Monday, July 15, 2019

Learning to innovate in the IoT Age

Lately, many commentators are given to sweeping claims about seismic change.  We are either in the 3rd or the 4th industrial revolution, depending on the commentator.  It can be hard to keep up.  However, where there is smoke there is often fire.  These commentators are correct in the sense that we are entering a time where the Internet of Things (IoT) and the data generated by billions of IoT devices will create radically new opportunities for innovation.  In one sense that fact is a good thing - it means innovation takes on an entirely new life.  In another sense it is a difficult thing - because so many companies haven't mastered the basics of innovating yet, before the deluge of data changes everything.  Innovation is about to get a lot more interesting, and I think a lot more complex.

If innovation today is like playing chess, innovation in the IoT age will be like playing three dimensional chess against several opponents simultaneously.  Companies that have mastered innovation today (and there are few that are really good at innovation now) will face much more complexity in innovating in the future.  Companies that have avoided innovation or who have fiddled around the edges are about to encounter a much more difficult task.

What makes innovating in the IoT Age challenging?

Until a few years ago, the vast majority of products were "dumb" products.  That is, they weren't connected to the internet or communication channels and did not create or publish data.  Your average physical product exists in a space outside of the internet and neither collects, generates or receives data.  As IoT devices and capabilities expand, this is going to change, and when it changes it changes everything.

Take for example my favorite insulated cup that I drink my breakfast beverage from every day.  It does not have sensors or IoT capability.  But if once it does, and if it connects to the internet to share data about my location, my beverage or other data about my life and experience, a number of things change in the creation and use of the cup, and the ability to obtain value from the cup after the purchase.

First, consider the creation of the cup.  Mass production of the insulated cup is simple without a sensor, but becomes a bit more complex by adding sensors, since the sensor must also have power or receive power from the environment, must gather data and share that data with the manufacturer through communication channels like Bluetooth or WiFi.  Simply designing and manufacturing the cup becomes more interesting, but that's the easy part.

Next, think about the business model implications of a connected cup.  One could imagine the ability to sell the cup with the sensor at full price, allowing the customer to determine if or when the sensors are turned on or connected to the internet.  Alternatively, one could imagine a business model in which the cup is provided at cost or perhaps even for free to consumers in return for full access to all the data generated.  In other words, there are many possible business models and consumer relationships possible where as in the past there were few.

Next, consider all of the data.  There are thousands or perhaps millions of insulated cups.  If all join the internet and share data, all of that data must be capture and managed.  We could go into a rather interesting discourse on what happens when millions of different products, each of which are acquired by millions of customers, all generate data every day.  The sheer volume of data generated by even a few IoT devices in your home is difficult to imagine, and also carries exceptional value.  AI and Machine Learning will be vital in many cases to parse out this data and combine it with other data to create new insights, recommend new offers, suggest new features.  However, most companies aren't ready to manage all the data, much less create value or insight from all that data.

So what's this got to do with innovation?

Today innovation is easy.  We understand customer needs or "jobs to be done" for a product or service and build a relatively simple, typically dumb product to meet those needs.  Since the product is dumb, we don't worry too much about business models, revenue models, data and data management, customer experience and other considerations.  Innovation today is primarily focused on getting the product's features - primarily physical features - right and getting the product to market on time.

As IoT enabled products become an increasing reality, innovators have to consider a much larger scope.  They may need to consider different revenue models or business models.  They may need to consider how data is captured, exchanged, and even monetized.  They may need to think about how data may enhance or detract from a customer experience.  They may need to consider how to augment their product with readily available third party data.  In other words, innovators will be forced to think through a number of alternatives and possibilities that just aren't on their radar today, and more importantly all of these considerations are intertwined.  For example, if you capture data, could that have an impact on the cost of the product?  The customer usage and experience of the product?  Will the data have value that can be monetized? 

Learning or relearning how to innovate

All of these factors and more are why I say that every firm will need to rethink how they innovate, and most will need to gain a much broader understanding of what innovation is, and what the product, service, business model and ecosystem considerations are for their products today, and more importantly in the future.

What innovation teams used to worry about were primarily physical features inherent to the product.  In the near future these issues will still remain top of mind, but will compete with issues and challenges related to data capture and exchange, business model and revenue model options, customer service and customer experience considerations and likely the need to involve third parties to provide data, data exchange, support or service for a connected device.  And all of that must be considered in the front end, a place that many companies haven't invested enough in up till now.

