Shipulski On Design

Archive for the ‘Top Line Growth’ Category

The biggest blocker of company growth is your successful business model.  And the more significant it’s historical success, the more it blocks.

Novelty meaningful to the customer is the life force of company growth.  The easiest novelty to understand is novelty of product function.  In a no-to-yes way, the old product couldn’t do it, but the new one can.  And the amount of seconds it takes for the customer to notice (and in the case of meaningful novelty, appreciate) the novelty is in an indication of its significance.  If it takes three months of using the product, rigorous data collection and a t-test, that’s not good.  If the customer turns on the product and the novelty smashes him in the forehead like a sledgehammer, well, that’s better.

It’s difficult to create a product with meaningful novelty.  Engineers know what they know, marketers know what they market, and the salesforce knows how to sell what they sell.  And novelty cuts across their comfort.  The technology is slightly different, the marketing message diverges a bit, and the sales argument must be modified.  The novelty is driven by the product and the people respond accordingly.  And, the new product builds on the old one so there’s familiarity.

Where injecting novelty into the product is a challenge, rubbing novelty on the business model provokes a level 5 pucker.  Nothing has the stopping power of a proposed change to the business model.  Novelty in the product is to novelty in the business model as lightning is to lightning bug – they share a word, but that’s it.

Novelty in the product is novelty of sheet metal, printed circuit boards and software.  Novelty in the business model is novelty in how people do their work and novelty in personal relationships.  Novelty in the product banal, novelty in the business model is personal.

No tools or best practices can loosen the pucker generated by novelty in the business model.  The tired business model has been the backplane of success for longer than anyone can remember.  The long-in-the-tooth model has worn deep ruts of success into the organization.  Even the all-powerful Lean Startup methodology can’t save you.

The healing must start with an open discussion about the impermanence of all things, including the business model.  The most enduring radioactive element has a half-life, and so does the venerable business model, even the most successful.

Where novelty in the product is technical, novelty in the business model is emotional. And that’s what makes it so powerful.  Sprinkling the business model with novelty is scary at a deeply personal level – career jeopardy, mortgage insecurity and family volatility are primal drivers.  But if you can push through, the rewards are magical.

Your business model has shaped you into an organization that’s optimized to do what it does. You can’t create new markets and sell to new products to new customers without changing your business model.  Your business model may have been your secret sauce, but the world’s tastes have changed.  It’s time to put your success behind you.

Image credit — MandaRose

Even after playing lots of tricks to reduce its energy consumption, our brains still consume a large portion of the calories we eat.  Like today’s smartphones it’s computing power is too big for it’s battery so its algorithms conserve every chance they get.  One of its go-to conservation strategies is to make mental models.  The models capture the essence of a system’s behavior without the overhead of retaining all the details of the system.

And as the brain goes about its day it tries to fit what it sees to its portfolio of mental models.  Because mental models are so efficient, to save juice the brain is pretty loose with how it decides if a model fits the situation.  In fact the brain doesn’t do a best fit, it does a first fit. Once a model is close enough, the model is applied, even if there’s a better one in the archives.

Overall, the brain does a good job.  It looks at a system and matches it with a model of a similar system it experienced in the past.  But behind it all the brain is making a dangerous assumption.  The brain assumes all systems are static.  And that makes for mental models that are static.  And because all systems change over time (the only thing we can argue about is the rate of change) the brain’s mental models are always out of date.

Over the years your brain as made a mental model of how your business works – customers do this, competitors do that, and markets do the other.  But by definition that mental model is outdated.  There needs to be a forcing function that causes us to refute our mental models so we can continually refine them. [A good mantra could be – all mental models are out of fashion until proven otherwise.]  But worse than not having a mechanism to refute them, we have a formal business process the demands we converge on our tired mental models year-on-year.  And the name of that wicked process – strategic planning.

It goes something like this. Take a little time from your regular job (though you still have to do all that regular work) and figure out how you’re going to grow your business by a large (and arbitrary) percentage. The plan must be achievable (no pie in the sky stuff), it should be tightly defined (even though everyone knows things are dynamic and the plan will change throughout the year), you must do everything you did last year and more and you have fewer resources than last year.  Any brain in it’s right will fit the old models to the new normal and put the plan together in the (insufficient) time allotted. The planning process reinforces the re-use of old models.

