Shipulski On Design

Archive for the ‘Uncertainty’ Category

Innovation is difficult because it requires novelty. And novelty is difficult because it’s different than last time. And different than last time is difficult because you’ve got to put yourself out there.  And putting yourself out there is difficult because no one wants to be judged negatively.

Success, no matter how small, reinforces what was done last time. There’s safety in doing it again. The return may be small, but the wheels won’t fall off.  You may run yourself into the ground over time, but you won’t fail catastrophically. You may not reach your growth targets, but you won’t get fired for slowly destroying the brand. In short, you won’t fail this year, but you will create the causes and conditions for a race to the bottom.

Diminishing returns are real. As a system improves it becomes more difficult to improve.  A ten percent improvement is more difficult every year and at some point, improvement becomes impossible.  In that way, success doesn’t breed success, it breeds more effort for less return. And as that improvement per unit effort decreases, it becomes ever more important (and ever more difficult) to do something different (to innovate).

Paradoxically, success makes it more difficult to innovate.

Success brings profits that could fund innovation. But, instead, success brings the expectation of predictable growth.  Last year we were successful and grew 10%. We know the recipe, so this year let’s grow 12%. We can do what we did last year, but do it more efficiently.  A sound bit of logic, except it assumes the rules haven’t changed and that competitors haven’t improved. But rules and competitors always change, and, at some point the the same old recipe for success runs out of gas.

It’s time to do something new (to innovate) when the same old effort brings reduced results. That change in output per unit effort means the recipe is tiring and it’s time for a new one. But with a new approach comes unpredictability, and for those who demand predictability, a new approach is scary. Sure, the yearly trend of reduced return on investment should scare them more, but it doesn’t.  The devil you know is less scary than the one you don’t.  But, it shouldn’t be.

Calculate your revenue dollars per sales associate and plot it over time.  If the metric is flat over the last three years, it was time to innovate three years ago.  If it’s decreasing over the last three years, it was time to innovate six years ago.

If you wait to innovate until revenue per sales person is flat, you waited too long.

No one likes to be judged negatively, more than that, no one likes their company to collapse and lose their job. So, choose to do something new (to innovate) and choose the possibility of being judged. That’s much better than choosing to go out of business.

Image credit – Michel Rathwell

There are four ways to run projects.

One – 80% Right, 100% Done, 100% On Time, 100% On Budget

• Fix time
• Fix resources
• Flex scope and certainty

Set a tight timeline and use the people and budget you have.  You’ll be done on time, but you must accept a reduced scope (fewer bells and whistles) and less certainty of how the product/service will perform and how well it will be received by customers. This is a good way to go when you’re starting a new adventure or investigating new space.

Two – 100% Right, 100% Done, 0% On Time, 0% On Budget

• Fix resources
• Fix scope and certainty
• Flex time

Use the team and budget you have and tightly define the scope (features) and define the level of certainty required by your customers. Because you can’t predict when the project will be done, you’ll be late and over budget, but your offering will be right and customers will like it. Use this method when your brand is known for predictability and stability. But, be weary of business implications of being late to market.

Three – 100% Right, 100% Done, 100% On Time, 0% On Budget

• Fix scope and certainty
• Fix time
• Flex resources

Tightly define the scope and level of certainty. Your customers will get what they expect and they’ll get it on time.  However, this method will be costly. If you hire contract resources, they will be expensive.  And if you use internal resources, you’ll have to stop one project to start this one. The benefits from the stopped project won’t be realized and will increase the effective cost to the company.  And even though time is fixed, this approach will likely be late.  It will take longer than planned to move resources from one project to another and will take longer than planned to hire contract resources and get them up and running.  Use this method if you’ve already established good working relationships with contract resources.  Avoid this method if you have difficulty stopping existing projects to start new ones.

Four – Not Right, Not Done, Not On Time, Not On Budget

• Fix time
• Fix resources
• Fix scope and certainty

Though almost every project plan is based on this approach, it never works.  Sure, it would be great if it worked, but it doesn’t, it hasn’t and it won’t. There’s not enough time to do the right work, not enough money to get the work done on time and no one is willing to flex on scope and certainty.  Everyone knows it won’t work and we do it anyway.  The result – a stressful project that doesn’t deliver and no one feels good about.

Image credit – Cees Schipper

Business and life are all about choosing how you want to allocate your time and money.  In life, it’s your personal time and money and in business it’s the company’s.

