Archive for the ‘Problems’ Category

Before solving, learn more about the problem.

Ideas are cheap, but converting them into a saleable product and building the engine to make it all happen is expensive.  Before spending the big money, spend more time than you think reasonable to answer these three questions.

Is the problem big enough? There’s no sense spending the time and money to solve a problem unless you have a good idea the payback is worth the cost. Before spending the money to create the solution, spend the time to assess the benefits that will come from solving the problem.

Before you can decide if the problem is big enough, you have to define the problem and know who has it.  One of the best ways to do this is to define how things are done today.  Draw a block diagram that defines the steps potential customers follow or draw a picture of how they do things today. Define the products/services they use today and ask them what it would mean if you solved their problem. What’s particularly difficult at this point is they may not know they have a problem.

But before moving on, formalize who has the problem.  Define the attributes of the potential customers and figure out how many have the same attributes and, possibly, the same problem. Define the segments narrowly to make sure each segment does, in fact, have the same problem.  There will be a tendency to paint with broad strokes to increase the addressable market, but stay narrow and maintain focus on a tight group of potential customers.

Estimate the value of the solution based on how it compares to the existing alternative.  And the only ones who can give you this information are the potential customers. And the only way they can give you the information is if you interview them and watch them work. And with this detailed knowledge, figure out the number of potential customers who have the problem.  Do all this BEFORE any solving.

Will they pay for it? The only way to know if potential customers will pay for your solution is to show them an offering – a description of your value proposition and how it differs from the existing alternatives, a demo (a mockup of a solution and not a functional prototype) and pricing.  (See LEANSTACK for more on an offering.)  There will be a tendency to wait until the solution is ready, but don’t wait. And there will be a reluctance attach a price to the solution, but that’s the only way you’ll know how much they value your solution. And there will be difficulty defining a tight value proposition because that requires you to narrowly define what the solution does for the potential customer.  And that’s scary because the value proposition will be clear and understandable and the potential customer will understand it well enough to decide they if they like it or not.

If you don’t assign a price and ask them to buy it, you’ll never know if they’ll buy it in real life.

Can you deliver it? List all the elements that must come together. Can you make it? Can you sell it? Can you ship it? Can you service it? Are your partners capable and committed? Do you have the money do put everything in place?

Like with a chain, it takes one bad link to make the whole thing fall apart. Figure out if any of your links are broken or missing. And don’t commit resources until they’re all in place and ready to go.

Image credit — Matthias Ripp

Advice To Young Design Engineers

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

Organizational Learning

The people within companies have development plans so they can learn new things and become more effective.  There are two types of development plans – one that builds on strengths and another that shore up shortcomings. And for both types, the most important step is to acknowledge it’s important to improve. Before a plan can be created to improve on a strength, there must be recognition that something good can come from the improvement. And before there can be a plan to improve on a shortcoming, there must be recognition that there’s something missing and it needs to be improved.

And thanks to Human Resources, the whole process is ritualized. The sequence is defined, the timing is defined and the tools are defined. Everyone knows when it will happen, how it will happen and, most importantly, that it will happen.  In that way, everyone knows it’s important to learn new skills for the betterment of all.

Organizational learning is altogether different and more difficult.  With personal learning, it’s clear who must do the learning (the person). But with organizational learning, it’s unclear who must learn because the organization, as a whole, must learn. But we can’t really see the need for organizational learning because we get trapped in trying to fix the symptoms. Team A has a problem, so let’s fix Team A. Or, Team B has a problem, so let’s fix Team B. But those are symptoms. Real organizational learning comes when we recognize problematic themes shared by all the teams. Real organization learning comes when we realize these problems don’t result from doing things wrong, rather, they are a natural byproduct of how the company goes about its work.

The difficulty with organizational learning is not fixing the thematic problems. The difficulty is recognizing the thematic problems. When all the processes are followed and all the best practices are used, yet the same problematic symptoms arise, the problem is inherent in the foundational processes and practices. Yet, these are the processes and practices responsible for past success. It’s difficult for company leaders recognize and declare that the things that made the company successful are now the things that are holding the company back. But that’s the organizational learning that must happen.

What worked last time will work next time, as long as the competitive landscape remains constant. But when the landscape changes, what worked last time doesn’t work anymore. And this, I think, is how recipes responsible for past success can, over time, begin to show cracks and create these systematic problems that are so difficult to see.

