for these two management philosophies to work together is in customer experience.
  3. Digital transformation is widely discussed, but not widely distributed (stealing from William Gibson).
    Digital transformation is a category term, embracing and encompassing a number of technologies, strategies and other factors.  The fact that the pace of change and adoption of the underlying technologies is different won't surprise you, but the gulf between the different technologies and their practical applications is rather large.  Machine Learning is being applied everywhere, and IoT is just a new way of saying "sensors".  There are billions of sensors already deployed across the globe.  However, blockchain is still in its infancy and few companies have a compelling use case for artificial intelligence.  Robotics are already widely deployed in factories and will become more so in service operations and human facing operations relatively quickly, but autonomous vehicles are still some distance away due to acceptance, regulations and insurance concerns.
  4. Few are prepared to manage all the data that will soon be generated.
    As more "digital transformation" occurs, as more sensors are deployed, more data gathered about people and their product usage, as more products produce more data about usage, far more data will be generated and stored.  Few companies are in a position to capitalize and use all that data efficiently, and those that do will have a major head start and gain so much more knowledge and experience that they will leave other competitors in the dust.
  5. Digital transformation (and all of its requisite technologies and implementations) may crowd out innovation.
    Digital transformation is not a blanket concept but a category of technologies that will be implemented, including IoT, Big Data, AI/ML, robotics, autonomous vehicles, blockchain, and their enablers - 5G, ubiquitous connectivity, cloud computing.  There are many technologies and many implementations in order to gain benefit.  My sense is that these technologies and their promise may overwhelm many companies and detract from innovation work, because a technology implementation (such as a project to implement more machine learning capability) has a definitive outcome and may quickly demonstrate benefits from cost cutting, whereas most innovation activities are somewhat risky and may or may not demonstrate value.  I continue to believe that innovation is on tenuous ground while this new phenomenon of digital transformation is paramount.
  6. In the end, it's just business and mostly about people.
    Our closing speaker at Innovate Carolina, Bermon Painter, said it best.  All of this, whether it's digital transformation or innovation, are just ways of doing business, and eventually all of this should be centered around people - customers, people in our company and in our value chain.  Does any of the technology get in the way or create frustrations for people anywhere in the value chain?  Do our innovations improve lives and create seamless interactions, or the opposite?  Whether it is new or old technology, new or old products, it is the people who ultimately matter.  Is that where your focus lies?
I'm interested in where all of this goes next, and how the interplay between digital transformation and innovation unfold.  Regardless of how it unfolds it will be an interesting ride.

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posted by Jeffrey Phillips at 7:22 AM 0 comments

Thursday, April 04, 2019

Why taking your best shot is all wrong in innovation

I was speaking with a prospective client recently and was dismayed to hear them talk about innovation in a manner that seems to suggest innovation is a "one and done" activity.  Then a good friend introduced me to the book Loonshots, which I haven't read, but did listen to a podcast about.  I'm not here to review Loonshots, but I do want to debunk the idea of innovation and its connotation to "shots" of any kind.

We use this kind of language all the time - "take your best shot".  We use this language in our personal lives and in our business lives.  This phrase is often used in a setting where the speaker is uncertain about his or her ability to do something, will attempt it anyway, but goes into the activity with some fatalism.  My concern is when we use this kind of thinking when we innovate.

Best Shots

When you innovate, you are often doing something new and unusual, that many times may not achieve the goals or expectations you hope for.  Further, you may be working on innovation without the proper training or skills, and with less than a full complement of resources.  This is why many people talk about giving innovation their "best shot".

In no other important business activity would we use such fatalistic language, have such a negative expectation and work in such a one off way.  In no other business process would we approach a problem with such poor definition and preparation.  Yet innovation is more important than ever, but we still approach it as if it's a one time, unusual proposition that we'll give our best (but probably inadequate) effort to, with little expectation of success.

Just read the phrase to yourself:  Give it your best shot.

The phrase even signals things that I believe are fallacies about innovation, that by repeating we allow to become reality.


First is the word "shot".  This is one reason I have discomfort with the "Loonshots" book.  In the podcast I listened to the publishers talked about Kennedy's plan to put a man on the moon.  This was a "Loonshot".  But NASA never envisioned only going once.  The idea behind innovation is not that it is an occasional "shot", but a constant, sustained effort, composed of small, incremental changes and larger, transformative or disruptive activities.  The phrase "give it your best shot" comes from (as best as I can tell) the 1700s and refers to shooting at a target, in a day when a musket could only be fired once, then slowly reloaded. Thus everything depended on the one shot.

