Shipulski On Design

Innovation, as a word, has become too big for its own good, and, as a word, is almost useless. Sure, it can be used to enable magical reinvention of business models and revolutionary products and technologies, but it can also be used to rationalize the rehash work we were going to do anyway. The words that send angry chills down the back of the would-be-innovative company – “We’re already doing it.”

When company leaders talk about doing more innovation, there’s a lot of pressure in the organization to point to innovative things already being done. The organization misinterprets the desire for more innovation as a negative commentary on their work. The mental dialog goes like this – We’re good at our work, we’re working as hard as we can, and we’re doing all we can to meet objectives – hey, look at this innovative stuff we’re doing. Clearly this isn’t what company leaders are looking for, but the word does have that influence.

What can feel better is to describe what is meant by innovation. Wherever we are, whatever successes we’ve had, we want to change our behaviors to create new, more profitable business models; create new products and technologies that obsolete our best, most profitable ones; and change our behaviors to create new, more profitable markets. The key is to acknowledge that our existing behaviors are the very thing that has created our success (and thank them for it), and to acknowledge the desire to build on our success by obsoleting it. When we ask for more innovation, we’re asking for new behaviors to dismantle our current day success behind us to create the next level of success.

There’s a tight link to innovation and failure – risk, learning, experimentation – but there’s a missing link with success. Acknowledgement of success helps the organization retain its self worth and helps them feel good about trying new stuff. However, even still, success is huge deterrent to innovation. Company success will retain the behaviors that created it, and more strongly, as new behaviors are injected, the antibodies of success will reject them. Our strength becomes our weakness.

Strong technologies become anchors to themselves; successful, stable, long-running markets hold tightly to resources that created them; and time-tested business models are above the law. New behaviors almost don’t stand a chance.

Fear of losing what we have is the number one innovation blocker. Where failure blocks innovation narrowly in the blast zone, success smears a thick layer of inaction across the organization. What’s most insidious, since we celebrate success, since we laud customer focus, since we track and reward efficiently doing what we’ve done, we systematically thicken and stiffen the layer that gums up innovation.

Instead of starting with a call-to-arms for innovation, it’s best to define company values, mission, and strategic objectives. Then, and only then, define innovation as the way to get there. First company objectives, then innovation as the path.

Innovation, as a word, isn’t important. What’s important are the new behaviors that will wrestle success to the ground, and pin it.

The technical stuff is the easy part. Technical systems respond predictably, but people don’t.

There’s nothing worse than solving the wrong problem, so before you start solving you’ve better done a whole lot of defining.

There is no exact answer; engineering is all about judgment.

Organizational structure is important.  Whatever the structure, see its strengths and make them work for you.  If you try to fight it, it will eat you.

Innovation isn’t about ideas, innovation is about commercializing ideas.

Engineering analysis can win minds, but not hearts. And hearts govern minds.

The engineer’s role is not to minimize risk; it’s to understand the commercial reward and take risk accordingly.

What people believe is far more powerful than what they think.

New technology threatens status quoers, and, in turn, they block it.

There is no problem unless someone important thinks there’s one.

All technical systems are really human systems masquerading as technical systems.

If you let it, fear dominates. Be afraid and do it anyway.  But along the way, keep in mind that others are too afraid to try.

Engineering is not sane and rational; engineering is about people.

I like Dave Snowden’s thinking on innovation – starvation, pressure, and perspective shift. Here’s what it means to me:

Starvation – Left to our own, we’ll do as we did before. Starvation of resources pushes thinking away from stale, worn paths. Almost in reverse, define what you don’t want, then construct intelligent constraints (the most difficult part of the whole deal) so it’s out of the design space. Constrain the team so they can’t use the most expensive material; constrain the team so they can’t use the same old technology; constrain them so they can’t use the tried and true business model. It’s reverse thinking, but constraints – telling them what they can’t do – frees up design space. Constraints say “Do anything you want, except this.” which constrains far less than specifications. Constrain them to free them.

Pressure – Left to our own, we’ll reuse old thinking. Time pressure drags thinking out of the ruts of our success. Define creative constraints then, to create pressure, give the team insufficient time to think it through. Force them to swim differently with the problem.  The best way I know is to explain the constraints then give the team fifteen minutes to build a prototype. (Yes, fifteen.) The prototype is non-functional, and can be made from whatever is on hand – cardboard, clay, duct tape, or packing peanuts. The short time frame creates pressure, and the pressure extrudes different thinking.  Building a prototype shifts from learning-in-the-brain to learning-with-the-hands. And since hands learn differently than brains, new thinking is cast.

