Shipulski On Design

Archive for the ‘New Thinking’ Category

It’s pretty clear that innovation is the way to go. There’s endless creation of new technologies, new materials, and new processes so innovation can create new things to sell. And there are multiple toolsets and philosophies to get it done, but it’s difficult.

When doing new there’s no experience, no predictions, no certainty. But innovation is no dummy and has come up with a way to overcome the uncertainty. It builds knowledge of systems through testing – build it, test it, measure it, fix it. Not easy, but doable. And what makes it all possible is the repeatable response of things like steel, motors, pumps, software, hard drives. Push on them repeatably and their response is repeatable; stress them in a predictable way and their response is predictable; break them in a controlled way and the failure mode can be exercised.

Once there’s a coherent hypothesis that has the potential to make magic, innovation builds it in the lab, creates a measurement system to evaluate goodness, and tests it. After the good idea, innovation is about converting the idea into a hypothesis – a prediction of what will happen and why – and testing them early and often. And once they work every-day-all-day and make into production, the factory measures them relentlessly to make sure the goodness is shipped with every unit, and the data is religiously plotted with control charts.

The next evolution of innovation will come from systematically improving people systems. There are some roadblocks but they can be overcome. In reality, they already have been overcome it’s just that no one realizes it.

People systems are more difficult because their responses are not repeatable – where steel bends repeatably for a given stress, people do not. Give a last minute deliverable to someone in a good mood, and the work gets done; give that same deliverable to the same person on a bad day, and you get a lot of yelling. And because bad moods beget bad moods, people modify each other’s behavior. And when that non-repeatable, one-person-modifying-another response scales up to the team level, business unit, company, and supply chain, you have a complex adaptive system – a system that cannot be predicted. But just as innovation of airliners and automobiles uses testing to build knowledge out of uncertainty, testing can do the same for people systems.

To start, assumptions about how people systems would respond to new input must be hardened into formal hypotheses. And for the killer hypotheses that hang together, an experiment is defined; a small target population is identified; a measurement system created; a baseline measurement is taken; and the experiment is run. Data is then collected, statistical analyses are made, and it’s clear if the hypothesis is validated or not. If validated, the solution is rolled out and the people system is improved. And in a control chart sense, the measurement system is transferred to the whole system and is left to run continuously to make sure the goodness doesn’t go away. If it’s invalidated, another hypothesis is generated and the process is repeated. (It’s actually better to test multiple hypotheses in parallel.)

In the past, this approach was impossible because the measurement system did not exist. What was needed was a simple, mobile data acquisition system for “people data”, a method to automatically index the data, and a method to quickly process and display the results. The experimental methods were clear, but there was no response for the experiments. Now there is.

People systems are governed by what people think and feel, and the stories they tell are the surrogates for their thoughts and feelings. When an experiment is conducted on a people system, the stories are the “people data” that is collected, quantified, and analyzed. The stories are the response to the experiment.

It is now possible to run an experiment where a sample population uses a smart phone and an app to collect stories (text, voice, pictures), index them, and automatically send them to a server where some software groups the stories and displays them in a way to see patterns (groups of commonly indexed stories). All this is done in real time. And, by clicking on a data point, the program brings up the story associated with that data point.

Here’s how it works. The app is loaded, people tell their stories on their phone, and a baseline is established (a baseline story pattern). Inputs or constraints are changed for the target population and new stories are collected. If the patterns change in a desirable way (statistical analysis is possible), the new inputs and constraints are rolled out. If the stories change in an undesirable way, the target population reverts back to standard conditions and the next hypothesis is tested.

Unbiased, real time, continuous information streams to make sense of your people systems is now possible. Real time, direct connection to your employees and your customers is a reality, and the implications are staggering.

Thank you Dave Snowden.

In school the problems you were given weren’t really problems at all. In school you opened the book to a specific page and there, right before you in paragraph form and numbered consecutively, was a neat row of “problems”. They were fully-defined, with known inputs, a formal equation that defined the system’s response, and one right answer. Nothing extra, nothing missing, nothing contradictory. Today’s problems are nothing like that.

Today’s problems don’t have a closed form solution; today’s problems don’t have a right answer. Three important factors come into play: companies and their systems are complex; the work, at some level, is always new; and people are always part of the equation.

It’s not that companies have a lot of moving parts (that makes them complicated); it’s that the parts can respond differently in different situations, can change over time (learn), and the parts can interact and change each others’ response (that’s complex). When you’re doing work you did last time, there’s a pretty good chance the system will perform like it did last time. But it’s a different story when the inputs are different, when the work is new.

When the work is new, there’s no precedent. The inputs are new and the response is newer. Perturb the system in a new way and you’re not sure how it will respond. New interactions between preciously unreactive parts make for exciting times. The seemingly unconnected parts ping each other through the ether, stiffen or slacken, and do their thing in a whole new way. Repeatability is out the window, and causal predictability is out of the question. New inputs (new work) slathers on layers of unknownness that must be handled differently.

