Shipulski On Design

Archive for the ‘Innovation’ Category

When you push, you make it easy for people resist. When you break trail, you make it easy for them to follow.

Efficiency is overrated, especially when it interferes with effectiveness.  Make it easy for effectiveness to carry the day.

You can push people off a cliff or build them a bridge to the other side. Hint – the bridge makes it easy.

Even new work is easy when people have their own reasons for doing it.

Making things easier is not easy.

Don’t tell people what to do.  Make it easy for them to use their good judgement.

Set the wrong causes and conditions and creativity screeches to a halt.  Set the right ones and it flows easily. Creativity is a result.

Don’t demand that people pull harder, make it easier for them to pull in the same direction.

Activity is easy to demonstrate and progress isn’t.  Figure out how to make progress easier to demonstrate.

The only way to make things easier is to try to make them easier.

Image credit – Richard Hurd

There’s disagreement on what is creative, innovative and disruptive. And there is no set of hard criteria to sort concepts into the three categories. Stepping back a bit, a lesser but still important sorting is an in-or-out categorization. Though not as good as discerning among the three, it is useful to decide if a new concept is in (one of the three) or out (not).

The closest thing to an acid test is assessment of the emotional response generated by a new concept. Here are some responses that I consider tell-tail signs of powerful ideas/concepts worthy of the descriptors creative, innovative, or disruptive.

When first shown, a prototype creates fear and defensiveness. The fear signals that the prototype threatens the status quo and defensiveness is objective evidence of the fear.

When first explained, a new concept creates anger and aggression. Because the concept doesn’t play by the rules, it disrespects everything holy, and the unfairness spawns indigence.

After some time, the dismissive comments about the new prototype fade and turn to discussions colored by deep sadness as the gravity of the situation hits home.

But the best leading indicator is surprise.  When a test result doesn’t match your expectations, it generates surprise. And since your expectations are built on your mental models, surprising concepts contradict your mental models. And since your mental models are formed by successful experiences, prototypes that create surprise violate previous success.

If you’re surprised by a new concept, it’s worth a deeper look. If you’re not surprised, move on.

If you’re not tolerant of surprise, you should be. And if you are tolerant of surprise, it’s time to become fervent.

Image credit – Raul Pop

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

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

Is it innovation or continuous improvement or is it innovation? Is it regular innovation or disruptive innovation? Is it new enough or too new? These questions are worse than meaningless as they suck emotional energy from the organization and divert emotional energy from the business objective.

With every initiative, there are risks, rewards, and resources. Risk generally tracks with newness, reward usually tracks with incremental customer goodness and resources are governed by the work.  Risk is about the probability of tackling the newness, reward is about the size of the prize and resources are about how the work is done. There is no best amount of risk as sometimes the right amount is none and other times it’s more than everyone prefers. And there’s no best amount of reward as it depends on the company’s goals. And there’s no right amount of resources because there’s no right scope.  For all three – risk, reward and resources – the right amount depends on the context.

For bottom line projects, it’s about maintaining product functionality while eliminating waste.  And while there’s no right amount of risk, reward and resources, three filters (people, process, tools) can help get everyone on the same page.

Here are the escalating categories for people – no new people, move people from group A to group B, hire more people like the ones we have, hire new people with skills we don’t have.  And for categories for process – no new processes, eliminate steps of existing processes, add steps to existing processes, create a process that’s new to the facility, create a process that’s new to the company, create process that’s new to the industry, create a process that’s new to the world.  And for tools – no new tools, modify existing tools, buy new tools, create new tools from scratch.

There are no right answers, but if you’ve got to hire people you’ve never hired, create processes that are new-to-world, and invent new tools, it’s clear to everyone the project is pushing the envelope. And if the reward is significant and resources are plentiful, it could be a good way to go.  And if there are no new hires, no new processes, and no new tools, don’t expect extravagant rewards. It’s not an exact science, but categorizing the newness in people, process, and tools and then comparing with the reward (payoff) makes clear any mismatches.  And when mismatches are clear they can be managed. Resources can be added, the scope can be reduced and reward can be revisited.

For top line projects, it’s about providing novel usefulness to customers at a reasonable cost.  And while risk, reward, and resources must be balanced, the filters are different.  For top line, the filters are breadth of applicability, competition, is/isn’t.

