Innovation FOMO and FOMAD

Today, memes enter and leave the lexicon so quickly that I almost hesitate to use newly coined words or phrases, in fear that they may have already become passe.  So you can imagine my trepidation in using FOMO - the "fear of missing out" - when writing about innovation.  However, rather than simply expand on innovation FOMO, I'd like to introduce another, even more important issue - FOMAD.  This is one of my own creation, and one I'm certain will be rippling through Twitter and the other social media platforms shortly.

FOMAD

What is FOMAD?  In the innovation context, FOMAD is the "fear of making a decision".  There is a tremendous amount of FOMAD in many innovation activities, and I think FOMAD is perhaps one of the most significant roadblocks to innovation success.  Here's why.

FOMAD is a symptom

FOMAD is a symptom of a consistently recurring problem in innovation.  Innovation teams have too little information or context about corporate direction, strategy, funding mechanisms or risk tolerance to decide whether or not the ideas they've created are useful or meaningful.  After days, weeks or months of innovation activity, they are left with a handful of what appear to be good ideas.  However, lacking good strategic context or clearly defined problems or evident financial support, the fear of making a decision about one of the ideas rises.  When all options seem equally viable and the path to a decision is unclear, all options seem equally attractive.  Innovation teams struggle with the fear of making a decision.

This symptom can be easily addressed and clarified by better scope definition, executive support and expectation setting earlier in an innovation activity.

FOMAD is about tradeoffs

FOMAD is also a problem due to scare allocation of resources - people, time and money - to innovation activities.  While scarcity and constraints are good fuel for innovation, they often create FOMAD when it's time to decide which ideas to champion, or even which problems or opportunities should be addressed by innovation.  The problem is that lack of resources and uncertain processes make innovation more of a gambling activity than an insightful, practiced activity.  So teams are left with the question - which big bet should we make?  Making one selection often means that you cannot invest in other good ideas, so decision making is delayed because the tradeoffs are uncomfortable or unfortunate.

FOMAD indicates career concerns

Fear of making a decision is also generated when careers are made or lost on a big project.  Too many times corporations build up an innovation activity and place too much emphasis on any one project.  Then, when the pressure mounts, it can be difficult for teams to get behind a good idea, recognizing that all new and transformative ideas have risk.  Even the best ideas can fail for all sorts of reasons.  Who wants to be the team that ardently supported an idea that eventually failed?  Failure of this type in many companies is a career-limiting move, what we used to call in my Accenture days a CLM.  Ever notice how wishy-washy many innovation teams are when called on to make a definitive statement about the potential success of an idea?  They know they cannot guarantee that the idea will receive the investment it requires, that it will be developed and launched successfully.  Thus it can be hard to make a definitive decision and back that decision when they don't control the downstream activities, and while many companies talk about failure as a learning exercise, it is more often a question of losing credibility.

FOMAD in your business indicates some key issues

Every business doing innovation has some FOMAD, but I've defined at least three reasons FOMAD might exist, and in doing so indicated some ways to reduce or eliminate FOMAD.

First, create clarity, funding and good scope for your innovation activities.  FOMAD is often a symptom of poor project definition or lack of executive support.

Second, while scarcity is a reality, innovation often receives far too little funding and can feel more like gambling that a careful investment.  Ensure the teams have enough funding to make good choices and that not every idea feels like the throw of the dice.

Third, mean what you say about failure.  Who wants to back a good idea when they can't guarantee the outcome but may be held accountable for the "failure"?  Failures are learning exercises - often expensive ones to be sure - but should be treated as such.  If failure is a career limiting move, then you can expect that your teams will be unwilling to ardently back good ideas.

These three instances of FOMAD are addressable. The first instance is a question of executive involvement, choosing important and urgent challenges and defining scope effectively.  The second instance is a question of resources and funding, having reasonable expectations for what it costs to do innovation and the potential return of ideas.  The third is about the expectations and culture of the organization, how people are rewarded and recognized (or punished) for failure, when failure was likely.

If your innovation activities aren't delivering what you expect, check your FOMAD.  And contact me, because I can help reduce and eliminate FOMAD in your business.

Why being ambidextrous is not enough - looking ahead to 2020

It's about that time of year where we begin to look back, to think about what we've accomplished and what lies ahead.  Knowing that the end of the year is in sight, and the holidays are almost upon us, we anticipate work slowing down, and perhaps for just a few days we can actually think - really think - about what's going to happen in 2020.

I've had the good fortune over the last six weeks to reach out and talk to a significant number of my colleagues, friends and some new acquaintances in the innovation space. What I've been trying to find out is 1) what is happening in the innovation space currently and 2) what do people think the future opportunities for innovation are?  I have a number of ideas and thoughts that I'd like to share - by calling on these conversations and my own opinion and research.

The key question I keep coming back to is:  can you juggle three really different needs and initiatives simultaneously?  Because I think increasingly an efficient core, an innovative edge and a digital transformation will all be important.

The beginning of the end, or the end of the beginning?

For more years than I can count, people have been calling for the "end" of innovation.  As Churchill said in the dark years of World War II, this could be the beginning of the end, or the end of the beginning.  Of the people I've talked to over the last six weeks, a blend of innovation consultants, analysts and corporate practitioners, most feel that innovation as a concept is reaching maturity.  That is, many companies believe that the capability to innovate is becoming a commodity inside businesses.  I think most management teams believe they can accomplish incremental innovation in house, and they are happy with that result.  So the question becomes - will there be a sustained push for more innovation, and will there be a need for more external assistance?  I think there will remain a focus on innovation, but with different agendas and motives.  Incremental innovation will become a consistent focus, while transformative and disruptive innovation will be sporadic at best. 

A good friend, Drew Boyd, who is no slouch at innovation himself, suggested that innovation moves in cycles.  For some firms we may be in a cycle where management teams are seeking to harvest ideas from previous investments in innovation.  It could be that many companies are waiting to see the fruits of the investments in innovation over the past few years, hesitant to invest more before seeing some outcomes.  Innovation - in this definition meaning creating valuable new products and services to drive organic growth, revenue and new profits - will always be in demand, yet my sense and the sense of others is that innovation for many reasons hasn't lived up to expectations in many corporations.  This failure to meet expectations (we can argue if these expectations were reasonable or the activities fully resourced) plus the emergence of digital transformation lead to the sense that interest in core innovation may wane slightly in the new year.

Shiny Objects ahead

There are, however, a few shiny objects on the horizon and closing fast.  The lure of digital transformation, and the excitement over the Internet of Things, machine learning and so forth is tangible.  Most companies know that this digital wave is about to crash, and most if they are honest with themselves know they aren't prepared.  This new management phenomenon will pull attention and funding away from innovation and in many cases this may be the right investment.  As more and more data is generated, companies stand to lose revenue, share and brand image if they don't respond with better digital capabilities.

However, management bandwidth is limited, so increased focus on digital transformation can only mean lesser focus on innovation, or pushing innovation into the fabric of the operating model.  Since few companies have fully adopted innovation as an operating capability, this means that its likely fewer innovation projects will be started, and when they are started it will help innovation activities receive funding if they focus on smart and connected outcomes.

This points out the opportunity to merge innovation, the creation of new products and services, which seems a bit long in the tooth, with digital transformation, which is emerging but not yet solidified.  If we can find ways to create new, smart and connected products and services that leverage innovation skills and digital skills, I think this is a win-win for everyone. I'm a bit concerned that much of the digital transformation focus in placed on specific tools (machine learning as an example) and not enough focus is on solving actual problems (what should machine learning do and what benefit does that create?).

The split between incremental and disruptive innovation

As noted above, most companies believe that they can do incremental innovation - that is, successfully add a new feature to an existing product, and they are probably right.  However, this capability basically keeps the lights on - incremental innovation does not create new revenue streams or enhance profit margins.  To "move the needle" companies need an occasional transformative or disruptive innovation.  And in this recognition lie both opportunities and problems.

There are opportunities to generate transformative ideas within large companies.  The staff are familiar with customer needs and emerging opportunities, so generating transformative or disruptive ideas is not difficult.  But converting disruptive ideas into new products or services within an existing business is difficult, because existing processes and business models, as well as executives whose businesses would be impacted by a transformative idea will resist creating such a disruptive idea internally.  Developing and launching new, transformative ideas that may cannibalize existing products or radically change operating models threaten existing revenue and profits, which make converting disruptive ideas into new products or services difficult.

Increasingly this means that most companies are likely to hone their incremental innovation skills, which in reality are an extension of familiar activities combining lean, agile and Six Sigma, and I believe will partner with startups and external firms to create interesting or disruptive new ideas.  I expect to see even more accelerators, incubators, corporate venturing programs and other mostly external laboratories for transformative and disruptive work.

