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Thinking Dynamically

If you’re asked to do cost reduction, before doing that work, ask for objective evidence that the work to grow the top line is adequately staffed. You can’t secure your company’s future through cost reduction, so before you spend time and effort to grow the bottom line, make sure the work to grow the top line is more than fully staffed. Without top-line growth, cost reduction is nothing more than a race to the bottom.

If you’re asked to do more of what was done last time, before doing that work, look back and plot how that line of goodness has improved over time. If the goodness over time is flat (it hasn’t increased), the technology is mature, there’s nothing left, and you should improve something else (a new line of goodness).  If the goodness continues to increase over time, ask customers if it’s already good enough.  Do this by asking if they’d pay more for more goodness. If they won’t pay more, it’s already good enough. Stop work on that tired, old line of goodness and work on a new one. If goodness over time is still increasing and customers will pay more, teach someone else how to improve that line of goodness so you can establish the next line of goodness which will be needed when the old one gets tired.

If you’re asked to make your product do more, before doing that work, figure out if the planet will be better off if your product does more. If the planet will frown if your product does more, make your product do less with far less.  In that way, your customers will get a bit less, but they’ll use far fewer resources and the planet will smile. And when the planet smiles, so will the stockholders of the company that provides less with far less.

If you’re asked to improve a specific line of goodness, before doing that work, look to see if competitive technologies are also improving on that same line of goodness.  If their improvement slope is steeper than yours, you will be overtaken. Find a new line of goodness to improve, or buy the dominant company in that’s making progress with the competitive technology. Don’t wait, or sooner rather than later, they’ll buy you.

If you’re asked to make your product do more, before doing that work, look at the byproducts that will increase and how that relates to the regulatory standards. If those nasty byproducts are (or will be) regulated, future improvements will be blocked by regulatory limits.  You can argue about when those limits will be a problem, but you can’t argue that those regulatory limits will ultimately take you out by the knees. It’s a tough pill to swallow, but it’s time to look to a new technology because your existing one will soon be outlawed.

Everything changes. Nothing is static. Technologies get better, then it’s difficult to make the next improvement. Competitors get better, then it’s difficult to be better than them. Environmental constraints get tighter, then you’re legally blocked from improvements that violate those constraints. Last year’s solutions become obsolete. Last year’s analysis tools become obsolete. Last year’s best materials are no longer best. And last year’s manufacturing best processes are no longer best. That’s just how it works.

Before you allocate precious resources to do what you did last time, spend a little time to analyze the situation in a dynamic sense. What changed since last time? Has the regulatory environment changed? Have competitors made improvements? Have new competitors emerged with new technologies? Has your legacy technology run out of gas or does it still have legs? Have new tools come of age and who is using them?

Everything has a half-life – technologies, products, services, tools, processes, business models, and people. When new things are come to be, the only thing you can guarantee is that time will run out and they will run their course. Even if your business model has been successful, it has a half-life and it will die.

Success causes us to think statically, but the universe behaves dynamically. The trick is to use the resources created by our success to sow the seeds that must grow into the solutions of an uncertain future. The best time to plant a tree was fifteen years ago, and the next best time to plant one is today.

Image credit — Matthew Dillon

To increase profits, make the planet smile.

What if the most profitable thing you could do was work that reduced the rise in the earth’s temperature? What if it was most profitable to reduce CO2 emissions, improve water quality or generate renewable energy? Or what if it was most profitable to do work that indirectly made the planet smile?

What if while your competitors greenwashed their products and you radically reduced the environmental impacts of yours? And what if the market would pay more for your greener product? And what if your competitors saw this and disregarded the early warning signs of their demise? This is what I call a compete-with-no-one condition. This is where your competitors eat each other’s ankles in a race to the bottom while you raise prices and sell more on a different line of goodness – environmental goodness.  This is where you compete against no one because you’re the only one with products that make the planet smile.

The problem with an environmentally-centric, compete-with-no-one approach is you have to put yourself out there and design and commercialize new products based on this “unproven” goodness.  In a world of profits through cost, quality and speed, you’ve got to choose profits through reduced CO2, improved water quality and renewable energy. Why would anyone pay more for a more environmentally responsible product when its price is higher than the ones that work well and pollute just as much as they did last year?