Here are the escalating categories for breadth of applicability – same customer in the same application, same customers in a new application, new customers in a new market, new customers in different industry, new customers in an industry created by the project. For competition – many competitors in the same industry, fewer competitors in the same industry, fewer competitors in a different industry, no competitors (compete with no one.) And for is/isn’t – improve what is, radically improve what is, create what isn’t.

Again, no right answers. But the plan is to sell to the same customers into markets with the same powerful competitors with only a slight improvement to the existing product, don’t expect radical rewards and don’t run a project that consumes significant resources. And, if the plan is to create a whole new industry where there are no competitors and it requires an entirely new service that doesn’t yet exist, the potential reward should be spectacular, expect to allocate a boatload of resources and prepare for the project to take longer than expected or to be cancelled before completion.

Balancing risk, reward and resources is not an exact science.  And the only way to get good at it is to calibrate new projects based on previous projects.  To start the calibration process, try the process on your most recent completed projects.  Categorize the projects with the relevant filters and define the resources consumed and the realized rewards.  And when planning the next project, categorize with the filters and define the resource plan and planned rewards and see how they compare with the completed projects.  And if there are mismatches, reconcile them with the realities of the previous projects.

Image credit – Ian Sane

Recreational athletes train because they enjoy the activity and they compete so they can tell themselves (and their friends) stories about the race. Their training routines are discretionary and their finish times are all about bragging rights. Professional athletes train because it’s their job. Their training is unpleasant, stressful and ritualistic. And it’s not optional. And their performance defines their livelihood. A slow finish time negatively impacts their career. With innovation, you have a choice – do you want to do it like a recreational athlete or like a professional? Do you want to do it like it’s discretionary or like your livelihood depends on it?

Like with the professional athlete, with innovation what worked last time is no longer good enough.  Innovation demands we perform outside our comfort zone.

Goals/Objectives are the key to performing out of our comfort zone. And to bust through intellectual inertia, one of the most common business objectives is a goal to grow revenue. “Grow the top line” is the motto of the professional innovator.

To deliver on performance goals, coaches give Strategic Guidance to the professional athlete, and it’s the same for company leaders – it’s their responsibility to guide the innovation approach. The innovation teams must know if their work should focus on a new business model, a new service or a new product. And to increase the bang for the buck, an Industry-First approach is recommended, where creation of new customer value is focused within a single industry. This narrows the scope and tightens up the work. The idea is to solve a problem for an industry and sell to the whole of it.  And to tighten things more, a Flagship Customer is defined with whom a direct partnership can be developed.  Two attributes of a Flagship Customer – big enough to create significant sales growth and powerful enough to pull the industry in its wake.

It’s the responsibility of the sales team to identify the Flagship Customer and broker the first meeting.  At the meeting, a Customer-Forward approach is proposed, where a diverse team visits the customer and dives into the details of their Goals/Objectives, their work and their problems. The objective is to discover new customer outcomes and create a plan to satisfy them.  The Discovery Burst Event (DBE) is the mechanism to do the work  It’s a week-long event where marketing, sales, engineering, manufacturing and technical services perform structured interviews to get to the root of the customer’s problems AND, in a Go-To-The-Work way, walk their processes and use their eyeballs to discover solutions to problems the customer didn’t know they had.  The DBE culminates with a report out to leaders of the Flagship Company where new customer outcome statements are defined along with a plan to assess the opportunities (impact/effort) and come back with proposals to satisfy the most important outcome statements.

After the DBE, the team returns home and evaluates and prioritizes the opportunities.  As soon as possible, the prioritization decisions are presented to the Flagship Customer along with project plans to create novel solutions.  In a tactical sense, there are new opportunities to sell existing products and services.  And in a strategic sense, there are opportunities to create new business models, new services and new products to reinvent the industry.

In the short term, sales of existing products increase radically.  And in the longer term, where new solutions must be created, the Innovation Burst Event (IBE) process is used to quickly create new concepts and review them with the customer in a timely way. And because the new concepts solve validated customer problems, by definition the new concepts will be valued by the customer. In a Customer-Forward way, the new concepts created by the IBE are driven by the customer’s business objectives and their problems.

This Full Circle approach to innovation pushes everyone out of their comfort zones to help them become professional innovators. Company leadership must stick out their necks and give strategic guidance, sales teams must move to a trusted advisor role, engineering and marketing teams must learn to listen to (and value) the customer’s perspective, and new ways of working – the Discovery Burst Event (DBE) and Innovation Burst Event (IBE) – must be embraced.  But that’s what it takes to become professional innovators.