The best way I know to recognize the need for organizational learning is to recognize changes in the competitive landscape. Once these changes are recognized, thought experiments can be run to evaluate potential impacts on how the company does business. Now that the landscape changed like this, it could stress our business model like that. Now that our competitors provide new services like this, it could create a gap in our capabilities like that.

Organizational learning occurs when the right leaders feel the problems. Fight the urge to fix the problems. Instead, create the causes and conditions for the right leaders to recognize they have a real problem on their hands.

Image credit – Jim Bauer

Make life easy for your customers.

Companies that have products want to improve them year-on-year.  This year’s must be better than last year’s.  For selfish reasons, we like to improve cost, speed and quality.  Cost reduction drops profit directly to the bottom line.  Increased speed reduces overhead (less labor per unit) and increases floor space productivity (more through the factory).  Improved quality reduces costs.  And for our customers, we like to improve their productivity by helping them do more value-added work with fewer resources.  More with less!   But there’s a problem – every year it gets more difficult to improve on last year, especially with our narrowly-defined view of what customers value.

And some companies talk about creating the next generation business model, though no one’s quite sure of what the business model actually is and what makes for a better one.

To break out of our narrow view of “better” and to avoid endless arguments over business models, I suggest an approach based on a simple mantra – Make It Easy.

Make it easy for the customer to _____________.

And take a broad view of what customers actually do.  Here are some ideas:

Make it easy to find you. If they can’t find you, they can’t buy from you.

Make it easy to understand what you do and why you do it. Give them a reason to buy.

Make it easy to choose the right solution.  No one likes buying the wrong thing.

Make it easy to pay. If they need a loan, why not find one for them?

Make it easy to receive. Think undamaged, recyclable packaging, easy to get off the truck.

Make it easy to install. Don’t think user manuals, think self-installation.

Make it easy to verify it’s ready to go. No screens, no menus. One green light.

Make it easy to deliver the value-added benefit.  We over-focus here and can benefit by thinking more broadly. Make it easy to set up, easy to verify the setup, easy to know how to use it, easy change over to the next job.

Make it easy to know the utilization. The product knows when it’s being used, why not give it the authority to automatically tell people how much free time it has?

Make it easy to maintain.  When the fastest machine in the world is down for the count, it becomes tied for the slowest machine in the world.  Make it easy to know what needs be replaced and when, make it easy to know how to replace it, make it easy to order the replacement parts, make it easy to verify the work was done correctly, make it easy to notify that the work was done correctly, and make it easy to reset the timers.

Make it easy to troubleshoot. Even the best maintenance programs don’t eliminate all the problems. Think auto-diagnosis. Then, like with maintenance, all the follow-on work should be easy.

Make it easy to improve. As the product is used, it learns.  It recognizes who is using it, remembers how they like it to behave, then assumes the desired persona.

Though this list is not exhaustive, it provides some food for thought.  Yes, most of the list is not traditionally considered value-added activities.  But, customers DO value improvements in these areas because these are the jobs they must do. If your competition is focused narrowly on productivity, why not differentiate by making it easy in a more broader sense? When you do, they’ll buy more.

And don’t argue about your business model.  Instead, choose important jobs to be done and make them easier for the customer.  In that way, how you prioritize your work defines your business model.  Think of the business model as a result.

And for a deeper dive on how to make it easy, here’s one of my favorite posts.  The takeaway – Don’t push people toward an objective. Instead, eliminate what’s in the way.

Image credit – Hernán Piñera

What’s your problem?

If you don’t have a problem, you’ve got a big problem.

It’s important to know where a problem happens, but also when it happens.

Solutions are 90% defining and the other half is solving.

To solve a problem, you’ve got to understand things as they are.

Before you start solving a new problem, solve the one you have now.

It’s good to solve your problems, but it’s better to solve you customers’ problems.

Opportunities are problems in sheep’s clothing.

There’s nothing worse than solving the wrong problem – all the cost with none of the solution.

When you’re stumped by a problem, make it worse then do the opposite.

With problem definition, error on the side of clarity.

All problems are business problems, unless you care about society’s problems.

Odds are, your problem has been solved by someone else.  Your real problem is to find them.

Define your problem as narrowly as possible, but no narrower.

Problems are not a sign of weakness.

Before adding something to solve the problem, try removing something.

If your problem involves more than two things, you have more than one problem.

The problem you think you have is never the problem you actually have.

Problems can be solved before, during or after they happen and the solutions are different.

Start with the biggest problem, otherwise you’re only getting ready to solve the biggest problem.

If you can’t draw a closeup sketch of the problem, you don’t understand it well enough.