One to create, another to scale

The idea that external or near external accelerators and incubators will create and validate new, transformative ideas isn't necessarily new.  Some companies are working in this manner already.  I just think increasingly we'll see more risk shifted to external organizations to create and validate ideas, and at the right time larger corporations will then acquire the solution and scale.  After all, isn't that what larger corporations do best, launch ideas into a viable marketplace and scale the good ideas?

I remain hopeful and skeptical.  Hopeful because the underlying story seems to make sense, but skeptical that larger companies can successfully identify good ideas in the ecosystem, acquire them in a relatively timely fashion and then scale ideas that weren't developed in house and may conflict with existing operations or brands.  Technology-driven companies do this kind of work finding emerging technologies in the open market, and it can take months or years to validate and acquire a technology that is just a component to a larger product or solution.  Imagine trying to determine the value of a partially tested solution and acquiring it and scaling it.

The story works but the successes so far leave room for growth.

Transformation, of everything

Jim Carroll, one of the leading speakers on the future, has determined that his new focus should be on transformation.  Note that I am dropping the leading "digital" from that description, because of course we are going to be transforming businesses and operations with digital technologies.  Digital transformation almost goes without saying.  We've been doing that since the first ERP implementations 30 years ago.

What we should be talking about is simply transforming our businesses, from large, static, slow-moving, monolithic and unresponsive to agile, insightful, creative and responsive organizations.  This transformation is enabled by digital technology, but also requires rethinking how people are deployed and managed, where the focus of the business lies and how the business interacts with and relates to customers.  More decision making needs to be pushed further down the org chart, and the org chart itself needs to evolve.  We need faster decisions, made closer to the customer, and far more agility, speed and innovation to compete.  Larger, older companies built on older models have further to go than newer, more digital and agile companies, but even newer companies must transform.

And I wonder if transform is the right word, because it implies a one time change, from this to that.  However, given the pace of change and the number of new entrants and the increasing power of digital and the internet, how businesses work will continue to change.  So transformation may not be a one time activity but a constant evolution.

You'll need three hands

Many people talk about ambidextrous companies - those that can maintain an efficient, effective core while simultaneously innovating to create new products and services.  The real test will be whether or not these ambidextrous companies can do both well while simultaneously transforming to meet new market conditions and customer expectations.

Wrapping Up

What we are ultimately talking about is not just product innovation, and where it occurs (incremental innovation inside, disruptive innovation outside) but also service and business model innovation, with the focus turned inward.  How might we innovate and transform our businesses to make them more agile, more nimble, to operate more quickly and decisively?  Can we maintain existing operations AND constantly evolve?  If so, how?  This question invites innovation back into the company, but with a different flavor and focus.  Now, speed, agility and business model innovation become paramount, and innovation capabilities and tools will be turned not only to the creation of new products for consumers, but to create new operating models, new organizational structures and new revenue models.  If you outsource all of your best innovation thinking, can you then turn the innovation skills to evolve your business when it needs to transform?

Digital transformation is a component of transformation, in the same way that ERP, CRM and the internet made today's businesses more efficient and profitable.  New expectations will leave slow, monolithic companies in the dust, however, and merely tinkering with digital transformation without changing services, customer expectations and business models will create a company that is ever more efficient at doing things that fewer and fewer customers want.

The expectations just went up.  Customers expect high quality products and services delivered at low prices, which means efficiency.  However, they also want interesting new products and services that address formerly unmet or unserved needs.  This means innovation.  But just as important is the ability to connect these devices and services to other data streams to create more meaning, more experience and more information.  This is the power of digital.

These concepts are tightly linked, and your company increasingly must be good at doing all three, simultaneously if you are to compete effectively in the future.

Innovation - fast and slow, for the right reasons

For quite some time we've been hearing about how important it is to do things quickly, with many new adjectives placed in front of the word "innovation". These words include adjectives such as "lean", "agile" and "rapid", to make the point that innovation should be stripped to its bare components, move as fast as possible and create minimum viable solutions.  What has worked in more traditional settings - manufacturing, process improvement, etc - is now being applied to innovation.  And to some extent that's good - innovation can't afford to get bogged down in lots of red tape.  But we ought to ask ourselves when it is important and necessary to move quickly, and equally what factors cause work to move slowly.

When to move slowly

You'll be a bit surprised, I know, to find out that my first point is a bit contrarian.  That is, not everything in innovation should move quickly.  In fact I've often said and written that to move quickly you first need to move slowly, or at least move with good information.  Far too many innovation activities start with ideas and move quickly to create minimum viable products, but these activities lack good understanding of the emerging future and lack customer insights and needs.  Moving quickly without important context is just failing faster, and failing without appropriate learning.

There are not nearly enough people or resources dedicated to understanding the emerging future, or tapped to understand unmet or unarticulated needs.  If the previous sentence is true for your company, then moving quickly through these activities, skipping them because you already "know" what's going to happen or just ignoring them in order to move faster isn't helpful.  You can move quickly to do innovation work if you are constantly updating the context in which new ideas should be generated.  You should not move quickly if moving quickly simply means ignoring customer needs and emerging trends.

Why innovation efforts often move slowly (part 1)

Innovation work often moves slowly for a number of reasons, that in reality are easily addressed.  These include:

• Uncertain scope
• Assigning people who are unfamiliar with innovation methods and tools
• Assigning people on a part-time basis, or on top of their existing jobs
• Working on ideas that cross internal silos where processes or communications are lacking
• Lack of funding for innovation programs

These bullets are always true, and always slow down innovation work.  Innovation itself is not necessarily a slow activity, it is often slowed by factors beyond the control of the innovation team.  Address the factors around the innovation activity and innovation can move very quickly.

Why innovation efforts often move slowly (part 2)

But what really causes innovation to move slowly are factors like disruption and risk avoidance.  If your organization has a well-defined and reasonably profitable business model, how anxious will the leadership team be to see you generate a wholly new business model or a product that cannibalizes existing products or services?  Executives can't be faulted for asking for more validation, more data, more customer tests when existing, profitable products or business models are at stake.  Risk avoidance and current revenue are often more important than potential profitable products and services.  No amount of lean tools or agile methodology will change that.  Only management commitment and cultural change will address those issues.

When can you move fast?

You can move fast in innovation work when you:

• Have capable teams, trained in innovation work
• Have a clear project scope and anticipated deliverables
• Have the people and funding you need, and no more
• Have management flying air cover for your work and your ideas
• Have a good understanding of emerging trends and customer needs

These factors will accelerate your "front end" work - that is, getting from opportunity to requirements.  You'll also want to address a large gating factor - how to get new product and service ideas into a packed product development process.  Innovation may move quickly, but the clog in the system is often in a transition from really good, validated ideas moving to new product development projects.

A minimum viable product is just that, minimum and barely viable.  Finishing and scaling an MVP is what drives real revenue, which means a good idea needs to go through the front end relatively quickly, and go through product development and market launch in a timely fashion as well.  Understanding the entire process, from opportunity identification to market launch is what will ultimately make innovation faster.

Why context is more important than ideas

Everyone has ideas - they are like the air, everywhere and ubiquitous.  People who say they don't have any ideas are merely referring to their lack of ideas about a specific issue or in a specific setting.  Everyone has ideas, all the time.  What they often lack is context.  Few people understand the value and importance of context when creating new ideas.

What I mean by context is that there are plenty of challenges, problems and opportunities in the world that COULD be solved, but many of them aren't solved, even after the problems are clearly identified.  For example, we grow far more food than necessary to ensure everyone on the planet has enough to eat, but people still go hungry.  Most hunger is not a condition of a lack of food, but a lack of ability to distribute, or too much food in the wrong places, or political or cultural barriers for food.  So while there are many challenges that could be solved, there may be many issues that keep the issue from being solved.  And this is what good innovators should understand.

An idea is only as valuable as its defined context

What experienced and successful innovators know is that an idea is only as valuable as its context.  Understand the context, and you can create several different or even opposing ideas that may be valuable.  Start from an idea and you'll still need to define the appropriate context if one exists.  The good news is that everything I've written so far is true if you are a startup, trying to create a new company, or a corporate innovator trying to generate ideas to become part of a portfolio of products and services.

Approaching innovation like qualifying a sales prospect

Ideas, like sales processes, need to have appropriate qualifying criteria.  In the sales world, we believe we have a viable prospect when we identify someone who:
 - has a need
 - we can solve the need with existing products or services
 - the prospect has a budget
 - their need is creating pain that must be addressed quickly
 - the prospect has the ability and willingness to make a decision

These are common qualifying questions for a sales process, to understand if a potential prospect is a qualified sales candidate.  Prospects may show interest, but lack a budget or the ability to make a decision.  Qualified candidates demonstrate all of the factors listed above.  That does not mean that a specific offering will "win" because other alternatives may be in consideration, or other political factors may weigh on the decision.

