Posts Tagged ‘Engineering Mindset’

Additive Manufacturing’s Holy Grail

The holy grail of Additive Manufacturing (AM) is high volume manufacturing.  And the reason is profit. Here’s the governing equation:

(Price – Cost) x Volume = Profit

The idea is to sell products for more than the cost to make them and sell a lot of them.  It’s an intoxicatingly simple proposition. And as long as you look only at the volume – the number of products sold per year – life is good. Just sell more and profits increase.  But for a couple reasons, it’s not that simple. First, volume is a result. Customers buy products only when those products deliver goodness at a reasonable price.  And second, volume delivers profit only when the cost is less than the price.  And there’s the rub with AM.

Here’s a rule – as volume increases, the cost of AM is increasingly higher than traditional manufacturing. This is doubly bad news for AM. Not only is AM more expensive, its profit disadvantage is particularly troubling at high volumes. Here’s another rule – if you’re looking to AM to reduce the cost of a part, look elsewhere. AM is not a bottom-feeder technology.

If you want to create profits with AM, use it to increase price. Use it to develop products that do more and sell for more.  The magic of AM is that it can create novel shapes that cannot be made with traditional technologies. And these novel shapes can create products with increased function that demand a higher price. For example, AM can create parts with internal features like serpentine cooling channels with fine-scale turbulators to remove more heat and enable smaller products or products that weigh less.  Lighter automobiles get better fuel mileage and customers will pay more. And parts that reduce automobile weight are more valuable.  And real estate under the hood is at a premium, and a smaller part creates room for other parts (more function) or frees up design space for new styling, both of which demand a higher price.

Now, back to cost.  There’s one exception to cost rule.  AM can reduce total product cost if it is used to eliminate high cost parts or consolidate multiple parts into a single AM part.  This is difficult to do, but it can be done.  But it takes some non-trivial cost analysis to make the case.  And, because the technology is relatively new, there’s some aversion to adopting AM.  An AM conversion can require a lot of testing and a significant cost reduction to take the risk and make the change.

To win with AM, think more function AND consolidation.  More (or new) function to support a higher price (and increase volume) and reduced cost to increase profit per part. Don’t do one or the other. Do both. That’s what GE did with its AM fuel nozzle in their new aircraft engines. They combined 20 parts into a single unit which weighed 25 percent less than a traditional nozzle and was more than five times as durable. And it reduced fuel consumption (more function, higher price).

AM is well-established in prototyping and becoming more established in low-volume manufacturing.  The holy grail for AM – high volume manufacturing – will become a broad reality as engineers learn how to design products to take advantage of AM’s unique ability to make previously un-makeable shapes and learn to design for radical part consolidation.

More function AND radical part consolidation.  Do both.

Image credit – Les Haines

The Additive Manufacturing Maturity Model

Additive Manufacturing (AM) is technology/product space with ever-increasing performance and an ever-increasing collection of products. There are many different physical principles used to add material and there are a range of part sizes that can be made ranging from micrometers to tens of meters.  And there is an ever-increasing collection of materials that can be deposited from water soluble plastics to exotic metals to specialty ceramics.

But AM tools and technologies don’t deliver value on their own.  In order to deliver value, companies must deploy AM to solve problems and implement solutions.  But where to start? What to do next? And how do you know when you’ve arrived?

To help with your AM journey, below a maturity model for AM.  There are eight categories, each with descriptions of increasing levels of maturity.  To start, baseline your company in the eight categories and then, once positioned, look to the higher levels of maturity for suggestions on how to move forward.

For a more refined calibration, a formal on-site assessment is available as well as a facilitated process to create and deploy an AM build-out plan.  For information on on-site assessment and AM deployment, send me a note at mike@shipulski.com.

