Shipulski On Design

If you don’t have a problem, you’ve got a big problem.

It’s important to know where a problem happens, but also when it happens.

Solutions are 90% defining and the other half is solving.

To solve a problem, you’ve got to understand things as they are.

Before you start solving a new problem, solve the one you have now.

It’s good to solve your problems, but it’s better to solve you customers’ problems.

Opportunities are problems in sheep’s clothing.

There’s nothing worse than solving the wrong problem – all the cost with none of the solution.

When you’re stumped by a problem, make it worse then do the opposite.

With problem definition, error on the side of clarity.

All problems are business problems, unless you care about society’s problems.

Odds are, your problem has been solved by someone else.  Your real problem is to find them.

Define your problem as narrowly as possible, but no narrower.

Problems are not a sign of weakness.

Before adding something to solve the problem, try removing something.

If your problem involves more than two things, you have more than one problem.

The problem you think you have is never the problem you actually have.

Problems can be solved before, during or after they happen and the solutions are different.

Start with the biggest problem, otherwise you’re only getting ready to solve the biggest problem.

If you can’t draw a closeup sketch of the problem, you don’t understand it well enough.

If you have an itchy backside and you scratch you head, you still have an itch. And it’s the same with problems.

If innovation is all about problem solving and problem solving is all about problem definition, well, there you have it.

Image credit – peasap

If you know what to do, do it. Don’t ask, just do.

If you’re pretty sure what to do, do it.  Don’t ask, just do.

If you think you may know what to do, do it.  Don’t ask, just do.

If you don’t know what to do, try something small.  Then, do more of what works and less of what doesn’t.

If your team doesn’t know what to do unless they ask you, tell them to do what they think is right.  And tell them to stop asking you what to do.

If your team won’t act without your consent, tell them to do what they think is right. Then, next time they seek your consent, be unavailable.

If the team knows what to do and they go around you because they know you don’t, praise them for going around you.  Then, set up a session where they educate you on what you should know.

If the team knows what to do and they know you don’t, but they don’t go around you because they are too afraid, apologize to them for creating a fear-based culture and ask them to do what they think is right.  Then, look inside to figure out how to let go of your insecurities and control issues.

If your team needs your support, support them.

If your team need you to get out of the way, go home early.

If your team needs you to break trail, break it.

If they need to see how it should go, show them.

If they need the rules broken, break them.

If they need the rules followed, follow them.

If they need to use their judgement, create the causes and conditions for them to use their judgement.

If they try something new and it doesn’t go as anticipated, praise them for trying something new.

If they try the same thing a second time and they get the same results and those results are still unanticipated, set up a meeting to figure out why they thought the same experiment would lead to different results.

Try to create the team that excels when you go on vacation.

Better yet, try to create the team that performs extremely well when you’re involved in the work and performs even better when you’re on vacation. Then, because you know you’ve prepared them for the future, happily move on to your next personal development opportunity.

Image credit — Puriri deVry

How do you know when it’s time to reinvent your product, service or business model? If you add ten units of energy and you get less in return than last time, it’s time to work in new design space.  If improvement in customer goodness (e.g., miles per gallon in a car) has slowed or stopped, it’s time to seek a new fuel source.  If recent patent filings are trivial enhancements that can be measured only with a large sample sizes and statistical analysis, the party is over.

When there’s so many new things to work on, how do you choose the next project? When you’re lost, you look at a map. And when there is no map, you make one.  The first bit of work is defined by the holes in the first revision of your map.  And once the holes are filled and patched, the next work emerges from the map itself. And, in a self-similar way, the next work continually emerges from the previous work until the project finishes.

But with so much new territory, how do you choose the right new territory to map?  You don’t.  Before there’s a need to map new territory, you must map the current territory.  What you’ll learn is there are immature areas that, when made mature, will deliver new value to customers.  And you’ll also learn the mature areas that must be blown up and replaced with infant solutions that will ultimately create the next evolution of your business.  And as you run thought experiments on your map – projecting advancements on the various elements – the right new territory will emerge.  And here’s a hint – the right new solutions will be enabled by the newly matured elements of the map.

But how do you predict where the right new solutions will emerge?  I can’t tell you that.  You are the experts, not me.  All I can say is, make the maps and you’ll know.

And when I say maps, I mean Wardely Maps – here’s a short video (go to 4:13 for the juicy bits).

Image credit – Simon Wardley

Innovation isn’t a thing in itself.  Companies need to meet their growth objectives and innovation is the word experts use to describe the practices and behaviors they think will maximize the likelihood of meeting those growth objectives. Innovation is a catchword phrase that has little to no meaning.  Don’t ask about innovation, ask how to meet your business objectives. Don’t ask about best practices, ask how has your company been successful and how to build on that success.  Don’t ask how the big companies have done it – you’re not them.  And, the behaviors of the successful companies are the same behaviors of the unsuccessful companies. The business books suffer from selection bias. You can’t copy another company’s innovation approach. You’re not them.  And your project is different and so is the context.

