Shipulski On Design

Archive for the ‘Innovation’ Category

By definition, when the work is new there is uncertainty.  And uncertainty can be stressful. But, instead of getting yourself all bound up, accept it.  More than that, relish in it.  Wear it as a badge of honor.  Not everyone gets the chance to work on something new – only the best do.  And, because you’ve been asked to do work with a strong tenor of uncertainty, someone thinks you’re the best.

But uncertainty is an unknown quantity, and our systems have been designed to reject it, not swim in it.  When companies want to get serious they drive toward a culture of accountability and the new work gets the back seat.  Accountability is mis-mapped to predictability, successful results and on time delivery.  Accountability, as we’ve mapped it, is the mortal enemy of new work.  When you’re working on a project with a strong element of uncertainty, the only certainty is the task you have in front of you.  There’s no certainty on how the task will turn out, rather, there’s only the simple certainty of the task.

With work with low uncertainty there are three year plans, launch timelines and predictable sales figures. Task one is well-defined and there’s a linear flow of standard work right behind it – task two through twenty-two are dialed in. But when working with uncertainty, the task at hand is all there is.  You don’t know the next task.  When someone asks what’s next the only thing you can say is “it depends.”  And that’s difficult in a culture of traditional accountability.

An “it depends” Gannt chart is an oxymoron, but with uncertainty step two is defined by step one.  If A, then B.  But if the wheels fall off, I’m not sure what we’ll do next.  The only thing worse than an “it depends” Gantt chart is an “I’m not sure” Gannt chart.  But with uncertainty, you can be sure you won’t be sure.  With uncertainty, traditional project planning goes out the window, and “it depends” project planning is the only way.

With uncertainty, traditional project planning is replaced by a clear distillation of the problem that must be solved.  Instead of a set of well-defined tasks, ask for a block diagram that defines the problem that must be solved.  And when there’s clarity and agreement on the problem that must be solved, the supporting tasks can be well-defined.  Step one – make a prototype like this and test it like that. Step two – it depends on how step one turns out.  If it goes like this then we’ll do that.  If it does that, we’ll do the other.  And if it does neither, we’re not sure what we’ll do.  You don’t have to like it, but that’s the way it is.

With uncertainty, the project plan isn’t the most important thing.  What’s most important is relentless effort to define the system as it is.  Here’s what the system is doing, here’s how we’d like it to behave and, based on our mechanism-based theory, here’s the prototype we’re going to build and here’s how we’re going to test it.  What are we going to do next?  It depends.

What’s next? It depends. What resources do you need? It depends. When will you be done? It depends.

Innovation is, by definition, work that is new.  And, innovation, by definition, is uncertain.  And that’s why with innovation, it depends.  And that’s why innovation is difficult.

And that’s why you’ve got to choose wisely when you choose the people that do your innovation work.

Image credit – Sara Biljana Gaon (off)

Everyone wants to do more innovation.  But how? To figure out what’s going on with their innovation programs, companies spend a lot of time to put projects into buckets but this generates nothing but arguments about whether projects are disruptive, radical innovation, discontinuous, or not.  Such a waste of energy and such a source of conflict.  Truth is, labels don’t matter.  The only thing that matters is if the projects, as a collection, meet corporate growth objectives.  Sure, there should be a short-medium-long look at the projects, but, for the three time horizons the question is the same – Do the projects meet the company’s growth objectives?

To create the causes and conditions for innovation, start with a clear growth objective by geography.  Innovation must be measured in dollars.

Good judgement is required to decide if a project is worthy of resources.  The incremental sales estimates are easy to put together.  The difficult parts are deciding if there’s enough sizzle to cause customers to buy and deciding if the company has the chops to do the work.  The difficulty isn’t with the caliber of judgement, rather it’s insufficient information provided to the people that must use their good judgement.  In shorth, there is poor clarity on what the projects are about. Any description of the projects blurry and done at a level of abstraction that’s too high.  Good judgement can’t be used when the picture is snowy, nor can it be effective with a flyby made in the stratosphere.

To create the causes and conditions for innovation, demand clarity and bedrock-level understanding.

To guarantee clarity and depth, use the framework of novel, useful, successful. Give the teams a tight requirement for clarity and depth and demand they meet it.  For each project, ask – What is the novelty? How is it useful? When the project is completed, how will everyone be successful?