Execution

  1. Specify AM machine – There a many types of AM machines. Learn to choose the right machine.
  2. Justify AM machine – Define the problem to be solved and the benefit of solving it.
  3. Budget for AM machine – Find a budget and create a line item.
  4. Pay for machine –  Choose the supplier and payment method – buy it, rent to own, credit card.
  5. Install machine – Choose location, provide necessary inputs and connectivity
  6. Create shapes/add material – Choose the right CAD system for the job, make the parts.
  7. Create support/service systems – Administer the job queue, change the consumables, maintenance.
  8. Security – Create a system for CAD files and part files to move securely throughout the organization.
  9. Standardize – Once the first machines are installed, converge on a small set of standard machines.
  10. Teach/Train – Create training material for running AM machine and creating shapes.

 

Solution

  1. Copy/Replace – Download a shape from the web and make a copy or replace a broken part.
  2. Adapt/Improve – Add a new feature or function, change color, improve performance.
  3. Create/Learn – Create something new, show your team, show your customers.
  4. Sell Products/Services – Sell high volume AM-produced products for a profit. (Stretch goal.)

 

Volume

  1. Make one part – Make one part and be done with it.
  2. Make five parts – Make a small number of parts and learn support material is a challenge.
  3. Make fifty parts – Make more than a handful of parts. Filament runs out, machines clog and jam.
  4. Make parts with a complete manufacturing system – This topic deserves a post all its own.

 

Complexity

  1. Make a single piece – Make one part.
  2. Make a multi-part assembly – Make multiple parts and fasten them together.
  3. Make a building block assembly – Make blocks that join to form an assembly larger than the build area.
  4. Consolidate – Redesign an assembly to consolidate multiple parts into fewer.
  5. Simplify – Redesign the consolidated assembly to eliminate features and simplify it.

 

Material

  1. Plastic – Low temperature plastic, multicolor plastics, high performance plastics.
  2. Metal – Low melting temperature with low conductivity, higher melting temps, higher conductivity
  3. Ceramics – common materials with standard binders, crazy materials with crazy binders.
  4. Hybrid – multiple types of plastics in a single part, multiple metals in one part, custom metal alloy.
  5. Incompatible materials – Think oil and water.

 

Scale

  1. 50 mm – Not too large and not too small. Fits the build area of medium-sized machine.
  2. 500 mm – Larger than the build area of medium-sized machine.
  3. 5 m – Requires a large machine or joining multiple parts in a building block way.
  4. 0.5 mm – Tiny parts, tiny machines, superior motion control and material control.

 

Organizational Breadth

  1. Individuals – Early adopters operate in isolation.
  2. Teams – Teams of early adopters gang together and spread the word.
  3. Functions – Functional groups band together to advance their trade.
  4. Supply Chain – Suppliers and customers work together to solve joint problems.
  5. Business Units – Whole business units spread AM throughout the body of their work.
  6. Company – Whole company adopts AM and deploys it broadly.

 

Strategic Importance

  1. Novelty – Early adopters think it’s cool and learn what AM can do.
  2. Point Solution – AM solves an important problem.
  3. Speed – AM speeds up the work.
  4. Profitability – AM improves profitability.
  5. Initiative – AM becomes an initiative and benefits are broadly multiplied.
  6. Competitive Advantage – AM generates growth and delivers on Vital Business Objectives (VBOs).

Image credit – Cheryl

The Effective Expert

What if you’re asked to do something you know isn’t right? Not from an ethical perspective, but from a well-read, well-practiced, world-thought-leader perspective? What if you know it’s a waste of time? What if you know it sets a dangerous precedent for doing the wrong work for the right reason? What if the person asking is in a position of power? What if you know they think they’re asking for the right work?

Do you delay and make up false reasons for the lack of progress? Do you get angry because you expect people in power know what they’re doing? Does your anger cause you to double-down on delay?  Or does it cause you to take a step back and regroup? Or do you give them what they ask for, knowing it will make it clear they don’t know what they’re doing?

What if you asked them why they want what they want? What if when you really listened you heard their request for help? What if you recognized they weren’t comfortable confiding in you and that’s why they didn’t tell you they needed your help? What if you could see they did not know how to ask? What if you realized you could help? What if you realized you wanted to help?

What if you honored their request and took an approach that got the right work done? What if you used their words as the premise and used your knowledge and kindness to twist the work into what it should be? What if you realized they gave you a compliment when they asked you to do the work? Better still, what if you realized you were the only person who could help and you felt good about your realization?