When the Toyota Prius hybrid first arrived on the market, it cost more than traditional cars and its performance was nothing special. Yet it sold. Yes, it had radically improved fuel economy, but the fuel savings didn’t justify the higher price, yet it sold. Competitors advertised that the Prius hybrid didn’t make financial sense, yet it sold. With the Prius hybrid, Toyota took an environmentally-centric, compete-with-no-one approach. They made little on each vehicle or even lost money, but they did it anyway. They did the most important thing. They started.

The Toyota Prius hybrid wasn’t a logical purchase, it was an emotional one.  People bought them to make a statement about themselves – I drive a funny-shaped car that gets great gas mileage, I’m environmentally responsible, and I want you to know that. And as other companies scoffed, Toyota created a new category and owned the whole thing.

And, slowly, as Toyota improved the technology and reduced their costs, the price of the Prius dropped and they sold more. And then all the other manufacturers jumped into the race and tried to catch up. And while everyone else cut their teeth on high volume manufacturing a hybrid vehicle, Toyota accelerated.

Below is a chart of hybrid electric vehicles (hev) sold in the US from 2000 to 2017.  Each color represents a different model and the Toyota Prius hybrid is represented by the tall blue segment of each year’s stacked bar.  In 2000, Toyota sold 5,562 Prius hybrids (60% of all hevs). In 2005, they sold 107,897 Prius hybrids, 17,989 Highlander hybrids and 20,674 Lexus hybrids for a total of 209,711 hybrids (69% of all hevs). In 2007, they sold 181,221 Prius and five other hybrid models for a total of 228,593 (65% of all hevs). In 2017, sold 15 hybrid models and the nearest competitor sold 4 models. The reduction from 2008 to 2011 is due to reduced gas prices. (Here’s a link to the chart.)

 

 

The success of the Prius vehicle set off the battery wars which set the stage for the plug-in hybrids (larger batteries) and all-electric vehicles (still larger batteries).  At the start, the Prius didn’t make sense in a race-to-the-bottom way, but it made sense to people that wanted to make the planet smile.  It cost more, and it sold. And that was enough for Toyota to make profits with a more environmentally friendly product. No, Prius didn’t save the planet, but it showed companies that it’s possible to make profits while making the planet smile (a bit). And it made it safe for companies to pursue the next generation of environmentally-friendly vehicles.

The only way to guarantee you won’t make more profits with environmentally responsible products is to believe you won’t. And that may be okay unless one of your companies believes it is possible.

Here’s a thought experiment. Put yourself ten years into the future. There is more CO2 in the atmosphere, the earth is warmer, sea levels are higher, water is more polluted and renewable energy is far cheaper. Are your sales higher if your product creates more CO2, or less? Are your sales higher if your product heats the earth, or cools it? Are your sales higher if your product pollutes water, or makes it cleaner? Are your sales higher because you bet against renewable energy, or because you embraced it? Are your sales higher because you made the planet frown, or smile?

Now, with your new perspective, bring yourself back to the present and do what it takes to increase sales ten years from now.  Your future self, your children, their children, and the planet will thank you.

Image credit saeru

When it rains, don’t blame the clouds.


When it rains, you get wet.  It doesn’t matter if you get mad at the clouds, you still get wet. And if you curse the sky, you still get wet. So, why the anger and cursing? Do you really think the clouds see you’re outside and choose to rain on you? Do you think the sky is out to get you?

When someone aims snarl words at you, you get angry because you take it personally.  But, their harsh words are about them, not you.  And they’re not aiming at you; you just happen to be near them when the words jump out of their mouth.  Like the clouds don’t choose to rain on you; you just happen to be under them when their water comes out.

It’s much easier to accept that the clouds are not out to get you because the clouds are not people. It takes a lot of personal work to let someone’s snarl words pass through you. But if a screen door can do it, so can you.

The screen door lets the breeze pass through.  It doesn’t flap or flutter, it just lets the hot air pass.  It’s there when it’s time to block the bugs but not there when it’s time to let the breeze pass.  The screen door doesn’t take the breeze personally, it lets it pass through.

When someone snarls at you, be a screen door and let those words pass through. Try to remember their words are about them, not you. When the snarl words are swirling, don’t be there emotionally. Don’t own their words; don’t accept their gift. Don’t be there emotionally.

But after the storm of words dissipates, be there for them. Ask them what’s bothering them. Listen. Try to understand. Empathize.  I bet you’ll learn what’s really going on with them.