Perspective Shift – Left to our own, we’ll do a remake. Perspective shift moves us to a different place to create a healthy disrespect for today’s thinking. Seen in the right new light, our successes should look problematic. (From the front a skunk isn’t so bad, but from behind things aren’t so good.) Building a bridge to a new perspective can shift things a little, but for a tectonic shift, formalize the consequences of inaction. Think – “If we don’t do this, a very bad thing will happen.” Perspective shift is all about creating action in a new direction.

You won’t get it right the first time, but, no matter.  The real enemy is inaction.

The system is big and complex and its output is outside your control. Trying to control these outputs is a depressing proposition, yet we’re routinely judged (and judge ourselves) on outputs.  I think it’s better to focus on system inputs, specifically your inputs to the system.

When the system responds with outputs different than desired, don’t get upset. It’s nothing personal. The system is just doing its job. It digests a smorgasbord of inputs from many agents just like you and does what it does. Certainly it’s alive, but it doesn’t know you. And certainly it doesn’t respond differently because you’re the one providing input. The system doesn’t take its output personally, and neither should you.

When the system’s output is not helpful, instead of feeling badly about yourself, shift your focus from system output to the input you provide it. (Remember, that’s all you have control over.) Did you do what you said you’d do? Were you generous? We’re you thoughtful? We’re you insightful? Did you give it your all or did you hold back? If you’re happy with the answers you should feel happy with yourself. Your input, your behavior, was just as it was supposed to be.  Now is a good time to fall back on the insightful grade school mantra, “You get what you get, and you don’t get upset.”

If your input was not what you wanted, then it’s time to look inside and ask yourself why. At times like these it’s easy to blame others and outside factors for our behavior. But at times like these  we must own the input, we must own the behavior. Now, owning the behavior doesn’t mean we’ll behave the same way going forward, it just means we own it. In order to improve our future inputs we’ve got to understand why we behaved as we did, and the first step to better future inputs is owning our past behavior.

Now, replace “system” with “person”, and the argument is the same. You are responsible for your input to the person, and they are responsible for their output (their response). When someone’s output is nonlinear and offensive, you’re not responsible for it, they are. Were you kind? Thoughtful? Insightful? If yes, you get what you get, and you don’t get upset. But what if you weren’t? Shouldn’t you feel responsible for their response? In a word, no. You should feel badly about your input – your behavior – and you should apologize. But their output is about them. They, like the system, responded the way they chose. If you want to be critical, be critical of your behavior. Look deeply at why you behaved as you did, and decide how you want to change it. Taking responsibility for their response gets in the way of taking responsibility for your behavior.

With complex systems, by definition it’s impossible to predict their output. (That’s why they’re called complex.) And the only way to understand them is to perturb them with your input and look for patterns in their responses. What that means is your inputs are well intended and ill informed. This is an especially challenging situation for those of us that have been conditioned (or born with the condition) to mis-take responsibility for system outputs. Taking responsibility for unpredictable system outputs is guaranteed frustration and loss of self-esteem. And it’s guaranteed to reduce the quality of your input over time.

When working with new systems in new ways, it’s especially important to take responsibility for your inputs at the expense of taking responsibility for unknowable system outputs. With innovation, we must spend a little and learn a lot. We must figure out how to perturb the system with our inputs and intelligently sift its outputs for patterns of understanding. The only way to do it is to fearlessly take responsibility for our inputs and fearless let the system take responsibility for its output.

We must courageously engineer and own our behavioral plan of attack, and modify it as we learn. And we must learn to let the system be responsible for its own behavior.

They say job satisfaction is important for productivity and quality. The thinking goes something like this: A happy worker is a productive one, and a satisfied worker does good work. This may be true, but it’s not always the best way.

I think we may be better served by a therapeutic dose of job dissatisfaction. Though there are many strains of job satisfaction, the most beneficial one spawns from a healthy dissatisfaction with our success. The tell-tale symptom of dissatisfaction is loneliness, and the invasive bacterium is misunderstanding. When the disease is progressing well, people feel lonely because they’re misunderstood.

Recycled ideas are well understood; company dogma is well understood; ideas that have created success are well understood. In order to be misunderstood, there must be new ideas, ideas that are different. Different ideas don’t fit existing diagnoses and create misunderstanding which festers into loneliness. In contrast, when groupthink is the disease there is no loneliness because there are no new ideas.

For those that believe last year’s ideas are good enough, different ideas are not to be celebrated. But for those that believe otherwise, new ideas are vital, different is to be celebrated, and loneliness is an important precursor to innovation.