Innovation isn’t a recreational sport, and it’s time to behave that way.

Image credit – Lwp Kommunikáció

When the work is new, it can’t be defined and managed like work that has been done before.

Sometimes there’s a tendency to spend months to define the market, the detailed specification and the project timeline and release the package as a tidal wave that floods the organization with new work.  Instead, start with a high-level description of the market, a rough specification and the major project milestones, all of which will morph, grow and inform each other as the team learns.  Instead of a big batch, think bite-sized installments that build on each other. Think straw-man that gets its flesh as the various organizations define their learning objectives and learn them.

Instead of target customer segments and idealized personas, define how the customers will interact with the new product or service. Use the storyboard format to capture sequence of events (what they do), the questions they ask themselves and how they know they’ve done it right. Make a storyboard for the top three to five most important activities the customers must do.  There’s good learning just trying to decide on the top three to five activities, never mind the deep learning that comes when you try to capture real activities of real customers. [Hint – the best people to capture real customer activities are real customers.]

Instead of a detailed list of inputs and outputs, fill in the details of the storyboards.  Create close-ups of the user interfaces and label the dials, buttons and screens.  When done well, the required inputs and outputs bubble to the surface.  And define the customer’s navigation path, as it defines the sequence of things and where the various inputs come to be and the various outputs need to be.  What’s nice is learning by iteration can be done quickly since its done in the domain of whiteboards and markers.

Instead of defining everything, just define what’s new and declare everything else is the same as last time.

The specification for the first prototypes is to bring the storyboards to life and to show the prototypes to real customers.  Refine and revise based on the learning, and rinse and repeat, as needed.

As the design migrates toward customer value and confidence builds, it’s then time to layer on the details and do a deep dive into the details – specs, test protocols, manufacturing, sales and distribution.

At early stages of innovation work, progress isn’t defined by activity, it’s defined by learning.  And it can look like nothing meaningful is happening as there is a lot of thinking and quiet time mixed in with infrequent bursts active activity.  But that’s what it takes to answer the big questions of the front end.

When in doubt, answer the big questions at the expense of the details.  And to stay on track, revisit and refine the learning objectives. And to improve confidence, show it to real customers.

And rinse and repeat, as needed.

Image credit – Jason Samfield

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

Try – when you’re not sure what to do.

Listen – when you want to learn.

Build – when you want to put flesh on the bones of your idea.

Think – when you want to make progress.

Show a customer – when you want to know what your idea is really worth.

Put it down – when you want your subconscious to solve a problem.

Define – when you want to solve.

Satisfy needs – when you want to sell products

Persevere – when the status quo kicks you in the shins.

Exercise – when you want set the conditions for great work.

Wait – when you want to run out of time and money.

Fear failure – when you want to block yourself from new work.

Fear success – when you want to stop innovation in its tracks.

Self-worth – when you want to overcome fear.

Sleep – when you want to be on your game.

Chance collision – when you want something interesting to work on.

Write – when you want to know what you really think.

Make a hand sketch – when you want to communicate your idea.

Ask for help – when you want to succeed.

Image credit – Daniel Dionne

Innovation is difficult because it demands new work. But, at a more basic level, it’s difficult because it requires an admission that the way you’ve done things is no longer viable. And, without public admission the old way won’t carry the day, innovation cannot move forward. After the admission there’s no innovation, but it’s one step closer.

After a public admission things must change, a cultural shift must happen for innovation to take hold. And for that, new governance processes are put in place, new processes are created to set new directions and new mechanisms are established to make sure the new work gets done.  Those high-level processes are good, but at a more basic level, the objectives of those process areto choose new projects, manage new projects and allocate resources differently. That’s all that’s needed to start innovation work.

But how to choose projects to move the company toward innovation? What are the decision criteria? What is the system to collect the data needed for the decisions? All these questions must be answered and the answers are unique to each company. But for every company, everything starts with a top line growth objective, which narrows to an approach based on an industry, geography or product line, which then further necks down to a new set of projects. Still no innovation, but there are new projects to work on.

