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(#68) Innovation · Mechanical Engineering Made Simple

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Welcome back design junkies to Mechanical Engineering Made
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Simple. If you enjoy the podcast, show
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your support with a like a follow or a comment.
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Let's keep designing, learning and levelling up together.
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Today we are diving deep into the infrastructure that well
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that surrounds successful new product development.
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And we're not talking about CAD or prototyping.
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No, not the hard skills exactly. We're tackling the key
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organizational, informational and strategic factors, the
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non-technical hurdles that engineers you know have to
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navigate to get a great idea from the lab bench to an actual
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commercial success. It really is the silent killer
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of innovation For engineers who pour all their energy into
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technical elegance, into optimizing a curve or improving
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a material property, it's just intensely frustrating when a
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project stalls. Or just guys?
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Or dies, Yeah, because of some intangible issue, a lack of
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resource commitment or, you know, shifting political winds
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inside the company. That's why our mission today is
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to explore those soft the difference between a really
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exciting R&D project and a massive commercial win.
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It often lies entirely in the culture, the commitment and a
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deep, structured understanding of the customers world.
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We need to figure out how successful organizations manage
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that. Messy often overlooks starting
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point, the fuzzy front end of innovation.
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And getting that front end right is, well, it's everything.
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Because if the environment isn't supportive, innovation just
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starves. If innovators feel that there
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is, you know, no way to get the resources to validate their
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ideas, or if they just lack that fundamental trust and senior
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management support, good ideas get filed away.
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And they die in the vine. So the signal that innovation
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matters has to be loud and clear, and it has to come from
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the very top. What's the specific
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organizational mechanism required to send that message to
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establish real governance? Senior management has to
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institutionalized their involvement.
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They need to for an innovation steering committee.
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And this isn't just like a quarterly check in.
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This committee has to be responsible for defining the
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strategic direction and the financial goals for the entire
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innovation portfolio, the whole thing, the whole thing.
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And, crucially, they must meet with the product teams at a
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minimum of once per month. That frequency is the signal.
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It tells the organization that innovation is a priority, not
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some side project, and that senior leaders are dedicating
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their scarce time to it. That sets the precedent.
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Then it gives the tactical teams the air cover they need.
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But how does that committee achieve alignment when you know
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management usually wants aggressive financial growth that
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R&D can't possibly deliver with the current resources?
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They use a tool called Portfolio Rollout Scenarios.
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These are basically modeling tools that rigorously illustrate
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the exact number and magnitude of products that need to be
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launched to hit those financial goals.
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So if the CEO says I want 20% revenue growth, the model spits
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out OK, but you can't get that with two small product line
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extensions. You need 3 game changers and
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five platform updates. Precisely.
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And that creates the aha moment that forces A reckoning.
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The scenarios show in black and white that the company's current
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budget, their risk tolerance, their resource allocation, it's
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all completely disconnected from their desired financial future.
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So it forces that conversation it.
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Forces it. It shows that drastic changes in
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process and scope and commitment are required.
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This is often the only way you can compel senior management to
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move beyond just, you know, incrementalism.
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OK. So that's strategic shift
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happens, but how do how do you make sure the projects that move
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forward are chosen on merit, not just, you know, based on who
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yells the loudest? Yes.
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How do you build that culture of rigor?
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You implement standardized, explicit go, no go criteria.
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These are essential because they make sure decisions are based on
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objective rigor and consistency, not on politics, not personal
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preference, and definitely not gut sense.
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So. That just demoralizes the team
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it. Demoralizes them and wastes a
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ton of resources. So what are these criteria need
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to cover? What are the big categories for
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that decision architecture? They have to cover 5 non
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negotiable hurdles. Strategic fit, market
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attractiveness, customer needs, technical feasibility, and of
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course the financial hurdles. All 5.
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All 5. The key is that a project only
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moves forward if it clears all of them.
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It has to be strategically sound and financially viable and meet
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a real customer need. If it fails just one category,
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the process stops. It doesn't matter how cool the
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technology is. That system sounds perfect for
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vetting known opportunities. But what happens when we
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introduce truly revolutionary tech?
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You know, the radical projects where uncertainty just
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skyrockets? How do those criteria hold up?
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They change dramatically because you're not just dealing with
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technical risk anymore. Major innovation projects face 4
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distinct categories of uncertainty.
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We always expect high levels of technical uncertainty and market
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uncertainty. Right.
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Can we build it and will anyone buy?
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It but there are also high levels of resource uncertainty
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and organization uncertainty. Who's going to fund the next
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stage and critically, which operating unit is going to own
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this high risk project once R&D says it's done?
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And this sounds like the dreaded transition management gap.