If you have an itchy backside and you scratch you head, you still have an itch. And it’s the same with problems.

If innovation is all about problem solving and problem solving is all about problem definition, well, there you have it.

Image credit – peasap

The Evolution of New Ideas

Before there is something new to see, there is just a good idea worthy of a prototype.  And before there can be good ideas there are a whole flock of bad ones. And until you have enough self confidence to have bad ideas, there is only the status quo. Creating something from nothing is difficult.

New things are new because they are different than the status quo. And if the status quo is one thing, it’s ruthless in desire to squelch the competition. In that way, new ideas will get trampled simply based on their newness. But also in that way, if your idea gets trampled it’s because the status quo noticed it and was threatened by it.  Don’t look at the trampling as a bad sign, look at it as a sign you are on the right track. With new ideas there’s no such thing as bad publicity.

The eureka moment is a lie. New ideas reveal themselves slowly, even to the person with the idea. They start as an old problem or, better yet, as a successful yet tired solution. The new idea takes its first form when frustration overcomes intellectual inertia a strange sketch emerges on the whiteboard. It’s not yet a good idea, rather it’s something that doesn’t make sense or doesn’t quite fit.

The idea can mull around as a precursor for quite a while. Sometimes the idea makes an evolutionary jump in a direction that’s not quite right only to slither back to it’s unfertilized state.  But as the environment changes around it, the idea jumps on the back of the new context with the hope of evolving itself into something intriguing.  Sometimes it jumps the divide and sometimes it slithers back to a lower energy state.  All this happens without conscious knowledge of the inventor.

It’s only after several mutations does the idea find enough strength to make its way into a prototype. And now as a prototype, repeats the whole process of seeking out evolutionary paths with the hope of evolving into a product or service that provides customer value. And again, it climbs and scratches up the evolutionary ladder to its most viable embodiment.

Creating something new from scratch is difficult. But, you are not alone. New ideas have a life force of their own and they want to come into being. Believe in yourself and believe in your ideas. Not every idea will be successful, but the only way to guarantee failure is to block yourself from nurturing ideas that threaten the status quo.

Image credit – lost places

Innovation in three words – Solve Different Problems

With innovation, novel solutions pay the bills – a new solution provides new value for the customer and the customer buys it from you.  The trick, however, is to come up with novel solutions.  To improve the rate and quality of novel solutions, there’s usually a focus on new tools, new problem-solving methods and training on both. The idea is get better at moving from problem to solution.  There’s certainly room for improvement in our problem-solving skills, but I think the pot of gold is hidden elsewhere.

Because novel solutions reside in uncharted design space, it follows that novel solutions will occur more frequently if the problem-solvers are pointed toward new design space.  And to make sure they don’t solve in the tired, old design space of success, constraints are used to wall it off.  Rule 1 – point the solvers toward new design space. Rule 2 – wall off the over-planted soil of success.

The best way to guide the problems solvers toward fertile design space is to create different problems for them to solve. And this guide-the-solvers thinking is a key to the success of the IBE (Innovation Burst Event), where Design Challenges are created in a way that forces the solvers from the familiar. And it’s these Design Challenges that ARE the new problems that bring the new solutions.  And to wall off old design space, the Design Challenges use creatively curated constraints to make it abundantly clear that old solutions won’t cut it.

Before improving the back-end problem solving process, why not change the front- end problem selecting process?

Chose to solve different problems, then learn to solve them differently.

Image credit – Rajarshi MITRA

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

To improve innovation, use fewer words.

Everyone knows innovation is difficult, but there’s no best way to make it easier. And everyone knows there’s plenty of opportunities to make innovation more effective, but, again, there’s no best way.  Clearly, there are ways to improve the process, and new tools can help, but the right process improvements depend on the existing process and the specific project.  And it’s the same for tools – the next tool depends on the existing toolbox and the new work required by the project.  With regard to tools and processes, the right next steps are not universal.

But with all companies’ innovation processes, there is a common factor – the innovation process is run by people. Regardless of process maturity or completeness, people run the process.  And this fundamental cuts across language, geography and company culture.  And it cuts across products, services, and business models.  Like it or not, innovation is done by people.

At the highest level, innovation converts ideas into something customers value and delivers the value to them for a profit. At the front end, innovation is about ideas, in the middle, it’s about problems and at the back end, it’s about execution. At the front, people have ideas, define them, evaluate them and decide which ones to advance. In the middle, people define the problems and solve them. And at the back end, people define changes to existing business process and run the processes in a new way.