Good innovators know that many of the same factors must exist for an idea to be successful.  If every idea were valuable, then innovation would be easy.  Since every idea must be placed into its appropriate context and evaluated, this means that far fewer ideas are actually interesting.

Getting the context right

So, when you have an idea, you must link the idea to:

• A demonstrated need or an emerging need that does not yet have a solution.
• In Blue Ocean Strategy, a hierarchy of needs is defined.  Unmet needs are needs that are recognized but not met yet.  Unarticulated needs are needs that will emerge, but customers simply don't know enough to try to address them.  The former are easier to serve, since they are often evident but overlooked.  The latter are more difficult because they require insight into future conditions.
• A need that is important to solve and that people want to solve
• There are plenty of needs or issues that people are simply willing to live with.  They are aware of the need but the urgency or importance of the need simply does not lead them to decide to make changes, or the effort to change to a new solution seems so daunting that they are willing to live with a little inconvenience in order to keep things the same.
•  An openness to risk and novelty
• Anytime you create a new solution, you ask consumers to work differently, act differently, purchase differently than they do today.  That means that the consumers you target must be open to new solution, some sense of risk and novelty.  This is true both for the customers or consumers of the idea, as well as the internal teams that must produce and provide the idea.
• Some ability to illustrate the potential valuable impact of the idea for the consumer
• Benefits are often hard to capture, and most ideas end up generating some but not all of the benefit they promise.  You must understand the expected benefit and be able to communicate that benefit to the potential consumer to understand an idea's value.
• Your company's ability to create a solution that addresses the need in the context of the customer or consumer.

So you can see that most organizations have it backwards.  They generate ideas that seem valuable and then fail to develop valuable products and services because they never took the time to determine the most valuable context.  You can work backwards from an idea to the appropriate context but few people do, and most ideas are shaped and influenced by a handful of people who had a specific context in mind.

What you should do is first get the context right - what needs exist?  Who have these needs?  Are they willing to address these needs or to change how they do things?  How much novelty will they endure?  What benefits are important to them?  If you understand this context, then you can shorten the time to generate good ideas, generate fewer ideas and enjoy more uptake of your best ideas.

All your data are belong to us

I'm riffing today on an old meme - "all your base are belong to us" - the poorly worded alert in a game that was released years ago.  The message was meant to inform the player that all of his or her bases were lost to the enemy.  The statement became a rather interesting theme in the gamer community, and was often seen on T-shirts back in the day.  Perhaps even today?

But what happens when all of your data belongs to someone else?  Doesn't Apple, Google, Facebook and many other firms already own a significant portion of your data, at least what you generate in your transactions through these platforms?  When you add up what data you are giving away for no cost to these social and online platforms, and combine it with what your credit card and financial service vendors know about you, and the amount of data you can obtain about anyone by scraping the internet, pretty soon it will be you who is receiving the notification that "all of your data belong to us".  It might not be surprising to have to pay for your data to be removed or made private.

The right of privacy that we give away

It's interesting to think about the rights we possess.  While not explicitly granted in the Constitution, a right to privacy has always been inferred, and valued by citizens in the United States.  What we are increasingly doing is giving up that right, in fact allowing ourselves to be fully known and our data and records easily obtainable, losing any control or power over the right to privacy.  Your data is increasingly a commodity that larger corporations use, sell and trade to each other to better target you with advertising, to make predictions about what you want or need, where you want to live, how you will vote or even what you want to eat.

The question becomes: does it matter if we sacrifice privacy for convenience?  Isn't the argument that giving up some privacy means we have more convenience, because Facebook, Google and others can customize our information and experiences based on what they know about us?  Certainly these services make our lives a bit easier, and provide more information at our fingertips that is more aligned to our needs and expectations.  But in this I think of an earlier warning, from one of our founding fathers.

Sacrificing privacy for convenience

Benjamin Franklin was confronted by other colonists who were willing to make compromises, willing to give up some freedoms for more security and predictability.  His response was that people who sacrifice liberty for security deserve neither.  In fact he was suggesting a slippery slope.  The more you get comfortable giving up a little liberty for security, the more comfortable security becomes, and you may be willing to give up more liberty for more security.

Likewise, if you give up a little privacy for low cost and convenience, you are more likely to give up all privacy for free goods and total convenience.  However, those "free" services come at a price - either limited, controlled information that the providers want you to see, or the sale of important data assets that by rights should be yours that you've traded away for more convenience.

Understanding the true cost of free services

What is the cost of giving away your data?  Initially, the tradeoff is simple.  At no cost to you, companies take or harvest data from you while you use their products or social media.  Google analyzes your search terms, Facebook analyzes your network and your commentary.  We give them this right by accepting their terms, in exchange for "free" services.  However, as more and more data is captured about you in more and more places, making connections between that data and learning more about you than you intended is relatively simple.  This is why so many ID protection firms are now able to sell us identity protection services.  From what I can see, the value of your privacy and peace of mind is something many people will pay Lifelock and other companies approximately $10/month.  But what happens as the people who have this data become more sophisticated?

The future is full of offers and recommendations

We are bombarded with offers, information and ads today based on relatively unsophisticated technology and fragmented communication channels.  As IoT, machine learning and ubiquitous connectivity emerge, we will enter a phase of mass customization in messaging and targeting unlike anything we've seen to date.  If you recall the movie Minority Report, in which the public display ads are configured and delivered directly to individuals, then you'll begin to understand what I mean.  The more we share information about ourselves, and the more that data is aggregated and analyzed, the more often and more targeted will be the attempts to communicate to us, influence us and sell us things that seem tailored to our needs.  In the not too distant future your devices, your kitchen appliances, your clock radio, even some of your consumables will all be smart and connected, and will all make offers and recommendations to you that are tailored to your needs, or at least what their producers believe are your needs.  If you think having one child following you around all day asking questions can be annoying, wait until many devices in every room, in your car, in retail establishments and public settings do this all the time.  What will your peace of mind and privacy be worth at that point?

Make no mistake, your data is valuable.  Data about what you do, what you buy, what your preferences are, how you will vote and many other factors about how you live, work and spend are valuable.  If you are going to trade them away, do so for real value, and understand the longer term implications.  While European citizens at least have the expectation of the "right to be forgotten" which is relatively dubious, we in the States have no such opportunity.  While Europeans may believe this right to be forgotten is powerful, in effect it means that a citizen must ask and confirm that every company that has their data legally must be contacted and must remove the offending data.  As long as one company has data, there are opportunities for it to proliferate again.  And that doesn't begin to consider those organizations that possess data illegally.

A couple of predictions

I think there will come a day, relatively soon, where people take back ownership of their data.  In fact we could see several things emerge.  First, a backlash against all of our data so widely shared and distributed, where the individual has little or no control of their data. GDPR is a first, but very watered down attempt at this. Second, an emerging opportunity for insurance to protect and defend our data and the record of our lives against people who would use our data for illegal or what we may consider illegitimate purposes. How will you feel when you are rejected by life or health insurance companies based on information they can collect and analyze about you before you apply? Third, an emerging standard where individuals complete a form that shares data that they themselves create, publish and maintain, and sell on to companies for a profit.  What better source of information about a person than the individual themselves, with an incentive to share more data based on the ability to rent or sell that data themselves?  What could emerge is a single, trusted source that allows people to post as much data about themselves as they wish to share, and for the individual to be responsible for policing and updating the data, so bigger companies can market to their exact wants and needs.

Then, most but not all of our data will belong to us, and individuals will gain more control over the development, publication and use of their data, and the financial benefits associated with the data.  I think we'll all be better served when more people understand the true value of their data, understand how much data is currently available about them and what companies can do with that data, and decide to take back the power to control their data themselves.

Data-driven or insights inspired?

As the phenomenon of digital transformation continues to unfold, we need to be wary of certain absolutes that will work their way into our language, our thinking and our consciousness.  It's common, especially in the early stages of any emerging trend for new ideas and new thinking to take on more meaning than is intended, and eventually to become accepted facts rather than the conjectures or ideas that they really are.  Later, the concepts or theories unfold, these ideas or concepts are demonstrated to be what they always were - early attempts to define or to provide context that provided some insight, but were not complete or holistic.  Such is the case with digital transformation today.