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So if a system like Stage Gate works for the small incremental
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changes, where do these big uncertain projects fall through
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the cracks? They fall into a vacuum.
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A radical project, even when it's technically complete, still
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carries extremely high market and organizational uncertainty.
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The operating business unit which is driven by short term
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profit by sales pressures they can't easily absorb a project
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where the market is underdeveloped and the sales
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forecasts are, well, basically speculation.
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So. It's in this dangerous middle
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ground that nobody owns. Nobody owns it, and so promising
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projects just drop off the radar.
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So if you've developed a revolutionary technology but the
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market isn't ready for it, you can't just wait.
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You have to force the issue yourself.
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And that brings us to a really remarkable example of this, the
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digital micro mirror device. Right.
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Texas Instruments developed the DMD chip, a tiny revolutionary
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semiconductor based display for high definition projectors.
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They solved these immense technical challenges, but then
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they just hit a wall of market uncertainty.
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The projector assemblers were too nervous.
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Totally risk averse. They wouldn't commit to new
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designs because TI couldn't prove that sufficient end user
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demand actually existed yet. But wouldn't building the whole
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engine dilute TI's focus? I mean, they're a chip maker.
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It forces them into a whole new vertical they probably didn't
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want to be in. It did, but it was a temporary
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tactical shift just to overcome that market barrier.
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TI strategically integrated forward.
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They temporarily changed their whole business model.
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Instead of just selling the chip, they built and provided
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the entire display engine. The chip, the lens, the housing.
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The power source, everything, they gave assemblers a complete
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ready to use solution and that accelerated market development
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and generated the demand. And once the market was there?
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Once the market was established and others saw the opportunity,
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TI systematically unbundled the innovation and went right back
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to selling just the core DMD chip.
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It was a calculated move designed purely to kill that
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market uncertainty. That kind of strategic
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flexibility seems essential for radical success.
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But before you can even define the tech or the business model,
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you have to know what the customer actually needs, not
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just what they say they need. Which brings us to the voice of
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the customer dilemma. The dilemma is that conventional
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market research, I'm talking surveys, simple focus groups.
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It usually only captures surface level stuff, gripes, or asking
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customers to comment on what already exists.
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But developers need raw, often unarticulated needs to drive
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real innovation. The old saying, right?
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If you ask people what they want, they'll just ask for a
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faster horse. Exactly.
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So how do we use interview tactics to get past the horse
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and find the automobile? Well, generally, individual
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one-on-one interviews are much better than group settings for
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getting broad and detailed needs.
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They let the interviewer go off on pangents, follow surprising
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answers without, you know, derailing an entire focus group,
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and. What's the most powerful
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technique? Focusing on extremes.
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The best and the worst experiences.
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Precisely When you ask customers about the best and worst
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experiences they've ever had with a product, you get the peak
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moments of delight and the absolute troughs of frustration.
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Ask a business traveler about a hotel, They list generic things.
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Ask about their worst stay. They talk about a broken
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suitcase wheel and the Wi-Fi failing during a critical
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presentation. And that's where the real needs
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are hiding. That's where you get the
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richest, most actionable data. But sometimes you can't rely on
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what the customer tells you at all.
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You have to rely on what they do.
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Especially when usability problems are so common they
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don't even see them as problems anymore.
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Let's talk about the power of ethnography.
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Ethnography is a highly inductive approach.
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It's focused entirely on context.
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The critical learning happens when researchers just immerse
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themselves. They spend time in the
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environment where the behavior actually takes place.
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You won't get statistical significance, but the insights
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are far more valuable for innovation.
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The story of the farmer and his perfect tractor is such a great
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illustration of this. Oh, absolutely.
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Researchers were interviewing a farmer in his kitchen and he
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swore up and down his tractor was perfect, couldn't be
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improved. But then they walked with him
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out to his shed. And context.
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In context, he voluntarily revealed over 20 unique
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modifications he had secretly made to the equipment.
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Custom handles, relocated controls, added tools, all to
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make his workflow easier. The environment exposed all
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these unarticulated usability issues that the farmer had just
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learned to live with. That is just gold for an
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engineering team and this kind of contextual awareness can also
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transform B to B and we look at Cemex, the cement company.
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They recognize that the biggest pain point for their
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construction customers wasn't the cement itself.
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It was the intense frustration and massive cost associated with
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bad timing. If cement arrives late, an
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entire crew is just standing around.
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It's a perishable product. Right.
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So by prioritizing rapid, reliable delivery, they
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reposition themselves as the Domino's Pizza of cement.
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They solve the core business pain, the risk and anxiety of
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the poor, which let them charge a huge premium to get.
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To those blue sky ideas though, you have to remove all the
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mental constraints of the current reality, which is the
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beauty of the customer idealized design or CID the wish mode.