A project must deliver novelty and the project leader must be able to define it on one page.  The best way to do this is to create physical (functional) model of the state-of-the-art system and modify it with the newness created by the project (novelty called out in red).  This model comes in the form of boxes that describe the system elements (simple nouns) and arrows that define the actions (simple verbs).  Think hammer (box – simple noun) hits (arrow -simple verb) nail (box – simple noun) as the state-of-the-art system and the novelty in red – a thumb protector (box) that blocks (arrow) hammer (box).  The project delivers a novel thumb protector that prevents a smashed thumb.  The novelty delivered by the project is clear, but does it pass the usefulness test?

To create the causes and conditions for innovation, demand a one-page functional model that defines and distills down to bedrock level the novelty created by the project.  And to help the project teams do it, hire a good teach teacher and give them the tools, time and training.

The novelty delivered by a project must be useful and the project leader must clearly define the usefulness on one page.  The best way to do this is with a one page hand sketch showing the customer actively using the novelty. In a jobs-to-be-done way, the sketch must define where, when and how the customer will realize the usefulness. And to force distillation blinding, demand they use a fat, felt tip marker. With this clarity, leaders with good judgement can use their judgement effectively. Good questions flow freely. Does every user of a hammer need this? Can a left-handed customer use the thumb guard? How does it stay on? Doesn’t it get in the way? Where do they put it when they’re done? Do they wear it all the time?  With this clarity, the questions are so good there is no escape.  If there are holes they will be uncovered.

To create the causes and conditions for innovation, demand a one-page hand sketch of the customer demonstrating the useful novelty.

To be successful, the useful novelty must be sufficiently meaningful that customers pay money for it.  The standard revenue projections are presented, but, because there is deep clarity on the novelty and usefulness, there is enough context for good judgement to be effective.  What fraction of hammer users hit their thumbs? How often? Don’t they smash their fingers too?  Why no finger protection?  Because of the clarity, there is no escape.

To create the causes and conditions, use the deep clarity to push hard on buying decisions and revenue projections.

The novel, useful, successful framework is a straightforward way to decide if the project portfolio will meet growth objectives.  It demands a clear understanding of the newness created by the project but, in return, provides context needed to use good judgement.  In that way, because projects cannot start without passing the usefulness and successfulness tests, resources are not allocated to unworthy projects.

But while clarity and this level of depth is a good start, it’s not enough.  It’s time for a deeper dive. The project must distill the novelty into a conflict diagram, another one-pager like the others, but deeper.  Like problem definition on steroids, a conflict must be defined in space – between two things (thumb and face of hammer head) – and time (just as the hammer hits thumb).  With that, leaders can ask before-during-after questions.  Why not break the conflict before it happens by making a holding mechanism that keeps the thumb out of the strike zone? Are you sure you want to solve it during the conflict time (when the hammer hits thumb)?  Why not solve it after the fact by selling ice packs for their swollen thumbs?

But, more on the conflict domain at another time.

For now, use novel, useful, successful to stop bad projects and start good ones.

Image credit – Natashi Jay

When doing new things there is no predictability. There’s speculation, extrapolation and frustration, but no prediction. And the labels don’t matter.  Whether it’s called creativity, innovation, discontinuous improvement or disruption there’s no prediction.

The trick in the domain complexity is to make progress without prediction.

The first step is to try to define the learning objective.  The learning objective is what you want to learn. And its format is – We want to learn that [fill in the learning objective here].  It’s fastest to tackle one learning objective at a time because small learning objectives are achieved quickly with small experiments.  But, it will be a struggle to figure out what to learn.  There will be too many learning objectives and none will be defined narrowly.  At this stage the fastest thing to do is stop and take a step back.

There’s nothing worse than learning about the wrong thing.  And it’s slow. (The fastest learning experiments are the ones that don’t have to be run.) Before learning for the sake of learning, take the necessary time to figure out what to learn. Ask some questions: If it worked could it reinvent your industry? Could it obsolete your best product? Could it cause competitors to throw in the towel?  If the answer is no, stop the project and choose one where the answer is yes. Choose a meaningful project, or don’t bother.

First learning objective – We want to learn that, when customers love the new concept, the company will assign appropriate resources to commercialize it.  If there’s no committment up front, stop.  If you get committment, keep going. (Without upfront buy-in the project relies on speculation, the wicked couple of prediction and wishful thinking.)

Second learning objective – We want to learn that customers love the new concept.  This is not “I think customers will love it.” or “Customers may love it.” In the standard learning objective format – We want to learn that [customers love the new concept].  Next comes the learning plan.