As subject matter experts, it’s in our best interest to have an open mind and an open heart.  Sure, it’s important to hang onto our knowledge, but it’s also important to let go our strong desire to be right and do all we can to improve effectiveness.

If we are so confident in our knowledge, shouldn’t it be relatively easy to give others the benefit of the doubt and be respectful of the possibility there may be a deeper fundamental behind the request for the “wrong work”?

As subject matter experts, our toughest job is to realize we don’t always see the whole picture and things aren’t always as they seem. And to remain open, it’s helpful to remember we became experts by doing things wrong. And to prioritize effectiveness, until proven otherwise, it’s helpful to assume everyone has good intentions.

Image credit — Ingrid Taylar

Be done with the past.

graspThe past has past, never to come again.  But if you tell yourself old stories the past is still with you.  If you hold onto your past it colors what you see, shapes what you think and silently governs what you do.  Not skillful, not helpful.  Old stories are old because things have changed.  The old plays won’t work. The rules are different, the players are different, the situation is different.  And you are different, unless you hold onto the past.

As a tactic we hold onto the past because of aversion to what’s going on around us. Like an ostrich we bury our head in the sands of the past to protect ourselves from unpleasant weather buffeting us in the now.  But there’s no protection. Grasping tightly to the past does nothing more than stop us in our tracks.

If you grasp too tightly to tired technology it’s game over.  And it’s the same with your tired business model – grasp too tightly and get run through by an upstart.  But for someone who wants to make a meaningful difference, what are the two things that are sacred? The successful technology and successful business model.

It’s difficult for an organization to decide if the successful technology should be reused or replaced.  The easy decision is to reuse it.  New products come faster, fewer resources are needed because the hard engineering work has been done and the technical and execution risks are lower.  The difficult decision is to scrap the old and develop the new.  The smart decision is to do both.  Launch products with the old technology while working feverishly to obsolete it.  These days the half-life of technology is short.  It’s always the right time to develop new technology.

The business model is even more difficult to scrap. It cuts across every team and every function.  It’s how the company did its work.  It’s how the company made its name. It’s how the company made its money.  It’s how families paid their mortgages.  It’s grasping to the past success of the business model that makes it almost impossible to obsolete.

People grasp onto the past for protection and companies are nothing more than a loosely connected network of people systems.  And these people systems have a shared past and a good memory.  It’s no wonder why old technologies and business models stick around longer than they should.

To let go of the past people must see things as they are.  That’s a slow process that starts with a clear-eyed assessment today’s landscapes. Make maps of the worldwide competitive landscape, intellectual property, worldwide regulatory legislation, emergent technologies (search YouTube) and the sea of crazy business models enabled by the cloud.

The best time to start the landscape analyses was two years ago, but the next best time to start is right now.  Don’t wait.

Image credit – John Fife

Creating a brand that lasts.

chillinOne of the best ways to improve your brand is to improve your products.  The most common way is to provide more goodness for less cost – think miles per gallon.  Usually it’s a straightforward battle between market leaders, where one claims quantifiable benefit over the other – Ours gets 40 mpg and theirs doesn’t.   And the numbers are tied to fully defined test protocols and testing agencies to bolster credibility.  Here’s the data.  Buy ours

But there’s a more powerful way to improve your brand, and that’s to map your products to reliability.  It’s far a more difficult game than the quantified head-to-head comparison of fuel economy and it’s a longer play, but done right, it’s a lasting play that is difficult to beat.  Run the thought experiment:  think about the brands you associate with reliability.  The brands that come to mind are strong, lasting brands, brands with staying power, brands whose products you want to buy, brands you don’t want to compete against.  When you buy their products you know what you’re going to get.  Your friends tell you stories about their products.

