Archive for the ‘Problems’ Category

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

See differently to solve differently.

There are many definitions for creativity and innovation, but none add meaningfully to how the work is done. Though it’s clear why the work is important – creativity and innovation underpin corporate prosperity and longevity – it’s especially helpful to know how to do it.

At the most basic level, creativity and innovation are about problem solving.  But it’s a special flavor of problem solving.  Creativity and innovation are about problems solving new problems in new ways.  The glamorous part is ‘solving in new ways’ and the important part is solving new problems.

With continuous improvement the same problems are solved over and over. Change this to eliminate waste, tweak that to reduce variation, adjust the same old thing to make it work a little better.  Sure, the problems change a bit, but they’re close cousins to the problems to the same old problems from last decade. With discontinuous improvement (which requires high levels of creativity and innovation) new problems are solved.  But how to tell if the problem is new?

Solving new problems starts with seeing problems differently.

Systems are large and complicated, and problems know how to hide in the nooks and crannies. In a Where’s Waldo way, the nugget of the problem buries itself in complication and misuses all the moving parts as distraction. Problems use complication as a cloaking mechanism so they are not seen as problems, but as symptoms.

Telescope to microscope. To see problems differently, zoom in.  Create a hand sketch of the problem at the microscopic level.  Start at the system level if you want, but zoom in until all you see is the problem.  Three rules: 1. Zoom in until there are only two elements on the page. 2. The two elements must touch. 3. The problem must reside between the two elements.

Noun-verb-noun. Think hammer hits nail and hammer hits thumb.  Hitting the nail is the reason people buy hammers and hitting the thumb is the problem.

A problem between two things. The hand sketch of the problem would show the face of the hammer head in contact with the surface of the thumb, and that’s all.  The problem is at the interface between the face of the hammer head and the surface of the thumb. It’s now clear where the problem must be solved. Not where the hand holds the shaft of the hammer, not at the claw, but where the face of the hammer smashes the thumb.

Before-during-after. The problem can be solved before the hammer smashes the thumb, while the hammer smashes the thumb, or after the thumb is smashed.  Which is the best way to solve it? It depends, that’s why it must be solved at the three times.

Advil and ice. Solving the problem after the fact is like repair or cleanup. The thumb has been smashed and repercussions are handled in the most expedient way.

Put something between. Solving the problem while it happens requires a blocking or protecting action. The hammer still hits the thumb, but the protective element takes the beating so the thumb doesn’t.

Hand in pocket. Solving the problem before it happens requires separation in time and space. Before the hammer can smash the thumb it is moved to a safe place – far away from where the hammer hits the nail.

Nail gun. If there’s no way for the thumb to get near the hammer mechanism, there is no problem.

Cordless drill. If there are no nails, there are no hammers and no problem.

Concrete walls. If there’s no need for wood, there’s no need for nails or a hammer. No hammer, no nails, no problem.

Discerning between symptoms and problems can help solve new problems. Seeing problems at the micro level can result in new solutions. Looking closely at problems to separate them time and space can help see problems differently.

Eliminating the tool responsible for the problem can get rid of the problem of a smashed thumb, but it creates another – how to provide the useful action of the driven nail.  But if you’ve been trying to protect thumbs for the last decade, you now have a chance to design a new way to fasten one piece of wood to another, create new walls that don’t use wood, or design structures that self-assemble.

Image credit – Rodger Evans

Innovation and the Mythical Idealized Future State

When it’s time to innovate, the first task is usually to define the Idealized Future State (IFS).  The IFS is a word picture that captures what it looks like when the innovation work has succeeded beyond our wildest dreams. The IFS, so it goes, is directional so we can march toward the right mountain and inspirational so we can sustain our pace over the roughest territory.

For the IFS to be directional, it must be aimed at something – a destination.  But there’s a problem. In a sea of uncertainty, where the work has never been done before and where there are no existing products, services or customers, there are an infinite number of IFRs/destinations to guide our innovation work.  Open question – When the territory is unknown, how do we choose the right IFS?

