Shipulski On Design

Archive for the ‘How To’ Category

There are three types of innovation: innovation that creates jobs, innovation that’s job neutral, and innovation that reduces jobs.

Innovation that reduces jobs is by far the most common. This innovation improves the efficiency of things that already exist – the mantra: do the same, but with less. No increase in sales, just fewer people employed.

Innovation that’s job neutral is less common. This innovation improves what you sell today so the customer will buy the new one instead of the old one. It’s a trade – instead of buying the old one they buy the new one. No increase in sales, same number of people employed.

Innovation that creates jobs is uncommon. This innovation radically changes what you sell today and moves it from expensive and complicated to affordable and accessible. Sell more, employ more.

Clay Christensen calls it Disruptive Innovation; Vijay Govindarajan calls it Reverse Innovation; and I call it Less-With-Far-Less.

The idea is the product that is sold to a relatively small customer base (due to its cost) is transformed into something new with far broader applicability (due to its hyper-low cost). Clay says to “look down” to see the new technologies that do less but have a super low cost structure which reduces the barrier to entry. And because more people can afford it, more people buy it. And these aren’t the folks that buy your existing products. They’re new customers.

Vijay says growth over the next decades will come from the developing world who today cannot afford the developed world’s product. But, when the price comes down (down by a factor of 10 then down by a factor of 100), you sell many more. And these folks, too, are new customers.

I say the design and marketing communities must get over their unnatural fascination with “more” thinking. To sell to new customers the best strategy is increase the number of people who can afford your product. And the best way to do that is to radically reduce the cost signature at the expense of features and function. If you can give ground a bit on the thing that makes your product successful, there is huge opportunity to reduce cost – think 80% less cost and 20% less function. Again, you sell new product to new customers.

Here’s a thought experiment to help put you in the right mental context: Create a plan to form a new business unit that cannot sell to your existing customers, must sell a product that does less (20%) and costs far less (80%), and must sell it in the developing world. Now, create a list of small projects to test new technologies with radically lower cost structures, likely from other industries. The constraint on the projects – you must be able to squeeze them into your existing workload and get them done with your existing budget and people. It doesn’t matter how long the projects take, but the investment must be below the radar.

The funny thing is, if you actually run a couple small projects (or even just one) to identify those new technologies, for short money you’ve started your journey to selling new products to new customers.

The Holy Grail of marketing is to identify emerging customer needs before anyone else and satisfy them to create new markets. It has been a long and fruitless slog as emerging needs have proven themselves elusive. And once candidates are identified, it’s a challenge to agree which are the game-changers and which are the ghosts. There are too many opinions and too few facts. But there’s treasure at the end of the rainbow and the quest continues.

Emerging things are just coming to be, just starting, so they appy to just a small subset of customers; and emerging things are new and different, so they’re unfamiliar. Unfamiliar plus small same size equals elusive.

I don’t believe in emerging customer needs, I believe in emergent customer behavior.

Emergent behavior is based on actions taken (past tense) and is objectively verifiable. Yes or no, did the customer use the product in a new way? Yes or no, did the customer make the product do something it wasn’t supposed to? Did they use it in a new industry? Did they modify the product on their own? Did they combine it with something altogether unrelated? No argument.

When you ask a customer how to improve your product, their answers aren’t all that important to them. But when a customer takes initiative and action, when they do something new and different with your product, it’s important to them. And even when just a few rouge customers take similar action, it’s worth understanding why they did it – there’s a good chance there’s treasure at the end of that rainbow.

With traditional VOC methods, it has been cost prohibitive to visit enough customers to learn about a handful at the fringes doing the same crazy new thing with your product. Also, with traditional VOCs, these “outliers” are thrown out because they’re, well, they’re outliers. But emergent behavior comes from these very outliers. New information streams and new ways to visualize them are needed to meet these challenges.

For these new information streams, think VOC without the travel; VOC without leading the witness; VOC where the cost of capturing their stories is so low there are so many stories captured that it’s possible to collect a handful of outliers doing what could be the seed for the next new market.