Data Driven

No phrase worries me more than what I hear repeated regularly as a mantra by our customers and prospects.  Everyone wants to be "data driven", which on the surface is an excellent idea.  If by "data driven" they mean making decisions based on data rather than conjecture or opinion, that's good.  If they mean allowing machines and processes to make decisions based on rules driven by high quality data, that's also good.  If they mean managing end to end processes that are highly connected and integrated and most of the work is done based on good data, rules and systems, so much the better.

But here's the thing:  data is for systems.  Data is not for people.  People need insights or knowledge derived from the data.  So if your business is going to be data driven, you are talking about a layer or two below the human element - stuff you can run automatically or in the dark.

Insights Inspired

I'd prefer to focus on being inspired by the insights from the data.  This is where humans add real value, in interpreting the data and obtaining insights or making discoveries based on information from the data.  We can be informed by these insights and even inspired to create or imagine new products, services and business models from insights gleaned from the data.  Our goal as business leaders should be that what can be automated and data driven should be, and we should turn our attention to interpreting the insights that come from the data and building new offerings, solving unmet needs and creating new channels, relationships and business models based on inspiration from what we can glean from the data.

The problem with data

Being data driven at an operational level will become a necessity, because most companies will want to eliminate inefficiencies and cut costs.  Replacing people with machines or automated processes will make a lot of sense if and when the data is right.  However, almost anyone involved in artificial intelligence and machine learning will tell you that the biggest challenges to using these tools effectively are:  1) enough data 2) of high enough quality and 3) with enough access to the data.

In other words, simply having data can't and won't make your organization a "data driven" company.  You need to focus on improving the data to provide higher quality data with greater consistency.  You need to have enough data for the machines to draw logical conclusions and define consistent rules.  You need to aggregate and provide access to data in order to make it usable.

Having a lot of data doesn't necessarily make it easier to be data driven, and the more sources and the larger the number of "types" of data make it even more difficult to normalize the data.  In fact it may be easier to become an insights inspired company rather than a data driven company, especially if you operate in a large legacy organization with a large number of IT systems which don't share data effectively.

The real point of this blog

So, violating all the rules of blog writing, I've left the "bottom line" statement till the end.  The real point of this blog is that being data driven is difficult but not impossible, but only a short term target and not really all that interesting.  Data driven companies will solve operational challenges - they'll optimize systems and cut costs through automation if their data is good and systems are integrated.  What we should be striving for is making better use of data by converting it into information which provides insights, which inspires companies to create new products, services and business models.  We ought to hope for, to aim for, using data in such a way that it impacts our strategic thinking, that the data inspires people to create new offers and new products.  Anything less is yet another attempt to improve efficiency and cut costs, and misses a huge opportunity for growth and differentiation.

Book Review: What about the Future? by Fred Phillips

I'm returning today to one of my favorite activities - a book review.  Good books are simply too rare, and good books about topics important to innovators are unfortunately even more rare.  However, I'm happy to say that I've just read a book about understanding the future that should be read by anyone interested in foresighting, forecasting or scenario planning.  If you are an innovator, or hope to create meaningful, viable products or services for customers, attempting to understand the future is vital to creating new products.

The book I'm reviewing today is entitled What about the Future?  It was written by Fred Phillips, who is a professor and also the editor of the journal Technological Forecasting and Societal Change.  In full disclosure Fred was also one of my favorite professors when I took his course on technology adoption at UT-Austin's MBA program.

The Book

Fred has written a book that I really liked, and to be honest I had a difficult time putting into a specific context.  It combines some rationale for examining the future, some discussion on different approaches for examining the future and several philosophical discussions about complexity and uncertainty.  It is a book that challenges your assumptions, provokes your thinking and provides some really excellent points about anticipating future change. 

In short, this is not a "how to" book, but a book that takes on the larger questions about what the future is, how uncertainty and complexity should influence our thinking and planning.  Ultimately I think Fred captures the purpose of the book in the statement from the introduction that reads "They need the skills for forming a fundamental perspective about the future".  And that's what this book seeks to provide.

Fred's approach

Fred lays out the book in an interesting sequence of chapters.  Early in the book he grounds the reader on concepts like risk and uncertainty.  He notes that while we are uncertain about the future we often are overly certain about the past, and provides illustrations why even the past is often a bit uncertain.

The middle chapters deal with why we might want to understand the future and the impacts to decision making and organizational structure if we have a better understanding of the future.

The closing chapters become a more philosophical discussion about the future and our ability to understand the future and, having reached conclusions about the future, the impact on business and public policy.

Fred brings a systematic way of thinking about the future, using many examples that will be familiar to those who conduct work in foresighting, forecasting or scenario planning.  He includes a number of charts, graphs and illustrations that help detail his approach and thinking.  His writing is crisp and his arguments are very incisive, so the text is easy to read yet thought provoking at the same time.

One of my favorite arguments he makes in the book is that "the purpose of forecasting is not to be right, but to be ready".  This is reminiscent of the adage that plans are nothing but planning is everything.  We can't possible get our predictions of the future exactly right, but we can exercise our understanding of potential futures to be ready as they occur.

Interesting ideas and arguments

A couple of ideas that Fred presents I found especially interesting include:

 - which is changing faster, technology or society?  The general response is that technology is changing faster than society, but Fred makes an argument that society is changing faster than technology.  He makes the argument that technology innovation is actually slowing, while factors like shared values are changing or disintegrating faster than ever.  What impact would a culture or society that's morphing faster than technology have?

 - Fred argues that the two most reliable ways to predict the future are demographics and the Kondratieff wave.  He makes the point that demographics is destiny, and by understanding demographic change we can anticipate other societal, technological and other demands. 

 - I was not familiar with Kondratieff but the ideas from this Russian economist make sense - they are based on cycles of economic expansion and lassitude.  Kondratieff projected 30 year cycles of increased innovation followed by 30 years of exploitation of the previous innovative period.  This idea of cycles of innovation and cycles of consumption make sense to me.

Other ideas

Later in the book Fred talks about the difficulty of imagining the future, using what he calls the Captain Cook problem - one of almost willful blindness.  He notes that the Tahitians failed to acknowledge or even recognize Cook's flotilla because they had become accustomed to identifying items on the ocean as flotsam, whales or canoes.  They could not see or understand what was directly in front of them because their mental models did not include an option for these new things.  Likewise, many people who want to understand the future may not recognize that aspects or artifacts of the future are already present.  Here we can borrow from William Gibson and note that the future is already here, just not widely distributed.

My favorite chapter

Chapter 11 is perhaps my favorite, because Fred provides a significant number of examples of trends that reach a tipping point, and thus move from potential change to accepted change.  He calls these "Crossovers" and the ideas behind the crossovers and what these crossovers tell us can help shape how we think about understanding the future in the future.  This chapter alone and the crossovers Fred documents are worth the price of the book.

Review and takeaway

This is an excellent book and should be read by a wide audience, especially those who have an interest in understanding how to approach the future.  Individuals in industry, government, public policy and other functions should have a better appreciation for the future and the interwoven aspects of complexity and uncertainty as Fred presents.

If I have concerns with the book it is because I am always seeking really definitive, practical tools and methods.  Fred hasn't written a "how to" book, he has written a "how to think about" book, and this gives the book a wider audience and a more philosophical bent than I expected.  If only more people in more companies and more positions of power in public policy and in government agencies spent more time thinking about and trying to understand the future, I think we'd all be far better off and far better prepared for what the future holds.

I'd highly recommend this book, not for the specific answers it provides but for the questions and thoughts it should provoke.

The music isn't in the piano

I was speaking with a long time colleague and trusted branding partner, Kevin Polonofsky from Revered recently about branding and marketing.  We were specifically discussing the idea of training people to do specific tasks that they did not have time to do, or had no passion to do.  One good example of this is innovation training.  In my work history I've done a lot of training for corporate clients on innovation methods and tools.  Many executives have asked that I train their teams, in order that the teams become more proficient at innovation.

Let me stop here and say that training, for people who have the focus and the passion to exercise the training, is exceptionally valuable.  On the other hand, training is sometimes used as a way to demonstrate that "we are doing something" but isn't intended to be put into practice, or executives don't quite know how to shape projects or opportunities that allow teams to put new learning into practice quickly.

As I was describing this phenomenon, Kevin said something I thought was profound, and I've paraphrased for the title of this blog post.  He said - "they think the music is in the piano".  When I asked him what he meant by that, he said that anyone can buy a piano but the piano does not create music.  It takes talent, training and commitment to make the music come out of the piano.  In the same way providing innovation training to teams that don't immediately start an innovation project, or who don't have the time or aren't compensated to do innovation work is pretty meaningless.

What's more, with the right training, practice and passion a good pianist can make many kinds of music from a piano, but the piano does not create the music.