Yes, new ideas can grow misunderstanding, but misunderstanding on its own cannot grow loneliness. Loneliness is fueled by caring, and without it the helpful strain of loneliness cannot grow. Caring for a better future, caring for company longevity, caring for a better way – each can create the conditions for loneliness to grow.

When loneliness is the symptom, the prognosis is good. The loneliness means the organization has new ideas; it means the ideas are so good people are willing to endure personal suffering to make them a reality; and, most importantly, it means people care deeply about the company and its long term success.

I urge you to keep your eye out for the markers that define the helpful strain of loneliness. And when you spot it, I hope you will care enough to dig in a little. I urge you think of this loneliness as the genes of a potentially game-changing idea.  When ideas are powerful enough to grow loneliness, they’re powerful enough to move from evolutionary into revolutionary.

How long will it take? The short answer – same as last time. How long do we want it to take? That’s a different question altogether.

If the last project took a year, so will the next one. Even if you want it to take six months, it will take a year. Unless, there’s a good reason it will be different. (And no, the simple fact you want it to take six months is not a good enough reason in itself.)

Some good reasons it will take longer than last time: more work, more newness, less reuse, more risk, and fewer resources. Some good reasons why it will go faster: less work, less newness, more reuse, less risk, more resources. Seems pretty tight and buttoned-up, but things aren’t that straight forward.

With resources, the core resources are usually under control.  It’s the shared resources that are the problem. With resources under their control (core resources) project teams typically do a good job – assign dedicated resources and get out of the way. Shared resources are named that way because they support multiple projects, and this is the problem. Shared resources create coupling among projects, and when one project runs long, resource backlogs ripple through the other projects. And it gets worse. The projects backlogged by the initial ripple splash back and reflect ripples back at each other. Understand the shared resources, and you understand a fundamental dynamic of all your projects.

Plain and simple – work content governs project timelines. And going forward I propose we never again ask “How long will it take?” and instead ask “How is the work content different than last time?” To estimate how long it will take, set up a short face-to-face meeting with the person who did it last time, and ask them how long it will take. Write it down, because that’s the best estimate of how long it will take.

It may be the best estimate, but it may not be a good one. The problem is uncertainty around newness. Two important questions to calibrate uncertainty: 1) How big of a stretch are you asking for? and 2) How much do you know about how you’ll get there? The first question drives focus, but it’s not always a good predictor of uncertainty.  Even seemingly small stretches can create huge problems. (A project that requires a 0.01% increase in the speed of light will be a long one.) What matters is if you can get there.

To start, use your best judgment to estimate the uncertainty, but as quickly as you can, put together a rude and crude experimental plan to reduce it. As fast as you can execute the experimental plan, and let the test results tell you if you can get there. If you can’t get there on the bench, you can’t get there, and you should work on a different project until you can.

The best way to understand how long a project will take is to understand the work content. And the most important work content to understand is the new work content. Choose several of your best people and ask them to run fast and focused experiments around the newness. Then, instead of asking them how long it will take, look at the test results and decide for yourself.

Our productivity-by-the-minute culture is killing us.

In business speed is king, and with it comes our short-sighted drag racing behavior. As we pull to the starting light our big engines shake and rumble, our pipes shoot flames, and our tires smoke. We stomp the throttle, accelerate to mach 1, kill the engine, and throw the chute. A quarter mile covered in record time, and champagne celebration.

But, because the pace was beyond sustainable, we can’t race again until the damage is repaired. Because it ran too hot the pit crew must pull the engine, because the torque was so outrageous the transmission must be swapped, and because the vibrations were so severe the frame must be checked for metal fatigue. But this is just another opportunity for more racing.

We externalize the setup, design the process for quick changeover, reduce waste, and focus on the vital few. No matter the pit crew doesn’t get sleep, or their families miss them. Engine swapped in record time, and obligatory celebration.

Sure, going fast is good. But business can’t be a series of back-to-back sprints. Plain and simple – people cannot sprint every day, all day. Business should be thought of as a marathon. A marathon run at a respectable pace, but a pace we’ve trained for, a pace we can sustain. With a torn hamstring the fastest sprinter makes no forward progress, and even the slowest marathoner is faster.

Sprint, yes, but only when it makes sense. Sprint, yes, but provide recovery time. Sprint, yes, but not if it will do personal harm.

Increasing speed is directionally correct, but our time horizon is too short. Instead of optimizing over a six second quarter mile, we should optimize for a marathon.