The objective of the new projects is to deliver new usefulness to the customer, which requires new technologies, new products and, possibly, new business models. And with all this newness comes increased uncertainty, and that’s the rub. The new uncertainty requires a different approach to project management, where the main focus moves from execution of standard tasks to fast learning loops. Still no innovation, but there’s recognition the projects must be run differently.

Resources must be allocated to new projects. To free up resources for the innovation work, traditional projects must be stopped so their resources can flow to the innovation work. (Innovation work cannot wait to hire a new set of innovation resources.)  Stopping existing projects, especially pet projects, is a major organizational stumbling block, but can be overcome with a good process. And once resources are allocated to new projects, to make sure the resources remain allocated, a separate budget is created for the innovation work. (There’s no other way.) Still no innovation, but there are people to do the innovation work.

The only thing left to do is the hardest part – to start the innovation work itself. And to start, I recommend the IBE (Innovation Burst Event). The IBE starts with a customer need that is translated into a set of design challenges which are solved by a cross-functional team.  In a two-day IBE, several novel concepts are created, each with a one page plan that defines next steps.  At the report-out at the end of the second day, the leaders responsible for allocating the commercialization resources review the concepts and plans and decide on next steps. After the first IBE, innovation has started.

There’s a lot of work to help the organization understand why innovation must be done. And there’s a lot of work to get the organization ready to do innovation. Old habits must be changed and old recipes must be abandoned. And once the battle for hearts and minds is won, there’s an equal amount of work to teach the organization how to do the new innovation work.

It’s important for the organization to understand why innovation is needed, but no customer value is delivered and no increased sales are booked until the organization delivers a commercialized solution.

Some companies start innovation work without doing the work to help the organization understand why innovation work is needed. And some companies do a great job of communicating the need for innovation and putting in place the governance processes, but fail to train the organization on how to do the innovation work.

Truth is, you’ve got to do both. If you spend time to convince the organization why innovation is important, why not get some return from your investment and teach them how to do the work? And if you train the organization how to do innovation work, why not develop the up-front why so everyone rallies behind the work?

Why isn’t enough and how isn’t enough. Don’t do one without the other.

Image credit — Sam Ryan

It’s not the tools. Innovation is not hampered by a lack of tools (See The Innovator’s Toolkit for 50 great ones.), it’s hampered because people don’t know how to start.  And it’s hampered because people don’t know how to choose the right tool for the job. How to start? It depends. If you have a technology and no market there are a set of tools to learn if there’s a market. Which tool is best? It depends on the context and learning objective. If you have a market and no technology there’s a different set of tools.  Which tool is best?  You guessed it.  It depends on the work. And the antidote for ‘it depends’ is good judgement.

It’s not the process.  There are at least several hundred documented innovation processes. Which one is best? There isn’t a best one – there can be no best practice (or process) for work that hasn’t been done before. So how to choose among the good practices? It depends on the culture, depends on the resources, depends on company strengths. Really, it depends on good judgment exercised by the project leader and the people that do the work.  Seasoned project leaders know the process is different every time because the context and work are different every time. And they do the work differently every time, even as standard work is thrust on them. With new work, good judgement eats standardization for lunch.

It’s not the organizational structure. Innovation is not limited by a lack of novel organizational structures. (For some of the best thinking, see Ralph Ohr’s writing.) For any and all organizational structures, innovation effectiveness is limited by people’s ability to ride the waves and swim against the organizational cross currents. In that way, innovation effectiveness is governed by their organizational good judgement.

Truth is, things have changed. Gone are the rigid, static processes. Gone are the fixed set of tools. Gone are the black-and-white, do-this-then-do-that prescriptive recipes. Going forward, static must become dynamic and rigid must become fluid. One-size-fits-all must evolve into adaptable. But, fortunately, gone are the illusions that the dominant player is too big to fail. And gone are the blinders that blocked us from taking the upstarts seriously.

This blog post was inspired by a recent blog post by Paul Hobcraft, a friend and grounded innovation professional. For a deeper perspective on the ever-increasing complexity and dynamic nature of innovation, his post is worth the read.

After I read Paul’s post, we talked about the import role judgement plays in innovation.  Though good judgement is not usually called out as an important factor that governs innovation effectiveness, we think it’s vitally important. And, as the pressure increases to deliver tangible innovation results, its importance will increase.

Some open questions on judgement: How to help people use their judgement more effectively? How to help them use it sooner? How to judge if someone has the right level of good judgement?

Image credit – Michael Coghlan