If you’ve ever done any winter hiking, you know that it’s important to know the terrain.  If there’s a mountain in the way, you either go over it or around it.  But there is one thing you can’t do is pretend it’s not there.  If you go around it, you’ve got to make sure you have enough energy, food, water and daylight to make the long trek to shelter.  If you go over it, you’ve got to make sure you have the ice picks, crampons, down jackets and climbing skills to make it up and down to shelter.  With winter hiking, the territory, gear and team capability matter. And the right decision is defined by situational awareness.

And what of the shelter? Does it sleep five, six or seven?  And because you have seven on your team, it’s not really shelter if it sleeps five.  And if you don’t know how many it sleeps, you’re not situationally aware.  And if you’re not situationally aware, on five may fit in the shelter and two will freeze to death.  Maybe before your trip you should look at the map and learn all the shelters their locations and how many the can hold. The right action and the safety of your crew depends on your situational awareness.

And the decision depends on how much daylight do you have left. Before you left basecamp it was possible to know when the sun will set. Did you take the time to look at the charts? Did you take advantage of the knowledge? If you don’t have enough sunlight, you’ve got to go over the top.  If you do, you can take the leisurely great circle route around the mountain.  And if you don’t know, you’ve got to roll the dice.  I’d prefer to be aware of the situation and keep the dice in my pocket.  And for that, you need to be aware of the situation.

Winter hiking is difficult enough even when you have maps of the terrain, weather forecasts, locations of the shelters and knowledge of when the sun will set. But it’s an unsafe activity when there are no maps of the territory, the weather is unknown and there’s no knowledge of the shelters.  But that’s just how it is with innovation – the territory has never been hiked, no maps, no weather forecast, and shelters are unknown.  With innovation, there’s no situational awareness unless you create it.  And that’s why with innovation, the first step is to create the maps.  No maps, no possibility of situational awareness.

The best people at situational awareness are the military. The know maps and they know how to use them.  The know to do recon to position the enemy on the map and they know to use the situational awareness (the map, the enemy’s location, and their direction of travel) to decide how what to do. If the enemy’s force is small and in poorly defensible position, there are a certain set of actions that are viable. If the enemy force is large and has the high ground, it’s time to sit tight or retreat with dignity. (To be clear, I’m a pacifist and this military example does mean I condone violence of any kind. It’s just that the military is super good at situational awareness.)

If you’re not making maps of the competitive landscape, you’re doing it wrong. If you’re not moving resources around and speculating how the competition will respond based on the topography and your position within it, you’re not sharpening your situational awareness and you’re not taking full advantage of the information around you.  If you don’t know where the mountains are you can’t avoid them or use them to slow your competition. And if you don’t know know where the shelters are an how many miles you can hike in a day, you don’t know if you’re overextending your position and putting your crew at risk.

Winter is coming. If you’re not creating maps to build situational awareness, what are you doing?

Image credit – Martin Fisch

Much like living organisms continually evolve to secure their place in the future, technological systems can be thought to display similar evolutionary behavior.  Viruses mutate so some of them can defeat the countermeasures of their host and live to fight another day. Technological systems, as an expression of a company’s desire to survive, evolve to defeat the competition and live to pay another dividend.

There are natural limits to evolutionary success in any single direction.  When one trait is improved it pushes on the natural limits imposed by the environment.  For example, a bacterium let loose in a friendly Petri dish will replicate until it eats all the food in the dish. Or, on a longer timescale, if the mass of a bird increases over generations when its food source is plentiful, the bird will get larger but will also get less agile. The predators who couldn’t catch the fast, little bird of old can easily catch and eat the sluggish heavyweight. In that way, there’s an edge condition created by the environmental Petri dishes and predators.  And it’s the same with technological systems.

Companies and their technological systems evolve within their competitive environment by scanning the fitness landscape and deciding where to try to improve.  The idea is to see preferential lines of improvement and create new technologies to take advantage of them.  Like their smaller biological counterparts, companies are minimum energy creatures and want to maximize reward (profit) with minimum effort (expense) and will continue to leverage successful lines of evolution until it senses diminishing returns.

The diminishing returns are a warning sign that the company is approaching an edge condition (a Petri dish of a finite size). In landscape lingo, there’s a cliff on the horizon. In technology lingo, the rate of improvement of the technology is slowing.  In either language, the edge is near and it’s time to evolve in a new direction because this current one is out of gas.

Like the bird whose mass increases over the generations when food is readily available, companies also get fat and slow when they successfully evolve in a single direction for too long.  And like the bird, they get eaten by a more agile competitor/predator. And just as the replication rate of the bacterium accelerates as the food in the Petri dish approaches zero, a company that doesn’t react to a slowing rate of technological improvement is sure to outlive its business model.