This thinking should be almost heretical to us.  Innovation, especially in a corporate setting, requires a lot of "shots", simultaneously, and consistently.  Unlike marksmen, who have a stationary target and lots of shooting practice, most innovators are aiming at an uncertain future and have little experience.  We need to help innovators understand how to improve their understanding of the future (research, trend spotting, scenario planning) and how to become more proficient at innovation methods and tools, but we also need to bake in the idea that more innovation should be done more often, more consistently and with different goals or outcomes in mind.


Another word I hate in the phrase "give it your best shot" is the word best.  How can we give something our "best shot" when we are 1) uncertain of the framing, scope or goals 2) unpracticed in the methods and tools 3) unsupported in the work and 4) working against cultures and corporate norms that push back against change?  Why must we make innovation a competition against everything the company does and reinforces, rather than make innovation something the company accepts and embraces, and prepares people to do?  Why enter this vital work with fatalism rather than with confidence?

So, when we repeat this phrase:  Give it your best shot, we are invoking the idea that an activity that used to be performed by experienced marksmen with plenty of experience and good conditions is now an activity performed with little experience or practice, in imperfect and often contradictory conditions, and only done once, and often with a sense of impending failure before we even start.

Sounds like a recipe for success, no?

What I'd prefer we think about

Rather, what I'd prefer is that we give teams the skills and tools they need to do innovation more effectively, preparing them for the work.  We should give them a sense that one innovation project isn't the end all or be all of the innovation work - there are persistent innovation activities working on both incremental and disruptive change constantly - the idea that we are taking many shots.  Further we should reduce risk and uncertainty by clarifying the conditions in which they work (changing the corporate culture), improving the field in which they work (better insights, better sense of future conditions) and in improving the confidence they have about the work.

If someone tells you to take your best shot at innovation, here's what you can say in return:

My best shot is actually a series of shots, and my success rate will be radically improved with training on innovation tools and methods, proper definition of the expected goals and outcomes, better understanding of the future market conditions and familiarity with customer needs, and working within a corporate culture that reinforces the work I do rather than resists it.

Don't be a solitary marksman.  Be the army.  Come in full force and bend the organization to your will.  Take many shots, at many different targets, all the time.  Send your best people to bootcamp to get them the skills they need to succeed.
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posted by Jeffrey Phillips at 5:19 AM 0 comments

Wednesday, March 20, 2019

Innovating when everything is "as a service"

I've been talking with a number of people who are more connected and smarter than me about digital transformation.  I've become convinced that the myriad and sundry tools and methods around digital transformation - cloud, ubiquitous high speed internet, IoT, AI, machine learning, robotics, augmented reality and all the rest - are going to create a major transformation in how consumers acquire and use products and services in the future, but more importantly how corporations and startups recognize value from their products and services.

This realization hit me when I was watching a short video recently where the speaker talked about how everything would be "as a service".  We are already familiar with this concept, in that many things we used to acquire and own are increasingly provided as a service.  In the not to distant future we could experience transportation as a service rather than purchase our own cars, or, my dream, lawn mowers as a service, where a trusted partner leaves a fully maintained and fueled mower at your doorstep just as you need it and picks it up the next day.

This transition into an "as a service" world changes the ownership model, the customer experience model and the revenue model, all at the same time.  What the "as a service" model doesn't fully contemplate, however, is the importance and value of data.  After all, does a mower really create interesting data that can be harvested?  Some products, like Alexa, create interesting data about the searches people conduct.  That data is valuable to create predictive analytics or to personalize offers. Where possible, we also need to consider how an existing or future product - no matter how "smart" or dumb the product is - will create data or use data - and what the data will mean as part of the value proposition.

What's all of this have to do with innovating?

In the past, we thought of disruptive new products, and occasionally thought about disrupting a channel or business model.  If the analysis above is anywhere near correct, the emerging digital transformation will require innovation on a completely different scale.  The product will simply be the kernal of a much broader offering, and the product may be something the company is more than willing to provide for free, in exchange for deeper understanding and ability to manage the data generated around the product.  This exchange of value, while it seems simple, is actually really complex in reality.

