Shipulski On Design

At the start of projects, no one knows what to do.  Engineering complains the specification isn’t fully defined so they cannot start, and marketing returns fire with their complaint – they don’t yet fully understand the customer needs, can’t lock down the product requirements, and need more time.  Marketing wants to keep things flexible and engineering wants to lock things down; and the result is a lot of thrashing and flailing and not nearly enough starting.

Both camps are right – the spec is only partially formed and customer needs are only partially understood – but the project must start anyway.  But the situation isn’t as bad as it seems.  At the start of a project fully wrung out specs and fully validated customer needs aren’t needed.  What’s needed is definition of product attributes that set its character, definition of how those attributes will be measured, and definition of the competitive products.  The actual values of the performance attributes aren’t needed, just their name, their relative magnitude expressed as percent improvement, and how they’ll be measured.

And to do this the project manager asks the engineering and marketing groups to work together to create simple bar charts for the most important product attributes and then schedules the meeting where the group jointly presents their single set of bar charts.

This little trick is more powerful than it seems.  In order to choose competitive products, a high level characterization of the product must be roughed out; and once chosen they paint a picture of the landscape and set the context for the new product.  And in order to choose the most important performance (or design) attributes, there must be convergence on why customers will buy it; and once chosen they set the context for the required design work.

Here’s an example.  Audi wants to start developing a new car.  The marketing-engineering team is tasked to identify the competitive products.  If the competitive products are BMW 7 series, Mercedes S class, and the new monster Hyundai, the character of the new car and the character of the project are pretty clear.  If the competitive products are Ford Focus, Fiat F500, and Mini Cooper, that’s a different project altogether.  For both projects the team doesn’t know every specification, but it knows enough to start.  And once the competitive products are defined, the key performance attributes can be selected rather easily.

But the last part is the hardest – to define how the performance characteristics will be measured, right down to the test protocols and test equipment.  For the new Audi fuel economy will be measured using both the European and North American drive cycles and measured in liters per 100 kilometer and miles per gallon (using a pre-defined fuel with an 89 octane rating); interior noise will be measured in six defined locations using sound meter XYZ and expressed in decibels; and overall performance will be measured by the lap time around the Nuremburg Ring under full daylight, dry conditions, and 25 Centigrade ambient temperature, measured in minutes.

Bar charts are created with the names of the competitive vehicles (and the new Audi) below each bar and performance attribute (and units, e.g., miles per gallon) on the right.  Side-by-side, it’s pretty clear how the new car must perform.  Though the exact number is not know, there’s enough to get started.

At the start of a project the objective is to make sure you’re focusing on the most performance attributes and to create clarity on how the attributes (and therefore the product) will be measured.  There’s nothing worse than spending engineering resources in the wrong area.  And it’s doubly bad if your misplaced efforts actually create constraints that limit or reduce performance of the most important attributes. And that’s what’s to be avoided.

As the project progresses, marketing converges on a detailed understanding of customer needs, and engineering converges on a complete set of specifications.  But at the start, everything is incomplete and no part of the project is completely nailed down.

The trick is to define the most important things as clearly as possible, and start.

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.

In a confusing way, the seemingly negative elements of novelty are actually tell-tale signs you’re doing it right.  Here are some examples:

No uncertainty, no upside.
No heresy, no game-changer.
No recipe, no worries.
No ambiguity, no new markets.
No effectiveness, no success.
No efficiency, no matter.
No disagreement, no gravity.
No answers, no problem.
No problem, no innovation.
No dispute, no dilemma.
No headache, no quandary.
No obstacle, no predicament.
No unrest, no virtue.
No failure, no creativity.
No discomfort, no relevance.
No agitation, no consequence.
No questions, no significance.
No best practice, no anxiety.
No downside, no upside.

Countries want their companies to create wealth and jobs, and to do it they want them to design products, make those products within their borders, and sell the products for more than the cost to make them. It’s a simple and sustainable recipe which makes for a highly competitive landscape, and it’s this competition that fuels innovation.

When companies do innovation they convert ideas into products which they make (jobs) and sell (wealth). But for innovation, not any old idea will do; innovation is about ideas that create novel and useful functionality. And standing squarely between ideas and commercialization are tough problems that must be solved. Solve them and products do new things (or do them better), become smaller, lighter, or faster, and people buy them (wealth).

But here’s the part to remember – problems are the precursor to innovation.

Before there can be an innovation you must have a problem. Before you develop new materials, you must have problems with your existing ones; before your new products do things better, you must have a problem with today’s; before your products are miniaturized, your existing ones must be too big. But problems aren’t acknowledged for their high station.

There are problems with problems – there’s an atmosphere of negativity around them, and you don’t like to admit you have them. And there’s power in problems – implicit in them are the need for change and consequence for inaction. But problems can be more powerful if you link them tightly and explicitly to innovation. If you do, problem solving becomes a far more popular sport, which, in turn, improves your problem solving ability.