Because the brain believes everything is static, it’s thinking goes like this – a plan based on anything other than the tried-and-true mental models cannot have certainty or predictability in time or resources.  And it’s thinking is right, in part.  But because all mental models are out of date, even plans based on existing models don’t have certainty and predictability.  And that’s where the wheels fall off.

To inject a bit more reality into strategic planning, ignore the tired old information streams that reinforce existing thinking and find new ones that provide information that contradicts existing mental models.  Dig deeply into the mismatch between the new information and the old mental models.  What is behind the difference?  Is the difference limited to a specific region or product line? Is the mismatch new or has it always been there?  The intent of this knee-deep dissection is not to invalidate the old models but to test and refine.

There is infinite detail in the world.  Take a look at a tree and there’s a trunk and canopy. Look at the canopy and see the leaves. Look deeper to see a leaf and its veins.  In order to effectively handle all this detail our brains create patterns and abstractions to reduce the amount of information needed to make it through the day.

In the case of the tree, the word “tree” is used to capture the whole thing – roots and all.  And at a higher level, “tree” can represent almost any type of tree at almost any stage in its life.  The abstraction is powerful because it reduces the complexity, as long as everyone’s clear which tree is which.

The message is this. Our brain takes shortcuts with its chunking of the world into mental models that go out style. And our brain uses different levels of abstraction for the same word to mean different things. Care must be taken to overtly question our mental models and overtly question the level of abstraction used when statements of facts are made.

Knowing what isn’t said is almost important as what is said. To maintain this level of clarity requires calm, centered awareness which today’s pace makes difficult.

There’s no pure cure for the syndrome. The best we can do is to be well-rested and aware. And to do that requires professional confidence and personal disciple.

Slowing down just a bit can be faster, and testing the assumptions behind our business models can be even faster.  Last year’s mental models and business models should be thought of as guilty until proven relevant.  And for that you need to make the time to think.

In today’s world we confuse activity with progress. But really, in today’s dynamic world thinking is progress.

Image credit – eyeliam.

Doing anything for the first time is difficult.  It goes with the territory.  Instead of seeing the associated anxiety as unwanted and unpleasant, maybe you can use it as an indicator of importance.  In that way, if you don’t feel anxious you know you’re doing what you’ve done before.

Innovation, as a word, has been over used (and misused).   Some have used the word to repackage the same old thing and make it fresh again, but more commonly people doing good work attach the word innovation to their work when it’s not.  Just because you improved something doesn’t mean it’s innovation.  This is the confusion made by the lean and Six Sigma movements – continuous improvement is not innovation.  The trouble with saying that out loud is people feel the distinction diminishes the importance of continuous improvement.  Continuous improvement is no less important than innovation, and no more.  You need them both – like shoes and socks.  But problems arise when continuous improvement is done in the name of innovation and innovation is done at the expense of continuous improvement – in both cases it’s shoes, no socks.

Coming up with an acid test for innovation is challenging.  Innovation is a know-it-when-you-see-it thing that’s difficult to describe in clear language.  It’s situational, contextual and there’s no prescription.   [One big failure mode with innovation is copying someone else’s best practice.  With innovation, cutting and pasting one company’s recipe into another company’s context does not work.] But prescriptions and recipes aside, it can be important to know when it’s innovation and when it isn’t.

If the work creates the foundation that secures your company’s growth goals, don’t worry about what to call it, just do it.  If that work doesn’t require something radically new and different, all-the-better.  But you likely set growth goals that were achievable regardless of the work you did.  But still, there’s no need to get hung up on the label you attach to the work.  If the work helps you sell to customers you could not sell to before, call it what you will, but do more of it.  If the work creates a whole new market, what you call it does not matter.  Just hurry up and do it again.

If your CEO is worried about the long term survivability of your company, don’t fuss over labelling your work with the right word, do something different.  If you have to lower your price to compete, don’t assign another name to the work, do different work.  If your new product is the same as your old product, don’t argue if it’s the result of continuous improvement or discontinuous improvement.  Just do something different next time.

Labelling your work with the right word is not the most important thing.  It’s far more important to ask yourself – Five years from now, if the company is offering a similar product to a similar set of customers, what will it be like to work at the company?  Said another way, arguing about who is doing innovation and who is not gets in the way of doing the work needed to keep the company solvent.

If the work scares you, that’s a good indication it’s meaningful.  And meaningful is good.  If it scares you because it may not work, you’re definitely trying something new.  And that’s good.  But it’s even better if the work scares you because it just might come to be.  If that’s the case, your body recognizes the work could dismantle a foundational element of your business – it either invalidates your business model or displaces a fundamental technology.   Regardless of the specifics, anxiety is a good surrogate for importance.