The companies that have mastered innovation will need to expand the definition and scale.  Those that have not mastered simple product innovation are about to be faced with a much more daunting challenge.  I'll address some of the factors that companies must consider when innovating in an IoT Age in a subsequent post.
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posted by Jeffrey Phillips at 7:48 AM 0 comments

Tuesday, July 09, 2019

What problem is AI or ML solving for you or your customer

I wanted to write today about AI and ML, and take a day or two off from my recurring posts on lessons learned from many years of leading corporate innovation.  It may seem strange that I'm also writing about AI and ML, or digital transformation generally, but increasingly it's clear that these two management concepts - innovation and digital transformation - are linked and will influence each other over the course of the next few years.  They share common challenges in that they both have big cultural impact, but differ in that AI, ML and other digital transformations seem more "real" and demonstrable, while innovation is still viewed as more problematic and risky.

One commonality they both share is the "shiny object" problem - that is, it's cool to be "doing" innovation or digital transformation, but to what end or what purpose?  Both digital transformation and innovation have this common element - that the mere activity seems to be validation enough, and that every team and every executive should be doing something with innovation and digital transformation, regardless of how well defined the activity is, or how clear or certain the outcomes.

One question I wish more people would stop and ask themselves about innovation, and digital transformation, is:  what opportunity or problem are we solving that is 1) important to us 2) important to customers 3) drives new value or radically reduces costs or increases efficiencies 4) has the support of management if we get it right.  And yes, that is a compound and multi-part question, but still one that everyone doing innovation and digital transformation projects should be able to answer rather succinctly.

Drives new value or radically reduces costs

You'll notice that in the multipart question there is a multi-part answer:  drives new value or radically reduces costs or increases efficiency.  I put that statement there because of the flying car phenomenon:  everyone over the age of 40 has been promised a flying car or jet backpack in their lifetime, and yet it never appears.  Yet the advance of technology has been astounding.  It's just that many new technologies are first applied to existing problems - making cars more nimble or more safe or more fuel efficient, rather than making them fly, which is a newer and riskier application.

AI and ML, and much of the digital transformation that will be accomplished as it is first adopted will have the same tenor - it will be applied to existing processes to accelerate them, reduce variations and remove humans from the process, except to manage exceptions.  Only then, once these technologies are proven, will they be applied to create radical new capabilities or insights.

So the question becomes:  what can AI or ML do right now better than existing capabilities or processes?  This is why you'll see a lot of RPA - robotic process automation - improving existing processes using robots or ML applications.  Your big goal if you are trying to get an AI or ML project off the ground is to determine what key challenges your organization has that can be improved through the use of AI or ML, and how to scope and manage the expectations.

Problems and Challenges

Your customer - internal or external - has problems and unfilled needs that can and should be easily defined and prioritized.  Once you've done that you can then determine which opportunities are best suited for AI and ML applications.  Then you'll need to understand the cost of implementing a digital transformation solution (often not that expensive since there are many open source applications) and also determine the amount of process definition, learning and data that are available to get the digital programs to work at least as efficiently as the people and processes in place.  Here's the rub - how the processes are defined now may not be optimal for AI or ML, and may need to be reconfigured, which can have knock on effects to the processes upstream and downstream from the activity you are focused on.  Plus, having enough good, clean, validated data to train the AI or ML can also be problematic.

But these implementation questions are somewhat secondary to a more important question - have you defined an important problem or need that an internal or external customer wants to have solved and is willing to pay for when you start implementing AI or ML?  This is often the same question that is asked about half way through an innovation project - "what are we really trying to solve, and for whom" - that should have been the basis for the project, rather than a discussion question half way through.
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posted by Jeffrey Phillips at 6:56 AM 0 comments

Monday, June 24, 2019

Making innovation your organizing theme

In my continuing series of posts about lessons learned from corporate innovation, today I'd like to expand on the idea of innovation language, and go even further.  I'd like to riff on the idea of innovation as central, organizing idea in a business rather than an occasional distraction.

Last Friday I wrote about the importance of defining a common language for innovation, so that people within a company are talking and working on the same things.  I've previously written on a number of other topics that are simply take aways from doing corporate innovation for a while, and seeing many of the same mistakes repeated over and over again.  Today's feature:  what if innovation was the central theme of your business?