Player Piano

Ah, but I can hear you say, some pianos don't need pianists.  And this is true.  Player pianos can create music without a piano player, but they are driven by a computer (today) or by a roll of paper that dictates which keys get pressed when, merely a recording of key strokes in the right order.  In the business world there is the equivalent of a player piano.  It's your existing processes and culture, which reinforce how work gets done, and ensures that for the most part work is done the same way every day and in every instance.  In fact we have perhaps the worst situation when we train internal teams on innovation.  They aren't especially interested in being pianists, and they know the piano they will be playing is already capable of playing only one song - the one it is programmed to play.

It's no wonder that many companies and teams struggle to innovate.  Most people have little time and little exposure to unmet needs, and and are so focused on getting the existing products out the door at the lowest possible cost that providing training for innovation seems almost superfluous.

Prodigies vs Practice

For some reason many businesses seem to think that their staff are prodigies when it comes to innovation.  That is, show them some innovation tools or methods at some point in their career and at their first attempt at innovation they'll create a masterpiece.  Innovation is far too unusual within an existing organization to be easy, and far too different to be completed effectively by people using tools for the first time without experience or practice.

So, this is where it all falls apart.  There are few innovation prodigies who are just naturally good at innovation, and unfortunately there are few companies where average people who aren't prodigies get to practice the tools and methods regularly.  So innovation is often attempted and rarely very successful because there are few prodigies and the rest of the people don't practice.

The best case is when people who have a passion for change and creativity are given the time they need, an opportunity or problem that challenges their thinking and the training on the tools that are necessary to do good innovation work.  In Kevin's metaphor about the piano, the music is innovation, and while the piano can make good music, it takes a prodigy or practice to bring it out.

Why I still get my Netflix movies in the mail

I'm a movie junkie - I love movies.  Old movies like Casablanca, or even new movies like John Wick 3.  Can't wait to see what John Wick can survive in the third installment.  I wore out a Blockbuster card back in the day when Blockbuster was a thing.  When I discovered Netflix, and its extensive catalog of movies, I was hooked.  Best thing about Netflix is they delivered to my mailbox.

Now, of course, Netflix and everyone else can stream movies to my TV, my laptop and my smartphone.  I even have a package (or at least AT&T says I do - they've never been able to get it to work) for HBO on my phone.  You might think with this plethora of offerings and choice I'd be a streaming guy on Netflix.  But you'd be wrong.

Why I love getting movies in the mail

I'm old school and admittedly so where movies are concerned.  My son, who is in his third year in engineering school, laughs every time I talk about my Netflix account.  Mostly I think because he can't piggy back and get downloads for free.  He could not believe we still get movies in the mail.  I thought about this fact for a while and like many things in life decided there was an innovation lesson in my approach.

It has to do with choice.  Netflix through the mail allows me to select and rank movies I'd like to watch, and I receive them one at a time. So I have unlimited choice in scheduling but exceptionally limited choice in the moment.  When it comes time to watch a movie in the evenings, we have exactly one choice.  Rather than turn to an almost unlimited selection of movies and content on the web or through a cable provider, I can say "well, I selected this one movie for a reason, so let's watch it".

For example, I've got A Clockwork Orange waiting for me at home.  If I were scanning through a long list of movies from my cable provider or from Netflix streaming, looking for movies to watch in the moment, I might think - I can always get A Clockwork Orange.  Too much opportunity and too much choice leads to difficult decision making and FOMO.  If I'm going to invest 2 hours in a movie I select on the fly it had better be good.  But when I have one choice in front of me, and one I've made from a long list of movies previously, then I'm usually happy with the selection.

Lessons for Innovators

There may be lessons here for innovators.  There is a psychological challenge known as choice overload or the paradox of choice.  This happens when people struggle to make decisions when offered too many choices.  I believe that many of our innovations fall prey choice overload, whether we are speaking of too many content choices online or too many features on a product.

Customers want to get a job done - in my case, enjoy an interesting and entertaining movie - without a lot of hassle or decision making.  When we introduce too many options and too much choice, we can provide what appears to be a greater benefit but may introduce confusion or anxiety - what if a better movie is available now?  Simply by creating a lot of content or features we create decision anxiety and increase FOMO, when a new product or service should reduce it.

There's another reason I love to get NetFlix in the mail.  My little red envelope is almost the only thing I get that isn't a bill or a flyer.  There's something almost gift-like about receiving the movie in the mail, and I think that's another lesson.  Increasingly we've lost the sense of wonder or experience with many of our products.  Apple used to strive for this, attempting to create a meaningful experience for customers when using its products, but I think they've jumped the shark lately.  What experience, emotion or unexpected gift does your product or service provide?

Do a job, simplify, create wonder

So, in closing, I'd say that innovators who create new products and services should always be asking the following questions, of themselves, their solutions and most importantly, their prospective customers:

1. Does what I'm creating help you accomplish your job to be done?
2. Does it do so in a way that reduces anxiety, stress or uncertainty?
3. Does it create a new customer experience that evokes wonder or heightened experience?
4. Will the product simplify my life and choices?

Perhaps I'm old-fashioned, but these are some of the reasons I still get my Netflix movies in the mail.

If it doesn't fit, it must be innovation

Years ago, Johnny Cochrane convinced a jury that OJ Simpson was not guilty of murdering Nichole Simpson.  While there were undoubtedly many factors that led to the acquittal, one of the biggest factors was the gloves.  When OJ tried on the gloves in the witness stand, the gloves did not seem to fit his hands.  Cochrane then uttered the famous line in his closing:  if the gloves do not fit you must acquit.

Whether you think that is a compelling line of reasoning for a jury trial or not, it might not be a bad way to think about innovation.  You see, many companies cannot adequately define innovation for their employees and teams.  Sure there are interesting definitions like "innovation is a new to the world idea" or "innovation is doing new things" but these are abstract concepts.  What employees need is clarity about what is "innovation" and more importantly, which innovations are useful and acceptable and are likely to get funded.  I think Cochrane's statement leads us to a potential solution.

Why do definitions matter?

Before we dive into how Cochrane's statement is very apropos for innovation, let me just digress to extol the importance of clear communication and innovation. When communication is good and definitions are clear, people can do good work.  When communications are poor or definitions are incomplete, people generally take one of three tacks:  1) they stop working until communications are clear or definitions improve, 2) they create their own definitions and start working or 3) they fall back on what they already know and trust.  All three outcomes as described here are bad for innovation:  two (the first and third) basically revert to the status quo.  The second has the innovation team dreaming up its own activities and defining its own outcomes.

When innovating, people need to know how much change to introduce, how much risk to assume, how much impact to create.  Without that information, everything is likely to be incremental.

Does it fit?

There are perhaps two types of innovation in the definition I'd like to propose.  Neither definition is "good' or "bad" but may be helpful when considering what innovation is and which innovations are useful.  What I've found over my 15 years of innovation consulting is that innovations either "fit" with how the company thinks and does business, or they don't.  Again, we aren't trying to ascertain the potential impact or market value of an idea, but trying to define which innovations will be accepted and funded.

This is almost the same as talking about incremental innovation and disruptive innovation, or "horizon one" innovation and "horizon 3" innovation.  Innovations that fit the existing operations, product lines and business models, that serve existing and adjacent customers will "fit" the business and are very likely to be accepted.  These are incremental innovations, small changes to existing products, services or ideas that won't cost much to develop and won't introduce a lot of risk.

It does not fit

Ideas that don't fit the existing product line structure, don't serve existing customers or don't fit within the existing business model do not fit and will often fail to attract internal investment.  That's because they introduce too much risk and change.  Ideas that require a new business model require working in a new way.  Ideas that require attracting new customers require new and potentially different marketing investments.  These ideas will occasionally rise in an innovation portfolio but will rarely receive internal approval.  Ideas like these are often pursued by startups or new entrants who have less to lose than incumbents.

Value Judgements

Neither incremental (those that fit) or disruptive (those that don't fit) ideas are necessarily good or bad.  The focus and impact will depend on the context and strategy in the moment.  The problem is that most, if not all ideas are expected to fit the existing operating model, and will therefore be incremental at best.  Ideas that don't fit aren't often welcomed and face a significant number of challenges.

A good innovation portfolio will include a significant number of both types of ideas - those that fit the model and those that don't.  Constantly ignoring ideas that don't fit your model simply cedes the emerging and interesting portions of your business to competitors or new entrants.

Instead of asking - "does it fit" we should, in fact we must ask fairly often - which ideas do we have that don't fit our operating model, and how many are we investing in.  

VUCA is a matter of perspective

VUCA is the new black.  Suddenly everyone has realized that sometimes the economy or markets are volatile or uncertain.  If I were older and cranky I'd blame this on the millennials, not because they are millennials but because they've never lived with a stock market that goes down.  Volatility seems like something we've only just discovered.  Not too many people seem to remember the stock market crash of 2008, but of course that was a decade ago.