There’s a complete a complete tool set to create products that map to reliability, and they work.  But to work them, the commercialization team has to have the right mindset.  The team must have the patience to formally define how all the systems work and how they interact. (Sounds easy, but it can be painfully time consuming and the level of detail is excruciatingly extreme.)  And they have to be willing to work through the discomfort or developing a common understanding how things actually work. (Sounds like this shouldn’t be an issue, but it is – at the start, everyone has a different idea on how the system works.)  But more importantly, they’ve got to get over the natural tendency to blame the customer for using the product incorrectly and learn to design for unintended use.

The team has got to embrace the idea that the product must be designed for use in unpredictable ways in uncontrolled conditions. Where most teams want to narrow the inputs, this team designs for a wider range of inputs.  Where it’s natural to tighten the inputs, this team designs the product to handle a broader set of inputs.  Instead of assuming everything will work as intended, the team must assume things won’t work as intended (if at all) and redesign the product so it’s insensitive to things not going as planned.  It’s strange, but the team has to design for hypothetical situations and potential problems.  And more strangely, it’s not enough to design for potential problems the team knows about, they’ve got to design for potential problems they don’t know about. (That’s not a typo.  The team must design for failure modes it doesn’t know about.)

How does a team design for failure modes it doesn’t know about? They build a computer-based behavioral model of the system, right down to the nuts, bolts and washers, and they create inputs that represent the environment around the system.  They define what each element does and how it connects to the others in the system, capturing the governing physics and propagation paths of connections. Then they purposefully break the functions using various classes of failure types, run the analysis and review the potential causes.  Or, in the reverse direction, the team perturbs the system’s elements with inputs and, as the inputs ripple through the design, they find previously unknown undesirable (harmful) functions.

Purposefully breaking the functions in known ways creates previously unknown potential failure causes.  The physics-based characterization and the interconnection (interaction) of the system elements generate unpredicted potential failure causes that can be eliminated through design.  In that way, the software model helps find potential failures the team did not know about.  And, purposefully changing inputs to the system, again through the physics and interconnection of the elements, generates previously unknown harmful functions that can be designed out of the product.

If you care about the long-term staying power of your brand, you may want to take a look at TechScan, the software tool that makes all this possible.

Image credit — Chris Ford.

Doing New Work

first rideIf you know what to do, do it.  But if you always know what to do, do something else.  There’s no excitement in turning the crank every-day-all-day, and there’s no personal growth.  You may be getting glowing reviews now, but when your process is documented and becomes standard work, you’ll become one of the trivial many that follow your perfected recipe, and your brain will turn soggy.

If you want to do the same things more productively, do continuous improvement.  Look at the work and design out the waste.  I suggest you look for the waiting and eliminate it.  (One hint – look for people or parts queueing up and right in front of the pile you’ll find the waste maker.)  But if you always eliminate waste, do something else.  Break from the minimization mindset and create something new.  Maximize something. Blow up the best practice or have the courage to obsolete your best work.  In a sea of continuous improvement, be the lighthouse of doing new.

When you do something for the first time, you don’t know how to do it. It’s scary, but that’s just the feeling you want.  The cold feeling in your chest is a leading indicator of personal growth.  (If you don’t have a sinking feeling in your gut, see paragraph 1.) But organizations don’t make it easy to do something for the first time.  The best approach is to start small.  Try small experiments that don’t require approval from a budget standpoint and are safe to fail.  Run the experiments under the radar and learn in private.  Grow your confidence in yourself and your thinking.  After you have some success, show your results to people you trust.  Their input will help you grow.  And you’ll need every bit of that personal growth because to staff and run a project to bring your new concept to life you’ll need resources.  And for that you’ll need to dance with the most dangerous enemy of doing new things – the deadly ROI calculation.

The R is for return.  To calculate the return for the new concept you need to know: how many you’ll sell, how much you’ll sell them for, how much it will cost, and how well it will work.  All this must be known BEFORE resources can be allocated. But that’s not possible because the new thing has never been done before.  Even before talking about investment (I), the ROI calculation makes a train wreck of new ideas.  To calculate investment, you’ve got to know how many person-hours will be needed, the cost of the materials to make the prototypes and the lab resources needed for testing.  But that’s impossible to know because the work has never been done before.  The ROI is a meaningless calculation for new ideas and its misapplication has spelled death for more good ideas than anything else known to man.