What will you build for customers to help them understand the useful novelty of the revolutionary concept?  For speed’s sake, build a non-functional prototype that stands for the concept.  It’s a thin skin wrapped around an empty box that conveys the essence of the novelty.  No skeleton, just skin.  And for speed’s sake, show it to fewer customers than you think reasonable.  And define the criteria to decide they love it.  There’s no trick here. Ask “Do they love it?” and use your best judgement.  At this early stage, the answer will be no.  But they’ll tell you why they don’t love it, and that’s just the learning you’re looking for.

Use customer input to reformulate the learning objective and build a new prototype and repeat.  The key here is to build fast, test fast, learn fast and repeat fast.  The art becomes defining the simplest learning objectives, building the simplest prototypes and making decisions with data from the fewest customers.

With complexity and newness prediction isn’t possible. But learning is.

And learning doesn’t have to take a lot of time.

Image credit — John William Waterhouse

All the scary words are grounded in change.  Innovation, by definition, is about change.  When something is innovative it’s novel, useful and successful.  Novel is another word for different and different means change.  That’s why innovation is scary.  And that’s why radical innovation is scarier.

Continuous improvement, where everything old is buffed and polished into something new, is about change.  When people have followed the same process for fifteen years and then it’s improved, people get scared.  In their minds improved isn’t improved, improved is different.  And different means change.  Continuous improvement is especially scary because it makes processes more productive and frees up people to do other things, unless, of course, there are no other things to do.  And when that happens their jobs go away.  Every continuous improvement expert knows when the first person loses their job due to process improvement the program is dead in the saddle, yet it happens.  And that’s scary on a number of fronts.

And then there’s disruption. While there’s disagreement on what it actually is, there is vicious agreement that after a disruption the campus will be unrecognizable. And unrecognizable things are unrecognizable because they are different from previous experience. And different means change.  With mortal innovation there are some limits, but with disruption everything is fair game. With disruption everything can change, including the venerable, yet decrepit, business model.  With self-disruption, the very thing responsible for success is made to go away by the people that that built it.  And that’s scary. And when a company is disrupted from the outside it can die. And, thankfully, that’s scary.

But change isn’t scary.  Thinking about change is scary.

There’s one condition where change is guaranteed – when the pain of the current situation is stronger than the fear of changing it.  One source of pain could be from a realization the ship will run aground if a new course isn’t taken.  When pain of the immanent shipwreck (caused by fear) overpowers the fear of uncharted waters, the captain readily pulls hard to starboard. And when the crew realizes it’s sink or swim, they swim.

Change doesn’t happen before it’s time. And before things get bad enough, it’s not time.

When the cruise ship is chugging along in fair seas, change won’t happen. Right before the fuel runs out and the generators quit, it’s all you can eat and margaritas for everyone.  And right after, when the air conditioning kicks out and the ice cream melts, it’s bedlam.  But bedlam is not the best way to go.  No sense waiting until the fuel’s gone to make change. Maybe someone should keep an eye the fuel gauge and let the captain know when there’s only a quarter tank.  That way there’s some time to point the ship toward the closest port.

There’s no reason to wait for a mutiny to turn the ship, but sometimes an almost mutiny is just the thing.

As a captain, it’s difficult to let things get worse so they can get better. But if there’s insufficient emotional energy to power change, things must get worse.  The best captains run close to the reef and scrape the hull.  The buffet tables shimmy, the smoked salmon fouls the deck and the liquor bottles rattle.  And when done well, there’s a deep groan from the bowels of the ship that makes it clear this is no drill.  And if there’s a loud call for all hands on deck and a cry for bilge pumps at the ready, all the better.

To pull hard in a new direction, sometimes the crew needs help to see things as they are, not as they were.

Image credit – Francis Bijl

For those who lead projects and people, failure is always lurking in the background.  And gone unchecked, it can hobble. Despite best efforts to put a shine on it, there’s still a strong negative element to failure.  No two ways about it, failure is mapped with inadequacy and error.  Failure is seen as the natural consequence of making a big mistake.  And there’s a finality to failure.  Sometimes it’s the end of a project and sometimes it’s the end of a career.  Failure severely limits personal growth and new behavior.  But at least failure is visible to the naked eye.  There’s no denying a good train wreck.

A fumble is not failure.  When something gets dropped or when a task doesn’t get done, that’s a fumble.  A fumble is not catastrophic and sometimes not even noteworthy.  A fumble is mapped with  a careless mistake that normally doesn’t happen.  No real cause.  It just happens. But it can be a leading indicator of bigger and badder things to come, and if you’re not looking closely, the fumble can go unnoticed. And the causes and conditions behind the fumble are usually unclear or unknown.  Where failure is dangerous because everyone knows when it happens, fumbles are dangerous because they can go unnoticed.