But the best thing you can do to improve your problem solving is to spend more time doing problem definition. But for innovation not any old problem definition will. Innovation requires level 5 problem definition where you take the time to define problems narrowly and deeply, to define them between just two things, to define when and where problems occur, to define them with sketches and cartoons to eliminate words, and to dig for physical mechanisms.

With the deep dive of level 5 you avoid digging in the wrong dirt and solving the wrong problem because it pinpoints the problem in space and time and explicitly calls out its mechanism. Level 5 problem definition doesn’t define the problem, it defines the solution.

It’s not glamorous, it’s not popular, and it’s difficult, but this deep, mechanism-based problem definition, where the problem is confined tightly in space and time, is the most important thing you can do to improve innovation.

With level 5 problem definition you can transform your company’s profitability and your country’s economy. It does not get any more relevant than that.

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

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

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

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

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

For systems with high levels of complexity, such as organizations, business models, and cross-domain business processes, it’s characterize the current state, identify the future state, and figure out how to close the gap. That’s how I was trained. Simple, elegant, and no longer fits me.

The block diagram of the current state is neat and clean. Sure, there are interactions and feedback loops but, known inputs generate known outputs. But for me there are problems with the implicit assumptions. Implicit is the notion that the block diagram correctly represents current state; that uncontrollable environmental elements won’t change the block diagram; that a new box or two and new inputs (the changes to achieve the idealized future state) won’t cause the blocks to change their transfer functions or disconnect themselves from blocks or rewire themselves to others.

But what really tipped me over was the realization that the blocks aren’t blocks at all. The blocks are people (or people with a thin wrapper of process around), and it’s the same for the inputs. When blocks turn to people, the complexity of the current state becomes clear, and it becomes clear it’s impossible to predict how the system will response when it’s prodded and cajoled toward the idealized future state. People don’t respond the same way to the same input, never mind respond predictably and repeatably to new input. When new people move to the neighborhood, the neighborhood behaves differently. People break relationships and form others at will. For me, the implicit assumptions no longer hold water.

For me the only way to know how a complex system will respond to rewiring and new input is to make small changes and watch it respond. If the changes are desirable, do more of that. If the changes are undesirable, do less.

With this approach the work moves from postulation to experimentation and causation – many small changes running parallel with the ability to discern the implications. And the investigations are done in a way to capture causality and maintain system integrity. Generate learning but don’t break the system.

It’s a low risk way to go because before wide-scale implementation the changes have already been validated. Scaling will be beneficial, safe, and somewhat quantifiable. And the stuff that didn’t work will never see the light of day.

If someone has an idea, and it’s coherent, it should be tested. And instead of arguing over whose idea will be tested, it becomes a quest to reduce the cost of the experiments and test the most ideas.

If you’re sitting in the present, you’re sitting in a good place – you’re more mindful of what’s going on, more aware of your thinking, and more thoughtful of your actions.  But there’s one thing sitting in the present can’t provide, and that’s perspective.  To create perspective, to understand the hows and whys of your journey to the present, requires reflection on the past. But to self reflect without distorting the image requires separation from your present.

Here’s an idea to create separation – an exercise in mental time travel where your past becomes your present and your present becomes your future.  It goes like this: Set your mental way-back machine for five years ago, turn the crank and jump back to a five-years-ago present. From your seat in your new present (your past), erase your future (your present) to open it up to unlimited possibilities.  Now, imagine a future (one of the infinite possible futures) that is identical to the one that actually happened. (But remember, you don’t know it happened, so it’s only a potential future state.) Okay.  You’re now ready to mint your own perspective.

From your seat in your new present (your past), ask yourself three questions.

If your imagined future (your actual present state) came to be:

1. How would you feel about your relationships with your friends, your community, and your family?
2. How would you feel about your health?
3. How would you feel about the alignment between your actions, values, and passions?

With your answers in hand (and I suggest you actually write them down), use your way-back machine to jump forward to the present present. Sitting in the present (the real one), read your answers (written five years ago) to the three questions above.

How do you feel about your answers?  What do you like about your answers? What makes you uncomfortable? What surprised you? Write down your answers because that’s the unfiltered perspective you were looking for.

Now the valuable part – two final questions (write down the actual answers):

Taking guidance from your newly self-minted perspective:

1. Going forward, while sitting in the present, what will you do more of?
2. Going forward, while sitting in the present, what will you do less of?

If you are sufficiently intrigued (or confused) to try the exercise and find value in it, please pay it forward and share it with others.

And don’t forget to repeat the process every year.

Own your ideas, not the drama.

Own your words, not the gossip.

Own your vision, not the dogma.

Own your effort, not the heckling.

Own your vacation, not the email.

Own your behavior, not the strife.

Own your talent, not the cynicism.

Own your deeds, not the rhetoric.

Own your caring, not the criticism.

Own your sincerity, not the hot air.

Own your actions, not the response.

Own your insights, not the rejection.

Own your originality, not the critique.

Own your passion, not the nay saying.

Own your loneliness, not the back story.

Own your health, not the irrational workload.

Own your thinking, not the misunderstanding.