To reduce the cost of acquisition, stories are entered using an app on a smart phone; to let emergent themes emerge, customers code their own stories with a common, non-biasing set of attributes; and to see patterns and outliers, the coded stories are displayed visually.

In the past, the mechanisms to collect and process these information streams did not exist. But they do now.

I hope you haven’t given up on the possibility of understanding what your customers will want in the near future, because it’s now possible.

I urge you to check out SenseMaker.

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

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

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

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

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

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

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

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

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

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

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

Thank you Dave Snowden.

Put yourself out there. Let it hang out. Give it a try. Just do it. The reality is few do it, and fewer do it often. But why?

In a word, fear. But it cuts much deeper than a word. Here’s a top down progression:

What will they think of your idea? If you summon the courage to say it out loud, your fear is they won’t like it, or they’ll think it’s stupid. But it goes deeper.

What with they think of you? If they think your idea is stupid, your fear is they’ll think you’re stupid. But so what?

How will it conflict with what you think of you? If they think you’re stupid, your fear is it will conflict with what you think of you. Now we’re on to it – full circle.

What do you think of you? It all comes down to your self-image – what you think is it and how you think it will stand up against the outside forces trying to pull it apart. The key is “what you think” and “how you think”. Like all cases, perception is reality; and when it comes to judging ourselves, we judge far too harshly. Our severe self-criticism deflates us far below the waterline of reality, and we see ourselves far shallower than our actions decree.

You’re stronger and more capable than you let yourself think. But no words can help with that; for that, only action will do. Summon the courage to act and take action. Just do it. And to calm yourself before you jump, hold onto this one fact – others’ criticism has never killed anyone. Stung, yes. Killed, no. Plain and simple, you won’t die if you put yourself out there. And even the worst bee stings subside with a little ice.

I’m not sure why we’re so willing to abdicate responsibility for what we think of ourselves, but we do. So where you may have abdicated responsibility in the past, in the now it’s time to take responsibility. It’s time to take responsibility and act on your own behalf.

Fear is real, and you should acknowledge it. But also acknowledge you give fear its power. Feel the fear, be afraid. But don’t succumb to the power you give it.

Put yourself out there. Do it tomorrow. You won’t die. And I bet you’ll surprise others.

But I’m sure you’ll surprise yourself more.

Planning is important work, but it’s non-value added work. Short and sweet – planning is waste.

Lean has taught us waste should be reduced, and the best way to reduce waste from planning is to spend less time planning. (I feel silly writing that.) Lean has taught us to reduce batch size, and the best way to reduce massive batch size of the annual planning marathon is to break it into smaller sessions. (I feel silly writing that too.)

Unreasonable time constraints increase creativity. To create next year’s plan, allocate just one for the whole thing. (Use a countdown timer.) And, because batch size must be reduced, repeat the process monthly. Twelve hours of the most productive planning ever, and countless planning hours converted into value added work.

Defining the future state and closing the gap is not the way to go. The way to go is to define the current state (where you are today) and define how to move forward. Use these two simple rules to guide you:

• Do more of what worked.
• Do less of what didn’t.

Here’s an example process:

The constraint – no new hires. (It’s most likely the case, so start there.)

Make a list of all the projects you’re working on. Decide which to stop right now (the STOP projects) and which you’ll finish by the end of the month (the COMPLETED projects). The remaining projects are the CONTINUE projects, and, since they’re aptly named, you should continue them next month. Then, count the number of STOP and COMPLETED projects – that’s the number of START projects you can start next month.

If the sum of STOP and COMPLETED is zero, ask if you can hire anyone this month. If the answer is no, see you next month.

If the sum is one, figure out what worked well, figure out how to build on it, and define the START project. Resources for the START project should be the same as the STOP or COMPLETED project.

If the sum is two, repeat.

Now ask if you can hire anyone this month. If the answer is no, you’re done. If the answer is yes, define how many you can hire.