Floundering is not fumbling. With floundering, nothing really happens.  No real setbacks, no real progress, no real energy. A project that flounders is a project that never reaches the finish line and never makes it to the cemetery.  To recognize floundering takes a lot of experience and good judgment because it doesn’t look like much. But that’s the point – not much is happening.  No wind in the sails and no storm on the horizon.  And to call it by name takes courage because there are no signs of danger.  Yet it’s dangerous for that very reason. Floundering can consume more resources than failure.

Fear is the fundamental behind failing, fumbling and floundering. But unlike failure, no one talks about fear. Talking about fear is too scary. And like fumbling and floundering, fear is invisible, especially if you’re not looking.  Like diabetes, fear is a silent killer. And where diabetes touches many, fear gets us all. Fear is invisible, powerful and prolific.  It’s a tall order to battle the invisible.

But where there’s fun there can be no fear. More precisely, there can be no negative consequence of fear. When there’s fun, everyone races around like their hair is on fire.  Not on fire in the burn unit way, but on fire in the energy to burn way. When there’s fun people help each other for no reason. They share, they communicate and they take risks.  When there’s fun no one asks for permission and the work gets done.  When there’s fun everyone goes home on time and their spouses are happy.  Fun is easy to see, but it’s not often seen because it’s rare.

If there’s one thing that can go toe-to-toe with fear, it’s fun. It’s that powerful. Fun is so powerful it can turn failure into learning.  But if it’s so powerful, why don’t we teach people to have fun? Why don’t we create the causes and conditions so fun erupts?

I don’t know why we don’t promote fun.  But, I do know fun is productive and fun is good for business.  But more important than that, fun is a lot of fun.

Image credit – JoshShculz

Expectations result from mental models and wants. When you have a mental model of a system and you want the system to behave in a way that fits your mental model, that’s an expectation.  And when you want the system to behave differently than your mental model, that’s also an expectation.  When the system matches your wants, the world is good.  And when your wants are out of line with the system, the world is not so good.

Speculation is not expectation. Speculation happens when you propose, based on your mental model, how the system will behave. With speculation, there’s no attachment to the result, no wanting it to be one way or another. There’s just watching and learning.  If the system confirms your mental model, the applicability of the model is reinforced (within this narrow context.) And when the system tramples your mental model, you change your mental model.  No attachment, no stress, no whining, no self-judgement.

When doing work that’s new, system response is unknown. Whether the system will be exercised in a new way or it’s an altogether new system, metal models are young and untested.  When it’s the first time, speculation is the way to go. Come up with your best mental model, run the experiment and record the results.  After sitting in data, refine your mental model and repeat.   If your mental model doesn’t fit the system, don’t judge yourself negatively, don’t hold yourself back, don’t shy away.  Refine your mental model and build-test-learn as fast as you can.  And if your mental model fits the system, don’t judge yourself in a positive way.  This was your first test and you don’t understand the system fully.  Refine your model and test for a deeper understanding.  [Note – systems have been known to temporarily conform to mental models to obfuscate their true character.]

When doing work that’s new, expectation gets in the way. If you expect your models to be right and they’re not, you learning rate is slower than your expectations.  That’s not such a big deal on its own, but the rippling self-judgement can be crippling. Your emotional state becomes fragile and it’s difficult to keep pushing through the work. You doubt yourself and your abilities; you won’t put yourself out there; and you won’t propose radical mental models for fear of looking like you don’t know what you’re doing.  You won’t run the right experiments and you never the understand the fundamental character of the system. You block your own learning.  If you expect your models won’t to fit the system, you block your learning from the start.  Sometimes your lack of confidence blocks you from even trying. [Note – not trying is the only way to guarantee you won’t learn.]

Within the domain of experiments, mental models and generic systems, it’s relatively easy to see the wisdom of speculations and the perils of expectations, where wanting leads to judging and judging leads to self-blocking.  But it’s not so easy to see in the domain of life where experiments are replaced with personal interactions and generic systems are replaced with everyday situations and mental models are ever-present.  But in both domains the rules and consequences are the same.

Just as in the lab, in day-to-day life expectations are dangerous.

Image credit – Dermot  O’Halloran

When money is tight, it’s still important to do new work, but it’s doubly important not to waste it.