I led a small software firm years ago during the transition from installed software to "as a service".  The impact of moving from a large, one time software sale, where we'd make hundreds of thousands of dollars, to a recurring monthly retainer that required years to make the same amount of money, meant we had to radically rework our operating and revenue models, or change businesses.  We chose the latter.  And in this analysis we aren't even considering the volumes of data that can and will come streaming out of many offerings, and the complexities of managing that data and using it to create new insights.

When we innovate in the future, we need to understand exactly what the value proposition for each offer is to the customer, and to the ecosystem, and to the company making the offer.  Where does each benefit?  How does the company make money?  Where does all the data go and who owns it?  What business model supports the interaction successfully?  In other words, Doblin's Ten Types are no longer discrete options, no longer an either/or proposition, but become a framework where you may consider all of the "types" for each innovation, and add a few more, to include value for data as an example.

We're not ready but we need to be

Few large companies are doing basic product innovation well, but they are light years ahead of those that aren't really innovating at all.  A visible and relatively rapid moving tidal wave is emerging as digital transformation takes root and we create more IoT, more AI, more ubiquitous wireless broadband, more cloud storage and so on.  These things won't be siloed for long, and as they combine into a true digital transformation they open up entirely new operating models.

If companies have struggled to innovate a basic product, what will happen when innovation requires thinking through new operating models, new revenue models and new business models and channels?  The opportunities are much, much larger but will most likely accrue to those that move decisively and quickly, and the doorways to those opportunities will also close quickly.

Where is IT in this?

I asked a question to many companies about this topic in a recent event.  I asked - if your innovation opportunity creates opportunities for collecting and managing data, and gaining value from that data - who on your team could support that?  Most suggested that it would be the responsibility of their internal IT team - not the product team, not the innovation team, not the people doing digital transformation - and then went on to say that their companies simply couldn't manage the data effectively. 

It's not an internal IT team's job to think through how data generated from a new product may impact revenue and how to collect and manage that data.  But right now in most corporations NO ONE is thinking about this, and they should be.  If you though innovating a new stand alone product is difficult, wait until you try to create a new solution that is based on a product that generates or collects data and shifts a business model.  New companies can do this because they've got little infrastructure to resist it.  Established companies will need to become uber agile and able to change quickly, something most are not able to do.

The rising tide is visible from shore, but few large firms are doing enough.  They are working on the fringes of innovation and implementing some digital transformation tools without considering how these combine to create new business model and operating model opportunities.  By the time they discover just how much change is possible, it may be too late.
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posted by Jeffrey Phillips at 7:08 AM 0 comments

Thursday, March 14, 2019

I'm running for the presidency of Innovation

I thought - why not?  Everyone else is running, so why be left out in the cold?  If the governor of Washington State can run on the single plank of climate change, if senators who have barely introduced themselves to their colleagues can run, if a west Texas Irishman named Beto can consider running, then so can I.  Of course my candidacy will be strictly tongue in cheek, and really meant to frame a more interesting question - where does innovation stand in all of this?

What's my platform?

If I'm going to make an imaginary run for president, it will be on the basis of innovation.  If I become president I'm going to find ways to make it easier for the government to innovate how it operates.  I'm going to find ways to improve our patent and trademark office to accelerate good patents and slow down or eliminate defensive patents.  I'm going to find ways to help all of our government agencies and programs innovate, to both cut costs and to improve services and customer experience.

But beyond that, I'm going to look to innovate how we provide government services, how we delegate responsibility, how we speed up the delivery of services.  For example, our response to Puerto Rico in the last hurricane.  The response was slow, and inadequate, but came on top of a large response in Houston and the challenge of getting supplies to an island.  But we should look at how we can innovate the delivery of services, because one major catastrophe or one difficult delivery point shouldn't become a barrier to an innovative agency.  And this promise goes beyond FEMA to all agencies and government activities.  We need to rethink how the government is structured, and how services are delivered.

Beyond government

Beyond government my administration will do more to encourage innovation in corporations.  That's not just with more R&D tax breaks, but with more cajoling of the executives to start putting innovation resources and funding behind their innovation promises.  We are in a fight for our competitive lives as global market changes occur (as China becomes larger and the EU disintegrates), as new technology shifts (digital transformation) and as the nature of work and where people work changes (increases in automation, decreases in traditional starter jobs).