Own your stress level, not the arbitrary due date.

Own your happiness.

We set visions, define idealized future states, define metrics, and create tools and processes to realize them. It’s all knit together, the puzzle pieces fight tightly, and it leaves out the most important part – people and their behavior.

Metrics represent the all-important output of our tools and processes, and we’re so fascinated by metrics because customers pay for outputs they stand for. The output of the product development process is the recipe for the product, and the output of the manufacturing process is product itself. We’re muscle bound with metrics because these outputs are vitally important to profitability. Here’s a rule: the processes and tools we deem most important have the most metrics.

Metrics measure outputs, and managing with output metrics is like driving a car while looking in the rear view mirror. But that’s what we do. But what about managing the inputs?

The inputs to tools are people and their behaviors. People use tools, and how they use them – their behavior – governs the goodness of the output. Sometimes we behave otherwise, but how people use the tools (the inputs) is more important than the tools. But don’t confuse the sequence of steps with behaviors.

All the steps can be intricately defined without capturing the desired behavior. 1.) Load the solid model – see Appendix C. 2.) Set up the boundary conditions using the complicated flow chart in Appendix D. 3.) Run the analysis. 4.) Interpret the results. (Which is far too complicated to capture even in the most complicated appendix.) But the steps don’t define the desired behavior. What’s the desired behavior if the flowchart doesn’t come up with boundary conditions that are appropriate? What’s the behavior to decide if they’re inappropriate? What’s the behavior if you’re not sure the results are valid? What’s the behavior to decide if an analysis is needed at all?

The desired behaviors could go something like this: If the boundary conditions don’t make sense, trust your judgment and figure out why it doesn’t make sense. Don’t spend all day, but use good judgment on how long to spend. If you’re still not sure, go ask someone you trust. Oh, and if you think an analysis isn’t needed, trust your judgment and don’t do one.

And it’s the same for processes – a sequence of steps, even the most complete definition, doesn’t capture the desired behavior when judgment is required.

To foster the desired behavior, people must feel they can be trusted – trusted to use their best judgment. But for people to feel trusted, they have to be trusted. And not trusted once, or once in a while, consistently trusted over time.

Computers and their software tools quickly predictably crank through millions of ultra-defined process steps. But when their processes require judgment, even their hyper-speed can’t save them. When things don’t fit, when it hasn’t been done before, when previous success no longer applies, it’s people and their judgment that must carry the day.

Everyone has the same computers and the same software tools – there’s little differentiation there. People are the big differentiators. And there’s a huge competitive advantage for those companies that create the culture where their people error on the side of exercising their judgment. And for that, you have to build a legacy of trust.

When I think of independence:

I know I can speak my mind, but must remember others have the same right.

I know how lucky I am, but must keep in mind others are not.

I think of my wonderful rights, but steep in the huge obligation that comes with them.

I sometimes forget I have first world problems, and know I cannot truly comprehend third world problems.

I know I didn’t have to sacrifice anything, but others willingly sacrificed everything.

I must remember that I have it good, and I have an obligation to give back.

I must remember that my independent thought isn’t necessarily right, it’s just independent.

I want to keep in front of me we’re all immigrants, we just differ in when we arrived.

I must remember that independence is fueled by diversity, and our differences must be respected and validated.

I know my kids take for their independence for granted, but so do I.

Changing your behavior is hard. Often, just wanting to change is insufficient, especially for change that runs deep. For deep change, on its own the want doesn’t cut it. What’s required is a powerful why. Why do you want to change? What’s your motivation?

But all whys are not created equal with some motivations more powerful than others. Is your motivation all about you, about your family, or society as a whole? The less it’s about you the greater its hold. Clarity on why is vital because it brings staying power.

A meaningful why can help maintain much needed determination as you push away from your as-is self. And determination is crucial because saying no to your previous behavior is exceptionally difficult because it demands full acknowledgement of your true self. In an unhealthy way, changing your behavior can be thought of as an admission – in the form of actions – that your behavior has not been up to snuff. But that’s not it. Changing your behavior is an admission you value yourself enough to face a self-imposed desire to bring more goodness; you value your family enough to bring them happiness, and you value life itself enough to reduce its suffering. It’s not about fixing something that’s broken; it’s about bringing more goodness and light.

Changing your behavior is no small thing, and to make it lasting requires deep grounding. To work through distractions; to hold onto the courage; to continually add the energy all require a strangle hold on what’s truly important. So I ask you know – what’s truly important?

You can fake it for a while, but in the end, because your motivation is not grounded, you’ll revert to your previous self. And I think this is worse than simply maintaining yourself as-is. You spend precious energy forcing the behavior because there’s no grounded motivation. Also, you set expectations that the temporary new behavior is now the standard, and when you revert expectations must be reset.

Here’s a proposal: Start small – latch on to a small why and create a small change. Feel what it feels like and own it. Use your new positivity to springboard to a bigger why and a bigger change and make that one stick. Next, stand on the shoulders of the goodness to reach for a bigger, broader why and a bigger, broader change. Then, repeat.