Latest / Mechanical Engineering Made Simple / (#81) Innovation Governance and Latent Customer Needs

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(#81) Innovation Governance and Latent Customer Needs · 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's,
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you know, no way to get the resources to validate their
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ideas, or if they just lack that fundamental trust in 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 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? How do you build that culture of
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rigor You. Implement standardized, explicit
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Go, no go criteria. These are essential because they
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make sure decisions are based on objective rigor and consistency,
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not on politics, not personal preference, and definitely not
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gut sense. So.
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That just demoralizes the team it.
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Demoralizes them and wastes a ton of resources.
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So what do? These criteria need to cover
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what are the big categories for that decision architecture.
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They have to cover 5 non negotiable hurdles.
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Strategic fit, market attractiveness, customer needs,
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technical feasibility, and of course the financial hurdles.
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All 5. All 5.
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The key is that a project only moves forward if it clears all
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of them. It has to be strategically sound
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and financially viable and meet a real customer need.
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If it fails just one category, the process stops.
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It doesn't matter how cool the technology is.
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That system sounds perfect for vetting known opportunities.
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But what happens when we introduce truly revolutionary
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tech? You know, the radical projects
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where uncertainty just skyrockets?
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How do those criteria hold up? They change dramatically because
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you're not just dealing with technical risk anymore.
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Major innovation projects face 4 distinct categories of
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uncertainty. We always expect high levels of
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technical uncertainty and market uncertainty.
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Right. Can we build it and will anyone
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buy? It but there are also high
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levels of resource uncertainty and organization uncertainty.
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Who's going to fund the next stage and critically, which
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operating unit is going to own this high risk project once R&D
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says it's done? And this sounds like the dreaded
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transition management gap. So if a system like Stage Gate
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works for the small incremental changes, where do these big
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uncertain projects fall through the cracks?
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They fall into a vacuum. A radical project, even when
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it's technically complete, still carries extremely high market
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and organizational uncertainty. The operating business unit,
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which is driven by short term profit by sales pressures they
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can't easily absorb. A project where the market is
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underdeveloped and the sales forecasts are, well, basically
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speculation. 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
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nervous. Totally risk averse.
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They wouldn't commit to new designs because TI couldn't
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prove that sufficient end user demand actually existed yet.
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But wouldn't building the whole engine dilute TI's focus?
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I mean, they're a chip maker. It forces them into a whole new
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vertical they probably didn't want to be in.
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It did, but it was a temporary tactical shift just to overcome
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that market barrier. TI strategically integrated
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forward. They temporarily changed their
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whole business model. Instead of just selling the
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chip, they built and provided the entire display engine.
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The chip, the lens, the housing, the.
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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 so.
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How do we use interview tactics to get past the horse and find
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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 pangins, 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 technique?
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Focusing on extremes. The best and the worst
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experiences. Precisely When you ask customers
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about the best and worst experiences they've ever had
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with a product, you get the peak moments of delight and the
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absolute troughs of frustration. Ask a business traveler about a
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hotel, They list generic things. Ask about their worst stay, They
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talk about a broken suitcase wheel and the Wi-Fi failing
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during a critical presentation. And.
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That's where the real needs are hiding.
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That's where you get the richest, most actionable data.
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But sometimes you can't rely on what the customer tells you at
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all. You have to rely on what they
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do. Especially when usability
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problems are so common they don't even see them as problems
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anymore. Let's talk about the power of
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ethnography. Ethnography is a highly
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inductive approach. It's focused entirely on
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context. The critical learning happens
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when researchers just immerse themselves.
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They spend time in the environment where the behavior
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actually takes place. You won't get statistical
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significance, but the insights are far more valuable for
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innovation. The story of the farmer and his
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perfect tractor is such a great illustration of this.
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Oh, absolutely. Researchers were interviewing a
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farmer in his kitchen and he swore up and down his tractor
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was perfect, couldn't be improved.
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But then they walked with him out to his shed.
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In context. In context, he voluntarily
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revealed over 20 unique modifications he had secretly
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made to the equipment. Custom handles, relocated
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controls, added tools, all to make his workflow easier.