With your number in hand, and building on what worked well, figure out the right START project. Resources must be limited by the number of new hires, and the project can’t start until the new hire is hired. (I feel silly writing that, but it must be written.) Or, if a START project can’t be started, use the new resource to pile on to an important CONTINUE project.

You’re done for the month, so send your updated plan to your boss and get back to work.

Next month, repeat.

The process will evolve nicely since you’ll refine it twelve times per year.

Ultimately, planning comes down to using your judgment to choose the next project based on the resources you’re given. The annual planning process is truly that simple, it’s just doesn’t look that way because it’s spread over so many months. So, if the company tells its leaders how many resources they have, and trusts them to use good judgment, yearly planning can be accomplished in twelve hours per year (literally). And since the plan is updated monthly, there’s no opportunity for emergency re-planning, and it will always be in line with reality.

Less waste and improved quality – isn’t that what lean taught us?

When you want to recognize people for their wonderful work, dollar-for-dollar, the best value on the planet is pizza.

Research shows monetary rewards aren’t all that rewarding, and the thinking carries with pizza – you can buy bargain brand, wood-fired, free-range, vegan, or designer, the power of pizza is independent of pedigree. The power of pizza is about the forethought and intention to make the celebration happen. You must realize that people made the extra effort; you must decide you want to tell them you appreciate their work; you must figure out the leaders of the folks that did the work so you can let them know their people did a great job and that you’re buying them pizza; you must schedule the venue (the venue doesn’t actually matter); send out the invitation; order the pizza; and host the celebration.   With pizza, you spend your time on behalf of their behavior, and that’s special.

Here are the rules of pizza:

Rule 1 – Buy 50% more pizza than is reasonable.  They didn’t skimp on their effort, so don’t skimp on the pizza.  When you buy extra pizza, you tell people they matter; you tell them they’re worth it; you tell them that no one will go hungry on your watch.  One good outcome – they take the extra pizza back to the office, their coworkers smell it, and ask where they got it.  Now, they get to tell the story of how, out of the blue, they were invited to a pizza party to recognize their excellent performance.  But the best possible outcome is the extra pizza is taken home and given to the kids. The kids get pizza, and the proud parent gets to tell the story of their special lunch.  Leftover pizza has real power.

Rule 2 – Buy a small salad.  For those that want to celebrate yet watch their waste line, salad says you thought of them.  But don’t buy a big salad because even the most vigilant salad-eaters celebrate with pizza. (See rule 1.)

Rule 3 – There is a natural hierarchy of drinks, and higher is better.  At the top are beer and wine (no need to explain); next is fully caffeinated, full calorie soda; next is diet soda; next is flavored seltzer (it’s the bubbles that matter).  If you’re considering anything less than seltzer, don’t.

Rule 4 – Keep the agenda simple.  Here’s a good template: 1. Thank you for your amazing work.  2. What kind of pizza do you want?

Rule 5 – Use pizza sparingly. It’s power is inversely proportional to frequency.

People don’t want compensation for their extra special work, they want recognition.  And pizza could be the purest form of recognition – simple, straightforward, and tangible.

In reality, pizza has nothing to do with pizza, and has everything to do with honest, heartfelt recognition of exceptional work.

Image credit – Jeff Kubina.

If you’re working in a company you like, and you want it to be around in the future, you want to know if it will grow.  If you’re looking to move to a new company, you want to know if it has legs – you want to know if it will grow. If you own stock, you want to know if the company will grow, and it’s the same if you want to buy stock.  And it’s certainly the case if you want to buy the whole company – if it can grow, it’s worth more.

To grow, a company has to differentiate itself from its competitors.  In the past, continuous improvement (CI) was a differentiator, but today CI is the minimum expectation, the cost of doing business.  The differentiator for growth is discontinuous improvement (DI).