There are a number of models to increase the probability of success of new work.  One well known approach is the VC model where multiple projects are run in parallel.  The trick is to start projects with the potential to deliver ultra-high returns.  The idea isn’t to minimize the investment but to place multiple bets.  When money’s tight, the VC model is not your friend.

Another method to increase the probability of success is to increase the learning rate.  The best known method is the Lean Startup method.  Come up with an idea, build a rough prototype, show it to potential customers and refine or pivot.  The process is repeated until a winning concept finds a previously unknown market segment and the money falls from the sky.   In a way, it’s like the VC Model, but it’s not a collection of projects run in parallel, it’s a sequential series of high return adventures punctuated by pivots. The Lean Startup is also quite good when money’s tight.  A shoe string budget fosters radical learning strategies and creates focus which are both good ideas when coffers are low.

And then there’s the VC/Lean Startup combo. A set of high potential projects run in parallel, each using Lean’s build, show, refine method to learn at light speed.  This is not the approach for empty pockets, but it’s a nice way to test game changing ideas quickly and efficiently.

Things are different when you try to do an innovation project within a successful company. Because the company is successful, all resources are highly utilized, if not triple-booked.  On the balance sheet there’s plenty of money, but practically the well is dry.  The organization is full up with ROI-based projects that will deliver marginal (but predictable) top line growth, and resources are tightly shackled to their projects.  Though there’s money in the bank, it feels like the account is over drawn.  And with this situation there’s a unique and expensive failure mode lurking in the shallows.

The front end of innovation work is resource light. New prototypes are created quickly and inexpensively and learning is fast and cheap.  Though the people doing the work are usually highly skilled and highly valuable, it doesn’t take a lot of people to create a functional prototype and test it with new customers.  And then, when the customers love it and it’s time to commercialize, there’s no one home. No one to do the work. And, unlike the relatively resource light front end work, commercialization work is resource heavy and expensive. The failure mode – the successful front end work is nothing but pure waste.  All the expense of creativity with none of innovation’s return.  And more painful, if the front end was successful the potential failure mode was destined to happen. There was no one to pick it up from the start.

The least expensive projects are the ones that never start. Before starting a project, ask “What if it works?”

image credit – jumping lab

If the work is new, there is no best practice.

When you read the best books you’ll understand what worked in situations that are different than yours.  When you read the case studies you’ll understand how one company succeeded in a way that won’t work in yours.  The best practices in the literature worked in a different situation, in a different time and a under different cultural framework.  They won’t work best for you.

Just because a practice worked last time doesn’t mean it’s a best practice this time.  More strongly, just because it worked last time doesn’t mean it was best last time. There may have been a better way.

When a problem has high urgency it should be solved in a fast way, but if urgency is low, the problem should be solved in an efficient way. Which way is best? If the consequences of getting it wrong are severe, analyses and parallel solutions are skillful, but if it’s not terribly important to get it right, a lower cost way is better.  But is either the best way?

The best practices found in books are usually described a high level of abstraction using action words, block diagrams and arrows.  And when described at such a high level, they’re not actionable.  You may know all the major steps, but you won’t know how each step should be done.  And if the detail is provided, the context of your situation is different and the prescriptive steps don’t apply.

Instead of best practices, think effective practices.  Effective because the people doing the work can do it effectively.  Effective because it fits with the capability and capacity of the people doing the work.  Effective because it meshes with existing processes and projects.  Effective because it fits with your budget, timeline and risk profile.  Effective because it fits with your company values.

Because all our systems are people systems, there are no best practices.

image credit — johnwayne2006

If you believe the work is meaningful, best effort flows from every pore.

If you believe in yourself, positivity carries the day.

If you believe the work will take twelve weeks, you won’t get it done in a day-and-a-half.

If you believe in yourself, when big problems find you, you run them to ground.

If you believe people have good intensions, there are no arguments, there is only progress.

If you believe in yourself, you are immune to criticism and negative self-talk.

If you believe people care about you, you’re never lonesome.

If you believe in your team, there’s always a way.

If you believe in yourself, people believe in you.  And like compound interest, the cycle builds on itself.

Image credit – Joe Shlabotnik

For established companies, when times are good, it’s not the right time to try something new – the resources are there but the motivation is not; and when times are tough it’s also the wrong time to try something new – the motivation is there but the breathing room is not.  There are an infinite number of scenarios, but for the established company it’s never a good time to try something new.