Use the best practice and standardize the work. There’s immense pressure to repeat what was done last time because our companies prefer incremental growth that’s predictable over unreasonable growth that’s less certain.  And add to that the personal risk and emotional discomfort of doing new things and it’s a wonder how we do anything new at all.

But magically, new things do bubble up from the bottom. People do find the courage to try things that obsolete the business model and deliver new lines of customer goodness.  And some even manage survive the run through the ROI gauntlet.  With odds stacked against them, your best people push through their fears cut through the culture of predictability.

Imagine what they will do when you demand they do new work, give them the tools, time and training to do it, and strike the ROI calculation from our vocabulary.

Image credit – Tony Sergo

Step-Wise Learning

staircaseAt every meeting you have a chance to move things forward or hold them back.  When a new idea is first introduced it’s bare-naked.  In its prenatal state, it’s wobbly and can’t stand on its own and is vulnerable to attack. But since it’s not yet developed, it’s impressionable and willing to evolve into what it could be.  With the right help it can go either way – die a swift death or sprout into something magical.

Early in gestation, the most worthy ideas don’t look that way.  They’re ugly, ill-formed, angry or threatening.  Or, they’re playful, silly or absurd.  Depending on your outlook, they can be a member of either camp. And as your outlook changes, they can jump from one camp to the other.  Or, they can sit with one leg in each.  But none of that is about the idea, it’s all about you.  The idea isn’t a thing in itself, it’s a reflection of you. The idea is nothing until you attach your feelings to it.  Whether it lives or dies depends on you.

Are you looking for reasons to say yes or reasons to say no?

On the surface, everyone in the organization looks like they’re fully booked with more smart goals than they can digest and have more deliverables than they swallow, but that’s not the case.  Though it looks like there’s no room for new ideas, there’s plenty of capacity to chew on new ideas if the team decides they want to.  Every team can spare and hour or two a week for the right ideas.  The only real question is do they want to?

If someone shows interest and initiative, it’s important to support their idea.  The smallest acceptable investment is a follow-on question that positively reinforces the behavior.  “That’s interesting, tell me more.” sends the right message.  Next, “How do you think we should test the idea?” makes it clear you are willing to take the next step.  If they can’t think of a way to test it, help them come up with a small, resource-lite experiment.  And if they respond with a five year plan and multi-million dollar investment, suggest a small experiment to demonstrate worthiness of the idea.  Sometimes it’s a thought experiment, sometimes it’s a discussion with a customer and sometimes it’s a prototype, but it’s always small.  Regardless of the idea, there’s always room for a small experiment.

Like a staircase, a series of small experiments build on each other to create big learning.  Each step is manageable – each investment is tolerable and each misstep is survivable – and with each experiment the learning objective is the same: Is the new idea worthy of taking the next step?  It’s a step-wise set of decisions to allocate resources on the right work to increase learning.  And after starting in the basement, with step-by-step experimentation and flight-by-flight investment, you find yourself on the fifth floor.

This is about changing behavior and learning.  Behavior doesn’t change overnight, it changes day-by-day, step-by-step.  And it’s the same for learning – it builds on what was learned yesterday.  And as long at the experiment is small, there can be no missteps.  And it doesn’t matter what the first experiment is all about, as long as you take the first step.

Your team will recognize your new behavior because it respectful of their ideas.  And when you respect their ideas, you respect them.  Soon enough you will have a team that stands taller and runs small experiments on their own.  Their experiments will grow bolder and their learning will curve will steepen.  Then, you’ll struggle to keep up with them, and you’ll have them right where you want them.

image credit — Rob Warde

To make a difference, add energy.

Static ChargeIf you want to make a difference, you’ve got to add energy.  And the more you can add the bigger difference you can make.

Doing new is difficult and demands (and deserves) all the energy you can muster.  Often it feels you’re the only one pushing in the right direction while everyone else is vehemently pushing the other way.  But stay true and stand tall.  This is not an indication things are going badly, this is a sign you’re doing meaningful work.  It’s supposed to feel that way.  If you’re exhausted, frustrated and sometimes a bit angry, you’re doing it right.  If you have a healthy disrespect for the status quo, it’s supposed to feel that way.