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The core principle is mandatory detachment.
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You tell participants to design their ideal product from a clean
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slate. You say assume the entire
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current system was destroyed last night.
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It's a psychological trick that stops them from self editing
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their ideas based on what they think is feasible.
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And IKEA actually used this to build a store.
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They did. Customers designing an idealized
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IKEA came up with an octagonal building with an open center,
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tons of natural light, and a restaurant Oasis near the
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entrance. You know, so you could eat
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before the long March through the maze.
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The new Chicago store was based heavily on that user design, and
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it showed significantly higher return visits and customer
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satisfaction. It proved that radical user
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input can actually define successful business
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architecture. OK.
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So we have organizational commitment through the steering
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committee. We have a strategy informed by
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roll out Cenarios and we have a Dee understanding of customer
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needs from ethograhy and CID. Now let's talk about organizing
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the engineering teams and how we quantify the value of their
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work. First up, team structure.
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Right. For NPD success, creativity is
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maximized when teams manage a flexible balance across what we
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call the virtuality fingerprint. This just captures things like
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physical proximity, communication methods, and how
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structured the tasks are. A lot of managers assume that Co
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location everyone in the same room all the time is always the
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best way to innovate. Why is that flawed?
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Because strict, constant colocation runs a serious risk
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of groupthink, people start to converge on the easiest, most
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agreed upon solution and it just kills diverse perspectives.
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So what do the most effective teams do?
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They use colocation strategically.
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They get together physically for the complex multidisciplinary
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decisions like a critical design review, but then they disperse
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for specialized individual tasks like detailed CAD work or
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component testing. This flexible approach maintains
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optimal creative potential. That's a powerful insight,
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finally justifying the R&D investment.
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For engineers, this means translating a technical feature
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like improve system uptime into measurable quantitative economic
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value for the customer. A crucial skill.
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We use a structured 6 step approach that starts with pane
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mapping. We find the customer's business
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difficulty through deep interviews and then trace it
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back through their operational process.
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The goal is to get from a vague pain to an actionable metric.
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Let's use that financial institution example where low
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system availability downtime was the pain.
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That's a technical effect that directly hits the bottom line.
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Exactly that technical failure point, low availability
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translated directly into two massive business pains, lost
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sales and customer defection. O We then quantify the value of
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fixing that technical flaw using their own oerational metrics.
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OK. So when you're calculating the
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value of increased sales from better U time, how do you
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structure that without it sounding like a complex algebra
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problem? You just map the operational
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flow to the money. It's a function of core
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variables. You look at the average number
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of trades per minute, times the securities to a trade, times the
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trading days per year, times the average price, times the
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difference in system availability, the old versus the
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new, and then times the fee rate.
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So it draws a clear, undeniable line.
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This investment in uptime converts directly into concrete
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revenue. What about the longer term value
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like customer loyalty? The value of customer loyalty is
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driven by three core metrics. The total number of customers
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multiplied by the average lifetime value of a customer
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multiplied by the customer defection rate.
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If you can reduce that defection rate by even a fraction of a
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percent by improving reliability, the value
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proposition for the R&D becomes massive.
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It can just dwarf the initial development cost.
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This really shows that an engineer's technical success
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hinges entirely on these other tools aligning strategy, finding
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latent needs, and proving the economic value.
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NPD's success requires engineers to be organizational navigators.
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You have to align your tech with the strategy via steering
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committees. You have to understand latent
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needs through ethnography. You need to manage flexible
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teams. And you have to translate every
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feature into measurable quantitative value for the
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customer. That is a master class in the
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infrastructure of innovation. Before we wrap, you shared a
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fascinating anecdote about a project that was a technical
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failure in one context, but a huge success in another.
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Yes, it's a powerful lesson. A-Team created this highly
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promising erasable ink for whiteboards.
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But during the final safety evaluation, the formulation was
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found to be highly toxic for a whiteboard pen that is a
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commercial failure. And if that team was working in
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a silo, the project would have been killed and the investment
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written off. Absolutely would have been.
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But because the organization required a periodic Independent
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Technology Summit, a committee dedicated to reviewing existing
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tech, the chemical composition was reviewed by people from
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outside the Penn division. And they saw a different
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application. The summit suggested
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transferring the toxic chemical formulation to the pesticide
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division. In that new context, the
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toxicity was a feature, not a bug.
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It quickly became a profitable component of a new product.
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So the final thought for you to chew on is this.
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The value of your innovation is often determined not by your
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original design brief, but by the organizational structures
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that are in place to recognize its potential in a completely
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different context. Look beyond your immediate goal.
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Your next success might be a technology that someone else
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labeled a failure.