In the heat of the moment, it’s easy to take things personally.  But if you visualize them as a cloud, maybe you can weather the storm they are trying to create. Or, it may be easier to imagine yourself as a screen door and let their words pass.

Either way, cloud or screen door,  it takes practice. And either way, it can make a big difference in your happiness.

The Importance of Helping Others

When someone you care about needs help, help them. Even when you have other things to do, help them anyway.

When people ask you for help, it’s a sign they trust you.  And they trust you because you’ve demonstrated over time that your words and behaviors match.  You said you’d do A and you did A. You said you’d do B and you did B. And because you’ve made that investment in them over the years, they value you and your time.  And because they value you and your time, they don’t want to be a burden to you. And if they think you’ve got a lot on your plate, they may downplay the importance of their need for help and say things like “It’s no big deal.” or “It’s not that important.” or “It’s okay, it can wait.”.

However unforcefully, they asked for help because the need it.  It was a big deal for them to ask because they know you are busy. And their willingness to dismiss or delay, is not a sign of unimportance of their need. Rather, it’s a show of their respect for you and your time.  They desperately need your help, but care enough about you to give you any opportunity to say no.  Those are the telltale signs that it’s time to stop what you’re doing and help them. This is the time when you can make the biggest difference. Stop immediately and help them.

Your helping starts with listening and listening starts with getting ready to listen. Smile and tell them that this little chat deserves a coffee or cold drink and walk with them to get a beverage.  This critical step serves several functions. It makes it clear you are willing to make time for them and puts them at ease; it gives you time to let go of what you were working on so you can give them your full attention; and it gives you a little time to put yourself in their shoes so you will be able to hear what really going on.

By making time for them, you’ve already helped them. Someone they trust and respect stopped what they were doing and made time for them. They’re already standing two inches taller.  And, with a clear head, you actively listen and understand, they grow another two inches. Often, just telling their story is enough for them to solve their own problem. In that way, your helping starts and ends with listening.  And other times, they don’t really want you to solve their problem, they just want you to listen and empathize. And when they’re looking for more, rather than giving them answers, they’d rather you ask clarifying questions and paraphrase to demonstrate understanding.

You can’t do this for everyone, but you can do it for the people you care about most.  Sure, you have to scamper to catch up on your own work, but it’s worth it.  By helping them you help yourself twice – once from happiness that comes from helping someone you care about and twice from the joy that comes from watching them do the same for people they care about.

Our work is difficult and our lives are busy. But our work gets easier when we get and give help. And even with our always-on, always-connected culture, life is about building meaningful connections. How can your life be too busy for that?

Maybe we have it backwards. What if meaningful connections aren’t something we create so we can do our work better? What if we think of work as nothing more than a mechanism to create meaningful connections?

Image credit – Jlhopgood.

How mature is your technology?

As a technologist it’s important to know the maturity of a technology.  Like people, technologies are born, they become children, then adolescents, then adults and then they die.  And like with people, the character and behavior of technologies change as they grown and age.  A fledgling technology may have a lot of potential, but it can’t pay the mortgage until it matures.  To know a technologies level of maturity is to know when it’s premature to invest, to know when it’s time to invest, to know when to ride it for all it’s worth and time to let it go.

Google has a tool called Ngram Viewer that performs keyword searches of a vast library of books and returns a plot of how frequently the word was found in the books.  Just type the word in the search line, specify the years (1800-2007) and look at the graph.

Below is a graph I created for three words: locomotive, automobile and airplane. (Link to graph.) If each word is assumed to represent a technology, the graph makes it clear when authors started to write about the technologies (left is earliest) and how frequently it was used (taller is more prevalent).  As a technology, locomotives came first, as they were mentioned in books as early as 1800.  Next came the automobile which hit the books just before 1900.  And then came the airplane which first showed itself in about 1915.

In the 1820s the locomotives were infants.  They were slow, inefficient and unreliable.  But over time they matured and replaced the Pony Express.  In the late 1890s the automobiles were also infants and also slow, inefficient and unreliable. But as they matured, they displaced some of the locomotives. And the airplanes of 1915 were unsafe and barely flight-worthy.  But over time they matured and displaced the automobiles for the longest trips.

[Side note – the blip in use of the word in 1940s is probably linked to World War II.]

