Shipulski On Design

Archive for the ‘Assumptions’ Category

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systems change over time (the only thing we can argue about is the rate of change) the brain’s mental models are always out of date.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  But by definition that mental model is outdated.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.

Immediately after there’s an elegant solution to a previously intractable problem, the solution is obvious to others.  But, just before the solution those same folks said it was impossible to solve.  I don’t know if there’s a name for this phenomenon, but it certainly causes hart burn for those brave enough to take on the toughest problems.

Intractable problems are so fundamental they are no longer seen as problems.  Over the years experts simply accept these problems as constraints that must be complied with.   Just as the laws of physics can’t be broken, experts behave as if these self-made constraints are iron-clad and believe these self-build walls define the viable design space.  To experts, there is only viable design space or bust.

A long time ago these problems were intractable, but now they are not.  Today there are new materials, new analysis techniques, new understanding of physics, new measurement systems and new business models.. But, they won’t be solved.  When problems go unchallenged and constrain design space they weave themselves into the fabric of how things are done and they disappear.   No one will solve them until they are seen for what they are.

It takes time to slow down and look deeply at what’s really going on.  But, today’s frantic pace, unnatural fascination with productivity and confusion of activity with progress make it almost impossible to slow down enough to see things as they are.  It takes a calm, centered person to spot a fundamental problem masquerading as standard work and best practice.  And once seen for what they are it takes a courageous person to call things as they are.  It’s a steep emotional battle to convince others their butts have been wet all these years because they’ve been sitting in a mud puddle.

Once they see the mud puddle for what it is, they must then believe it’s actually possible to stand up and walk out of the puddle toward previously non-viable design space where there are dry towels and a change of clothes.  But when your butt has always been wet, it’s difficult to imagine having a dry one.

It’s difficult to slow down to see things as they are and it’s difficult to re-map the territory.   But it’s important.  As continuous improvement reaches the limit of diminishing returns, there are no other options.  It’s time to solve the intractable problems.

Image credit – Steven Depolo

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

If you’re serious about innovation, you must learn, as second nature, to convert your ideas into prototypes.

Funny thing about ideas is they’re never fully formed – they morph and twist as you talk about them, and as long as you keep talking they keep changing. Evolution of your ideas is good, but in the conversation domain they never get defined well enough (down to the nuts-and-bolts level) for others (and you) to know what you’re really talking about. Converting your ideas into prototypes puts an end to all the nonsense.

Job 1 of the prototype is to help you flesh out your idea – to help you understand what it’s all about. Using whatever you have on hand, create a physical embodiment of your idea. The idea is to build until you can’t, to build until you identify a question you can’t answer. Then, with learning objective in hand, go figure out what you need to know, and then resume building. If you get to a place where your prototype fully captures the essence of your idea, it’s time to move to Job 2. To be clear, the prototype’s job is to communicate the idea – it’s symbolic of your idea – and it’s definitely not a fully functional prototype.

Job 2 of the prototype is to help others understand your idea. There’s a simple constraint in this phase – you cannot use words – you cannot speak – to describe your prototype. It must speak for itself. You can respond to questions, but that’s it. So with your rough and tumble prototype in hand, set up a meeting and simply plop the prototype in front of your critics (coworkers) and watch and listen. With your hand over your mouth, watch for how they interact with the prototype and listen to their questions. They won’t interact with it the way you expect, so learn from that. And, write down their questions and answer them if you can. Their questions help you see your idea from different perspectives, to see it more completely. And for the questions you cannot answer, they the next set of learning objectives. Go away, learn and modify your prototype accordingly (or build a different one altogether). Repeat the learning loop until the group has a common understanding of the idea and a list of questions that only a customer can answer.

Job 3 is to help customers understand your idea. At this stage it’s best if the prototype is at least partially functional, but it’s okay if it “represents” the idea in clear way. The requirement is prototype is complete enough for the customer can form an opinion. Job 3 is a lot like Job 2, except replace coworker with customer. Same constraint – no verbal explanation of the prototype, but you can certainly answer their direction questions (usually best answered with a clarifying question of your own such as “Why do you ask?”) Capture how they interact with the prototype and their questions (video is the best here). Take the data back to headquarters, and decide if you want to build 100 more prototypes to get a broader set of opinions; build 1000 more and do a small regional launch; or scrap it.

Building a prototype is the fastest, most effective way to communicate an idea. And it’s the best way to learn. The act of building forces you to make dozens of small decisions to questions you didn’t know you had to answer and the physical nature the prototype gives a three dimensional expression of the idea. There may be disagreement on the value of the idea the prototype stands for, but there will be no ambiguity about the idea.

If you’re not building prototypes early and often, you’re not doing innovation. It’s that simple.