With innovation, the biggest waste of emotional energy is quest for (and arguments around) best practices.  Because innovation is done in domains of high ambiguity, there can be no best practices. Your project has no similarity with your previous projects or the tightest case studies in the literature. There may be good practice or emergent practice, but there can be no best practice. When there is no uncertainty and no ambiguity, a project can use best practices.  But, that’s not innovation.  If best practices are a strong tenant of your innovation program, run away.

The front end of the innovation process is all about choosing projects. If you want to be more innovative, choose to work on different projects. It’s that simple. But, make no mistake, the principle may be simple the practice is not. Though there’s no acid test for innovation, here are three rules to get you started. (And if you pass these three tests, you’re on your way.)

• If you’ve done it before, it’s not innovation.
• If you know how it will turn out, it’s not innovation.
• If it doesn’t scare the hell out of you, it’s not innovation.

Once a project is selected, the next cataclysmic waste of time is the construction of a detailed project plan.  With a well-defined project, a well-defined project plan is a reasonable request.  But, for an innovation project with a high degree of ambiguity, a well-defined project plan is impossible.  If your innovation leader demands a detailed project plan, it’s usually because they are used running to well-defined continuous improvement projects.  If for your innovation projects you’re asked for a detailed project plan, run away.

With innovation projects, you can define step 1.  And step 2? It depends.  If step 1 works, modify step 2 based on the learning and try step 2.  And if step 1 doesn’t work, reformulate step 1 and try again. Repeat this process until the project is complete.  One step at a time until you’re done.

Innovation projects are unpredictable.  If your innovation projects require hard completion dates, run away.

Innovation projects are all about learning and they are best defined and managed using Learning Objectives (LOs). Instead of step 1 and step 2, think LO1 and LO2.  Though there’s little written about LOs, there’s not much to them.  Here’s the taxonomy of a LO: We want to learn if [enter what you want to learn].  Innovation projects are nothing more than a series of interconnected LOs.  LO2 may require the completion of LO1 or L1 and LO2 could be done in parallel, but that’s your call. Your project plan can be nothing more than a precedence diagram of the Learning Objectives.  There’s no need for a detailed Gantt chart. If you’re asked for a detailed Gantt chart, you guessed it – run away.

The Learning Objective defines what you learn, how you want to learn, who will do the learning and when they want to do it.  The best way to track LOs is with an Excel spreadsheet with one tab for each LO.  For each LO tab, there’s a table that defines the actions, who will do them, what they’ll measure and when they plan to get the actions done. Since the tasks are tightly defined, it’s possible to define reasonable dates.  But, since there can be a precedence to the LOs (LO2 depends on the successful completion of LO1), LO2 can be thought of a sequence of events that start when LO1 is completed.  In that way, an innovation project can be defined with a single LO spreadsheet that defines the LOs, the tasks to achieve the LOs, who will do the tasks, how success will be determined and when the work will be done. If you want to learn how to do innovation, learn how to use Learning Objectives.

There are more element of innovation to discuss, for example how to define customer segments, how to identify the most important problems, how to create creative solutions, how to estimate financial value of a project and how to go to market.  But, those are for another post.

Until then, why not choose a project that scares you, define a small set of Learning Objectives and get going?

Image credit – JD Hancock

In today’s world of continuous improvement, everything is seen as an opportunity for improvement. The good news is things are improving. But the bad news is without governance and good judgement, things can flip from “lots of opportunity for improvement” to “nothing is good enough.”  And when that happens people would rather hang their heads than stick out their necks.

When there’s an improvement goal is propose like this “We’ve got to improve the throughput of process A by 12% over the next three months.” a company that respects their people should want (and expect) responses like these:

As you know, the team is already working to improve processes C, D, and E and we’re behind on those improvement projects. Is improvement of process A more important than the other three? If so, which project do you want to stop so we can start work on process A? If not, can we wait until we finish one of the existing projects before we start a new one?  If not, why are you overloading us when we’re making it clear we already have too much work?

Are we missing customer ship dates on process A? If so, shouldn’t we move resources to process A right now to work off the backlog? If we have no extra resources, let’s authorize some overtime so we can catch up. If not, why is it okay to tolerate late shipments to our customers? Are you saying you want us to do more improvement work AND increase production without overtime?

That’s a pretty specific improvement goal. What are the top three root causes for reduced throughput? Well, if the first part of the improvement is to define the root causes, how do you know we can achieve 12% improvement in 3 months? We learned in our training that Deming said all targets are artificial. Are you trying to impose an artificial improvement target and set us up for failure?