Tools are a specialized infrastructure that helps people run lower-level processes within the innovation framework. At the front, people have ideas about new tools, or how to use them in a new way, define the ideas, evaluate them, and decide which tools to advance. In the middle, people define problems with the tools and solve them. And at the back end, they run the new tools in new ways.

With innovation processes and tools, people choose the best ideas, people solve problems and people implement solutions.

In order to choose the best ideas, people must communicate the ideas to the decision makers in a clear, rich, nuanced way. The better the idea is communicated, the better the decision. But it’s difficult to communicate an idea, even when the idea is not new. For example, try to describe your business model using just words. And it’s more difficult when the idea is new. Try to describe a new (untested) business model using just your words. For me, words are not a good way to communicate new ideas.

Improved communication improves innovation. To improve communication of ideas, use fewer words. Draw a picture, create a cartoon, make a storyboard, or make a video.  Let the decision maker ask questions of your visuals and respond with another cartoon, a modified storyboard or a new sketch.  Repeat the process until the decision maker stops asking questions.  Because communication is improved, the quality of the decision is improved.

Improved problem solving improves innovation. To improve problem-solving, improve problem definition (the understanding of problem definition.) Create a block diagram of the problem – with elements of the system represented by blocks and labeled with nouns, and with actions and information flow represented by arrows labeled with verbs. Or create a sketch of the customer caught in the act of experiencing the problem.  Define the problem in time (when it happens) so it can be solved before, during or after. And in all cases, limit yourself to one page. Continue to modify the visuals until there’s a common definition of the problem (the words stop.)  When the problem is defined and communicated in this way, the problem solves itself. Problem-solving is seven-eighths problem definition.

Improved execution improves innovation. To improve execution, improve clarity of the definition of success.  And again, minimize the words. Draw a picture that defines success using charts or graphs and data. Create the axes and label them (don’t forget the units of measure). Include data from the baseline product (or process) and define the minimum performance criterion in red.  And add the sample size (number of tests.) Use one page for each definition of success and sequence them in order of importance. Start with the work that has never been done before.  And to go deeper, define the test protocol used to create the data.

For a new business model, the one-page picture could be a process diagram with new blocks for new customers or partners or new arrows for new information flows. There could be time requirements (response time) or throughput requirements (units per month). Or it could be a series of sketches of new deliverables provided by the business model, each with clearly defined criteria to judge success. When communicated clearly to the teams, definitions of success are beacons of light that guide the boats as the tide pulls them through the project or when uncharted rocks suddenly appear to starboard.

Innovation demands communication and communication demands mechanisms. In the domain of uncertainty, words are not the best communicators.  Create visual communication mechanisms that distill and converge on a common understanding.

A picture isn’t worth a thousand words, it gets rid of a thousand.

Image credit – Michael Coghlan

Rule 1: Allocate resources for effectiveness.

We live in a resource constrained world where there’s always more work than time.  Resources are always tighter than tight and tough choices must be made. The first choice is to figure out what change you want to make in the world. How do you want put a dent in the universe? What injustice do you want to put to rest? Which paradigm do you want to turn on its head?

In business and in life, the question is the same – How do you want to spend your time?

Before you can move in the right direction, you need a direction. At this stage, the best way to allocate your resources is to define the system as it is. What’s going on right now? What are the fundamentals? What are the incentives? Who has power?  Who benefits when things move left and who loses when things go right?  What are the main elements of the system? How do they interact? What information passes between them? You know you’ve arrived when you have a functional model of the system with all the elements, all the interactions and all the information flows.

With an understanding of how things are, how do you want to spend your time? Do you want to validate your functional model? If yes, allocate your resources to test your model. Run small experiments to validate (or invalidate) your worldview.  If you have sufficient confidence in your model, allocate your resources to define how things could be.  How do you want the fundamentals to change? What are the new incentives? Who do you want to have the power? And what are the new system elements, their new interactions and new information flows?

When working in the domain of ‘what could be’ the only thing to worry about is what’s next. What’s after the next step?  Not sure. How many resources will be required to reach the finish line? Don’t know. What do we do after the next step? It depends on how it goes with this step. For those that are used to working within an efficiency framework this phase is a challenge, as there can be no grand plan, no way to predict when more resources will be needed and no way to guarantee resources will work efficiently. For the ‘what could be’ phase, it’s better to use a framework of effectiveness.

In a one-foot-in-front-of-the-other way, the only thing that matters in the ‘what could be’ domain is effectively achieving the next learning objective. It’s not important that the learning is done most efficiently, it matters that the learning is done well and done quickly.  Efficiently learning the wrong thing is not effective. Running experiments efficiently without learning what you need to is not effective. And learning slowly but efficiently is not effective.

