Shipulski On Design

Posts Tagged ‘Engineering Mindset’

When new ideas come from the outside, they are dismissed out of hand.  The technical term for this behavior is Not Invented Here (NIH).  Because it was not invented by the party with official responsibility, that party stomps it into dust.  But NIH doesn’t stomp in public; it stomps in mysterious ways.

Wow!  That’s a great idea!  Then, mysteriously, no progress is made and it dies a slow death.

That’s cool! Then there’s a really good reason why it can’t be worked.

That’s interesting!  Then that morphs into the kiss of death.

We never thought of that.  But it won’t scale.

That’s novel!  But no one is asking for it.

That’s terribly exciting! We’ll study it into submission.

That’s incredibly different!  And likely too different.

When the company’s novel ideas die on the vine, they likely die at the hands of NIH. If you can’t understand why a novel idea never made it out of the lab, investigate the crime scene and you may find NIH’s fingerprints.  If customers liked the new idea yet it went nowhere, it could be NIH was behind the crime. If it makes sense, but it doesn’t make progress, NIH is the prime suspect.

If a team is not receptive to novel ideas from the outside, it’s because they consider their own ideas sufficiently good to meet their goals.  Things are going well and there’s no reason to adopt new ideas from the outside.  And buried in this description are the two ways to overcome NIH.

The fastest way to overcome NIH is to help a new idea transition from an idea conceived by someone outside the team to an idea created by someone inside the team.  Here’s how that goes.  The idea is first demonstrated by the external team in the form of a functional prototype.  This first step aims to help the internal team understand the new idea.  Then, the first waiting period is endured where nothing happens.  After the waiting period, a somewhat different functional prototype is created by the external team and shown to the internal team.  The objective is to help the internal team understand the new idea a little better.  Then, the second waiting period is endured where nothing happens.  Then, a third functional prototype is created and shown to the internal team.  This time, shortcomings are called out by the external team that can only be addressed by the internal team.  Then, the last waiting period is endured.  Then, after the third waiting period, the internal team addresses the shortcomings and makes the idea their own.  NIH is dead, and it’s off to the races.

The second fastest way to overcome NIH is to wait for the internal team to transition to a team that is receptive to new ideas initiated outside the team.  The only way for a team to make the transition is for them to realize that their internal ideas are insufficient to meet their objectives.  This can only come after their internal ideas are shown to be inadequate multiple times.  Only after exhausting all other possibilities, will a team consider ideas generated from outside the team.

When the external team recognizes the internal team is out of ideas, they demonstrate a functional prototype to the internal team.  And they do it in an “informational” way, meaning the prototype is investigatory in nature and not intended to become the seed of the internal team’s next generation platform.  And as it turns out, it’s only a strange coincidence that the functional prototype is precisely what the internal team needs to fuel the next-generation platform.  And the prototype is not fully wrung out.  And as it turns out, the parts that need to be wrung out are exactly what the external team knows how to do.  And when the internal team needs expertise from the external team to address the novel elements, as it turns out the external team conveniently has the time to help out.

Not Invented Here (NIH) is real.  And it’s a powerful force. And it can be overcome.  And when it is overcome, the results are spectacular.

Image credit — Becky Mastubara

Since resources are expensive, it can be helpful to see the environment around your product as a source of inexpensive resources that can be modified to perform useful functions.  Here are some examples.

Gravity is a force you can use to do your bidding. Since gravity is always oriented toward the center of the earth, if you change the orientation of an object, you change the direction gravity exerts itself relative to the object. If you flip the object upside down, gravity will push instead of pull.

And it’s the same for buoyancy but in reverse.  If you submerge an object of interest in water and add air (bubbles) from below, the bubbles will rise and push in areas where the bubbles collect.  If you flip over the object, the bubbles will collect in different areas and push in the opposite direction relative to the object.

And if you have water and bubbles, you have a delivery system.  Add a special substance to the air which will collect at the interface between the water and air and the bubbles will deliver it northward.

If you have motion, you also have wind resistance or drag force (but not in deep space).  To create more force, increase speed or increase the area that interacts with the moving air. To change the direction of the force relative to the object, change the orientation of the object relative to the direction of motion.