There are always too many things to do, too much to work on. And because of this, we must choose. Some have more choice than others, but we all have choice. And to choose, there are several lenses we look through.

What’s good enough? If it’s good enough, there’s no need to work on it. “Good enough” means it’s not a constraint; it’s not in the way of where you want to go.

What’s not good enough? If it’s not good enough, it’s important to work on it. “Not good enough” means it IS a constraint; it IS in the way; it’s blocking your destination.

What’s not happening? If it’s not happening and the vacancy is blocking you from your destination, work on it. Implicit in the three lenses is the assumption of an idealized future state, a well-defined endpoint.

It’s the known endpoint that’s used to judge if there’s a blocking constraint or something missing. And there are two schools of thought on idealized future states – the systems, environment, competition, and interactions are well understood and idealized future states are the way to go, or things are too complex to predict how things will go. If you’re a member of the idealized-future-state-is-the-way-to-go camp, you’re home free – just use your best judgment to choose the most important constraints and hit them hard. If you’re a believer in complexity and its power to scuttle your predictions, things are a bit more nuanced.

Where the future state folks look through the eyepiece of the telescope toward the chosen nebula, the complexity folks look through the other end of the telescope toward the atomic structure of where things are right now. Complexity thinkers think it’s best to understand where you are, how you got there, and the mindset that guided your journey. With that knowledge you can rough out the evolutionary potential of the future and use that to decide what to work on.

If you got here by holding on to what you had, it’s pretty clear you should try to do more of that, unless, of course, the rules have changed. And to figure out if the rules have changed? Well, you should run small experiments to test if the same rules apply in the same way. Then, do more of what worked and less of what didn’t. And if nothing works even on a small scale, you don’t have anything to hold onto and it’s time to try something altogether new.

If you got here with the hybrid approach – by holding on to what you had complimented with a healthy dose of doing new stuff (innovation), it’s clear you should try to do more of that, unless, of course, you’re trying to expand into new markets which have different needs, different customers, and different pocketbooks. To figure out what will work, runs small experiments, and do more of what worked and less of what didn’t. If nothing works, your next round of small experiments should be radically different. And again, more of what worked, less of what didn’t.

And if you’re a young company and have yet to arrive, you’re already running small experiments to see what will work, so keep going.

There’s a half-life to the things that got us here, and it’s difficult to predict their decay. That’s why it’s best to take small bets on a number of new fronts – small investment, broad investigation of markets, and fast learning. And there’s value in setting a rough course heading into the future, as long as we realize this type of celestial navigation must be informed by regular sextant sightings and course corrections they inform.

Image credit – Hubble Heritage.

I’ve had some great teachers in my life, and I’m grateful for them.  They taught me their hard-earned secrets, their simple secrets.  Though each had their own special gifts, they all gave them in the same way – they asked the simplest questions.

Today’s world is complex – everything interacts with everything else; and today’s pace is blistering – it’s tough to make time to understand what’s really going on.  To battle the complexity and pace, force yourself to come up with the simplest questions.  Here are some of my favorites:

For new products:

• Who will buy it?
• What must it do?
• What should it cost?

For new technologies:

• What problem are you trying to solve?
• How will you know you solved it?
• What work hasn’t been done before?

For new business models:

• Why are you holding onto your decrepit business model?

For problems:

• Can you draw a picture of it on one page?
• Can you make it come and go?

For decisions:

• What is the minimum viable test?
• Why not test three or four options at the same time?

For people issues:

• Are you okay?
• How can I help you?

For most any situation:

• Why?

These questions are powerful because they cut through the noise, but their power couples them to fear and embarrassment – fear that if you ask you’ll embarrass someone.  These questions have the power to make it clear that all the activity and hype is nothing more than a big cloud of dust heading off in the wrong direction. And because of that, it’s scary to ask these questions.

It doesn’t matter if you steal these questions directly (you have my permission), twist them to make them your own, or come up with new ones altogether.  What matters is you spend the time to make them simple and you summon the courage to ask.

Image credit — Montecruz Foto.

Things are cyclic, but there seems to be no end to the crusade of continuous improvement. (Does anyone remember how the Crusades turned out?) If only to take the edge off, there needs to be an injection of absurdity.

There’s no pressure with absurdity – no one expects an absurd idea to work.  If you ask for an innovative idea, you’ll likely get no response because there’s pressure from the expectation the innovative idea must be successful. And if you do get a response, you’ll likely get served a plain burrito of incremental improvement garnished with sour cream and guacamole to trick your eye and doused in hot sauce to trick your palate. If you ask for an absurd idea, you get laughter and something you’ve never heard before.