Biology and technology are similar in that they try new things (create variants of themselves) in order to live another day.  But there’s a big difference – where biology is blind (it doesn’t know what will work and what won’t), technology is sighted (people that create use their understanding to choose the variants they think will work best).  And another difference is that biological evolution can build only on viable variants where technology can use mental models as scaffolds to skip non-viable embodiments to cross a chasm.

There’s no need to fall off the cliff.  As a leading indicator, monitor the rate of improvement of your technology.  If its rate of improvement is still accelerating, it’s time to develop the next line of evolution. If its rate is declining, you waited too long. It’s time to double down on two new lines of evolution because you’re behind the curve. And remember, like with the population of bacteria in the Petri dish, sales will keep growing right up until the business model runs out of food or a competitor eats you.

Image credit — Amanda

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

Anything worth its salt will meet with resistance. More strongly, if you get no resistance, don’t bother.

There’s huge momentum around doing what worked last time.  Same as last time but better; build on success; leverage last year’s investment; we know how to do it. Why are these arguments so appealing? Two words: comfort and perceived risk. Why these arguments shouldn’t be so appealing: complacency and opportunity cost.

We think statically and selectively.  We look in the rear view mirror, write down what happened and say “let’s do that again.” Hey, why not? We made the initial investment and did the leg work.  We created the script.  Let’s get some mileage out of it.  And we selectively remember the positive elements and actively forget the uncertainty of the moment.  We had no idea it was going to work, and we forget that part. It worked better than we imagined and we remember the “working better” part. And we forget we imagined it would go differently. And we forget that was a long time ago and we don’t take the time to realize things are different now. The rules are dynamic, yet our thinking is static.

We compete with the past tense. We did this and they did that, and, therefore, that’s what will happen again. So wrong. We’ve got smarter; they’ve got smarter; battery capacity has tripled; power electronics are twice as efficient; efficiency of solar panels has doubled; CRISPR can edit our genes.  The rules are different but the sheet music hasn’t changed. The established players sing the same songs and the upstarts cut them off at the knees.

If you were successful last time and everyone thinks your proposed project is a good idea, ball it up and throw it in the trash. It reeks of stale thinking. If your project plan is dismissed by the experts because it contradicts the tired recipe of success, congratulations! You may be onto something!  Stomp on the accelerator and don’t look back.

If your proposal meets with consensus, hang your head and try again. You missed the mark. If they scream “heretic” and want to burn you at the stake, double down.  If the CEO isn’t adamantly against it, you’re not trying hard enough.  If she throws you out of the room half way through your presentation, you may have a winner!

Yesterday’s recipes for success are today’s worn paths of mediocracy.

If you’re confident it will work, you shouldn’t be. If you’re filled with electric excitement it might actually work and scared to death it might end in a wild fireball of burn metal toxic fumes, what are you waiting for?!

Heretics were burned at the stake because the establishment knew they were right.  Goddard was right and the New York Times wasn’t.  Decades later they apologized – rockets work is space. And though the Qualifiers and Pope Paul V were unanimous in their dismissal of Galileo and Copernicus, the heretics had it right – the sun is at the center of everything.

Don’t seek out dissent, but if all you get is consensus, be wary. Don’t be adversarial, but if all you get is open arms, question your thesis. Don’t be confrontational, but if all you get is acceptance, something’s wrong.

If there’s no resistance, work on something else.

Image Credit WPI (Robert Goddard’s Lab)

If the work doesn’t stretch you, choose new work.  Don’t go overboard and make all your work stretch you and don’t choose work that will break you.  There’s a balance point somewhere between 0% and 100% stretch and that balance point is different for everyone and it changes over time.  Point is, seek your balance point.

To find the right balance point, start with an assessment of your stretch level. List the number of projects you have and sum the number of major deliverables you’ve got to deliver.  If you have more than three projects, you have too many.  And if you think you take on more than three because you’re superhuman, you’re wrong.  The data is clear – multitasking is a fallacy.  If you have four projects you have too many. And it’s the same with three, but you’d think I was crazy if I suggested you limit your projects to two.  The right balance point starts with reducing the number of projects you work on.

Now that you eliminated four or five projects and narrowed the portfolio down to the vital two or three, it’s time to list your major deliverables. Take a piece of paper and write them in a column down the left side of the page. And in a column next to the projects, categorize each of them as: -1 (done it before), 0 (done something similar), 1 (new to me), 2 (new to team), 3 (new to company), 5 (new to industry), 11 (new to world).