Now for the real complexity culprit – people. Companies are nothing more than people systems in the shape of a company. And the work, well, that’s done by people. And people are well known to be complex. In a bad mood, we respond one way; confident and secure we respond in another. And people have memory. If something bad happened last time, next time we respond differently. And interactions among people are super complex – group think, seniority, trust, and social media.

Our problems swim with us in a hierarchical sea of complexity. That’s just how it is. Keep that in mind next time you put together your Gantt chart and next time you’re asked to guarantee the outcome of an innovation project.

Complexity is real, and there are real ways to handle it. But that’s for another time. Until then, I suggest you bone up on Dave Snowden’s work. When it comes to complexity, he’s the real deal.

Image credit – miguelb.

From the outside it’s unclear how things happen; but from the inside it’s clear as day. No, it’s not your bulletproof processes; it’s not your top down strategy; and it’s not your operating plans. It’s your people.

At some level everything happens like this:

An idea comes to you that makes little sense, so you drop it. But it comes again, and then again. It visits regularly over the months and each time reveals a bit of its true self. But still, it’s incomplete. So you walk around with it and it eats at you; like a parasite, it gets stronger at your expense. Then, it matures and grows its voice – and it talks to you. It talks all the time; it won’t let you sleep; it pollutes you; it gets in the way; it colors you; and finally you become the human embodiment of the idea.

And then it tips you. With one last push, it creates enough discomfort to roll over the fear of acknowledging its existence, and you set up the meeting.

You call the band and let them know it’s time again to tour. You’ve been through it before and you all know deal. You know your instruments and you know how to harmonize. You know what they can do (because they’ve done it before) and you trust them. You sing them the song of your idea and they listen. Then you ask them to improvise and sing it back, and you listen. The mutual listening moves the idea forward, and you agree to take a run at it.

You ask how it should go. The lead vocalist tells you how it should be sung; the lead guitar works out the fingering; the drummer beats out the rhythm; and the keyboardist grins and says this will be fun. You all know the sheet music and you head back to your silos to make it happen.
In record time, the work gets done and you get back together to review the results. As a group you decide if the track is good enough play in public. If it is, you set up the meeting with a broader audience to let them hear your new music. If it’s not, you head back to the recording studio to amplify what worked and dampen what didn’t. You keep re-recording until your symphony is ready for the critics.

Things happen because artists who want to make a difference band together and make a difference. With no complicated Gantt chart, no master plan, no request for approval, and no additional resources, they make beautiful music where there had been none. As if from thin air, they create something from nothing. But it’s not from thin air; it’s from passion, dedication, trust, and mutual respect.

The business books over-complicate it. Things happen because people make them happen – it’s that simple.

There’s a natural hierarchy to work.  Your job, if you choose to accept it is to climb the ladder of hierarchy rung-by-rung. Here’s how to go about it:

Level 1. Work you can say no to – Say no to it. Say no effectively as you can, but say it. Saying no to level 1 work frees you up for the higher levels.

Level 2. Work you can get someone else to do – Get someone else to do it. Give the work to someone who considers the work a good reach, or a growth opportunity. This isn’t about shirking responsibility, it’s about growing young talent. Maybe you can spend a little time mentoring and the freed up time doing higher level work. Make sure you give away the credit so next time others will ask you for the opportunity to do this type of work for you.

Level 3. Work you’ve done before, but can’t wiggle out of – Do it with flair, style, and efficiency; do it differently than last time, then run away before someone asks you to do it again. Or, do it badly so next time they ask someone else to do it. Depending on the circumstance, either way can work.

Level 4. Work you haven’t done before, but can’t wiggle out of – Come up with a new recipe for this type of work, and do it so well it’s unassailable. This time your contribution is the recipe; next time your contribution is to teach it to someone else. (See level 2.)

Level 5. Work that scares others – Figure out why it scares them; break it into small bites; and take the smallest first bite (so others can’t see the failure).  If it works, take a bigger bite; if it doesn’t, take a different smallest bite.  Repeat, as needed. Next time, since you’ve done it before, treat it like level 3 work. Better still, treat it like level 2.

Level 6. Work that scares you – Figure out why it scares you, then follow the steps for level 5.

Level 7. Work no one knows to ask you to do – You know your subject matter better than anyone, so figure out the right work and give it a try.  This flavor is difficult because it comes at the expense of work you’re already signed up to do and no one is asking you to do it. But you should have the time because you followed the guidance in the previous levels.

Level 8. Work that obsoletes the very thing that made your company successful – This is rarified air – no place for the novice. Ultimately, someone will do this work, and it might as well be you.  At least you’ll be able to manage the disruption on your own terms.

In the end, your task, if you choose to accept it, is to migrate toward the work that obsoletes yourself. For only then can you start back at level 1 on the ladder of your own making.

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

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

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

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

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

Accomplishments in 2013

• Fourth year of weekly blog posts without missing a beat or repeating a post. (251 posts in total.)
• Third year of daily tweets – 2,170 in all. (@mikeshipulski)
• Second year as Top 40 Innovation Bloggers (#12) – Innovation Excellence, the web’s top innovation site.
• Seventh consecutive year as Keynote Speaker at International Forum on DFMA.
• Fourth year of LinkedIn working group – Systematic DFMA Deployment.
• Third year writing a column for Assembly Magazine (6 more columns this year).
• Wrote a book — PRODUCT PROCESS PEOPLE – Designing for Change (Which my subscribers can download for free.)