When drowning in the sea of standard work, it takes powerful mojo to save your soul.  And the absurdity jetpack is the only thing I know with enough go to launch yourself to the uncharted oasis of new thinking.  Immense force is needed because continuous improvement has serious mass – black hole mass. Like with light, a new idea gets pulled over the event horizon into the darkness of incremental thinking.  But absurdity doesn’t care.  It’s so far from the center lean’s pull is no match.

But to understand absurdity’s superpower is to understand what makes things absurd.  Things are declared absurd when they cut against the grain of our success.  It’s too scary to look into the bright sun of our experiences, so instead of questioning their validity and applicability, the idea is deemed absurd.  But what if the rules have changed and the fundamentals of last year’s success no longer apply?  What if the absurd idea actually fits with the new normal?  In a strange Copernican switch, holding onto to what worked becomes absurd.

Absurd ideas sometimes don’t pan out.  But sometimes they do.  When someone laughs at your idea, take note – you may be on to something.  Consider the laughter an artifact of misunderstanding, and consider the misunderstanding a leading indicator of the opportunity to reset customer expectations.  And if someone calls your idea absurd, give them a big hug of thanks, and get busy figuring out how to build a new business around it.

Hypothesis is a charged word – It has a scientific color; it smacks of sterility; it is thought to be done by academics; and it’s sometimes classified as special class of guessing. In thought and action, hypothesis is misunderstood.

We twist the word so it doesn’t apply in our situation; we label it to distance ourselves; we tag it with snarl connotations to protect ourselves. We do this because we’re afraid of the word’s power.

Replace hypothesis with “I think this will happen – [fill in the blank.]” and it’s clear why we’re afraid.  Hypothesis, as an activity, has the power to make it clear to everyone that you really don’t know what’s going on. Hypothesis demands you speculate based on your knowledge, and the fear is when you’re wrong (and you will be) people will think your knowledge (and you) is of a meager kind. Hypothesis demands you put yourself out there for the world to see. And that’s why it’s rarely done. And since it’s rarely done, its benefits are not understood.

Innovation is all the rage these days, and innovation is all about learning. And where necessity is the mother of invention, hypothesis is the father of learning. Hypothesis breeds learning by providing a comparison between what you thought would happen and what happened. The difference is a measure of your knowledge; and how the difference changes over time is a measure of your learning. If the difference widens over time, you’re getting cold; if it stays constant, you’re treading water; and if it converges, you’re learning.

Like a good parent, hypothesis knows which rules can be bent and which won’t be compromised. In the hypothesis household clarity and honesty are not optional – clarity around the problem at hand; clarity around how you’ll test and measure; and honesty around the limits of your knowledge.

Learning is important – no one can argue – and learning starts with a hypothesis. More strongly, learning is so important you should work through your fear around hypothesis and increase your learning rate.

Really, hypothesis isn’t the stern parent you think. Hypothesis will make time to teach you to ride your bike without training wheels, and be right there to bandage your skinned knees.

And, like a good parent, if you ask hypothesis for help, I think this will happen – [you’ll learn more and learn faster.]

We strive to get everyone on the same page, to align the crew in a shared direction. The thinking goes – If we’re all pulling in the same direction, we’ll get there faster and more efficiently. Yes, the destination will come sooner, but what if it’s not there when we get there?

There’s implicit permanence to our go-forward travel plans. We look out three years and plan our destination as if today’s rules and fundamentals will still apply. We think – That imaginary tropical vacation spot will be beautiful in three years because it looks beautiful through the kalidascope of today’s success. But as the recent natural disasters have taught us, whole islands can be destroyed in an instant. But still, the impermenance of today’s tried-and-true business models is lost on us, and we see the unknowable future as statically as the unchangeable map of the continents.

Thing is, all around us there are weak indications the fundamental tradewinds have started to shift – weak signals of impermenance that may invalidate today’s course heading. But weak signals are difficult to hear – the white noise of yesterday’s success drowns out the forward-looking weak signals.  And more problematic, once heard, weak signals are easily dismissed because their song threatens the successful status quo.

You feel weak signals in your chest. It could be a weak signal when your experience tells you things should go one way and they actually go another. Martin Zwilling (Forbes) has some great examples. (Thanks to Deb Mills-Scofield [@dscofield] for retweeting the article.)

100% alignment reduces adaptability because it deadens us to weak signals, and that’s a problem in these times of great impermanence. To counter the negative elements of alignment, there must be a balancing injection of healthy misalignment.  This is an important and thankless task falls on the shoulders of a special breed – the radical fringe.  They’re the folks smart enough to knit disjointed whispers into coherent ideas that could unravel everything and brave enough to test them.

Disruptive movements and revolutions build momentum quietly and slowly.  But if you can recognize them early, there’s a chance you can get into position to ride their tsunami instead of being ambushed and scuttled by it.  But you’ve got to listen closely because these young movements are stealthy and all they leave in their wake are weak signals.