For the -1s, teach an entry level person how to do it and make sure they do it well. For the 0s, find someone who deserves a growth opportunity and let them have the work. And check in with them to make sure they do a good job.  The idea is to free yourself for the stretch work.

For the 1s, find the best person in the team who has done it before and ask them how to do it.  Then, do as they suggest but build on their work and take it to the next level.

For the 2s, find the best person in the company who has done it before and ask them how to do it. Then, build on their approach and make it your own.

For the 3s, do your research and find out who in your industry has done it before.  Figure out how they did it and improve on their work.

For the 5s, do your research and figure out who has done similar work in another industry.  Adapt their work to your application and twist it into something magical.

And for the 11s, they’re a special project category that live in rarified air and deserve a separate blog post of their own.

Start with where you are – evaluate your existing deliverables, cull them to a reasonable workload and assess your level of stretch.  And, where it makes sense, stop doing work you’ve done before and start doing work you haven’t done yet. Stretch yourself, but be reasonable.  It’s better to take one bite and swallow than take three and choke.

Image credit – filtran

Novelty, or newness, can be a great way to assess the status of things.  The level of novelty is a barometer for the level of uncertainty and unpredictability.  If you haven’t done it before, it’s novel and you should expect the work to be uncertain and unpredictable. If you’ve done it before, it’s not novel and you should expect the work to go as it did last time. But like the barometer that measures a range of atmospheric pressures and gives an indication of the weather over the next hours, novelty ranges from high to low in small increments and so does the associated weather conditions.

Barometers have a standard scale that measures pressure.  When the summer air is clear and there are no clouds, the atmospheric pressure is high and on the rise and you should put on sun screen.  When it’s hurricane season and super-low system approaches, the drops to the floor and you should evacuate.  The nice thing about barometers is they are objective. On all continents, they can objectively measure the pressure and display it. No judgement, just read the scale. And regardless of the level of pressure and the number of times they measure it, the needle matches the pressure.  No Kentucky windage.  But novelty isn’t like that.

The only way to predict how things will go based on the level of novelty is to use judgement.  There is no universal scale for novelty that works on all projects and all continents.  Evaluating the level of novelty and predicting how the projects will go requires good judgement. And the only way to develop good judgment is to use bad judgment until it gets better.

All novelty isn’t created equal. And that’s the trouble.  Some novelty has a big impact on the weather and some doesn’t.  The trick is to know the difference.  And how to tell the difference? If when you make a change in one part of the system (add novelty) and the novelty causes a big change in the function or operation of the system, that novelty is important. The system is telling you to use a light hand on the tiller. If the novelty doesn’t make much difference in system performance, drive on. The trick is to test early and often – simple tests that give thumbs-up or thumbs-down results.  And if you try to run a test and you can’t get the test to run at all, there’s a hurricane is on the horizon.

When the work is new, you don’t really know which novelty will bite you. But there’s one rule: all novelty will bite you until proven otherwise.  Make a list of the novel elements of the and test them crudely and quickly.

Creativity and innovation are dominated by uncertainty. And in the domain of uncertainty, not only are the solutions unknown, the problems are unknown. And yet, we still try to use the tried-and-true toolbox of certainty even after it’s abundantly clear those wrenches don’t fit.

When wallowing in the mud of uncertainty and company leaders ask, “When will you be done?”, the only real answer is a description of the next thing you’ll try to learn. “We will learn if Step 1 is possible.” And then the predicted response, “Well, when will you be done with that?”  The only valid response is, “It depends.”  Though truthful, this goes over like a lead balloon.  And the dialog continues – “Okay, then, what is Step 2?”  The unpalatable answer, “It depends. If Step 1 is successful, we’ll move onto Step 2, but if Step 1 is unsuccessful, we’ll step back and regroup.” This, too, though truthful, is unsatisfactory.

When doing creative work, there’s immense pressure to be done on time. But, that pressure is inappropriate. Yes, there can be pressure to learn quickly and effectively, but the expectation to be done within an arbitrary timeline is ludicrous.  Managers don’t know this, but when they demand a completion date for a task that has never been done before, the people doing the creative work know the manager doesn’t know what they’re doing.  They won’t tell the manager what they think, but they definitely think it. And when pushed to give a completion date, they’ll give one, knowing full well the predicted date is just as arbitrary as the manager’s desired timeline.