In our chase for speed’s euphoric high, our drug of choice is efficiency. Like speed, efficiency is good. But, just as speed’s time horizon is too short, efficiency’s scale of optimization is too small. We optimize locally and the net result is global sub-optimization. This is clearly an artifact of what we measure. Clearly, we must measure differently.

Every day we chase the dopamine high of efficiency, but ignore the mind-blowing power of effectiveness. If you sprint day after day, you may be efficient, but you’re definitely ineffective. Sprint every day for a month, sleep four hours a night, and spend six weeks away from your family. Are you really in a good position to make a make-or-break decision? How can you possibly be effective? I wish Finance knew how to measure effectiveness as well as it does efficiency.

As a company leader, stop sprinting. As a company leader, stop optimizing locally. As a company leader, stop focusing on efficiency. As a company leader, demonstrate and reward effectiveness. As a company leader, go home and spend time with your family.

We often forget, but regardless of industry, technology, product, or service, it’s a battle for hearts and minds.

The building blocks of business are processes, machines, software, and computers, but people are the underpinning.  The building blocks respond in a repeatable way – same input, same output – and without judgment.  People, however, not so much.

People respond differently depending on delivery – even small nuances can alter the response, and when hot buttons are pushed responses can be highly nonlinear. One day to the next, people’s responses to similar input can be markedly different.  Yet we forget people are not like software or machines, and we go about our work with expectations people will respond with highly rational, highly linear,  A-then-B logic.  But in a battle between rational and emotional, it’s emotional by a landslide.

Thankfully, we’re not just cogs in the machine.  But for the machine to run, it’s imperative to win the hearts and minds. (I feel a little silly writing this because it’s so fundamental, but it needs to be written.)  And it’s hearts then minds.  The heart is won by emotion, and once the emotional connection is made, the heart tells the mind to look at the situation and construct logic to fit.  The heart clears the path so the mind can in good conscience come along for the ride.

Hearts are best won face-to-face, but, unfortunately today’s default mode is PowerPoint-to-face.  We don’t have to like it, but it’s here to stay.  And so, we must learn to win hearts, to make an emotional connection, to tell stories with PowerPoint.

To tell a story with PowerPoint, we must bring ourselves to the forefront and send PowerPoint to the back.  To prevent ourselves from hiding behind our slides, take the words off and replace them with a single, large image – instead of a complex word-stuffed jumble, think framed artwork.  While their faces look at the picture, tell their hearts a story.  Eliminate words from the slides and the story emerges.

[There’s still a place for words, but limit yourself to three words per slide, and make them big – 60 point font. And keep it under ten slides.   More than that and you haven’t distilled the story in your head.]

Whatever business you’re in, you’re in the people business.  Win hearts and minds follow.  And so do profits.

That’s a best practice. Look, there’s another one. We need a best practice. What’s the best practice?  Let’s standardize on the best practice.  Arrrgh.  Enough, already, with best practices.

There are no best practices, only actions that have worked for others in other situations.  Yet we feverishly seek them out, apply them out of context, and expect they’ll solve a problem unrelated to their heritage.

To me, the right practices are today’s practices.  They’re the base camp from which to start a journey toward new ones.  To create the next evolution of today’s practices, for new practices to emerge, a destination must be defined. This destination is dictated by problems with what we do today.  Ultimately, at the highest level, problems with our practices are spawned by gaps, shortfalls, or problems in meeting company objectives.  Define the shortfall – 15% increase in profits – and emergent practices naturally diffuse to the surface.

There are two choices: choose someone else’s best practices and twist, prune, and bend them to fit, or define the incremental functionality you’d like to create and lay out the activities (practices) to make it happen. Either way, the key is starting with the problem.

The important part – the right practices, the new activities, the novel work, whatever you call it, emerges from the need.

It’s a problem hierarchy, a problem flow-down.  The company starts by declaring a problem – profits must increase by 15% – and the drill-down occurs until a set of new action (new behaviors, new processes, new activities) is defined that solves the low level problems. And when the low level problems are solved, the benefits avalanche to satisfy the declared problem – profits increased by 15%.

It’s all about clarity — clearly define the starting point, clearly define the destination, and express the gaps in a single page, picture-based problem statements.  With this type of problem definition, you can put your hand over your mouth, with the other hand point to the picture, and everyone understands it the same way. No words, just understanding.

And once everyone understands things clearly, the right next steps (new practices) emerge.

If you want to learn, to really learn, experiment.

But I’m not talking about elaborate experiments; I’m talking about crude ones. Not simple ones, crude ones.

We were taught the best experiments maximize learning, but that’s dead wrong. The best experiments are fast, and the best way to be fast is to minimize the investment.