VUCA is now getting tossed around like it is a new idea, which is NOT true. VUCA is, however, more relevant than ever to people who refuse to take the long view, or who refuse to prepare.  What is volatility or uncertainty after all, if you have a longer term view?  What appear to be massive swings in an economy or a market in the short term turn out to be small hills and valleys over a 20 or 30 year horizon.  There is of course the famous and perhaps misquoted statement by Zhou Enlai, the Chinese premier, who replied "too early to say" when asked about the impact of the French revolution.  Some people have suggested this is the sage advice of a people who take a long view, reflecting on the impact of the French revolution in the 1789.  Others note that he might have been referring to violence in France in 1968.  This quote has the benefit of being true and the added bonus of proving that ambiguity and uncertainty matter.

VUCA

VUCA, like many four letter acronyms, probably springs from military usage.  It stands for Volatile, Uncertain, Complex and Ambiguous.  A learned scholar would note that there's not a lot of difference between these words.  Many things that are volatile are also uncertain.  Uncertain and ambiguous are almost synonyms.  Many things that are complex can be uncertain or ambiguous.  VUCA is just a way of saying difficult to describe or understand.

We innovators and purveyors of future insight talk about VUCA like it's a problem.  Wouldn't it be nice if the world were predictable, stationary, completely certain.  The problem is that very few people want to live in a world with such predictability and stability.  We'd get bored fairly quickly I think, and those of us who like change would go absolutely crazy.  I think it's healthy for people to live in a VUCA world.  It only becomes a problem when the world becomes too uncertain, too volatile or too complex, and that measure is often in the eyes of the beholder.

Three ways to respond to VUCA

There are options to respond to a VUCA situation.  The first is to react to the volatility and change after the fact and complain about what a crazy, VUCA world we live in.  This is what most people do, simply react after the fact and complain about change, as if change isn't the norm.  Sorry to sound judgemental but this is the least interesting, least engaging response and one that places the blame on change that is already occurring.

The second option is to take a long view.  Notice that much change reverses itself or corrects over time.  I noticed just this week that jean shorts seem to be back in style, after being the butt of jokes (jorts anyone?) for years.  The market crashed in 2008 and reached the same point as the top of the market a few years later.  In this model we ignore the momentary blips and look for longer term, not reacting to every change.  This model relies on patience, past performance and slowly adapting to the markets and environments as necessary.  Call this the dollar-cost averaging approach.  If you don't know the reference, ask your broker.

The third option to address VUCA is to look ahead, examine trends and conduct foresighting or scenario planning.  The future, as we've been assured, is out there, and there is evidence of what is going to happen, many times long before it happens.  Uncertainty can be reduced by looking at the possible options and their likelihood of occurrence.  Volatility can be anticipated if we look forward and expect it.  Playing out various scenarios helps to illuminate what is likely to happen and what the requisite reactions will be from those who are simply reacting to the events.

VUCA is what happens to intellectually lazy people

Isn't VUCA just an excuse for "I was too busy or preoccupied or lazy to do a little investigation into what could happen?"  Maybe VUCA isn't an acronym but Latin for "didn't do enough planning".  Of course much of this diatribe is tongue firmly planted in cheek.  The world is more volatile and markets and economies are more uncertain than ever.

 But on the flip side we have more information and are more connected than ever.  Instead of being a victim of VUCA and acting like VUCA impacts are unpredictable and unavoidable, perhaps we should become more proactive, trying to anticipate the volatility, trying to reduce the uncertainty, trying to simplify the complexity.  But that takes foresight, thinking and free time, all of which are sadly in short supply in too many businesses today.

If you need help, contact me.  I've conducted dozens of foresighting and scenario planning exercises for non-profits, universities, government agencies and of course corporations.  If you are living in a VUCA world and don't want to simply react to changes, and don't have the patience to simply wait them out, we can help.  You can reduce the impact of volatility, create more clarity and simplify complexity by working to understand the future.

Customer experience is about to undergo a significant transformation

I've been writing lately about the intersection of innovation and digital transformation, first because it is a very current topic and second because there are fascinating possibilities as innovation and digital transformation collide.  Increasingly, new product development is being digitized (that it, it is becoming an increasingly digital experience with generative design) and new product development must incorporate digital capabilities - sensors, data, communications.  Soon all products will be smart products.  But I digress.

The real point I wanted to write about today is that while all of this new innovation and digital transformation is occurring, it is very easy to get caught up in the technology and emerging capabilities and miss what is probably the most important focal point of your work - as an innovator or as a person focused on digital transformation.  Do you call someone working in digital transformation a digital transformer?

The important focal point - the thing that should be paramount in your thinking is:  how does this improve customer experience?  Customer experience and how customers engage and interact with your solutions is becoming the most important factor in product design, development and innovation.  Digital transformation is simply accelerating this change.

Why is customer experience paramount?

It's similar to the Maslow's hierarchy of needs.  Once a specific set of needs has been relatively well provided for, you move to a higher and often more esoteric set of needs.  Once shelter and food are reasonably well provided for, you move on to well being and happiness as an example.  The same is true for products and services.

Once a product has the appropriate features and capabilities, you move into a new state:  does this product or service enhance my experience?  take for example two competing products, both of which have the same list of features. The first device is much easier to use, integrates into the way you live and work and seamlessly interacts with other devices.  The other is more difficult to use, doesn't integrate and doesn't interact or play well with other devices.  The customer experience of the first device makes it much more attractive than the second device, even though they both have the same capabilities and features.  All things being equal, most people will choose the first device.  That's because the basic needs are satisfied and now customer experience,usability and design matter more.

Why is this accelerated by digital transformation?

I'll argue that we are at peak or perhaps even beyond peak product design.  For years we celebrated individuals who designed products.  Jony Ive was a well-known figure from Apple because of his designs.  However, the value from products and services is increasingly in the data and connectivity, so improving the experience from a digital perspective is increasingly more important than the physical design - it does not lessen the demand for good physical design, just shifts focus.

Digital transformation allows innovators and digital transformers to create new experiences from digitally connected devices, adding value with data and experiences like augmented reality, voice control and other factors.  Don't be fooled though, simply adding more data or more digital features isn't going to win.  Good design and customer experience at the digital level matters a lot, since the vast majority of consumers aren't digital natives.  However, we can expect a lot more focus on customer experience, regardless of the type and nature of the offering or solution.

CX and UX in demand

What we can anticipate is that individuals who understand customer experience and usability will be in great demand, especially those who understand the importance of usability and experience in an increasingly digital product offering.  Understanding that people want access to data and information, but on their terms, that is easy to use and easy to understand and augments or enhances a physical product or experience is vital.

This poses an interesting predicament - we have been focusing on developing data scientists, who understand the data, but have we spent as much time developing data experience professionals, who understand how to make the experience of data and digitally enhanced products effective?  Of course the science leads the experience - it's that way with every new technology advancement.  How quickly do we catch up with digital experience?

Digital transformation: Pandora's box or cornucopia?

Digital transformation.  Everyone from the CEO to the janitor understands that digital transformation is important.  Every competitor is talking about what digital transformation will do for their business - create new revenues, cut inefficiencies and costs, discover new value in previously unremarkable data.  Digital transformation is the latest management philosophy, like ERP or business process re-engineering or innovation that have come before it.  Yet unlike some of these previous philosophies, digital transformation has the power to actually transform a business, rather than simply improve core processes or cut costs.

Right now, digital transformation is a moniker without a definition.  Some people refer to digital transformation as digitalization - improving systems and processes to the point where the business runs on fully integrated digital data and systems.  Other people refer to the goal of being "data driven" - that is, letting data drive processes and decisions.  Some people refer to digital transformation as the advent of artificial intelligence and machine learning as a core component of business operations.  The truth is, like innovation, digital transformation is in the eye, and the definition, of the beholder.  And when definitions are loose and not shared, different implementations will create different outcomes, and what could be a transformative activity is likely to become a discrete project.

Digital and Transformative

There are digital projects and there are transformative projects, but there are very few digital transformative projects.  I use the emphasis intentionally, for this reason:  improving your ability to manage your data (a digital project) won't necessarily transform your business, and you can transform your business without necessarily improving your digital operations, but both are discrete projects.

Digital transformation is a journey.  There.  I said it.  It is an old trope but sometimes old sayings are valid.  To transform a company and make it much more digital, agile, fast and innovative, it will take time and commitment.  This is not a one time AI project in a portion of the business, but an intentional change to how business is done.  Nothing like that happens quickly or in isolation.  Many of the leading firms working on digital transformation have been at it for several years, and when they are being honest they'll admit they have several more years to go to achieve any real digital transformation.