Top 5 Posts

1. What They Didn’t Teach Me In Engineering School — a reflection on my learning after my learning.
2. Guided Divergence — balancing act of letting go and shaping the future.
3. Innovation in 26 words — literally.
4. Lasting Behavioral Change — easy to say, tough to do.
5. Prototype The Unfamiliar — test early and often.

I look forward to a great year 5.

More-with-less is our mantra for innovation. But these three simple words are dangerous because they push us almost exclusively toward efficiency. On the surface, efficiency innovations sound good, and they can be, but more often than not efficiency innovations are about less and fewer. When you create a new technology that does more and costs less the cost reduction comes from fewer hours by fewer people. And if the cash created by the efficiency finances more efficiency, there are fewer jobs. When you create an innovative process that enables a move from machining to forming, hard tooling and molding machines reduce cost by reducing labor hours. And if the profits fund more efficiency, there are fewer jobs. When you create an innovative new material that does things better and costs less, the reduced costs come from fewer labor hours to process the material. And if more efficiency is funded, there are less people with jobs. (The cost reduction could also come from lower cost natural resources, but their costs are low partly because digging them up is done with fewer labor hours, or more efficiently.)

But more-with-less and the resulting efficiency improvements are helpful when their profits are used to fund disruptive innovation. With disruptive innovation the keywords are still less and fewer, but instead of less cost, the product’s output is less; and instead of fewer labor hours, the product does fewer things and satisfies fewer people.

It takes courage to run innovation projects that create products that do less, but that’s what has to happen. When disruptive technologies are young they don’t perform as well as established technologies, but they come with hidden benefits that ultimatley spawn new markets, and that’s what makes them special. But in order to see these translucent benefits you must have confidence in yourself, openness, and a deep personal desire to make a difference. But that’s not enough because disruptive innovations threaten the very thing that made you successful – the products you sell today and the people that made it happen. And that gets to the fundamental difference between efficiency innovations and disruptive innovations.

Efficiency innovations are about doing the familiar in a better way – same basic stuff, similar product functionality, and sold the same way to the same people. Disruptive innovations are about doing less than before, doing it with a less favorable cost signature, and doing it for different (and far fewer) people. Where efficiency innovation is familiar, disruptive innovation is contradictory. And this difference sets the the pace of the two innovations. Where efficiency innovation is governed by the speed of the technology, disruptive innovation is governed by the speed of people.

With efficiency innovations, when the technology is ready it jumps into the product and the product jumps into the market. With disruptive innovations, when the technology is ready it goes nowhere because people don’t think it’s ready – it doesn’t do enough. With efficiency innovations, the new technology serves existing customers so it launches; with disruptive, technology readiness is insufficient because people see no existing market and no existing customers so they make it languish in the corner. With efficiency, it launches when ready because margins are better than before; with disruptive, it’s blocked because people don’t see how the new technology will ultimately mature to overtake and replace the tired mainstream products (or maybe because they do.)

Done poorly efficiency innovation is a race to the bottom; done well it funds disruptive innovation and the race to the top. When coordinated the two play together nicely, but they are altogether different. One is about doing the familiar in a more efficient way, and the other is about disrupting and displacing the very thing (and people) that made you successful.

Most importantly, efficiency innovation moves at the speed of technology while disruptive innovation moves at the speed of people.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

There are a lot of complex self-help programs out there to help us reach our potential. These programs are designed to take us to the next level by building on what we have. And they do help. But implicitly the programs assume we’ve got a foundation in place and it’s solid enough to stand on. But I think our foundation is rickety.

To be what we must be is our responsibility, and if we’re going to get any value from our self-help programs it’s our responsibility to establish the conditions for growth.

Here are three forgotten pillars that must be in place if we’re to grow:

Good sleep habits – most of us our sleep deprived, yet the data is clear that a rested brain thinks better. If we’re to grow, we’ve got to think better, and to think better we need more rest.

Good eating habits – most of us eat poorly. We eat too much which hurts our bodies and we eat too infrequently which hurts our brains. We all know our muscles need calories or they don’t work well, but what we forget is our brain also needs calories. (It’s 2% of our weight but consumes about 20% of our total calories.) And when we eat infrequently our blood sugar drops and so does our brains’ ability to think. If we’re to grow, we need to eat better.

Good fitness habits – most of us don’t exercise daily. Our brain is connected to our body, and they interact. When the muscles are exercised they cause the brain to make chemicals that sooth and calm. When we exercise we have a better attitude, have more stamina, and think better. If we’re to grow, we need more exercise.

The big three are far more powerful than the best self-help scheme, but they’re also far scarier. They’re so scary because they’re easy to measure and completely within our control.

After a one month trial you’ll know if you’ve slept more, worked out more, and ate better. And if you haven’t, you’ll also know who is responsible.