In some cases, it can be important what you call the work.  But far more important than getting the name right is doing the right work.  If you want to argue about something, argue if the work is meaningful.  And once a decision is reached, act accordingly.  And if you want to have a debate, debate the importance of the work, then do the important work as fast as you can.

Do the important work at the expense of arguing about the words.

Innovation isn’t a thing in itself; rather, it’s a result of something. Set the right input conditions, monitor the right things in the right ways, and innovation weaves itself into the genetic makeup of your company.  Like ivy, it grabs onto outcroppings that are the heretics and wedges itself into the cracks of the organization.  It grows unpredictably, it grows unevenly, it grows slowly.  And one day you wake up and your building is covered with the stuff.

Ivy doesn’t grow by mistake – It takes some initial plantings in strategic locations, some water, some sun, something to attach to, a green thumb and patience.  Innovation is the same way.

There’s no way to predict how ivy will grow.  One young plant may dominate the others; one trunk may have more spurs and spread broadly; some tangles will twist on each other and spiral off in unforeseen directions; some vines will go nowhere.  Though you don’t know exactly how it will turn out, you know it will be beautiful when the ivy works its evolutionary magic.  And it’s the same with innovation.

Ivy and innovation are more similar than it seems, and here are some rules that work for both:

• If you don’t plant anything, nothing grows.
• If growing conditions aren’t right, nothing good comes of it.
• Without worthy scaffolding, it will be slow going.
• The best time to plant the seeds was three years ago.
• The second best time to plant is today.
• If you expect predictability and certainty, you’ll be frustrated.

Innovation is the output of a set of biological systems – our people systems – and that’s why it’s helpful to think of innovation as if it’s alive because, well, it is.  And like with a thriving colony of ants that grows steadily year-on-year, these living systems work well.  From 10,000 foot perspective ants and innovation look the same – lots of chaotic scurrying, carrying and digging.  And from an ant-to-ant, innovator-to-innovator perspective they are the same – individuals working as a coordinated collective within a shared mindset of long term sustainability.

Image credit – Cindy Cornett Seigle

Chief Innovation Officer is a glorious title, and seems like the best job imaginable.  Just imagine – every-day-all-day it’s: think good thoughts, imagine the future, and bring new things to life.  Sounds wonderful, but more than anything, it’s a lonely slog.

In theory it’s a great idea – help the company realize (and acknowledge) what it’s doing wrong (and has been for a long time now), take resources from powerful business units and move them to a fledgling business units that don’t yet sell anything, and do it without creating conflict.  Sounds fun, doesn’t it?

Though there are several common problems with the role of Chief Innovation Officer (CIO), the most significant structural issue, by far, is the CIO has no direct control over how resources are allocated. Innovation creates products, services and business models that are novel, useful and successful.  That means innovation starts with ideas and ends with commercialized products and services.  And no getting around it, this work requires resources.  The CIO is charged with making innovation come to be, yet authority to allocate resources is withheld. If you’re thinking about hiring a Chief Innovation Officer, here’s a rule to live by:

If resources are not moved to projects that generate novel ideas, convert those ideas into crazy prototypes and then into magical products that sell like hotcakes, even the best Chief Innovation Officer will be fired within two years.

Structurally, I think it’s best if the powerful business units (who control the resources) are charged with innovation and the CIO is charged with helping them.  The CIO helps the business units create a forward-looking mindset, helps bring new thinking into the old equation, and provides subject matter expertise from outside the company.  While this addresses the main structural issue, it does not address the loneliness.

The CIO’s view of what worked is diametrically opposed to those that made it happen.  Where the business units want to do more of what worked, the CIO wants to dismantle the engine of success.  Where the engineers that designed the last product want to do wring out more goodness out of the aging hulk that is your best product, the CIO wants to obsolete it.  Where the business units see the tried-and-true business model as the recipe for success, the CIO sees it as a tired old cowpath leading to the same old dried up watering hole.  If this sounds lonely, it’s because it is.

To combat this fundamental loneliness, the CIO needs to become part of a small group of trusted CIOs from non-competing companies. (NDAs required, of course.)  The group provides its members much needed perspective, understanding and support.  At the first meeting the CIO is comforted by the fact that loneliness is just part of the equation and, going forward, no longer takes it personally.  Here are some example deliverables for the group.