In the past the government was a big investor in new R&D, leading to specialized software and hardware that eventually had commercial use.  That model is reaching the tipping point - if it hasn't already - where the government is increasingly familiar with taking on COTS products and using them.  We need a new space race, a new digital transformation focus, a new innovation focus to get people bought in to the need for more innovation, more frequently and more consistently.

As your innovation president, I promise to work harder to make the government more innovative, to innovate how we legislate and especially how we budget and deliver services.  Just as importantly, I promise to put pressure on our leading corporations to do more innovation, and to do all I can to encourage startups.  As part of this I propose giving a green card to any person graduating with a masters or PhD in a science or technology field, who will stay and create a business.

We need to find ways to remove risk and uncertainty where possible, and create new sources of venture capital and risk capital to help smaller businesses get started.  We don't necessarily need more unicorns, but more viable companies that create interesting and innovative products and services.

What more could a president do?

Beyond a few of these activities and investments, perhaps the most important thing I could do as president for innovation is constant reinforcement.  Many presidents - both in government and in the private sector - have an innovation summit or a short focus on innovation and then declare victory.  My goal will be to keep innovation in the forefront, in multiple communications, in multiple cabinet meetings and in regular communications to the population.

This is why I mentioned above the new space race, the new burning platform.  We need to talk about innovation and why it matters, but more importantly what it will achieve or help us overcome.  Innovation is simply a tool to help us accomplish new things.  We need to do a better job creating focus on what innovation should be focused on and how it helps government, the private sector, our states and communities and so forth, to demonstrate that innovation is helping achieve measurable outcomes and goals.  As your president, I will appoint a cabinet level member to define our new moon shot and keep innovation at the top of my agenda.

Just as the space race energized a whole generation of scientists, engineers and innovators, we need a new rallying cry, to improve how the government innovates and how corporations and startups commit more energy and effort to innovation.  As your president, this will be my overriding focus.  Do I have your vote?

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posted by Jeffrey Phillips at 1:00 PM 0 comments

Wednesday, February 27, 2019

Where speed, innovation, technology and strategy collide

An old saying, often attributed to a Chinese philosopher, goes something like this:  may you live in interesting times.  Some people say that it isn't a "saying" so much as a subtle curse.  Interesting times - interesting to whom?  Interesting why?  I think we are all about to find out what interesting times look like, because those times are about to unfold, and no one can really interpret the repercussions.

Major shifts on the horizon

Why are times about to become more interesting?  There are a number of reasons, many of which I've listed in the title of the post.  Currently we have national and global economic tension, the rise of nationalism, large trading communities breaking apart (Brexit) and trade tensions between large trading partners - the US and China for example.  Old trading patterns and rules of engagement may be re-evaluated or may change entirely.  Digital transformation - a "third wave" of information technology that creates an entirely new way to capture real time data and perhaps make sense of that data on the fly, could radically change how businesses operate, how they make money and how they interact with customers, consumers and suppliers.  We aren't quite certain yet how IoT, Blockchain, cryptocurrencies, artificial intelligence, robotics and other technologies will change things.  All we can say for certain is that these technologies and the digital transformation they create will change things.

While these shifts are underway, other forces are at work.  The pace of change - a common refrain in my writing - seems to only accelerate.  Large companies, built over centuries, are brought low overnight.  Small companies formed in spare bedrooms in a very short period of time have the same valuation as large hospitality chains in operation for decades.  In a digital, asset-light or asset-less model, companies can scale exceptionally quickly, and larger firms with decades of development seem somewhat stuck with their legacy investments.  Data is becoming a new currency, more meaningful than the products we acquire or services we use.  As more people gain access to the internet and gain more education and more experience interacting and creating connections, more data is created and more interactions and business is transacted, leading to more interesting data and more connections - thus more value for the companies managing and tracking that data.

Impact on strategy and innovation

What does this mean for two concepts near and dear to my heart - strategy and innovation?  If strategy is a "plan of action designed to achieve a major aim" then what should our strategies look like as we encounter a competitive environment with little stability and a significant amount of change?  What should our "major aims" be?  I doubt Zuckerberg ever dreamed he'd have control of so much data, and that the data would be so valuable, when he set out to create a "facebook" of college classmates on line.  The Facebook of today wasn't his original strategy, any more than the Google of today was what Page and Brin where thinking when they started a search engine.

