Shipulski On Design

Archive for the ‘Fundementals’ Category

We all have computer models – economic models, buying models, voting models, thermal, stress, and vibration. A strange thing happens when our models reside in the computer: their output becomes gospel, unchallengeable. And to set the hook, computerized output is bolstered by slick graphics, auto-generated graphs, and pretty colors.

Model fundamentals are usually well defined, proven, and grounded – not the problem. The problem is applicability. Do the fundamentals apply? Do they apply in the same way? Do different fundamentals apply? We never ask those questions. That’s the problem.

New folks don’t have the context to courageously challenge fundamentals and more experienced folks have had the imagination flogged out of them. So who’s left to challenge applicability of fundamentals? You know who’s left.

It’s smart folks with courage that challenge fundamentals; it’s people willing to contradict previous success (even theirs) that challenge fundamentals; it’s people willing to extend beyond that challenge fundamentals; it’s people willing to risk their career that challenge fundamentals.

Want to challenge fundamentals? Hire, engage, and support smart folks with courage.

There are three categories of knowing: we know we know, we don’t know, and we think we know.

When we know we know - we understand fundamentals, we have a model, we have evidence, we can predict. We can build on this knowledge. We’re not often in this state, but it sure feels good when we are. The trick here is to understand the applicability of the knowledge. Change the inputs, change the system, or change the environment and we must question our knowledge. Do the fundamentals still apply?

When we don’t know – no fundamentals, no model, and no predictions. No danger on building on bad knowledge. Life is uncomplicated. Next task: develop the fundamentals; build a model. We’re in this state more often than we admit, and there’s the danger. It’s politically difficult to say “I don’t know.” But it must be said. Otherwise we’re expected to predict the future and to build on the knowledge (that we don’t have).

When we think we know – no fundamentals, no model, and predictions we bet our businesses on. Danger. It feels just as good as when we know we know, but it shouldn’t. Momentum in the wrong direction and we don’t know it. And we’re likely in this state more often than not. But this is a meta-state, an unstable state. The trick is to push on our knowledge so we tip into one of the other two states. Push on our knowledge so we know if we know.

Do you know the fundamentals? Do you have a model? Can you predict?

Companies (and countries) are slowly learning that moving manufacturing to low cost countries is a big mistake, a mistake of economy-busting proportion. (More costly than any war.) With labor costs at 10% of product cost, saving 20% on labor yields a staggering 2% cost savings. 2%. Say that out loud. 2%. Are you kidding me? 2%? Really? Moving machines all over the planet for 2%? What about cost increases from longer supply chains, poor quality, and loss of control? Move manufacturing to a country with low cost labor? Are you kidding me? Who came up with that idea? Certainly not a knowledgeable manufacturing person. Don’t chase low cost labor, design it out.

(I feel silly writing this. This is so basic.  Blocking-and-tackling. Design 101. But we’ve lost our way, so I will write.)

Use Design for Assembly (DFA) and Design for Manufacturing (DFM) to design out 25-50% of the labor time and make product where you have control. The end. Do it. Do it now. But do it for the right reasons – throughput, and quality.  (And there’s that little thing about radical material cost reduction which yield cost savings of 20+%, but that’s for another time).

The real benefit of labor reduction is not dollars, it’s time. Less time, more throughput. Half the labor time, double the throughput. One factory performs like two. Bring it back. Fill your factories. Repeat the mantra and you’ll bring it back:

Half the labor and one factory performs like two.

QC stands for Quality Control. No control, no quality. Ever try to control things from 10 time zones in the past? It does not work. It has not worked. Bring it back. Bring back your manufacturing to improve quality. Your brand will thank you. Put the C back in QC – bring it back.

Forward this to your highest level Design Leaders. Tell them they can turn things around; tell them they’re the only ones who can pull it off; tell them we need; tell them we’re counting on them; tell them we’ll help; tell them to bring it back.

Companies pursue lots of ideas; some turn out well and some badly. Since we can’t tell with 100% certainty if an idea will work, bad ones are a cost of doing business. And it makes sense to tolerate them. The cost of a few bad ones is well worth the upside of a game-changer. It’s like the VC model.

However, there’s a class that must be avoided at all costs: the dumb-ass idea – an idea we should know will not work before we try it. It’s not a bad idea,  it’s beyond stupid, it’s deadly.

A dumb-ass idea violates fundamentals.

What’s so scary is today’s ready, fire, aim pace makes us more susceptible than ever. Our dumb-ass antibodies need strengthening. We need an immunization, a filter to discern if we’re respecting the fundamentals. We need a dumb-ass filter.

To immunize ourselves it’s helpful to understand how these ideas come to be. Here are some mutant strains:

Local optimization – We improve part of the system at the expense of the overall system. Chasing low cost labor is a good example where labor savings are dwarfed by increased costs of logistics, training, quality, and support.

A cloudy lens – We come up with an idea based on incomplete, biased, or inappropriate data. A good example is financial data which captures cost in a most artificial way. Overhead calculation is the poster child.

Cause and effect – We don’t know which is which; we confuse symptom with root cause and correlation with causation. Expect the unexpected with this mix up.

Scaling – We assume success in the lab is scalable to success across the globe. Everything does not scale, and less scales cost effectively.

Fear – We want to go fast because our competition is already there; we want to go slow because were afraid to fail.

What’s the best dumb-ass filter? It’s a formal and simple definition of the fundamentals. Use one page thinking – fundamentals one page, lots of pictures and few words. There’s no escape.

How to go about it? Settle yourself. Catch your breath. Let your pulse slow. Then, create a one pager (pictures, pictures, pictures) that defines the fundamentals and run it by someone you trust, someone without a vested interest, someone who has learned from their own dumb-ass thinking. (Those folks can spot it at twenty paces.) Defend it to them. Defend it to yourself. Run yourself through the gauntlet.

What are the fundamentals? Do they apply in this situation? How do you know? Answer these and you’re on your way to self-inoculation.