Identify the person who can allocate resources and put together a plan to help that person have a big problem (no incentive compensation?) if results from the innovation work are not realized.

Make a list of the active, staffed technology projects and categorize them as: improving what already exists, no-to-yes (make a product/service do something it cannot), or yes-to-no (eliminate functionality to radically reduce the cost signature and create new markets).

For the active, staffed projects, define the market-customer-partner assumptions (market segment, sales volume, price, cost, distribution and sales models) and create a plan to validate (or invalidate) them.

To the person with the resources and the problem if the innovation work fizzles, present the portfolio of the active, staffed projects and its validated roll-up of net profit, and ask if portfolio meets the growth objectives for the company.  If yes, help the business execute the projects and launch the products/services.  If no, put a plan together to run Innovation Burst Events (IBEs) to come up with more creative ideas that will close the gap.

The burning question is – How to go about creating a CIO group from scratch?  For that, you need to find the right impresario that can pull together a seemingly disparate group of highly talented CIOs, help them forge a trusting relationship and bring them the new thinking they need.

Finding someone like that may be the toughest thing of all.

Image credit – Giant Humanitarian Robot.

Innovation starts with different, and when you propose something that’s different from the recipe responsible for success, innovation becomes the enemy of success. And because innovation and different are always joined at the hip, the conflict between success and innovation is always part of the equation. Nothing good can come from pretending the conflict does not exist, and it’s impossible to circumvent. The only way to deal with the conflict is to push through it.

Emotional energy is the forcing function that pushes through conflict, and the only people that can generate it are the people doing the work. As a leader, your job is to create and harness this invisible power, and for that, you need mechanisms.

To start, you must map innovation to “different”.  The first trick is to ask for ideas that are different. Where brainstorming asks for quantity, firmly and formally discredit it and ask for ideas that are different. And the more different, the better. Jeffrey Baumgartner has it right with his Anticonventional Thinking (ACT) methodology where he pushes even further and asks for ideas that are anti-conventional.

The intent is to create emotional energy, and to do that there’s nothing better than telling the innovation team their ideas are far too conventional. When you dismiss their best ideas because they’re not different enough, you provide clear contrast between the ideas they created and the ones you want. And this contrast creates internal conflict between their best thinking and the thinking you want.  This internal conflict generates the magical emotional energy needed to push through the conflict between innovation and success.  In that way, you create intrinsic conflict to overpower the extrinsic conflict.

Because innovation is powered by emotional energy, conflict is the right word.  Yes, it feels too strong and connotes quarrel and combat, but it’s the right word because it captures the much needed energy and intensity around the work. Just as when “opportunity” is used in place of “problem” and the urgency, importance, and emotion of the situation wanes, emotional energy is squandered when other words are used in place of “conflict”.

And it’s also the right word when it comes to solutions. Anti-conventional ideas demand anti-conventional solutions, both of which are powered by emotional energy. In the case of solutions, though, the emotional energy around “conflict” is used to overcome intellectual inertia.

Solving problems won’t get you mind-bending solutions, but breaking conflicts will. The idea is to use mechanisms and language to move from solving problems to breaking conflicts. Solving problems is regular work done as a matter of course and regular work creates regular solutions.  But with innovation, regular solutions won’t cut it.  We need irregular solutions that break from the worn tracks of predictable thinking. And do to this, all convention must be stripped away and all attachments broken to see and think differently.  And, to jolt people out of their comfort zone, contrast must be clearly defined and purposefully amplified.

The best method I know to break intellectual inertia is ARIZ and algorithmic method for innovative solutions built on the foundation of TRIZ.  With ARIZ, a functional model of the system is created using verb-noun pairs with the constraint that no industry jargon can be used. (Jargon links the mind to traditional thinking.) Then, for clarity, the functional model is then reduced to a conflict between two system elements and defined in time and place (the conflict domain.)  The conflict is then made generic to create further distance from the familiar.  From there the conflict is purposefully amplified to create a situation where one of the conflicting elements must be in two states at the same time (conflicting states) – hot and cold; large and small; stiff and flexible.  The conflicting states make it impossible to rely on preexisting solutions (familiar thinking.)  Though this short description of ARIZ doesn’t do it justice, it does make clear ARIZ’s intention – to use conflicts to break intellectual inertia.