But businesses need clarity in their strategy in order to direct resources, to align people to key opportunities, to operate at peak efficiency.  We will need new strategy, and maybe even new strategic tools in order to operate under these new conditions. 

And where there is strategy, there should be innovation, and the reverse is almost always equally true.  Innovation is simply a method of achieving some portions of strategy - typically focused on growth or differentiation, or entry into new markets or segments.  Not everything that is strategic must be executed through innovation, and not all innovation is strategy.  Innovation should have an important place in the pantheon of strategic tools and methods, and when strategy is difficult or unclear, innovation becomes even more difficult to define and achieve.

What's next?

Thus it is with some concern that I look at the confluence of increasing speed, digital transformation, global trade unrest, increasing customer demands and think:  what are the new strategies that allow businesses to compete successfully in an environment with so much change and uncertainty?  If businesses cannot create reasonable strategic plans, then how can they effectively create new innovation programs and activities?

This lament is focused primarily on large corporations, which have deep experience and legacy investments.  There was probably never a better time to be an entrepreneur or startup, a company with one compelling innovative idea, because with new digital tools and technologies and ready access to large markets, we'll see more startups grow quickly and scale to compete with larger corporations, constantly slicing off valuable customer segments or markets or geographies much faster than ever before.  We may arrive at the juncture where large corporations request more oversight and protection from their regulators and government officials, just to make it more difficult for entrepreneurs to enter and compete.  Patriotism, after all, is the last refuge of a scoundrel, according to Samuel Johnson.  Increased oversight and regulation will sustain larger firms that cannot move quickly but will to some extent stymie innovation.  But not for long.  In some instances services will spring up that consumers demand, ahead of regulations - look no further than the regulations trying to catch up with electric scooters or AirBnb.

The reality is, we are going to need new strategic thinking, and new strategic models, to face all of the change that is about to unfold in the next 10-20 years.  It's entirely possible that
  • many jobs will disappear, with humans replaced by robots.
  • new trading partnerships will form, old ones disappear
  • new energy sources shift the focus of global economies
  • green thinking shifts where we place emphasis and resources
  • digital transformation shifts how we build companies
  • national and international politics and power shift dramatically
We'll need strategies that envision the future, that enable more speed, flexibility and agility in the business model and structure, and that work at the same speed, if not greater speed, than changes in the customer base and the market.  We'll need new tools and methods to understand what is going on and put it into context.  We'll need to get much closer to customers and consumers, engaged with them as we aren't today.  We'll need to rethink how we innovate - it could be that all we do is innovate, given how short product cycles are likely to be in the future.

We will definitely live in interesting times, very soon if not already.  How we as strategists and innovators begin to understand these times and create tools and frameworks to help companies understand and act much more proactively is going to matter a lot.
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posted by Jeffrey Phillips at 5:52 AM 0 comments

Wednesday, February 20, 2019

Beware conventional wisdom in innovation and digital transformation

One of my favorite quotes comes from Shaw, who said that all change in life originate from unreasonable people.  Reasonable people, he said, will accept the status quo and change their lives to adapt to the status quo.  Unreasonable people won't.  Unreasonable people force change rather than accept the status quo.  So, he argued, all change is dependent on unreasonable people. 

So it's interesting to me to read a completely reasonable list of "things to do" before implementing AI or any of the new digital transformation toolkit and think:  that's absolutely correct in theory and likely 100% wrong.  I thought that when I read the article entitled 3 Steps to Gear up for AI and the future of work.  The advice is meaningful and probably useful, conveyed thousands of times about new technologies or new approaches.  It advocates:
  1. Determine a Use Case for the new technology or approach
  2. Train people to be more proficient users of the new technology
  3. Start small - find small successes
This advice was true for the following list of management concepts:
  • ERP
  • Lean
  • Agile
  • Six Sigma
  • Doing business on the internet
 and I suspect many, many more.  It's not that conventional wisdom is wrong, it's just that there may be situations where the conventional wisdom may not be correct.

For innovation and digital transformation, perhaps we should be a bit more unreasonable.