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The environment exposed all these unarticulated usability
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issues that the farmer had just learned to live with.
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That is just gold for an engineering team and this kind
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of contextual awareness can also transform B to B and we look at
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Cemex, the cement company. They recognize that the biggest
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pain point for their construction customers wasn't
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the cement itself. It was the intense frustration
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and massive cost associated with bad timing.
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If cement arrives late, an entire crew is just standing
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around. It's a perishable product.
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Right. So by prioritizing rapid,
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reliable delivery, they reposition themselves as a
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Domino's Pizza of cement. They solve the core business
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pain, the risk and anxiety of the poor, which let them charge
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a huge premium to get to. Those blue sky ideas though, you
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have to remove all the mental constraints of the current
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reality, which is the beauty of the customer idealized design or
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CID, the wish mode. The core principle is mandatory
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detachment. You tell participants to design
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their ideal product from a clean slate.
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You say assume the entire current system was destroyed
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last night. It's a psychological trick that
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stops them from self editing their ideas based on what they
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think is feasible. And IKEA actually used this to
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build a store. They did.
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Customers designing an idealized IKEA came up with an octagonal
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building with an open center, tons of natural light, and a
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restaurant Oasis near the entrance.
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You know, so you could eat before the long March through
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the maze. The new Chicago store was based
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heavily on that user design, and it showed significantly higher
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return visits and customer satisfaction.
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It proved that radical user input can actually define
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successful business architecture.
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OK. So we have organizational
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commitment through the steering committee.
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We have a strategy informed by rollouts scenarios and we have a
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Dee understanding of customer needs from ethograhy and CID.
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Now let's talk about organizing the engineering teams and how we
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quantify the value of their work.
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First up, team structure. Right.
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For NPD success, creativity is maximized when teams manage a
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flexible balance across what we call the virtuality fingerprint.
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This just captures things like physical proximity,
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communication methods, and how structured the tasks are.
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A lot of managers assume that Co location everyone in the same
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room all the time is always the best way to innovate.
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Why is that flawed? Because strict constant Co
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location runs a serious risk of groupthink, people start to
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converge on the easiest, most agreed upon solution and it just
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kills diverse perspectives. So what do the most effective
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teams do? They use Co location
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strategically. They get together physically for
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the complex multidisciplinary decisions like a critical design
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review, but then they disperse for specialized individual tasks
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like detailed CAD work or component testing.
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This flexible approach maintains optimal creative potential.
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That's a powerful insight, finally justifying the R&D
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investment. For engineers, this means
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translating a technical feature like improve system uptime into
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measurable quantitative economic value for the customer.
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A crucial skill. We use a structured 6 step
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approach that starts with pane mapping.
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We find the customer's business difficulty through deep
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interviews and then trace it back through their operational
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process. The goal is to get from a vague
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pain to an actionable metric. Let's use that financial
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institution example where low system availability downtime was
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the pain. That's a technical effect that
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directly hits the bottom line. Exactly that technical failure
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point, low availability translated directly into two
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massive business pains, lost sales and customer defection.
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O We then quantify the value of fixing that technical flaw using
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their own oerational metrics. OK.
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So when you're calculating the value of increased sales from
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better uptime, how do you structure that without it
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sounding like a complex algebra problem?
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You just map the operational flow to the money.
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It's a function of core variables.
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You look at the average number of trades per minute, times the
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securities to a trade, times the trading days per year, times the
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average price, times the difference in system
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availability, the old versus the new, and then times the fee
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rate. So it.
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Draws a clear, undeniable line. This investment in uptime
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converts directly into concrete revenue.
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What about the longer term value like customer loyalty?
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The value of customer loyalty is driven by three core metrics.
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The total number of customers multiplied by the average
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lifetime value of a customer multiplied by the customer
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defection rate. If you can reduce that defection
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rate by even a fraction of a percent by improving
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reliability, the value proposition for the R&D becomes
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massive. It can just dwarf the initial
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development cost. This.
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Really shows that an engineer's technical success hinges
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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.