With DI, there’s an unhealthy fascination with idea generation.  While idea generation is important, companies aren’t short on ideas, they’re short on execution.  But the one DI differentiator is the flavor of the ideas.  To do DI a company needs ideas that are radically different than the ones they’re selling now.  If the ideas are slightly twisted variants of today’s products and business models, that’s a sure sign continuous improvement has infiltrated and polluted the growth engine. The gears of the DI engine are gummed up and there’s no way the company can sustain growth.  For objective evidence the company has the chops to generate the right ideas, look for a process that forces their thinking from the familiar, something like Jeffrey Baumgartner’s Anticonventional Thinking (ACT).

For DI-driven growth, the ability to execute is most important.  With execution, the first differentiator is how the company investigates radically new ideas.  There are three differentiators – a focus on speed, a “market first” approach, and the use of minimum viable tests (MVTs).  With new ideas, it’s all about how fast you can learn, so speed should come through loud and clear.  Without a market, the best idea is worthless, so look for “market first” thinking.  Idea evaluation starts with a hypothesis that a specific market exists (the market is clearly defined in the hypothesis) which is evaluated with a minimum viable test (MVT) to prove or disprove the market’s existence.  MVTs should error on the side of speed – small, localized testing.  The more familiar minimum viable product (MVP) is often an important part of the market evaluation work.  It’s all about learning about the market as fast as possible.

Now, with a validated market, the differentiator is how fast company can rally around the radically new idea and start the technology and product work.  The companies that can’t execute slot the new project at the end of their queue and get to it when they get to it.  The ones that can execute stop an existing (lower value) project and start the new project yesterday.  This stop-to-start behavior is a huge differentiator.

The company’s that can’t execute take a ready-fire-aim approach – they just start.  The companies that differentiate themselves use systems thinking to identify gaps in resources and capabilities and close them. They do the tough work of prioritizing one project over another and fully staff the important ones at the expense of the lesser projects.  Rather than starting three projects and finishing none, the companies that know how to do DI start one, finish one, and repeat.  They know with DI, there’s no partial credit for a project that’s half done.

All companies have growth plans, and at the highest level they all hang together, but some growth plans are better than others.  To judge the goodness of the growth plan takes a deeper look, a look into the work itself.  And once you know about the work, the real differentiator is whether the company has the chops to execute it.

Image credit – John Leach.

It’s harder than ever to innovate, and getting harder.

The focus on growth can be empowering, but when coupled with signed-in-blood accountability, empowering turns to puckering.  It’s an unfair double-bind. Damned if you try something new and it doesn’t work, and damned if you stay the course and don’t hit the numbers.  The most popular approach seems to be to do more of what worked.  A good approach, but not as good as it’s made out to be.

Doing more of what worked is good, and it works.  But it can’t stand on its own.  With today’s unreasonable workloads, every resource is fully booked and before doing more of anything, you’ve got to do less of something else.  ‘More of what worked’ must walk hand-in-hand with ‘Stop what didn’t work.’  Without stopping, without freeing up resources, ‘more of what worked’ is insufficient and unsustainable.

But even the two together are insufficient, and there’s a much needed third leg to stabilize the stool – ‘starting new work.’  Resources freed by stopping are allocated to starting new work, and this work, also known as innovation, is the major source of growth.

‘More of what worked’ is all about productivity – doing more with the same resources; and so is ‘stopping what didn’t work’ – reclaiming and reallocating ineffective resources. Both are important, but more importantly – they’re not innovation.

As you’re well aware, the rules are changing faster than ever, and at some point what worked last year won’t work this year. The only way to stay ahead of a catastrophe is to make small bets in unproven areas.  If the bets are successful, they turn into profitable innovation and growth. But the real value is the resiliency that comes from the ritualistic testing/learning cycles.

Going all-in on what worked last year is one of the riskiest bets you can make.

Whether at work or home, there are highs and lows.   And you’re not getting special treatment, that’s how it is for everyone.  And it’s a powerful fundamental, so don’t try to control it, ride it.