Digital Transformation

First, we've skipped a step.  We need to define what digital transformation is, or what we think it is.  I'll define it as the implementation of a number of technologies (like AI, machine learning, blockchain, IoT, robotics, big data and so on) which transforms business processes and strategies.  Since each technology has a multitude of potential use cases, from generating new products and services to increasing revenue to cutting costs, we should be more circumspect about what the value proposition and use case is.  And, since most new technologies enter the mainstream market by creating greater efficiencies, perhaps we should more accurately ask:  what significant customer need can it address, or what significant inefficiency or cost can it remove? Further, how important or significant should the need or opportunity be?

They don't call it digital incrementalization.  They call it digital transformation.   The same is true for innovation.  We need to be thinking bigger.  The time to conduct small experiments around the fringe is over.  We need to use approaches and tools like digital transformation and innovation to solve important and urgent efficiency and cost needs, or to resolve major customer needs.  There's your "use case".

And yes, I've combined my response to the "use case" point and the "start small" point into one lengthy paragraph.  If by now your company cannot use innovation or digital transformation to do some big things, to create interesting new products or business models, or to radically transform the customer experience, the end is near.  The time for starting small was 5-10 years ago while innovation and digital transformation were still relatively new.  You cannot compete with other firms that are doing much larger or bolder experiments because the cycles of learning and implementation are collapsing.

John Boyd said it best in his OODA loop (Orient-Observe-Decide-Act).  If a competitor can progress through this loop faster than you can, you are a target, not an adversary. Starting small, experimenting and then scaling up is valuable when the technologies or capabilities are still new.  When everyone is doing them, it's time to make bigger bets.  Corporations need to be more agile, yes, and experiment, yes, but also must be able to scale quickly and implement quickly.


The article also advocates training.  There are several concerns I have with training, on new technologies such as AI or blockchain, or on innovation tools and methods.  While it always sounds appropriate to invest in training your people on tools and methods you need them to use, too often training isn't valuable or worse, it is wasted.  There are a couple of reasons for this.

First, training is the first corporate expense to get cut in lean times.  While deep, formal training is often valuable, it is also often hard to schedule and hard to justify. Training is never "top of mind" for people who are implementing technology, and is often difficult to acquire and schedule for those who should be using the new technology.

Second, training is often wasted in innovation work because we train people on innovation tools or methods but send them back to do their regular jobs.  If you want innovation training to be valuable, you need to train people on tools and methods they use immediately after the training.  Otherwise, don't bother, because the regular work cadence will soon cause them to ignore or forget anything new they've learned if they don't use it.

Third, training for digital transformation tools is also a bit difficult, because you first have to identify which method or tool you'll implement, what problem or need you are trying to solve, and how the method or tool creates insights or data or simplifies a process to solve the problem.  In many cases digital transformation may simply remove people from an activity, so the training they may need is training in a completely new role.  Other training requirements include the ability to implement the new technology - but it's probably better to hire this work rather than train people for it, and to be able to understand and assess the information that the digital tools create.  It's probably this last idea that is most useful, but also most contextual.  The insights that each digital technology provides and how the data is interpreted will be different in case by case basis.  It will require people with excellent data interpretation and contextual skills to interpret well.

What instead?

What if the right answers for innovation and digital transformation - at least at this point in history - aren't start small, train users and identify use cases - but instead the new conventional wisdom should be:
  1. Address wicked problems head on with the goal of completely solving them, focusing either on radical cost reduction or dramatic improvements in customer experience
  2. Think differently about training, in 3 dimensions:  buy the experience you need rather than train for it (technology), train people to understand the information presented by new tools and methods, prepare to train people for new jobs and roles once their existing jobs are eliminated
  3. Start big and go bigger - the pace of change doesn't allow small, continuous experiments when technologies and capabilities are relatively mature.  Go big or stay home.
Perhaps the answer is to be unreasonable, to aim for the stars, rather than to settle for low earth orbit.

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posted by Jeffrey Phillips at 10:43 AM 0 comments

Monday, February 18, 2019

Why digital transformation will drive business model innovation

As a follow up to my previous post about the intersection of digital transformation and innovation, I wanted to conduct a thought experiment to illustrate why the real impact of all the impending change from digital transformation and innovation will be business model related.  While the implementation of new technologies is interesting and challenging, and creating new products and services is daunting, at least you can still do that primarily if not exclusively in your existing business model.  What happens when the business model is no longer viable?