Secondary and Tertiary effects

What's equally if not more important than the realization that digital transformation is a journey of many projects and not a single project is the subsequent understanding that the transformation isn't simply a technology or business process transformation, but will eventually impact:
 - data
 - customer service and experience
 - business models and revenue models
 - partners and the delivery or service ecosystem

While digital changes that you implement today may not seem to impact how you interact with customers, the channels you use or the service experiences customers enjoy, think about the fact that you are transforming your business, as customers and expectations are also being transformed.  If you believe you can continue to operate in the models and methods of the past, while transforming only the data portion of your business, you are sadly mistaken.

Digital transformation will change much more than the data, internal processes and products.  Take for example the new Lumi diapers from Pampers.  These are diapers with a sensor to alert parents to their child's activity and the dampness of the diaper.  With a single sensor (digital capability) information can flow from the diaper to the parent's phone or PC.  Also included in this solution is a digital camera, which the parent can use to turn on or off and view the child at a distance.

From that description, all we've done is place a sensor on a diaper, and exchange data.  But look at what happens next.  The app on the PC or table must be interactive and useful for parents in order for this to succeed.  Thus, customer experience becomes important.  Then, for Pampers to actually benefit from this device they must drive more diaper sales, and create more loyalty, so being able to order diapers from the app is a fairly simple addition, changing the business dynamic between Pampers, the retail channel and the parent.  Of course the delivery of diapers is part of the customer experience as well.

One small change, many secondary and tertiary effects

The challenge with digital transformation at a project level or at a corporate level is the unexpected or even unanticipated secondary and tertiary effects.  By simply including a sensor or data device on a product, you create data flow which creates new insights and opportunities for customer interaction, leading to the importance of customer experience.  As the customer becomes more involved in the data stream, the company has new opportunities to market goods and services, changing the retail channel dynamic and creating new revenue streams and business models.  To support these new models, new and existing ecosystem partners must play an integrated role to provide the service and product expected.

Pandora's Box or Horn of Plenty?

The pessimistic side of me says that many companies will focus on the data flow as they add intelligence to devices, and ignore all of these secondary possibilities.  Some portion of me wonders if these opportunities are a Pandora's Box, full of promise at the start but unleashing issues we haven't fully addressed like ethics and privacy.

But perhaps the best metaphor for the prepared and thoughtful company is a horn of plenty.  There are many opportunities within a digital transformation, and companies that fully consider their opportunities, including the immediately obvious data and analytics opportunities but also the opportunities new data exchange creates, can reap fairly dramatic rewards.

Smart, fast, innovative and digital

The title of this post is the answer to the question:  what does my business need to look like in the future in order to be successful?  I think that increasingly we can make the assumption that the pace of change will remain about the same, the world and markets we participate in will remain volatile and the increasing effects of the digital transformation will only increase.  Therefore, slow, rigid, dumb companies that cannot evolve quickly, cannot become nimble and can't innovate are already dying a slow death.  I'm looking at you, Sears.

I think most people would agree that the factors I've listed in my post title are conditions for future success, but many might debate the depth of knowledge or engagement that is required to really succeed.  Further, it may be apparent that many of these attributes are desirable, but they may be addressed in a siloed or discrete manner, rather than with the understanding that these aren't discrete or standalone capabilities but are mutually reinforcing, and need to be continuous capabilities.  To compete effectively you can't simply make a one-time digital transformation and rest on that new infrastructure.  Digital will keep changing and your new platform will need to change with it.

The same is true with innovation. Your company might "become" innovative but once it has achieved this milestone it must continue to conduct and perfect its innovation chops.  There are no one time effects in the race to remain relevant.  These aren't throw away lines in a management report or one time showcase projects.  These are the new operating realities.

Digital and Smart

These two factors are a good case in point.  It is entirely possible to be digital - to have a lot of digital, automated processes and good data management and hygiene and to be relatively dumb.  Having a digital framework and good data management does not ensure the ability to act with insight and precision, to become a "smart" organization.  Even in companies that are making the digital transformation today, too much of the data remains uninterpreted and unused, and decisions are made without the benefit of good information and insight.  It's not enough to make a digital transformation, because no one really knows what that means.  It's more important to use digital techniques and tools to become smarter than your competition.

Digital and Fast

Again, two factors that could work together that are at risk of working in opposition.  Digital transformation means creating new processes, managing data more effectively, automating processes which should enable speed and agility, but in many cases simply reinforces the status quo and blocks agility and change.  Ask yourself - does our digital transformation work help us work faster, to become more nimble and agile, or does it simply create barriers to new change?

Being digital should enable a company to work at greater speed, to be able to anticipate course changes and move with agility.  So far many "digital transformations" I've seen do the opposite.

Digital and Innovative

Finally, we reach the culmination of the review.  Being digital does not ensure that your company will become more innovative.  In fact it could mean the exact opposite.  If you are doing digital transformation you are implementing machine learning or artificial intelligence, robotics or IoT.  You are improving your ability to gather, manage and use data.  In other words, your teams are using their engineering brains.  Are you at the same time using your creative brains to imagine new solutions, new ideas and discover new opportunities and problems?  More importantly, is your digital transformation guided by the need for efficiency or the quest for better innovation?

The key word is AND

Future competitive strength will reside in organizations that are smart, fast, digital and innovative.  As the subheading suggests, the key word is "AND".  These capabilities aren't mutually exclusive - they rely on each other for greater success, and can't be one time activities - they must become internal capabilities that are constantly evolving and improving.  When you stop working on one of these, all the rest will suffer.  We have to learn to think differently about our companies, their operating models and internal core competencies and capabilities and prepare them to work in a new way, where digital is a priority, where speed and innovation are paramount and where intelligence and insight guide every action.

Digital transformation marks the demise of product innovation

There comes a time when every phenomenon reaches its zenith, before a long fall or a sudden collapse.  We like to refer to this point in the cycle as the "tipping point" - the point at which we can remain in stasis or the structures will collapse.  We are warned that we are close to the tipping point for global warming, for example, where more carbon dioxide in the atmosphere may result in weather and climate changes that create catastrophic change in the weather, sea levels and other factors.

I'm going to stipulate that the business cycle and innovation are at a tipping point.  For close to 20 years (dating approximately from when Jobs returned to Apple) we've been living in the product innovation era.  That era I believe is rapidly drawing to a close, and shortly will collapse, because of other factors such as digital transformation.  When the transition occurs, those companies still focusing on discrete product innovation will be left in a difficult place, because the skills they are building and the focus on product innovation will be less important than emerging abilities in digital transformation and in agile, nimble business models.  They will have succeeded in preparing to fight the previous war, as my military friends like to say.

Several converging forces

There are several reasons why we'll see at least a slow decline in product innovation, if not a collapse.  First is corporate, especially executive cynicism.  Innovation hasn't delivered on its promises in many cases.  There are many reasons why, most notably the inability to accept risks and learn from exploration, as well as the fact that most businesses are too locked into their operating models, business models and markets to do more than incremental innovation.

The second reason is that we are reaching the point of feature saturation.  Most companies don't innovate entirely new products.  For the most part they add additional features and capabilities to existing products.  When cars compete on the number of cup holders and TV remotes require a PhD to determine how to use them, we've reached feature saturation.  There's really not much further we can go with many of the existing products.

The third reason for forecasting a rapid demise in product innovation is the emergence of digital transformation.  As data becomes more important and frankly more valuable and scalable than tangible products, companies will shift to digital products or products that produce data.  What they haven't yet realized is the digital transformation will require shifts to their business models and revenue streams.  Digital transformation will require that companies become a lot more agile and nimble, able to adjust their business models and revenue streams as customer demand shifts.

There's a silver lining in that cloud

If this all sounds a bit dire or ominous, take heart.  There is a silver lining for those companies that recognize where we are on the life cycle of the product innovation era, and what's about to unfold.  Digital Transformation holds within it the demise of physical product innovation but contains within it the new opportunities for business model agility and innovation.  Big businesses will simply have to think differently about what their operating structures and models must be.  No longer will they be able to tinker on the edges with new products.  Innovation will move to the very core of the business, to consider what all the new data means, and how to take advantage of the data streams and insights.

Digital transformation can open up an entirely new way of thinking about innovation, but that innovation will focus on what has traditionally been the most resistant to innovation and change - the existing structures and business models.  Companies that realize this and become more flexible, nimble and agile will use digital transformation to innovate how they operate.  Other firms will do some digital transformation but attempt to retain their old business models, and will collapse due to the conflicting goals of old models and new data.