Meaningful work has a long time constant and you’ve got to run these meaningful projects like marathons, uphill marathons.  Every day you put in your 26 miles at a sustainable pace  – no slower, but no faster.  This is long, difficult work that doesn’t run by itself, you’ve got to push it like a sled.  Every day you’ve got to push.  To push every day like this takes a lot of physical strength, but it takes even more mental strength.  You’ve got to stay focused on the critical path and push that sled every day.  And you need to preserve enough mental energy to effectively ignore the non-critical path sleds.  You’ve got to be able to decide which tasks you must get your whole body behind and which tasks you must discount.  And you’ve got to preserve enough energy to believe in yourself.

Meaningful work cannot be accomplished by sprinting full speed five days a week.  It’s a marathon, and you’ve got to work that way and train that way.  Get your rest, get your exercise, eat right, spend time with friends and family, and put your soul into your work.

Choose work that is meaningful and add energy.  Add it every day.  Add it openly.  Add it purposefully. Add it genuinely.   Add energy like you’re an aircraft carrier and others will get pulled along by your wake.  Add energy like you’re bulldozer and others will get out of your way.  Add energy like you’re contagious and others will be infected.

Image credit – anton borzov

Change your risk disposition.

royal army parachute dogInnovation creates things that are novel, useful and successful.  Something that’s novel is something that’s different, and something that’s different creates uncertainty.  And, as we know, uncertainty is the enemy of all things sacred.

Lean and Six Sigma have been so successful that the manufacturing analogy has created a generation that expects all things to be predictable, controllable and repeatable.  Above all else, this generation values certainty.  Make the numbers; reduce variability; reduce waste; do it on time  – all mantras of the manufacturing analogy, all advocates of predictability and all enemies of uncertainty.

With the manufacturing analogy, a culture of accountability is the natural end game (especially when it comes to outcomes), but what most don’t understand is a culture that values accountability of outcomes is a culture that cannot tolerate uncertainty.  And what fewer understand is a culture intolerant of uncertainty is a culture intolerant of innovation.

By definition, innovation and uncertainty are a matched pair – you can’t have one without the other.  You can have both or neither – that’s the rule.  And though we usually use the word “risk” rather than “uncertainty”, risk is a result of uncertainty and uncertainty is the fundamental.

When a product is launched and it’s poorly received, it’s likely due to an untested value proposition. And the reason the value proposition went untested is uncertainty, uncertainty around the negative consequences of challenging authority.  Someone on high decreed the value proposition was real and the organization, based on how leadership responded in the past, did not challenge the decree because the last person who challenged authority was fired, demoted or ostracized.

When the new product is 3% better than the last one, again, the enemy is uncertainty.  This time it’s either uncertainty around what the customer will value or uncertainty around the ability to execute on technology work.  The organization cannot tolerate the risk (uncertainty), so it does what it did last time.

When the new product has more new features and functions than it has a right to, intolerance to uncertainty is the root cause.  This time it’s uncertainty around the negative consequences of prioritizing one feature over another.  Said another way, it’s about uncertainty (and the resulting fear) around using judgement.

These three scenarios are reward looking, as the uncertainty has already negatively impacted the innovation work.  To mitigate the negative impacts on innovation, uncertainty must be part of the equation from the outset.

When it’s time for you to call for more innovation, it’s also the time to acknowledge you want more uncertainty.  And it’s not enough to say you’ll tolerate more uncertainty because that takes you off the hook and puts it all on the innovators.  You must tell the company you expect more uncertainty.  This is important because the innovators won’t limit their work by an unnaturally low uncertainty threshold, rather they’ll do the work demanded by the hyper-aggressive growth goals.

And when you ask for more uncertainty, it’s time to explicitly tell people you expect them to use their judgment more freely and more frequently.  With uncertainty there is no best practice, but there is best judgment.  And when your best people use their best judgement, uncertainty is navigated in the most effective way.