Using GM as an example

To illustrate this point let's consider General Motors, or for that matter any car company.  These companies are the bedrock of the manufacturing prowess of the United States and other developed economies, and create jobs for the core company and for a long tail supply chain.  Does digital transformation and innovation have any potential impact on their business?  You be the judge.

Shift in car acquisition

If consumer tastes change and if autonomous vehicles (which are just specialized robots) become a more compelling offering, consumers will likely view transportation as a service.  Rather than acquire cars as assets with high prices and rapid depreciation, and ongoing maintenance, consumers are more likely to simply acquire rides.  Uber and Lyft are simply the transition point, where we use other people's cars to get rides.  As this movement gains steam, and autonomous vehicles gain traction, it's increasingly likely that individuals don't acquire cars, they pay for transportation or miles traveled.

This means that 1) the number of cars purchased is likely to fall, because the existing cars are used more efficiently and 2) individuals and families acquire fewer cars.  In this case the dealer network increasingly becomes obsolescent, and sales of new cars move to fleet sales.


If sales move from individual buyers to fleets, financing models change.  Most car companies make a profit from both the sales of the vehicle and also financing a loan.  If fewer individuals acquire car loans, financing profits fall.  If large corporations offer transportation services, the financing may simply be transferred to larger organizations, but those larger organizations will demand lower interest rates, making financing less profitable.  Thus the large automotive companies may take another hit from losing some financing margin.

Shifts in branding?

If you don't actually drive the car, do you care about its performance?  Most of us don't really take advantage of the zero-60 acceleration or tight suspensions of some higher end luxury cars anyway.  As the car becomes an automated commodity, how does BMW and Mercedes differentiate its autonomous vehicle from Kia or Hyundai?  The real battle will be on interior options and luxury on one hand, and utility and carrying capacity on the other hand.  How companies differentiate their cars and their companies will have to change.

 Supply Chain

During all of this transition to autonomous vehicles or ride services, digital transformation is also changing the supply chain.  Blockchain and IoT provide greater oversight into where components are made and sourced, and big data helps identify cost issues, leading to more pressure on the supply chain.  New technology entering the car to manage issues like lidar, steering, acceleration and so forth introduce new supply chain members which provide far more value than the traditional supply chain members.  Older members of the supply chain providing simpler components feel increasing pressure to automate and cut costs, while newer members bring far more technology savvy and agility.  The supply chain will be under increasing pressure to reduce costs while increasing technology and flexibility.

All the while artificial intelligence and machine learning are providing insights into consumer behavior and usage and identifying issues within the supply chain and the manufacturing process.  This means constant updates to how car parts and cars themselves are designed, manufactured and assembled.  Production lines are constantly reconfigured to adjust to new insights from AI and ML, which conflicts with older union work rules. 

What happens?

In the end GM and other car manufacturers may need to be able to survive selling fewer cars to a much smaller buying public made up mostly of corporations offering rides as a service.  They will differentiate through lower service costs and may lose much of their branding as autonomous vehicles become a white good, branded by the service provider.  The car companies will have to survive with lower profits from financing and flat to slowly decreasing sales.  The dealer network may become obsolete, and with enough 3-D printing and CAD modeling even the after market for car parts may become less attractive.

While this is a radical departure from GM's model today it is not that alarmist. Many of these conditions are already apparent and emerging or will occur shortly.  Digital Transformation, ubiquitous connectivity, the capacity to store, process and manage large data volumes and consumers shifting desires are already having an impact.  And this is just for the car companies.  We haven't even scratched the surface of the secondary and tertiary markets for fueling, insurance, driver's education, taxis and many other transportation issues.

Everything resolves at the business model.  GM can make money in any of these scenarios, but the business models for the way they operate today, and the way they may need to operate in the near future are exceptionally different.  Want to know why Ford and GM are getting out of the sedan business?  So they can make enough money on their trucks and SUVs to put a down payment on the dramatic changes that are necessary for them to survive.

Whether we are talking about digital transformation or innovation, everything resolves to the business model.  We need better tools and new ways of thinking about how the business model can and will evolve, and how to shift from the existing business model to the required new business models before these shifts occur.

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posted by Jeffrey Phillips at 8:04 AM 0 comments