If you have water, you can also have ice.  If you need a solid substance look to the water.  Flow water over the surface of interest and pull out heat (cool) where you want the ice to form. With this method, you can create a protective coating that can regrow as it gets worn off.

If you have water, you can make ice to create force.  Drill a blind hole in a piece of a brittle material (granite), fill the hole with water, and freeze the water by cooling the granite (or leave it outside in the winter).  When the water freezes it will expand, push on the granite and break it.

These are some contrived examples, but I hope they help you see a whole new set of free resources you can use to make your magic.

Thank you, VF.

Image credit – audi_insperation

Everything has a half-life, but we don’t behave that way.  Especially when it comes to success.  The thinking goes – if it was successful last time, it will be successful next time.  So, do it again. And again.  It’s an efficient strategy – the heavy resources to bring it to life have already been spent. And it’s predictable – the same customers, the same value proposition, the same supply base, the same distribution channel, and the same technology. And it’s dangerous.

Success is successful right up until it isn’t. It will go away. But it will take time.  A successful product line won’t fall off the face of the earth overnight. It will deliver profits year-over-year and your company will come to expect them.  And your company will get hooked on the lifestyle enabled by those profits. And because of the addiction, when they start to drop off the company will do whatever it takes to convince itself all is well.  No need to change.  If anything, it’s time to double-down on the successful formula.

Here’s a rule: When your successful recipe no longer brings success, it’s not time to double-down.

Success’s decline will be slow, so you have time.  But creating a new recipe takes a long time, so it’s time to declare that the decline has already started. And it’s time to learn how to start work on the new recipe.

Hardship 1 – Allocate resources differently. The whole company wants to spend resources on the same old recipes, even when told not to.  It’s time to create a funding stream that’s independent of the normal yearly planning cycle.  Simply put, the people at the top have to reallocate a part of the operating budget to projects that will create the next successful platform.

Hardship 2 – Work differently. The company is used to polishing the old products and they don’t know how to create new ones. You need to hire someone who can partner with outside companies (likely startups), build internal teams with a healthy disrespect for previous success, create mechanisms to support those teams and teach them how to work in domains of high uncertainty.

Hardship 3 – See value differently. How do you provide value today? How will you provide value when you can’t do it that way? What is your business model? Are you sure that’s your business model? Which elements of your business model are immature? Are you sure? What is the next logical evolution of how you go about your business? Hire someone to help you answer those questions and create projects to bring the solutions to life.

Hardship 4 – Measure differently. When there’s no customer, no technology and no product, there’s no revenue.  You’ve got to learn how to measure the value of the work (and the progress) with something other than revenue.  Good luck with that.

Hardship 5 – Compensate differently. People that create something from nothing want different compensation than people that do continuous improvement. And you want to move quickly, violate the status quo, push through constraints and create whole new markets. Figure out the compensation schemes that give them what they want and helps them deliver what you want.

This work is hard, but it’s not impossible. But your company doesn’t have all the pieces to make it happen.  Don’t be afraid to look outside your company for help and partnership.

Image credit — Insider Monkey

If your solution isn’t sold to a customer, you didn’t do your job. Find a friend in Marketing.

If your solution can’t be made by Manufacturing, you didn’t do your job.  Find a friend in Manufacturing.

Reuse all you can, then be bold about trying one or two new things.

Broaden your horizons.

Before solving a problem, make sure you’re solving the right one.

Don’t add complexity. Instead, make it easy for your customers.

Learn the difference between renewable and non-renewable resources and learn how to design with the renewable ones.

Learn how to do a Life Cycle Assessment.

Learn to see functional coupling and design it out.

Be afraid but embrace uncertainty.

Learn how to communicate your ideas in simple ways. Jargon is a sign of weakness.

Before you can make sure you’re solving the right problem, you’ve got to know what problem you’re trying to solve.

Learn quickly by defining the tightest learning objective.

Don’t seek credit, seek solutions. Thrive, don’t strive.

Be afraid, and run toward the toughest problems.

Help people.  That’s your job.

Image credit – Marco Verch

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

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

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

The 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

One 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.

If 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

At 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