Continuous improvement is infinitely good, but resources are finite.  Like it or not, continuous improvement work WILL be bound by the resources on hand. Might as well ask for continuous improvement work in a way that’s in line with the reality of the team’s capacity.

And one thing to remember for all projects – there’s no partial credit.  When you’re 80% done on ten projects, zero projects are done.  It’s infinitely better to be 100% done on a single project.

Image credit – Gabriel Rojas Hruska

Innovation is all about learning.  And if the objective of innovation is learning, why not start with learning objectives?

Here’s a recipe for learning: define what you want to learn, figure how you want to learn, define what you’ll measure, work the learning plan, define what you learned and repeat.

With innovation, the learning is usually around what customers/users want, what new things (or processes) must be created to satisfy their needs and how to deliver the useful novelty to them.  Seems pretty straightforward, until you realize the three elements interact vigorously.  Customers’ wants change after you show them the new things you created. The constraints around how you can deliver the useful novelty (new product or service) limit the novelty you can create.  And if the customers don’t like the novelty you can create, well, don’t bother delivering it because they won’t buy it.

And that’s why it’s almost impossible to develop a formal innovation process with a firm sequence of operations.  Turns out, in reality the actual process looks more like a fur ball than a flow chart. With incomplete knowledge of the customer, you’ve got to define the target customer, knowing full-well you don’t have it right. And at the same time, and, again, with incomplete knowledge, you’ve got to assume you understand their problems and figure out how to solve them.  And at the same time, you’ve got to understand the limitations of the commercialization engine and decide which parts can be reused and which parts must be blown up and replaced with something new.  All three explore their domains like the proverbial drunken sailor, bumping into lampposts, tripping over curbs and stumbling over each other.  And with each iteration, they become less drunk.

If you create an innovation process that defines all the if-then statements, it’s too complicated to be useful.  And, because the if-thens are rearward-looking, they don’t apply the current project because every innovation project is different. (If it’s the same as last time, it’s not innovation.)  And if you step up the ladder of abstraction and write the process at a high level, the process steps are vague, poorly-defined and less than useful.  What’s a drunken sailor to do?

Define the learning objectives, define the learning plan, define what you’ll measure, execute the learning plan, define what you learned and repeat.

When the objective is learning, start with the learning objectives.

Image credit Jean L.

Henry Ford famously said if he asked people what they wanted, they would have asked for faster horses.  And there’s a lot of truth to his statement. If you ask potential customers what they want next, they’ll give you an answer. And when you show them the prototype, they won’t like it.  Their intentions are good and their answers are truthful, but when you give them what they ask for and put the prototype in their hands, they will experience it in a way they did not expect.  It will be different than they thought.  Thinking how something will be is different than physically interacting with it.  That’s how it is with new things.

And just like with the horses, because they don’t know the emergent technologies and their radically different capabilities, they can’t ask for what’s possible.  They won’t ask for a combustion engine that eliminates their horses because all they know is horses.  They’ll ask for more horses, bigger horses or smaller ones, but they won’t ask for combustion cylinders.

The trick is to understand what people do and why they do it.  Like an anthropologist, spend time watching and understanding. And, if you can, understand what they don’t do and why they don’t do it.  The new and deeper understanding of their actions, along with the reasons for them, create an anchoring perspective from which to understand how emergent technologies can change their lives.

Technologies evolve along worn paths. And depending on the maturity of the technology, some worth paths are more preferential than others.  For example, if fuel economy is stagnant for the last ten years it means it’s likely time for a young technology to emerge that uses a different physical principle such as battery power.  Though technology’s evolutionary direction is not predictable in an exact sense, it is dispositional.  Like the meteorologist can’t pinpoint where the storm center will hit the coast or predict the maximum wind speed to within one or two miles per hour, she can say which states should hunker down and tell you if the wind will be strong enough to blow out your windows.  She cannot predict the specifics, but she knows there’s a storm on the horizon and she knows its character, disposition and tendencies.

Now, anchored in how people use the state-of-the-art technologies (ride horseback, ride in buggies, use a team of horses to pull a heavy wagon) look at what the new technologies want to become (horses to combustion engine) and image how people’s lives would be better (faster trips, longer pleasure rides, heavier payloads, no barns and cleaner streets.)  Now, using the new technology, build a prototype and show it to customers.  Put them in the driver’s seat and blow their minds.  Listen to the questions they ask so you can better understand the technology from their perspective because just as they don’t understand the technology, you don’t understand what the technology means to them, the people who will buy it.  Use their questions to improve the technology and the product.

Technologists know technology, technology knows what it wants to be when it grows up and customers know what they want after they see what could be.  And to create a new business, it takes all three working together.

Image credit — William Creswell

At first glance, it seems easy to run a good test, but nothing can be further from the truth.