But for the locomotive, there’s a story with a story.  Below is a graph I created for: steam locomotive, diesel locomotive and electric locomotive.  After it matured in the 1840s and became faster and more efficient, the steam locomotive displaced the wagon trains.  But, as technology likes to do, the electric locomotive matured several decades after it’s birth in 1880 and displaced it’s technological parent the steam locomotive.  There was no smoke with the electric locomotive (city applications) and it did not need to stop to replenish it’s coal and water.  And then, because turn-about is fair play, the diesel locomotive displaced some of the electric locomotives.

The Ngram Viewer tool isn’t used for technology development because books are published long after the initial technology development is completed and there is no data after 20o7.  But, it provides a good example of how new technologies emerge in society and how they grow and displace each other.

To assess the maturity of the youngest technologies, technologists perform similar time-based analyses but on different data sets.  Specialized tools are used to make similar graphs for patents, where infant technologies become public when they’re disclosed in the form of patents.  Also, special tools are used to analyze the prevalence of keywords (i.e., locomotives) for scientific publications.  The analysis is similar to the Ngram Viewer analysis, but the scientific publications describe the new technologies much sooner after their birth.

To know the maturity of the technology is to know when a technology has legs and when it’s time to invent it’s replacement.  There’s nothing worse than trying to improve a mature technology like the diesel locomotive when you should be inventing the next generation Maglev train.

Image credit – kanegen

Even entrepreneurial work must fit with the brand.

To meet ever-increasing growth objectives, established companies want to be more entrepreneurial.  And the thinking goes like this – launch new products and services to create new markets, do it quickly and do it on a shoestring.  Do that Lean Startup thing.  Build minimum viable prototypes (MVPs), show them to customers, incorporate their feedback, make new MVPs, show them again, and then thoselaunch.

For software products, that may work well, largely because it takes little time to create MVPs, customers can try the products without meeting face-to-face and updating the code doesn’t take all that long.  But for products and services that require new hardware, actual hardware, it’s a different story.  New hardware takes a long time to invent, a long time to convert into an MVP, a long time to show customers and a long time to incorporate feedback.  Creating new hardware and launching quickly in an entrepreneurial way don’t belong in the same sentence, unless there’s no new hardware.

For hardware, don’t think smartphones, think autonomous cars.  And how’s that going for Google and the other software companies? As it turns out, it seems that designing hardware and software are different.  Yes, there’s a whole lot of software in there, but there’s also a whole lot of new sensor systems (hardware).  And, what complicates things further is that it’s all packed into an integrated system of subsystems where the hardware and software must cooperate to make the good things happen.  And, when the consequences of a failure are severe, it’s more important to work out the bugs.

And that’s the rub with entrepreneurship and an established brand.  For quick adoption, there’s strong desire to leverage the established brand – GM, Ford, BMW – but the output of the entrepreneurial work (new product or service) has to fit with the brand.  GM can’t launch something that’s half-baked with the promise to fix it later. Ford can come out with a new app that is clunky and communicates intermittently with their hardware (cars) because it will reflect poorly on all their products.  In short, they’ll sell fewer cars.  And BMW can’t come out with an entrepreneurial all-electric car that handles poorly and is slow off the start.  If they do, they’ll sell fewer cars.  If you’re an established company with an established brand, the output of your entrepreneurial work must fit with the established brand.

If you’re a software startup, launch it when it’s half-baked and fix it later, as long as no one will die when it flakes out.  And because it’s software, iterate early and often. And, there’s no need to worry about what it will do to the brand, because you haven’t created it yet.  But if you’re a hardware startup, be careful not to launch before it’s ready because you won’t be able to move quickly and you’ll be stuck with your entrepreneurial work for longer than you want.  Maybe, even long enough to sink the brand before it ever learned to swim.  Developing hardware is slow.  And developing robust hardware-software systems is far slower.

If you’re an established company with an established brand, tread lightly with that Lean Startup thing, even when it’s just software.  An entrepreneurial software product that works poorly can take down the brand, if, of course, your brand stands for robust, predictable, value and safety.  And if the entrepreneurial product relies on new hardware, be doubly careful.  If it goes belly-up, it will be slow to go away and will put a lot of pressure on that wonderful brand you took so long to build.

If you’re an established brand, it may be best to buy your entrepreneurial products and services from the startups that took the risk and made it happen.  That way you can buy their successful track record and stand it on the shoulders of your hard-won brand.

Image credit – simpleinsomnia

With novelty, less can be more.