But, really, if you ask for more uncertainty you won’t get it. The level of uncertainty in the trenches is set by your risk disposition.  People in your company know, based on leadership’s actions – what’s rewarded and what’s punished – the company’s risk disposition and it governs their actions. If you take the pulse of your portfolio of technology projects you will see your risk disposition.  The thing to remember is your risk disposition is the boss and the level of innovation is subservient.

When the CEO demands you change the innovation work for the better, politely suggest a plan to change the company’s risk disposition.  And when the CEO asks how to do that, politely suggest a visit to Jim McCormick’s website.

Image credit – Suzanne Gerber

To make the right decision, use the right data.

wheels fall offWhen it’s time for a tough decision, it’s time to use data.  The idea is the data removes biases and opinions so the decision is grounded in the fundamentals.  But using the right data the right way takes a lot of disciple and care.

The most straightforward decision is a decision between two things – an either or – and here’s how it goes.

The first step is to agree on the test protocols and measure systems used to create the data.  To eliminate biases, this is done before any testing.  The test protocols are the actual procedural steps to run the tests and are revision controlled documents.  The measurement systems are also fully defined.  This includes the make and model of the machine/hardware, full definition of the fixtures and supporting equipment, and a measurement protocol (the steps to do the measurements).

The next step is to create the charts and graphs used to present the data. (Again, this is done before any testing.) The simplest and best is the bar chart – with one bar for A and one bar for B.  But for all formats, the axes are labeled (including units), the test protocol is referenced (with its document number and revision letter), and the title is created.  The title defines the type of test, important shared elements of the tested configurations and important input conditions.   The title helps make sure the tested configurations are the same in the ways they should be.  And to be doubly sure they’re the same, once the graph is populated with the actual test data, a small image of the tested configurations can be added next to each bar.

The configurations under test change over time, and it’s important to maintain linkage between the test data and the tested configuration.  This can be accomplished with descriptive titles and formal revision numbers of the test configurations.  When you choose design concept A over concept B but unknowingly use data from the wrong revisions it’s still a data-driven decision, it’s just wrong one.

But the most important problem to guard against is a mismatch between the tested configuration and the configuration used to create the cost estimate.  To increase profit, test results want to increase and costs wants to decrease, and this natural pressure can create divergence between the tested and costed configurations. Test results predict how the configuration under test will perform in the field.  The cost estimate predicts how much the costed configuration will cost.  Though there’s strong desire to have the performance of one configuration and the cost of another, things don’t work that way.  When you launch you’ll get the performance of AND cost of the configuration you launched.  You might as well choose the configuration to launch using performance data and cost as a matched pair.

All this detail may feel like overkill, but it’s not because the consequences of getting it wrong can decimate profitability. Here’s why:

Profit = (price – cost) x volume.

Test results predict goodness, and goodness defines what the customer will pay (price) and how many they’ll buy (volume).  And cost is cost.  And when it comes to profit, if you make the right decision with the wrong data, the wheels fall off.

Image credit – alabaster crow photographic

Innovation Through Preparation

Pack what you needInnovation is about new; innovation is about different; innovation is about “never been done before”; and innovation is about preparation.

Though preparation seems to contradict the free-thinking nature of innovation, it doesn’t.  In fact, where brainstorming diverts attention, the right innovation preparation focuses it; where brainstorming seeks more ideas, preparation seeks fewer and more creative ones; where brainstorming does not constrain, effective innovation preparation does exactly that.

Ideas are the sexy part of innovation; commercialization is the profitable part; and preparation is the most important part.  Before developing creative, novel ideas, there must be a customer of those ideas, someone that, once created, will run with them.  The tell-tale sign of the true customer is they have a problem if the innovation (commercialization) doesn’t happen. Usually, their problem is they won’t make their growth goals or won’t get their bonus without the innovation work.  From a preparation standpoint, the first step is to define the customer of the yet-to-be created disruptive concepts.