For the IFS to be inspirational, it must create yearning for something better (the destination). And for the yearning to be real, we must believe the destination is right for us. Open question – How can we yearn for an IFS when we really can’t know it’s the right destination?

Maps aren’t the territory, but they are a collection of all possible destinations within the design space of the map.  If you have the right map, it contains your destination. And for a long time now, the old paper maps have helped people find their destinations. But on their own maps don’t tell us the direction to drive.  If you have a map of the US and you want to drive to Kansas, in which direction do you drive? It depends. If in California, drive east; if in Mississippi, drive north; if in New Hampshire, drive west; and in Minnesota, drive south. If Kansas is your idealized future state, the map alone won’t get your there.  The direction you drive depends on your location.

GPS has been a nice addition to maps. Enter the destination on the map, ask the satellites to position us globally and it’s clear which way to drive. (I drive west to reach Kansas.) But the magic of GPS isn’t in the electronic map, GPS is magic because it solves the location problem.

Before defining the idealized future state, define your location. It grounds the innovation work in the reality of what is, and people can rally around what is. And before setting the innovation direction with the IFS, define the next problems to solve and walk in their direction.

Image credit – Adrian Brady

With innovation, it depends.

By definition, when the work is new there is uncertainty.  And uncertainty can be stressful. But, instead of getting yourself all bound up, accept it.  More than that, relish in it.  Wear it as a badge of honor.  Not everyone gets the chance to work on something new – only the best do.  And, because you’ve been asked to do work with a strong tenor of uncertainty, someone thinks you’re the best.

But uncertainty is an unknown quantity, and our systems have been designed to reject it, not swim in it.  When companies want to get serious they drive toward a culture of accountability and the new work gets the back seat.  Accountability is mis-mapped to predictability, successful results and on time delivery.  Accountability, as we’ve mapped it, is the mortal enemy of new work.  When you’re working on a project with a strong element of uncertainty, the only certainty is the task you have in front of you.  There’s no certainty on how the task will turn out, rather, there’s only the simple certainty of the task.

With work with low uncertainty there are three year plans, launch timelines and predictable sales figures. Task one is well-defined and there’s a linear flow of standard work right behind it – task two through twenty-two are dialed in. But when working with uncertainty, the task at hand is all there is.  You don’t know the next task.  When someone asks what’s next the only thing you can say is “it depends.”  And that’s difficult in a culture of traditional accountability.

An “it depends” Gannt chart is an oxymoron, but with uncertainty step two is defined by step one.  If A, then B.  But if the wheels fall off, I’m not sure what we’ll do next.  The only thing worse than an “it depends” Gantt chart is an “I’m not sure” Gannt chart.  But with uncertainty, you can be sure you won’t be sure.  With uncertainty, traditional project planning goes out the window, and “it depends” project planning is the only way.

With uncertainty, traditional project planning is replaced by a clear distillation of the problem that must be solved.  Instead of a set of well-defined tasks, ask for a block diagram that defines the problem that must be solved.  And when there’s clarity and agreement on the problem that must be solved, the supporting tasks can be well-defined.  Step one – make a prototype like this and test it like that. Step two – it depends on how step one turns out.  If it goes like this then we’ll do that.  If it does that, we’ll do the other.  And if it does neither, we’re not sure what we’ll do.  You don’t have to like it, but that’s the way it is.

With uncertainty, the project plan isn’t the most important thing.  What’s most important is relentless effort to define the system as it is.  Here’s what the system is doing, here’s how we’d like it to behave and, based on our mechanism-based theory, here’s the prototype we’re going to build and here’s how we’re going to test it.  What are we going to do next?  It depends.

What’s next? It depends. What resources do you need? It depends. When will you be done? It depends.

Innovation is, by definition, work that is new.  And, innovation, by definition, is uncertain.  And that’s why with innovation, it depends.  And that’s why innovation is difficult.

And that’s why you’ve got to choose wisely when you choose the people that do your innovation work.

Image credit – Sara Biljana Gaon (off)

Mike Shipulski Mike Shipulski
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