The first step is to define the idea/concept you want to validate or invalidate.  The best way is to complete one of these two sentences: I want to learn that [type your idea here] is true. Or, I want to learn that [enter your idea here] is false.

Next, ask yourself this question: What information do I need to validate (or invalidate) [type your idea here]?  Write down the information you need.  In the engineering domain, this is straightforward: I need the temperature of this, the pressure of that, the force generated on part xyz or the time (in seconds) before the system catches fire.  But for people-related ideas, things aren’t so straightforward. Some things you may want to know are: how much will you pay for this new thing, how many will you buy, on a scale of 1 to 5 how much do you like it?

Now the tough part – how will you judge pass or fail?  What is the maximum acceptable temperature? What is the minimum pressure? What is the maximum force that can be tolerated? How many seconds must the system survive before catching fire?  And for people: What is the minimum price that can support a viable business? How many must they buy before the company can prosper? And if they like it at level 3, it’s a go. And here’s the most importance sentence of the entire post:

The decision criteria must be defined BEFORE running the test.

If you wait to define the go/no-go criteria until after you run the test and review the data, you’ll adjust the decision criteria so you make the decision you wanted to make before running the test. If you’re not going to define the decision criteria before running the test, don’t bother running the test and follow your gut.  Your decision will be a bad one, but at least you’ll save the time and money associated with the test.

And before running the test, define the test protocol.  Think recipe in a cookbook: a pinch of this, a quart of that, mix it together and bake at 350 degrees Fahrenheit for 40 minutes.  The best protocols are simple and clear and result in the same sequence of events regardless of who runs the test.  And make sure the measurement method is part of the protocol – use this thermocouple, use that pressure gauge, use the script to ask the questions about price and the number they’d buy.

And even with all this rigor, good judgement is still part of the equation.  But the judgment is limited to questions like: did we follow the protocol? Did the measurement system function properly? Do the initial assumptions still hold? Did anything change since we defined the learning objective and defined the test protocol?

To create formal learning objectives, to write well-defined test protocols and to formalize the decision criteria before running the test require rigor, discipline, time and money.  But, because the cost of making a bad decision is so high, the cost of running good tests is a bargain at twice the price.

Image credit – NASA Goddard Flight Center

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

Before there is something new to see, there is just a good idea worthy of a prototype.  And before there can be good ideas there are a whole flock of bad ones. And until you have enough self confidence to have bad ideas, there is only the status quo. Creating something from nothing is difficult.

New things are new because they are different than the status quo. And if the status quo is one thing, it’s ruthless in desire to squelch the competition. In that way, new ideas will get trampled simply based on their newness. But also in that way, if your idea gets trampled it’s because the status quo noticed it and was threatened by it.  Don’t look at the trampling as a bad sign, look at it as a sign you are on the right track. With new ideas there’s no such thing as bad publicity.

The eureka moment is a lie. New ideas reveal themselves slowly, even to the person with the idea. They start as an old problem or, better yet, as a successful yet tired solution. The new idea takes its first form when frustration overcomes intellectual inertia a strange sketch emerges on the whiteboard. It’s not yet a good idea, rather it’s something that doesn’t make sense or doesn’t quite fit.

The idea can mull around as a precursor for quite a while. Sometimes the idea makes an evolutionary jump in a direction that’s not quite right only to slither back to it’s unfertilized state.  But as the environment changes around it, the idea jumps on the back of the new context with the hope of evolving itself into something intriguing.  Sometimes it jumps the divide and sometimes it slithers back to a lower energy state.  All this happens without conscious knowledge of the inventor.

It’s only after several mutations does the idea find enough strength to make its way into a prototype. And now as a prototype, repeats the whole process of seeking out evolutionary paths with the hope of evolving into a product or service that provides customer value. And again, it climbs and scratches up the evolutionary ladder to its most viable embodiment.

Creating something new from scratch is difficult. But, you are not alone. New ideas have a life force of their own and they want to come into being. Believe in yourself and believe in your ideas. Not every idea will be successful, but the only way to guarantee failure is to block yourself from nurturing ideas that threaten the status quo.

Image credit – lost places

Doing challenging work isn’t difficult. Starting challenging work is difficult.

The downside of making a mistake is far less than the downside of not starting.

If you know how it will turn out, you waited too long to start.

Stopping is fine, as long as it’s followed closely by starting.

The scope of the project you start is defined by the cash in your pocket.

If you don’t start you can’t learn.

The project doesn’t have to be all figured out before starting, you just have to start.

Starting is scary because it’s important.

Before you can start you’ve got to decide to start.

If you’re finally ready to start, you should have started yesterday.

Without starting there can be no finishing.

Starting is blocked by both the fear of success and the fear of failure.

You don’t need to be ready to start, you just need to start.

The only thing in the way of starting is you.

Image credit — Dermot O’Halloran