Innovation butts heads and creates conflict with almost everything, but it’s not destructive conflict.  Innovation has the best intentions and wants only to create constructive conflict that leads to continued success. Innovation knows your tired business model is almost out of gas and desperately wants to create its replacement, but it knows your successful business model and its tried-and-true thinking are deeply rooted in the organization.  And innovation knows the roots are grounded in emotion and  it’s not about pruning it’s about  emotional uprooting.

Conflict is a powerful word, but the right word.  Use the ACT mechanism to ask for ideas that constructively conflict with your success and use the ARIZ mechanism to ask for solutions that constructively conflict with your best thinking.

With innovation there is always conflict.  You might as well make it constructive conflict and pull your organization into the future kicking and screaming.

Image credit – Kevin Thai

When it’s time for a tough decision, it’s time to use data.  The idea is the data removes biases and opinions so the decision is grounded in the fundamentals.  But using the right data the right way takes a lot of disciple and care.

The most straightforward decision is a decision between two things – an either or – and here’s how it goes.

The first step is to agree on the test protocols and measure systems used to create the data.  To eliminate biases, this is done before any testing.  The test protocols are the actual procedural steps to run the tests and are revision controlled documents.  The measurement systems are also fully defined.  This includes the make and model of the machine/hardware, full definition of the fixtures and supporting equipment, and a measurement protocol (the steps to do the measurements).

The next step is to create the charts and graphs used to present the data. (Again, this is done before any testing.) The simplest and best is the bar chart – with one bar for A and one bar for B.  But for all formats, the axes are labeled (including units), the test protocol is referenced (with its document number and revision letter), and the title is created.  The title defines the type of test, important shared elements of the tested configurations and important input conditions.   The title helps make sure the tested configurations are the same in the ways they should be.  And to be doubly sure they’re the same, once the graph is populated with the actual test data, a small image of the tested configurations can be added next to each bar.

The configurations under test change over time, and it’s important to maintain linkage between the test data and the tested configuration.  This can be accomplished with descriptive titles and formal revision numbers of the test configurations.  When you choose design concept A over concept B but unknowingly use data from the wrong revisions it’s still a data-driven decision, it’s just wrong one.

But the most important problem to guard against is a mismatch between the tested configuration and the configuration used to create the cost estimate.  To increase profit, test results want to increase and costs wants to decrease, and this natural pressure can create divergence between the tested and costed configurations. Test results predict how the configuration under test will perform in the field.  The cost estimate predicts how much the costed configuration will cost.  Though there’s strong desire to have the performance of one configuration and the cost of another, things don’t work that way.  When you launch you’ll get the performance of AND cost of the configuration you launched.  You might as well choose the configuration to launch using performance data and cost as a matched pair.

All this detail may feel like overkill, but it’s not because the consequences of getting it wrong can decimate profitability. Here’s why:

Profit = (price – cost) x volume.

Test results predict goodness, and goodness defines what the customer will pay (price) and how many they’ll buy (volume).  And cost is cost.  And when it comes to profit, if you make the right decision with the wrong data, the wheels fall off.

Image credit – alabaster crow photographic

Innovation starts with recognition of a big, meaningful problem. It can come from the strategic planning process; from an ongoing technology project that isn’t going well; an ongoing product development project that’s stuck in the trenches; or a competitor’s unforeseen action. But where it comes from isn’t the point. What matters is it’s recognized by someone important enough to allocate resources to make the problem go away. (If it’s recognized by someone who can’t muster the resources, it creates frustration, not progress.)

Once recognized, the importance of the problem is communicated to the organization. Usually, a problem is important because it blocks growth, e.g., a missing element of the new business model, technology that falls short of the distinctive value proposition (DVP), or products that can’t deliver on your promises. But whether something’s in the way or missing, the problem’s importance is best linked to a growth objective.

Company leaders then communicate to the organization, using one page. Here’s an example:

WHY – we have a problem. The company’s stock price cannot grow without meeting the growth goals, and currently we cannot meet them. Here’s what’s needed.
WHAT – grow sales by 30%.
WHERE – in emerging markets.
WHEN – in two years.
HOW – develop a new line of products for the developing world.

Along with recognition of importance, there must be recognition that old ways won’t cut it and new thinking is required. That way the company knows it’s okay to try new things.

Company leaders pull together a small group and charters them to spend a bit of time to develop concepts for the new product line and come back and report their go-forward reccommendations. But before any of the work is done, resources are set aside to work on the best ones, otherwise no one will work on them and everyone will know the company is not serious about innovation.