The future is here, just not widely distributed

If this all sounds futuristic, you aren't looking close enough.  Some of what I'm writing about is already here, just not widely distributed.  Airbnb and Uber are examples of what a more nimble, asset-less company might look like.  Time will tell if they are the avatars or just the next iteration on a journey toward a new type of company.  Companies that understand how to use the data that digital transformation creates and create business models, revenue models and operating models based on the data and needs of customers will succeed, and they'll operate in a different fashion, with different structures and different models than companies do today.

It's both a challenge and an opportunity, blending digital transformation and new innovation models.  Are you ready for some real change in big corporations?  Or, will they slowly wither and die as newer, more nimble players demonstrate the ability to use data effectively?

Digital Transformation will also transform Product Innovation, by the way

There is one really ironic twist to all of this.  Just as we are 'ending' an era of product innovation, digital transformation will revive product innovation, mostly by adding new sensors and IoT capabilities to existing products.  If the data is valuable (and it is) companies will want to gather and harvest the data in any way they can, so more products will become smart and connected.  That's one way the product innovation era will be extended, mostly to the benefit of digital transformation and data.

Challenges when innovating smart, connected devices

I've been struck by the importance of two rapidly converging forces - digital transformation and new product innovation.  As we've discussed, here and elsewhere, ad nauseam, there is increasing demand for new products and services, making stretching the capacity of tenuous innovation processes and teams.  When we add in the new requirement that many of these new products must also be smart and connected, innovation gets a lot more interesting and a lot more difficult.

What does it take to create not just a new product, but a new product that is smart and connected?  Certainly it takes more than simply gluing a sensor to an existing device.  If only it were that simple.  Let's think about what it takes to create smart and connected new devices by considering the simply air filter.  Yes, 3M has released a smart and connected air filter.  As I noted in a previous post, capital equipment (tractors as an example) have been smart and connected for years, but when the concept jumps to consumables like air filters, literally any device can be smart and connected, and that changes everything.

Smart AND connected

First, let's talk about our language.  There are a number of what I'd call "smart" products that capture data or respond to surroundings.  These devices can analyze the environment and turn on or off or take a specific action.  They are somewhat "smart" in that they operate in a way that responds to commands or to the environment.  But many of these aren't necessarily connected to the internet or other systems.

Smart and connected requires that the product include senors and other IoT capability AND share that information with the consumer and with the manufacturer or distributor through the internet.  When the data is shared beyond the household, the smart and connected device becomes the basis for a new potential revenue and business relationship.

What's more important, the product or the data

Using 3M's air filter as an example, we can begin to see that the end product will become the razor and the data created and shared will become the razor blades, only in reverse.  The air filter's value to 3M in terms of revenue and profit is marginal, but the value of the data gathered, managed, analyzed and repackaged is much higher.  As the data is shared, and aggregated from other sources and combined with other geographic, demographic or psychographic data it creates insights for new products and new services and can be packaged and sold to others.  This in turn offers the potential for new business models, new recurring relationships with consumers that the company can control and monitor and new product development based on insights from the data.

Emerging impact on customer experience

A smart connected filter also means that 3M can create and leverage new customer experiences.  Previously if I acquired an air filter I did so based on availability and cost, since the filters were mostly commodities.  If I acquire the 3M smart filter and download the app and have a good experience learning about my usage and in the reordering process, I may "lock in" to 3M's products and even a recurring revenue stream if the customer experience is good.  For a product where traditionally customer experience wasn't important, suddenly secondary issues like customer experience with reordering or the applications or data presentation matters.

Managing and harvesting data

There are so many considerations when transitioning a traditionally "dumb" product to a smart, connected product.  I've noted the challenges with customer experience just above.  Another is the nature and volume of data that will be generated, and the importance of gaining insight and value from that data.  While many of these products may not generate a lot of data, the aggregate data generated will be significant.  Imagine that 3M sells hundreds of thousands of air filters in a year and each is connected and shares even just a few bits of data every day.  That data provides a baseline about product usage.  But when consumers sign in to 3M's app more data becomes available - the customer's location, purchase preferences, reordering models and so forth, for every home that has a smart device.  With that data 3M can then merge their data with more data about location, geography, neighborhood incomes and other data to get a full picture of the client profile, usage, buying patterns and other data to use to improve products, offer new incentives or advertising or package and sell the data.

Transition from dumb to smart and connected

So, far from a simple transition, there are significant shifts when moving to a smart, connected device.  Beyond simply adding a sensor and connectivity, which are not simple but are probably the easier activities, companies will have to consider the data generated and how to obtain value, the enhanced customer interaction and experience and the potential impact to existing business relationships and business models.

If you find that this is more complex than you first imagined, you are right.  My team can help think through this with a framework we've built that considers many of these components to a successful smart, connected device as part of innovation and new product development.  Contact us if you'd like to learn more. 

The conflict between digital transformation and speed

Just one more post about the importance of speed and agility and I'll leave this tired trope alone.  It took over 50 years for a reasonable majority of US households to obtain landline telephone service.  It took less than 10 years for a majority of households to obtain cellphone services and less than a handful of years for a majority of households to access and use Facebook.  There are a few points to make about that progression:

• The initial investments were huge - putting wires up all over America, especially when many people still lived in rural areas, and the costs and benefits of a home phone were tenuous.
• As people became convinced that home phones were valuable, cell phones emerged and again the cost/benefit was relatively uncertain when anyone could drop a quarter into a neighborhood pay phone.  When the phones started offering other features and immediate convenience became paramount, cell phones really accelerated.
• Facebook and other platforms are built on the previous two ideas - ubiquitous connectivity through a global backbone and often wireless connectivity based on smart phones.  Building on these or other platforms, one can get to the market much more quickly and efficiently for digital products.

These ideas matter because we are increasingly acquiring digital products and exchanging information, even when we are acquiring or using physical products.  Thus, the idea that "digital transformation" is vital almost goes without saying.  What few people are talking about is the conflict between being "digital" and acting at speed.

Mutually reinforcing or at conflict?

The supporters and especially the vendors who are backing "digital transformation" want you to believe that you can work at speed only through digital transformation, and for the most part they are right.  But what they aren't telling you is there is no final destination for digital transformation.  It isn't a place on the map, but a journey that once started never reaches a destination.  Once you create fully digital business processes you'll need to collect and manage the data and obtain insight from the data to put back into your business.  Analyzing and understanding the data generated is just as important (if not more so) than simply automating and digitizing the processes.  Yet analyzing and understanding the meaning of the data is more difficult and more time consuming.

So good digital processes and insights CAN offer more speed to insight, speed to product and speed to market.  But only if your systems and processes are tuned to digital work, and only if you can manage the data generated.  But as only close observer of the IT revolution knows, once on the treadmill, you can never get off and it only goes faster.

Plus, there is a "dark side" to technology and the IT that supports it.  Any architecture that makes you efficient, able to process more data or make more decisions, often also makes your processes and decision making more structured and more rigid.  ERP has proven this time and again, helping organizations work more efficiently but often locking them into older operating models and processes.

Will digital transformation be an accelerator or an inhibitor?

The reasonable answer to the question above is:  yes.  Initially, digital transformation will accelerate business operations.  Of course many companies are just beginning this journey, and are learning how to make sense of the data they generate and obtain new insights.  Once they begin to fully engage the benefits of digital transformation, will these mechanisms and processes become enablers or barriers to future changes in business models?  If history is any guide, we can project that digital transformation will become first an enabler, and then potentially a barrier to agility and speed.

That's because any new implementation is first a disruptor and then becomes the norm, to be coddled and protected.  Plus, an additional challenge is that the more data is created and the more valuable it becomes, the more important it is to manage and analyze the data, creating a vicious cycle.  One wonders at the amount of data that will be generated in the next few years and how much of it will be actively and successfully analyzed and interpreted.

Speed and agility will be paramount

One other item - no matter how important the data becomes, moving with agility, decisiveness and speed will always win.  The ability to preempt competitors and customers with attractive and viable solutions, getting there first with the best product and accruing as much market share as possible, will be the deciding differentiator.  So no matter how much data you can accumulate and analyze, if it becomes analysis paralysis, slowing and diverting your company from working at speed, digital transformation won't be helpful.

The question companies should be asking themselves in the face of digital transformation messaging is:  how does this digital transformation help me make better decisions faster, and move at better and more decisive speed than my competitors and customers?  If you can't answer that question definitively, reframe your digital transformation activities and projects.  Notice I did not say "stop" those projects, because you should be experimenting now.  But these projects must help you get smarter and faster simultaneously.  Getting smarter without getting faster is second or third place.  Getting faster without getting smarter is suicide.