For startup companies, when times are good, it’s the right time to try something new – the resources are there and so is the motivation; and when times are tough it’s also the right time to try something new – the motivation is there and breathing room is a sign of weakness.  Again, the scenarios are infinite, but for the startup is always a good time to try something new.

But this is not a binary world. To create new markets and new customers, established companies must be a little bit startup, and to scale, startups must ultimately be a little bit established. This ambidextrous company is good on paper, but in the trenches it gets challenging. (Read Ralph Ohr for an expert treatment.)  The establishment regime never wants to do anything new and the startup regime always wants to.  There’s no middle ground – both factions judge each other through jaded lenses of ROI and learning rate and mutual misunderstanding carries the day.  Trouble is, all companies need both – established companies need new markets and startups need to scale. But it’s more complicated than that.

As a company matures the balance of power should move from startup to established.  But this tricky because the one thing power doesn’t like to do is move from one camp to another. This is the reason for the “perpetual startup” and this is why it’s difficult to scale.  As the established company gets long in the tooth the balance of power should move from the establishment to the startup.  But, again, power doesn’t like to change teams, and established companies squelch their fledgling startup work. But it’s more complicated, still.

The competition is ever-improving, the economy is ever-changing and the planet is ever-warming.  New technologies come on-line, and new business models test the waters. Some work, some don’t.  Huge companies buy startups just to snuff them out and established companies go away.  The environment is ever-changing on all fronts.  And the impermanence pushes and pulls on the pendulum of power dynamics.

All companies want predictability, but they’ll never have it.  All growth models are built on rearward-looking fundamentals and forward-looking conjecture.  Companies will always have the comfort of their invalid models, but will never the predictability they so desperately want.  Instead of predictability, companies would be better served by a strong sense of how it wants to go about its business and overpowering genetics of adaptability.

For a strong definition of how to go about business, a simple declaration does nicely. “We want to spend 80% of our resources on established-company work and 20% on startup-company work.” (Or 90-10, or 95-5.)  And each quarter, the company measures itself against its charter, and small changes are made to keep things on track.  Unless, of course, if the environment changes or the business model runs out of gas.  And then the company adapts.  It changes its approach and it’s projects to achieve its declared 80-20 charter, or, changes the charter altogether.

A strong charter and adaptability don’t seem like good partners, but they are.  The charter brings focus and adaptability brings the change necessary to survive in an every-changing environment.  It’s not easy, but it’s effective.  As long as you have the right leaders.

Image credit – Rick Abraham1

When doing something from the first time you’re going to get it wrong.  There’s no shame in that because that’s how it goes with new work. But more strongly, if you don’t get it wrong you’re not trying hard enough.  And more strongly, embrace the inherent wrongness as a guiding principle.

Take Small Bites. With new work, a small scope is better than a large one.  But it’s exciting to do new work and there’s a desire to deliver as much novel usefulness as possible.  And, without realizing it, the excitement can lead to a project bloated with novelty.  With the best intentions, the project team is underwater with too much work and too little time.  With new work, it’s better to take one bite and swallow than three and choke.

Ratchet Thinking. With new work comes passion and energy.  And though the twins can be helpful and fun to have around, they’re not always well-behaved.  Passion can push a project forward but can also push it off a cliff. Energy creates pace and can quickly accelerate a project though the milestones, but energy can be careless and can just as easily accelerate a project in the wrong direction.  And that’s where ratchet thinking can help.

As an approach, the objective of ratchet thinking is to create small movements in the right direction without the possibility of back-sliding.  Solve a problem and click forward one notch; solve a second problem and click forward another notch.  But, with ratchet thinking, if the third problem isn’t solved, the project holds its ground at the second notch.  It takes a bit more time to choose the right problem and to solve it in a way that cannot unwind progress, but ultimately it’s faster.  Ratchet thinking takes the right small bite, chews, swallows.

Zero Cost of Change. New work is all about adding new functions, enhancing features and fixing what’s broken.  In other words, new work is all about change. And the faster change can happen, the faster the product/service/business model is ready for sale.  But as the cost of change increases the rate of changes slows.  So why not design the project to eliminate the cost of change?

To do that, design the hardware with a bit more capability and headroom so there’s some wiggle room to handle the changes that will come.  Use a modular approach for the software to minimize the interactions of software changes and make sure the software can be updated remotely without customer involvement.  And put in place a good revision control (and tracking) mechanism.

Doing new work is full of contradictions: move quickly, but take the time to think things through; take on as much as you can, but no more; be wrong, but in the right way; and sometimes slower is faster.

But doing new work you must.

image credit – leasqueaky