In the name of speed, don’t maximize learning, minimize the investment.

Let’s get right to it. One of the best tricks to minimize investment is to minimize learning – learning per experiment, that is. Define learning narrowly, design the minimum experiment, and run the trial. Learning per trial is low, but learning per month skyrockets because the number of trials per month skyrockets. But it gets better. There’s an interesting learning exponential at work. The first trial informs the second which shapes the third. But instead of three units of learning, it’s cubic. And minimizing learning doesn’t just half the time to run a trial, it reduces it by 100 or more. It’s earning to the hundredth power.

Another way to minimize investment is to minimize resolution. Don’t think nanometers, think thumbs up, thumbs down. Design the trial so the coarsest measuring stick gives an immediate and unambiguous response. There’s no investment in expensive measurement gear and no time invested in interpretation of results. Think sledgehammer to the forehead.

A third way to minimize investment is to evaluate relative differences. The best example is the simple, yet powerful, A-B test . Run two configurations, decide which is better, and run quickly in the direction of goodness.  No need to fret about how much better, just sprint toward it.  The same goes for trial 1 versus trial 2 comparisons. Here’s the tricky algorithm: If trial 2 is better, do more of that.  And the good news applies here too –  the learning exponential is still in play. Better to the hundredth power, in record time.

I don’t care what norms you have to bend or what rules you have to break. If you do one thing, run more trials.

But don’t take my word for it. Dr. Seuss had it right:

And I would run them in a boat!
And I would run them with a goat…
And I will run them in the rain.
And in the dark. And on a train.
And in a car. And in a tree.
They are so good so good you see!

We all want more innovation, though sometimes we’re not sure why. Turns out, the why important.

We want to be more innovative. That’s a good vision statement, but it’s not actionable. There are lots of ways to be innovative, and it’s vitally important to figure out the best flavor. Why do you want to be more innovative?

We want to be more innovative to grow sales. Okay, that’s a step closer, but not actionable. There are many ways to grow sales. For example, the best and fastest way to sell more units is to reduce the price by half. Is that what you want? Why do you want to grow sales?

We want to be more innovative to grow sales so we can grow profits. Closer than ever, but we’ve got to dig in and create a plan.

First, let’s begin with the end in mind. We’ve got to decide how we’ll judge success. How much do we want to grow profits? Double, you say? Good – that’s clear and measurable. I like it. When will we double profits? In four years, you say? Another good answer – clear and measureable. How much money can we spend to hit the goal? $5 million over four years. And does that incremental spending count against the profit target? Yes, year five must double this year’s profits plus $5 million.

Now that we know the what, let’s put together the how. Let’s start with geography. Will we focus on increasing profits in our existing first world markets? Will we build out our fledgling developing markets? Will we create new third world markets? Each market has different tastes, cultures, languages, infrastructure requirements, and ability to pay. And because of this, each requires markedly different innovations, skill sets, and working relationships. This decision must be made now if we’re to put together the right innovation team and organizational structure.

Now that we’ve decided on geography, will we do product innovation or business model innovation? If we do product innovation, do we want to extend existing product lines, supplement them with new product lines, or replace them altogether with new ones? Based on our geography decision, do we want to improve existing functionality, create new functionality, or reduce cost by 80% of while retaining 80% of existing functionality?

If we want to do business model innovation, that’s big medicine. It will require we throw away some of the stuff that has made us successful. And it will touch almost everyone. If we’re going to take that on, the CEO must take a heavy hand.

For simplicity, I described a straightforward, linear process where the whys are clearly defined and measurable and there’s sequential flow into a step-wise process to define the how. But it practice, there’s nothing simple or linear about the process. At best there’s overwhelming ambiguity around why, what, and when, and at worst, there’s visceral disagreement. And worse, with 0% clarity and an absent definition of success, there are several passionate factions with fully built-out plans that they know will work.

In truth, figuring out what innovation means and making it happen is a clustered-jumbled path where whats inform whys, whys transfigure hows, which, in turn, boomerang back to morph the whats. It’s circular, recursive, and difficult.

Innovation creates things that are novel, useful, and successful.  Novel means different, different means change, and change is scary. Useful is contextual – useful to whom and how will they use it? – and requires judgment. (Innovations don’t yet exist, so innovation efforts must move forward on predicted usefulness.) And successful is toughest of all because on top of predicted usefulness sit many other facets of newness that must come together in a predicted way, all of which can be verified only after the fact.

Innovation is a different animal altogether, almost like it eats itself. Just think – the most successful innovations come at the expense of what’s been successful.