When it’s time to create something new, most people try to imagine the future and then put a plan together to make it happen.  There’s lots of talk about the idealize future state, cries for a clean slate design or an edict for a greenfield solution.  Truth is, that’s a recipe for disaster. Truth is, there is no such thing as a clean slate or green field. And because there are an infinite number of future states, it’s highly improbable your idealized future state is the one the universe will choose to make real.

To create something new, don’t look to the future. Instead, sit in the present and understand the system as it is. Define the major elements and what they do.  Define connections among the elements.  Create a functional diagram using blocks for the major elements, using a noun to name each block, and use arrows to define the interactions between the elements, using a verb to label each arrow. This sounds like a complete waste of time because it’s assumed that everyone knows how the current state system behaves.  The system has been the backbone of our success, of course everyone knows the inputs, the outputs, who does what and why they do it.

I have created countless functional models of as-is systems and never has everyone agreed on how it works.  More strongly, most of the time the group of experts can’t even create a complete model of the as-is system without doing some digging. And even after three iterations of the model, some think it’s complete, some think it’s incomplete and others think it’s wrong. And, sometimes, the team must run experiments to determine how things work.  How can you imagine an idealized future state when you don’t understand the system as it is?  The short answer – you can’t.

And once there’s a common understanding of the system as it is, if there’s a call for a clean sheet design, run away.  A call for a clean sheet design is sure fire sign that company leadership doesn’t know what they’re doing.  When creating something new it’s best to inject the minimum level of novelty and reuse the rest (of the system as it is).  If you can get away with 1% novelty and 99% reuse, do it.  Novelty, by definition, hasn’t been done before. And things that have never been done before don’t happen quickly, if they happen at all. There’s no extra credit for maximizing novelty. Think of novelty like ghost pepper sauce – a little goes a long way.  If you want to know how to handle novelty, imagine a clean sheet design and do the opposite.

Greenfield designs should be avoided like the plague. The existing system has coevolved with its end users so that the system satisfies the right needs, the users know how to use the system and they know what to expect from it.  In a hand-in-glove way, the as-is system is comfortable for end users because it fits them.  And that’s a big deal.  Any deviation from baseline design (novelty) will create discomfort and stress for end users, even if that novelty is responsible for the enhancement you’re trying to deliver.  Novelty violates customer expectations and violating customer expectations is a dangerous game. Again, when you think novelty, think ghost peppers. If you want to know how to handle novelty, imagine a green field and do the opposite.

This approach is not incrementalism.  Where you need novelty, inject it.  And where you don’t need it, reuse. Design the system to maximize new value but do it with minimum novelty.  Or, better still, offer less with far less. Think 90% of the value with 10% of the cost.

Image credit – Laurie Rantala

If you’re not learning, what are you doing?

You can’t learn until you acknowledge you don’t understand.

No one knows everything. No sense pretending, especially if you want to learn.

If you don’t know what you want to learn, any learning will do.

If you’re not surprised, the learning could have been deeper.

When you learn it won’t work it’s not failure, it’s learning.

When assumptions are formalized, it’s possible to learn they’re wrong.

Hypotheses are for the laboratory and learning objectives are for everywhere else.

Where learning is useful, relearning is wasteful.

When is it best to learn it won’t work? Then why do wait so long to learn it?

Last year’s learning is out of fashion and it’s time to freshen up your wardrobe.

If you’re surprised, congratulations.

Where doing is activity, learning is progress.

When you’re an expert, you’ve got to learn to unlearn.

Learning quickly is good, but learning the right thing is better.

The best thing to learn is how to learn.

Image credit – NASA Goddard Space Flight Center

You can’t control much with innovation, but you can control how you allocate resources.

In business, the only direct lever to pull is resource allocation. The people are already on the books, just change what they work on. But pulling that off is difficult.

No need to wait for new hires, just move resources from one project to another.  Stop project A and start project B.  Simple, right? Not so much. Emotional attachment causes project A to defend their resources and project B to complain the resources haven’t moved. Resources will be slow to flow.

No need to take the time to develop new capability, just reassign capable resources from business 1 to business 2 and watch progress unfold. No problem, right? Wrong. There’s immense organizational drama from prioritizing one business over another. Again, the pace of resource flow will be glacial.

And with innovation, the drama is doubled. It’s threatening when resources flow from mainstream projects with tangible (but small) returns to more speculative projects with highly uncertain returns.  But that’s what must happen.

If there’s a mismatch between the words and resource allocation, believe resource allocation.