When the sailing is smooth, at some point it won’t be – the winds change, that’s what they do.  And when you’re suddenly buffeted from a new direction, you take action. But what action? More sail or less? Port or starboard? Heave the anchor or abandon ship? It depends.

Your actions depend on your why.  Regardless of wind or tide, your why points where it points and guides your actions. Much like magnetic north doesn’t move if you spin your compass, your long term why knows where it points.  If the storm on the horizon is dead ahead, you go around it.  But it’s a balance – deviate to skirt the storm, but do it with your long term destination in mind.  If you know your long term why, the best course heading is clear.

Often you set sail without realizing you don’t have your why battened down and stowed. When you sail where you sailed last time, you know the landmarks and use them to navigate. You can unknowingly leave your why at the pier and still get to your destination. But when you’re blown out to sea and can no longer see the landmarks, your moral compass, your long term why, is the only way to tack and jibe toward your destination.

Before you set sail, it’s best to know why you’re in the boat.

What’s a new market worth without a new technology to capture it? The same as a new technology without a new market – not much. Technology and market are a matched set, but not like peanut butter and jelly, (With enough milk, a peanut butter sandwich isn’t bad.) rather, more like H₂ and O: whether it’s H₂ without O or O without H₂ – there’s no water. With technology and market, there’s no partial credit – there’s nothing without both.

You’d think with such a tight coupling, market and technology would be highly coordinated, but that’s not the case. There’s a deep organizational chasm between them. But worse, each has their own language, tools, and processes. Plain and simple, the two organizations don’t know how to talk to each other, and the result is the wrong technology for the right market (if you’re a marketer) or the right technology for the wrong market (if you’re a technologist.) Both ways, customers suffer and so do business results.

The biggest difference, however, is around customers. Where marketers pull, technologists push – can’t be more different than that. But neither is right, both are. There’s no sense arguing which is more important, which is right, or which worked better last time because you need both. No partial credit.

If you speak only French and have a meeting with someone who speaks only Portuguese, well, that’s like meeting between marketers and technologists. Both are busy as can be, and neither knows what the other is doing. There’s a huge need for translators – marketers that speak technologist and technologists that talk marketing. But how to develop them?

The first step is to develop a common understanding of why. Why do you want to develop the new market? Why hasn’t anyone been able to create the new market? Why can’t we develop a new technology to make it happen? It’s a good start when both sides have a common understanding of the whys.

To transcend the language barrier, don’t use words, use video. To help technologists understand unmet customer needs, show them a video of a real customer in action, a real customer with a real problem. No words, no sales pitch, just show the video. (Put your hand over your mouth if you have to.) Show them how the work is done, and straight away they’ll scurry to the lab and create the right new technologies to help you crack the new market. Technologists don’t believe marketers; technologists believe their own eyes, so let them.

To help marketers understand technology, don’t use words, use live demos. Technologists – set up a live demo to show what the technology can do. Put the marketer in front of the technology and let them drive, but you can’t tell them how to drive. You too must put your hand over your mouth. Let them understand it the way they want to understand it, the way a customer would understand it. They won’t use it the way you think they should, they’ll use it like a customer. Marketers don’t understand technology, they understand their own eyes, so let them.

And after the videos and the live demos, it’s time to agree on a customer surrogate. The customer surrogate usually takes the form of a fully defined test protocol and fully defined test results. And when done well, the surrogate generates test results that correlate with goodness needed to crack the new market. As the surrogate’s test results increase, so does goodness (as the customer defines it.) Instead of using words to agree on what the new technology must do, agreement is grounded in a well defined test protocol and a clear, repeatable set of test results. Everyone can use their eyes to watch the actual hardware being tested and see the actual test results. No words.

To close the loop and determine if everyone is on the same page, ask the marketers and technologist to co-create the marketing brochure for the new product. Since the brochure is written for the customer, it forces the team use plain language which can be understood by all. No marketing jargon or engineering speak – just plain language.

And now, with the marketing brochure written, it’s time to start creating the right new market and the right new technology.

Photo credit – TORLEY.

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.