But learning objectives can create common ground. Starting with “We want to learn if…”, learning objectives define what the project team must learn. Though there’s no agreement on when things will be completed, everyone can agree on the learning objectives. And with clearly defined learning objectives and measurable definitions of success, the project can move forward with consensus. There is still consternation over the lack of hard deadlines for the learning objectives, but there is agreement on the sequence of events, tests protocols or analyses that will be carried out to learn what must be learned.

Two rules to live by: If you know when you’ll be done, you’re not doing innovation. And if no one is surprised by the solution, you’re not doing creative work.

Image credit – Michael Carian

At some point, what worked last time won’t work this time. It’s not if the business model will go belly-up, it’s when. There are two choices. We can bury our heads in the sands of the status quo, or we can proactively observe the world in a forward-looking way and continually reorient ourselves as we analyze and synthesize what we see.

The world is dynamic, but we behave like it’s static. We have massive intellectual inertia around what works today.  In a rearward-looking way, we want to hold onto today’s mental models and we reject the natural dynamism swirling around us.  But the signals are clear. There’s cultural change, political change, climate change and population change. And a lower level, there’s customer change, competition change, technology change, coworker change, family change and personal change. And still, we cling to static mental models and static business models. But how to move from static to dynamic?

Continual observation and scanning is a good place to start. And since things become real when resources are allocated, allocating resources to continually observe and scan sends a strong message. We created this new position because things are changing quickly and we need to be more aware and more open minded to the dynamic nature of our world.  Sure, observation should be focused and there should be a good process to decide on focus areas, but that’s not the point. The point is things are changing and we will continually scan for storms brewing just over the horizon.  And, yes, there should be tools and templates to record and organize the observations, but the important point is we are actively looking for change in our environment.

Observation has no value unless the observed information is used for orientation in the new normal.  For orientation, analysis and synthesis is required across many information sources to develop ways to deal with the unfamiliar and unforeseen. [1] It’s important to have mechanisms to analyze and synthesize, but the value comes when beliefs are revised and mental models are updated. Because the information cuts against history, tradition and culture, to make shift in thinking requires diversity of perspective, empathy and a give-and-take dialog. [1] It’s a nonlinear process that is ironed out as you go.  It’s messy and necessary.

It’s risky to embrace a new perspective, but it’s far riskier to hold onto what worked last time.

[1] Osinga, Frans, P.B. Science, Strategy and War, The strategic theory of John Boyd. New York: Routledge, 2007.

image credit – gabe popa

When the work is new, it can’t be defined and managed like work that has been done before.

Sometimes there’s a tendency to spend months to define the market, the detailed specification and the project timeline and release the package as a tidal wave that floods the organization with new work.  Instead, start with a high-level description of the market, a rough specification and the major project milestones, all of which will morph, grow and inform each other as the team learns.  Instead of a big batch, think bite-sized installments that build on each other. Think straw-man that gets its flesh as the various organizations define their learning objectives and learn them.

Instead of target customer segments and idealized personas, define how the customers will interact with the new product or service. Use the storyboard format to capture sequence of events (what they do), the questions they ask themselves and how they know they’ve done it right. Make a storyboard for the top three to five most important activities the customers must do.  There’s good learning just trying to decide on the top three to five activities, never mind the deep learning that comes when you try to capture real activities of real customers. [Hint – the best people to capture real customer activities are real customers.]

Instead of a detailed list of inputs and outputs, fill in the details of the storyboards.  Create close-ups of the user interfaces and label the dials, buttons and screens.  When done well, the required inputs and outputs bubble to the surface.  And define the customer’s navigation path, as it defines the sequence of things and where the various inputs come to be and the various outputs need to be.  What’s nice is learning by iteration can be done quickly since its done in the domain of whiteboards and markers.

Instead of defining everything, just define what’s new and declare everything else is the same as last time.

The specification for the first prototypes is to bring the storyboards to life and to show the prototypes to real customers.  Refine and revise based on the learning, and rinse and repeat, as needed.

As the design migrates toward customer value and confidence builds, it’s then time to layer on the details and do a deep dive into the details – specs, test protocols, manufacturing, sales and distribution.

At early stages of innovation work, progress isn’t defined by activity, it’s defined by learning.  And it can look like nothing meaningful is happening as there is a lot of thinking and quiet time mixed in with infrequent bursts active activity.  But that’s what it takes to answer the big questions of the front end.

When in doubt, answer the big questions at the expense of the details.  And to stay on track, revisit and refine the learning objectives. And to improve confidence, show it to real customers.

And rinse and repeat, as needed.

Image credit – Jason Samfield