If the innovation banners are plastered on all the walls and everyone has the tee shirt, yet the resources don’t flow to the innovation work, it’s an innovation farce. Run away.  Here’s what the four HOWs of innovation look like through the lens of resource allocation.

How To Start. Define the yearly funding level for innovation resources that is independent of the yearly planning process.  In short, create an innovation tax at a fixed percentage of revenue.  This gets funded before anything else.  It’s the pay-yourself-first approach to innovation. And when the money is allocated and the resources flow, there’s no need for banners and tee shirts.  Alignment comes with the money.

Next, choose a leader to put in place standing processes to continuously funnel project ideas into a common hopper.  One pile for all ideas – university research, mergers and acquisitions, voice of the technology, voice of the customer (direct observation and listening), patents and YouTube videos of purposeful misuse of your product.

How To Choose. Define funding levels across the various flavors of projects in the portfolio and set up a standing meeting for senior leaders to choose the best projects. This selection process is light on analysis and heavy on judgment, so allocate leaders who are not afraid to use good judgement. And set up a standing meeting with the CEO to pace the selection work (make sure senior leaders allocate their time.)

How To Execute. Internal, external, or partner, the work defines the right way to allocate resources.  Based on the work, choose the right organization and the best leader and fully staff the project before considering a second project.  The most popular failure mode is running too many projects in parallel and getting none done.  The second popular failure mode forgetting to fund the support resources needed for innovation.  Allocate money for tools, time, training and a teacher. Establish a standing meeting where senior leaders review the projects.  This must be outside the review process normal projects.

How To Improve. No one ever allocates time to do this.  To get the work done, trick the system and include the work as a standing agenda item in the How To Execute review meetings.  Find a problem, fix a problem. Improve as you go.

Allocate the best resources to the best projects and make sure senior leaders allocate time to the innovation work. The best predictors of successful innovation are the character of the fully-staffed, fully-funded projects and the character of people that run them.

Image credit – conorwithonen

The Certainty of Uncertainty

Eye Of The StormWhen the output cannot be predicted, that’s uncertainty.  And if there’s one thing to be certain of it’s uncertainty is always part of the equation.

With uncertainty, the generally accepted practice is minimization, and the method of choice is to control inputs.  The best example is a high volume manufacturing process where inputs are controlled to reduce variation of the output (or reduce the uncertainty around goodness).  Six Sigma tightens the screws on suppliers, materials, process steps, assembly tools and measurement gear so the first car off the production line is the same as the last one.  That way, customers are certain to get what they’re promised.  Minimization of uncertainty makes a lot of sense in the manufacturing analogy.

But there’s no free lunch with uncertainty, and the price of all this control is inflexibility.  The manufacturing process can do only what it’s designed to do – to make what it was designed to make – and no more.  And it can provide certainty of output only over a finite input range.  Within the appropriate range of inputs there is certainty, but outside that range there is uncertainty.  Even in the most well defined, highly controlled processes where great expense is taken to reduce uncertainty, there is uncertainty.  Even the best automotive assembly lines can be disrupted by things like tsunamis, earthquakes, epidemics and labor strikes (100% certainty doesn’t exist).  But still, in the manufacturing context minimization of uncertainty is a sound strategy.

When the intent of a process is to do things that have never been done and to bring new things to life, minimization of uncertainty is directionally incorrect.  Said a different way, creativity and innovation demand uncertainty.  More clearly – if there’s no uncertainty in the trenches, there’s no innovation.

The manufacturing analogy has been pushed too far from the factory.  Just as Six Sigma has eliminated variation (and uncertainty) from things it shouldn’t (creativity work), lean and its two uncertainty killers (best practices and standard work) have been jammed into the gears of innovation and gummed up the works.

Standard work and best practices were invented to reduce variation in how work is done with the objective of, you guessed it, reducing uncertainty. The idea is to continuously improve and converge on the right recipe (sequence of operations or process steps) so the work is done the same way every-day-all-day.  By definition, innovation work (the process steps) is never done the same way twice.  The rule with best practices is simple – it should be reused every time there’s a need for that exact process.  That makes sense.  But it makes no sense to use a best practice when a process is done for the first time.

[Okay, the purists say that all transactional elements of innovation should follow standard work, and theoretically that’s right.  But practically, the backwash of standard work, even when applied to transactional work, infects the psyche of the innovator and reduces uncertainty where uncertainty should be bolstered.]