To create new concepts, the small group plans an Innovation Burst Event (IBE). On one page they define the DVP for the new product line, which describes how the new customers will use the new products in new ways. They use the one page DVP to select the right team for the IBE and to define fertile design space to investigate. To force new thinking, the planning group creates creative constraints and design challenges to guide divergence toward new design space.

The off-site location is selected; the good food is ordered; the IBE is scheduled; and the team is invited. The company leader who recognized the problem kicks off the IBE with a short description of the problem and its importance, and tells the team she can’t wait to hear their recoomendations at the report-out at the end of the day.

With too little time, the IBE team steps through the design challenges, creates new concepts, and builds thinking prototypes. The prototypes are the center of attention at the report-out.

At the report-out, company leaders allocate IP resources to file patents on the best concepts and commission a team of marketers, technologists, and IP staff to learn if viable technologies are possible, if they’re patentable, and if the DVP is viable.(Will it work, can we patent it, and will they buy it.)

The marketer-technologist-IP team builds prototypes and tests them in the market. The prototypes are barely functional, if at all, and their job is to learn if the DVP resonates. (Think minimum viable prototype.) It’s all about build-test-learn, and the learning loops are fast and furious at the expese of statistical significance. (Judgement carries the day in this phase.)

With viable technology, patentable ideas, and DVP in hand, the tri-lobed team reports out to company leaders who sanctioned their work. And, like with the IBE, the leaders allocate more IP resources to file more patents and commission the commercialization team.

The commercialization team is the tried-and-true group that launches products. Design engineering makes it reliable; manufacturing makes it repeatable; marketing makes it irresistible; sales makes it successful. At the design reviews more patents are filed and at manufacturing readiness reviews it’s all about process capability and throughput.

Because the work is driven by problems that limit growth, the result of the innovation work is exactly what’s needed to fuel growth – in this case a successful product line for the developing world. Start with the right problem and end up with the right solution. (Always a good idea.)

With innovation programs, all the talk is about tools and methods, but the two things that really make the difference are lightning fast learning loops and resources to do the innovation work. And there’s an important philosophical chasm to cross – because patents are usually left out of the innovation equation – like an afterthought chasing a quota – innovation should become the umbrella over patents and technology. But because IP reports into finance and technology into engineering, it will be a tough chasm to bridge.

It’s clear fast learning loops are important for fast learning, but they’re also important for building culture. At the end of a cycle, the teams report back to leadership, and each report-out is an opportunity to shape the innovation culture. Praise the good stuff and ignore the rest, and the innovation culture moves toward the praise.

There’s a natural progression of the work. Start – do one project; spread – use the learning to do the next ones; systematize – embed the new behaviors into existing business processes; sustain – praise the best performers and promote them.

When innovation starts with business objectives, the objectives are met; when innovation starts with company leadership, resources are allocated and the work gets done; and when the work shapes the culture, the work accelerates. Anything less isn’t innovation.

Image credit – Jaybird

There are three types of innovation: innovation that creates jobs, innovation that’s job neutral, and innovation that reduces jobs.

Innovation that reduces jobs is by far the most common. This innovation improves the efficiency of things that already exist – the mantra: do the same, but with less. No increase in sales, just fewer people employed.

Innovation that’s job neutral is less common. This innovation improves what you sell today so the customer will buy the new one instead of the old one. It’s a trade – instead of buying the old one they buy the new one. No increase in sales, same number of people employed.

Innovation that creates jobs is uncommon. This innovation radically changes what you sell today and moves it from expensive and complicated to affordable and accessible. Sell more, employ more.

Clay Christensen calls it Disruptive Innovation; Vijay Govindarajan calls it Reverse Innovation; and I call it Less-With-Far-Less.

The idea is the product that is sold to a relatively small customer base (due to its cost) is transformed into something new with far broader applicability (due to its hyper-low cost). Clay says to “look down” to see the new technologies that do less but have a super low cost structure which reduces the barrier to entry. And because more people can afford it, more people buy it. And these aren’t the folks that buy your existing products. They’re new customers.

Vijay says growth over the next decades will come from the developing world who today cannot afford the developed world’s product. But, when the price comes down (down by a factor of 10 then down by a factor of 100), you sell many more. And these folks, too, are new customers.