The most effective way I know to create novel concepts is the IBE (Innovation Burst Event), where a small team gets together for a day to solve some focused design challenges and create novel design concepts.  But before that can happen, the innovation preparation work must happen.  This work is done in the Focus phase. The questions and discussion below defines the preparation work for a successful IBE.

1. Why is it so important to do this innovation work?

What defines the need for the innovation work?  The answer tells the IBE team why they’re in the room and why their work is important. Usually, the “why” is a growth goal at the business unit level or projects in the strategic plan that are missing the necessary sizzle. If you can’t come up with a slide or two with growth goals or new projects, the need for innovation is only emotional.  If you have the slides, these will be used to kick off the IBE.

 

2. Who is the customer of the novel concepts?

Who will choose which concepts will be converted into working prototypes? Who will convert the prototypes into new products? Who will launch the new products? Who has the authority to allocate the necessary resources? These questions define the customers of the new concepts.  Once defined, the customers become part of the IBE team.  The customers kick off the IBE and explain why the innovation work is important and what they’ll do with the concepts once created.  The customers must attend the IBE report-out and decide which concepts they’ll convert to working prototypes and patents.

Now, so the IBE will generate the right concepts, the more detailed preparation work can begin.  This work is led by marketing.  Here are the questions to scope and guide the IBE.

 

3. How will the innovative new product be used?

How will the innovative product be used in new way? This question is best answered with a hand sketch of the customer using the new product in a new way, but a short written description (30 words, or so) will do in a pinch. The answer gives the IBE team a good understanding, from a customer perspective, what new things the product must do.

What are the new elements of the design that enable the new functionality or performance? The answer focuses the IBE on the new design elements needed to make real the new product function in the new way.

What are the valuable customer outcomes (VCOs) enabled by the innovative new product? The answer grounds the IBE team in the fundamental reason why the customer will buy the new product.  Again, this is answered from the customer perspective.

 

4. How will the new innovative new product be marketed and sold?

What is the tag line for the new product? The answer defines, at the highest level, what the new product is all about. This shapes the mindset of the IBE team and points them in the right direction.

What is the major benefit of the new product? The answer to this question defines what your marketing says in their marketing/sales literature.  When the IBE team knows this, you can be sure the new concepts support the marketing language.

 

5. By whom will the innovative new product be used?

In which geography does the end user live? There’s a big difference between developed markets and developing markets.  The answer to the question sets the context for the new concepts, specifically around infrastructure constraints.

What is their ability to pay? Pocketbooks are different across the globe, and the customer’s ability to pay guides the IBE team toward concepts that fit the right pocket book.

What is the literacy level of the end customer?  If the customer can read, the IBE team creates concepts that take advantage of that ability.  If the customer cannot read, the IBE team creates concepts that are far different.

 

6. How will the innovative new product change the competitive landscape?

Who will be angry when the new product hits the market? The answer defines the competition.  It gives broad context for the IBE team and builds emotional energy around displacing adversaries.

Why will they be angry? With the answer to this one, the IBE team has good perspective on the flavor of pain and displeasure created by the concepts.  Again, it shapes the perspective of the IBE team.  And, it educates the marketing/sales work needed to address competitors’ countermeasures.

Who will benefit when the new product hits the market? This defines new partners and supporters that can be part of the new solutions or participants in a new business model or sales process.

What will customer throw away, reuse, or recycle? This question defines the level of disruption.  If the new products cause your existing customers to throw away the products of your existing customers, it’s a pure market share play.  The level of disruption is low and the level of disruption of the concepts should also be low.  On the other end of the spectrum, if the new products are  sold to new customers who won’t throw anything away, you creating a whole new market, which is the ultimate disruption, and the concepts must be highly disruptive.  Either way, the IBE team’s perspective is aligned with the level appropriate level of disruption, and so are the new concepts.

 

Answering all these questions before the creative works seems like a lot of front-loaded preparation work, and it is. But, it’s also the most important thing you can do to make sure the concept work, technology work, patent work, and commercialization work gives your customers what they need and delivers on your company’s growth objectives.

Image credit — ccdoh1.

Mike Shipulski Mike Shipulski
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