Uncertainty is an important part of innovation, but it should not be maximized (it’s as inappropriate as minimizing).  And there is no best practice for calculating the right amount.  To strike a good balance, hold onto the fact that uncertainty and flexibility are a matched pair, and when doing something for the first time flexibility is a friend.  And when standard work and best practices are imposed in the name of innovation efficiency, remember it’s far more important to have innovation effectiveness.

Image credit – NMK Photography

 

Innovation’s Double Helix

DNA towerA technology without a market is as valuable as a market without a technology – they’re both worthless. At one end of the spectrum you have something interesting running in the lab and at the other you have an interesting insight around a new market. But one won’t do, and from either end of the rainbow your quest is to find the pot of gold at the other end.

Scenario A – As a marketing leader you went out into the market, heard the unhearable, saw the unseeable and the gears of your mind gnashed and clunked until it brought into being a surprising insight. Now it’s time to come back to the technical community in search of a technology. For this clarity is key, but for technologists the voice of the customer is a foreign language, and worse, you’ve invented a new dialect.

Step 1. Dig up marketing literate for an existing product that’s the closest to satisfying your surprising market insight.

Step 2. In front of the technologists mark up the existing marketing literature so it satisfies the surprising insight. (Think – same as the old product, but different.) Starting with something they know and building from there helps the technologists see the newness from the grounded context of existing products and technologies.

Step 3. Then, with the technologists, draw a hand sketch of the customer using the new product in a new way, then underneath the sketch write a single sentence that describes the valuable customer outcome (from the customer’s perspective).

Step 4. Together with the technologists define the new design elements of the prouct to make the product perform like the sketch and satisfy the valuable customer outcome.

Step 5. With the technologists go out to the lab and make a prototype of the new design element, bolt it on to an existing product platform and use the product in the manner described in your sketch.  If it doesn’t work as it should, modify the prototype until it does.

Step 6. Take the prototype to the market and ask them if it delivers on the valuable customer outcome. If it doesn’t, modify the prototype until it does. And when it does, launch it.

Scenario B – As a technologist you went out into the lab, thought the unthinkable, pondered the impossible and the gears of your mind gnashed and clunked until it brought into being a surprising technology. Now it’s time to come back to the marketing community in search of a market. For this clarity is key, but for marketing the voice of the technology is a foreign language, and worse, like your counterpart in Scenario A, you’ve invented a new dialect.

Step 1. Dig up the product spec for an existing product that’s closest to your new technology.

Step 2. In front of the marketers mark up the product spec so it describes the functionality of the new technology. (Think – same as the old product, but different.)  Starting with something they know and building from there helps the marketers see the newness from the grounded context of existing products and technologies.

Step 3. Again in front of the marketers, define the new elements of the technology that make the product perform like it does.

Step 4. With the marketers, draw a hand sketch of the customer using the new product in a new way, then underneath the sketch write a single sentence that describes the valuable customer outcome (from the customer’s perspective).

Step 5. Together with the marketers and the prototype go out to the field and let customers use it as THEY see fit. If they use it in the manner described in your sketch, you’ve identified a potential customer segment. If they don’t, modify the sketch and valuable outcome sentence until it matches their use, or seek out other customers who use it like the sketch.

Step 6. Decide on the most interesting product use and customer outcome, and take the prototype to the target customers. Ask them if it delivers on the valuable customer outcome. If it doesn’t, investigate different customer segments until it does. And when it does, launch it.

Scenarios A and B are contrived. In scenario A, product use and valuable customer outcomes are static and the technology changes to fit them. In Scenario B, it’s reversed – static technology and dynamic product use and customer outcomes.  While the scenarios are helpful to see the work from two perspectives and define the end points, that’s not how it happens.

Innovation is always a clustered-jumble of the two scenarios. In fact it’s more like a double helix where the customer strand winds around the technology and the technology strand winds around the customer. One strand takes the lead and mutates the other, which, in turn, spirals learning in unforseen directions.

There’s no getting around it – market and technology co-evolve. There’s no best practice, there’s no best orgainizational structure, and breaking things down the smallest elements won’t get you there.

Instead of spending time and money sequencing the innovation genome, take your cue from nature – try stuff and do more of what worked and less of what didn’t.

And remember the cardinal rule – the organization with the best genes wins.

Image credit – kool_skatkat

Mike Shipulski Mike Shipulski
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