The natural mindset of innovation is more-centric. More throughput; more performance; more features and functions; more services; more sales regions and markets; more applications; more of what worked last time. With innovation, we naturally gravitate toward more.

There are two flavors of more, one better than the other. The better brother is more that does something for the first time. For example, the addition of the first airbags to automobiles – clearly an addition (previous vehicles had none) and clearly a meaningful innovation. More people survived car crashes because of the new airbags. This something-from-nothing more is magic, innovative, and scarce.

Most more work is of a lesser class – the more-of-what-is class. Where the first airbags were amazing, moving from eight airbags to nine – not so much. When the first safety razors replaced straight razors, they virtually eliminated fatal and almost fatal injuries, which was a big deal; but when the third and fourth blades were added, it was more trivial than magical. It was more for more’s sake; it was more because we didn’t know what else to do.

While more is more natural, less is more powerful. The Innovator’s Dilemma clearly called out the power of less. When the long-in-the-tooth S-curve flattens, Christensen says to look down, to look down and create technologies that do less. Actually, he tells us someone will give ground on the very thing that built the venerable S-curve to make possible a done-for-the-first-time innovation.  He goes on to say you might as well be the one to dismantle your S-curve before a somebody else beats you to it. Yes, a wonderful way to realize the juciest innovation is with a less-centric mindset.

The LED revolution was made possible with less-centric thinking. As the incandescent S-curve hit puberty, wattage climbed and more powerful lights became cost effective; and as it matured, output per unit cost increased. More on more.  And looking down from the graying S-curve was the lowly LED, whose output was far, far less.

But what the LED gave up in output it gained in less power draw and smaller size.  As it turned out, there was a need for light where there had been none – in highly mobile applications where less size and weight were prized. And in these new applications, there was just a wisp of available power, and incandesent’s power draw was too much.  If only there was a technology with less power draw.

But at the start, volumes for LEDs were far less than incandesent’s; profit margin was less; and most importantly, their output was far less than any self-respecting lightbulb.  From on high, LEDs weren’t real lights; they were toys that would never amount to anything.

You can break intellectual inertia around more, and good things will happen. New design space is created from thin air once you are forced from the familiar. But it takes force. Creative use of constraints can help.

Get a small team together and creatively construct constraints that outlaw the goodness that makes your product great. The incandescent group’s constraint could be: create a light source that must make far less light. The automotive group’s constraint: create a vehicle that must have less range – battery powered cars.  The smartphone group: create a smartphone with the fewest functions – wrist phone without Blutooth to something in your pocket , longer battery life, phone in the ear, phone in your eyeglasses.

Less is unnatural, and less is scary. The fear is your customers will get less and they won’t like it. But don’t be afraid because you’re going to sell to altogether different customers in altogether markets and applications. And fear not, because to those new customers you’ll sell more, not less. You’ll sell them something that’s the first of its kind, something that does more of what hasn’t been done before. It may do only a little bit of that something, but that’s far more than not being able to do it all.

Don’t tell anyone, but the next level of more will come from less.

It’s easier to spot when it’s a rut of failure – product costs too high, product function is too low, and the feeding frenzy where your competitors eat your profits for lunch. Easy, yes, but still possible to miss, especially when everyone’s super busy cranking out heaps of the same old stuff in the same old way, and demonstrating massive amounts of activity without making any real progress. It’s like treading water – lots of activity to keep your head above water, but without the realization you’re just churning in the same place.

But far more difficult to see (and far more dangerous) is the invisible rut of success, where cranking out the same old stuff in the same old way is lauded.  Simply put – there’s no visible reason to change. More strongly put, when locked in this invisible rut newness is shunned and newness makers are ostracized. In short, there’s a huge disincentive to change and immense pressure to deepen the rut.

To see the invisible run requires the help of an outsider, an experienced field guide who can interpret the telltale signs of the rut and help you see it for what it is.  For engineering, the rut looks like cranking out derivative products that reuse the tired recipes from the previous generations;  it looks like using the same old materials in the same old ways; like running the same old analyses with the same old tools; all-the-while with increasing sales and praise for improved engineering productivity.

And once your trusted engineering outsider helps you see your rut for what it is, it’s time to figure out how to pull your engineering wagon out of the deep rut of success.  And with your new plan in hand, it’s finally time to point your engineering wagon in a new direction. The good news – you’re no longer in a rut and can choose a new course heading; the bad news – you’re no longer in a rut so you must choose one.

It’s difficult to see your current success as the limiting factor to your future success, and once recognized it’s difficult to pull yourself out of your rut and set a new direction.  One bit of advice – get help from a trusted outsider.  And who can you trust?  You can trust someone who has already pulled themselves out of their invisible rut of success.