Allocate resources to learn what needs to be learned. Allocate resources to learn effectively, not efficiently. Allocate your best people and give them the time they need.  And don’t expect an efficient path. There will be unplanned lefts and rights. There will be U-turns. There will times when there’s lots of thinking and little activity, but at this stage activity isn’t progress, thinking is. It may look like a drunkard’s walk, but that’s how it goes with this work.

When the objective of the work isn’t to solve the problem but to come up with the right question, allocate resources in a way that prioritizes effectiveness over efficiency. When working in the domain of ‘what could be’ allocate resources on the learning objective at hand. Don’t worry too much about the follow-on learning objectives because you may never earn the right to take them on.

In the domain of uncertainty, the best way to allocate the resources is to learn what you need to learn and then figure out what to learn next.

Image credit – John Flannery

How To Reduce Innovation Risk

The trouble with innovation is it’s risky.  Sure, the upside is nice (increased sales), but the downside (it doesn’t work) is distasteful. Everyone is looking for the magic pill to change the risk-reward ratio of innovation, but there is no pill.  Though there are some things you can do to tip the scale in your favor.

All problems are business problems.  Problem solving is the key to innovation, and all problems are business problems.  And as companies embrace the triple bottom line philosophy, where they strive to make progress in three areas – environmental, social and financial, there’s a clear framework to define business problems.

Start with a business objective.  It’s best to define a business problem in terms of a shortcoming in business results. And the holy grail of business objectives is the growth objective.  No one wants to be the obstacle, but, more importantly, everyone is happy to align their career with closing the gap in the growth objective.  In that way, if solving a problem is directly linked to achieving the growth objective, it will get solved.

Sell more.  The best way to achieve the growth objective is to sell more. Bottom line savings won’t get you there.  You need the sizzle of the top line. When solving a problem is linked to selling more, it will get solved.

Customers are the only people that buy things.  If you want to sell more, you’ve got to sell it to customers. And customers buy novel usefulness.  When solving a problem creates novel usefulness that customers like, the problem will get solved.  However, before trying to solve the problem, verify customers will buy what you’re selling.

No-To-Yes.  Small increases in efficiency and productivity don’t cause customers to radically change their buying habits.  For that your new product or service must do something new. In a No-To-Yes way, the old one couldn’t but the new one can. If solving the problem turns no to yes, it will get solved.

Would they buy it? Before solving, make sure customers will buy the useful novelty. (To know, clearly define the novelty in a hand sketch and ask them what they think.) If they say yes, see the next question.

Would it meet our growth objectives? Before solving, do the math. Does the solution result in incremental sales larger than the growth objective? If yes, see the next question.

Would we commercialize it? Before solving, map out the commercialization work. If there are no resources to commercialize, stop.  If the resources to commercialize would be freed up, solve it.

Defining is solving. Up until now, solving has been premature. And it’s still not time. Create a functional model of the existing product or service using blocks (nouns) and arrows (verbs). Then, to create the problem(s), add/modify/delete functions to enable the novel usefulness customers will buy.  There will be at least one problem – the system cannot perform the new function. Now it’s time to take a deep dive into the physics and bring the new function to life.  There will likely be other problems.  Existing functions may be blocked by the changes needed for the new function. Harmful actions may develop or some functions will be satisfied in an insufficient way.  The key is to understand the physics in the most complete way.  And solve one problem at a time.

Adaptation before creation. Most problems have been solved in another industry. Instead of reinventing the wheel, use TRIZ to find the solutions in other industries and adapt them to your product or service.  This is a powerful lever to reduce innovation risk.

There’s nothing worse than solving the wrong problem.  And you know it’s the wrong problem if the solution doesn’t: solve a business problem, achieve the growth objective, create more sales, provide No-To-Yes functionality customers will buy, and you won’t allocate the resources to commercialize.

And if the problem successfully runs the gauntlet and is worth solving, spend time to define it rigorously.  To understand the bedrock physics, create a functional of the system, add the new functionality and see what breaks.  Then use TRIZ to create a generic solution, search for the solution across other industries and adapt it.

The key to innovation is problem solving. But to reduce the risk, before solving, spend time and energy to make sure it’s the right problem to solve.

It’s far faster to solve the right problem slowly than to solve the wrong one quickly.

Image credit – Kate Ter Haar

Mike Shipulski Mike Shipulski
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