I say the design and marketing communities must get over their unnatural fascination with “more” thinking. To sell to new customers the best strategy is increase the number of people who can afford your product. And the best way to do that is to radically reduce the cost signature at the expense of features and function. If you can give ground a bit on the thing that makes your product successful, there is huge opportunity to reduce cost – think 80% less cost and 20% less function. Again, you sell new product to new customers.

Here’s a thought experiment to help put you in the right mental context: Create a plan to form a new business unit that cannot sell to your existing customers, must sell a product that does less (20%) and costs far less (80%), and must sell it in the developing world. Now, create a list of small projects to test new technologies with radically lower cost structures, likely from other industries. The constraint on the projects – you must be able to squeeze them into your existing workload and get them done with your existing budget and people. It doesn’t matter how long the projects take, but the investment must be below the radar.

The funny thing is, if you actually run a couple small projects (or even just one) to identify those new technologies, for short money you’ve started your journey to selling new products to new customers.

The Holy Grail of marketing is to identify emerging customer needs before anyone else and satisfy them to create new markets. It has been a long and fruitless slog as emerging needs have proven themselves elusive. And once candidates are identified, it’s a challenge to agree which are the game-changers and which are the ghosts. There are too many opinions and too few facts. But there’s treasure at the end of the rainbow and the quest continues.

Emerging things are just coming to be, just starting, so they appy to just a small subset of customers; and emerging things are new and different, so they’re unfamiliar. Unfamiliar plus small same size equals elusive.

I don’t believe in emerging customer needs, I believe in emergent customer behavior.

Emergent behavior is based on actions taken (past tense) and is objectively verifiable. Yes or no, did the customer use the product in a new way? Yes or no, did the customer make the product do something it wasn’t supposed to? Did they use it in a new industry? Did they modify the product on their own? Did they combine it with something altogether unrelated? No argument.

When you ask a customer how to improve your product, their answers aren’t all that important to them. But when a customer takes initiative and action, when they do something new and different with your product, it’s important to them. And even when just a few rouge customers take similar action, it’s worth understanding why they did it – there’s a good chance there’s treasure at the end of that rainbow.

With traditional VOC methods, it has been cost prohibitive to visit enough customers to learn about a handful at the fringes doing the same crazy new thing with your product. Also, with traditional VOCs, these “outliers” are thrown out because they’re, well, they’re outliers. But emergent behavior comes from these very outliers. New information streams and new ways to visualize them are needed to meet these challenges.

For these new information streams, think VOC without the travel; VOC without leading the witness; VOC where the cost of capturing their stories is so low there are so many stories captured that it’s possible to collect a handful of outliers doing what could be the seed for the next new market.

To reduce the cost of acquisition, stories are entered using an app on a smart phone; to let emergent themes emerge, customers code their own stories with a common, non-biasing set of attributes; and to see patterns and outliers, the coded stories are displayed visually.

In the past, the mechanisms to collect and process these information streams did not exist. But they do now.

I hope you haven’t given up on the possibility of understanding what your customers will want in the near future, because it’s now possible.

I urge you to check out SenseMaker.

It’s harder than ever to innovate, and getting harder.

The focus on growth can be empowering, but when coupled with signed-in-blood accountability, empowering turns to puckering.  It’s an unfair double-bind. Damned if you try something new and it doesn’t work, and damned if you stay the course and don’t hit the numbers.  The most popular approach seems to be to do more of what worked.  A good approach, but not as good as it’s made out to be.

Doing more of what worked is good, and it works.  But it can’t stand on its own.  With today’s unreasonable workloads, every resource is fully booked and before doing more of anything, you’ve got to do less of something else.  ‘More of what worked’ must walk hand-in-hand with ‘Stop what didn’t work.’  Without stopping, without freeing up resources, ‘more of what worked’ is insufficient and unsustainable.

But even the two together are insufficient, and there’s a much needed third leg to stabilize the stool – ‘starting new work.’  Resources freed by stopping are allocated to starting new work, and this work, also known as innovation, is the major source of growth.

‘More of what worked’ is all about productivity – doing more with the same resources; and so is ‘stopping what didn’t work’ – reclaiming and reallocating ineffective resources. Both are important, but more importantly – they’re not innovation.

As you’re well aware, the rules are changing faster than ever, and at some point what worked last year won’t work this year. The only way to stay ahead of a catastrophe is to make small bets in unproven areas.  If the bets are successful, they turn into profitable innovation and growth. But the real value is the resiliency that comes from the ritualistic testing/learning cycles.

Going all-in on what worked last year is one of the riskiest bets you can make.