A brief history lesson

I came of age as a consultant in the Malcolm Baldridge award days, when companies vied with each other to demonstrate how capable they were at delivering high quality goods.  This was in response to the Japanese companies doing a better job building high quality cars and electronics.  From that wave we've had successive efficiency strategies:  Six Sigma (an outgrowth of the quality movement), business process re-engineering, lean, outsourcing and right-sizing.  Over the last 40 years or so, the vast majority of our management time and attention has been focused on efficiency.  To the point where many strategies begin with - how does this help us cut costs, or help us increase throughput at the same cost?

Today, efficiency is the organizing theme of most businesses.  Leaders reinforce the idea that the company can do anything as long as it stays efficient.  Efficiency is used as a ruler to judge other activities. Does this new idea increase productivity and efficiency, remove risk and variance?

My concern with this approach is that we will tailor our systems and narrow our thinking and efficiency ourselves right into obsolescence.

What if innovation was the organizing theme?  

What if, instead of trying to wedge innovation activities into a culture and strategy focused on efficiency and productivity we had an organizing theme that said innovation was central to everything we do?  I venture to guess that many companies have slogans that say that innovation is central to what they do, but a brief exploration of what they focus on, what they measure and what they produce suggests otherwise.

Why would it make sense to make innovation the organizing theme of a business, rather than efficiency?  Making efficiency the core theme of the business assumes that the competitive environment changes slowly, and that efficiency and size matter when competing.  It also seems to suggest that small changes to existing products are preferred by customers over new products and solutions.  I'm going to suggest that in an era where change is as dynamic as we are seeing, large corporations need to be far more creative and innovative, because change is ever present, new technologies and solutions are being introduced faster than ever before and customer expectations and demands are changing constantly.  Slow and steady may have been the watchword in the past, but it seems like innovation is more critical to long term success.

Revisiting the innovation portfolio

And while introducing innovation as the central organizing theme may seem radical, it's not if a company has an intentional strategy for innovation investments - a viable innovation strategy and portfolio.  If we borrow the "three horizons" model for just a second, we can see that horizon one innovation is "incremental" innovation - small changes to existing products and services - which seems familiar to many companies.  It's horizon two and three where most falter.

Creating a meaningful program of investment across the three horizons will mean that a significant portion of the innovation activity is likely to fall in the incremental or horizon one sector, so that's doesn't introduce a lot of change.  And creating an intentional investment strategy in horizon two and three can only help the company look forward. So this suggestion isn't as radical as you'd think.

Plus, there is a way to loop back to the idea of productivity and efficiency.  By creating intentional innovation strategy, and defining innovation goals and processes, a company can make innovation a bit more understandable and even somewhat predictable.  Creating methods and innovation processes and training your teams helps them become more capable and productive.  Then we'll be using efficiency skills to drive more innovation.  Which is probably where we ought to be.

Keeping efficiency, introducing innovation

So a new way to organize, to set strategy and to infect a culture should be to organize around intentional innovation, while leveraging past efficiency tactics and tools.  Defining a three horizons model and making innovation strategy and outcomes more central to the business to learn to work at faster speeds while constantly adjusting to market and consumer needs will require some of the skills learned from the days of efficiency first.  But efficiency alone won't create new products or services or adapt to new customer demands.  It's time to shift our organizing theme from efficiency to innovation.
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posted by Jeffrey Phillips at 9:59 AM 0 comments

Friday, June 21, 2019

Language: the most challenging and trival innovation barrier

In my continuing series of lessons I've learned from 15 years of corporate innovation, I've tackled issues including the reasons ideas need sponsors, or why ideas are easy and good ideas are difficult.  In this episode I'm going to talk about my experiences as a translator and interpreter.  You see, one of the most important things I've learned is that no one has a standard language for innovation, and one of my most important tasks as a consultant (and least appreciated roles) is to create a language for innovation and act as an interpreter, often between people within the same company.

I'd like to discuss the problems with innovation definitions, labels and language and what you can do to avoid all this confusion.

Innovation Language

Unlike, say accounting, where assets are assets and liabilities are liabilities (I'm joking a little but there is a great amount of consistency in accounting) few innovation activities, deliverables or strategies are consistently defined.  For example, I regularly talk about and use the "three horizons" model for innovation, which defines incremental, breakthrough and disruptive innovation as three risk and technology driven horizons and potential innovation outcomes.  This is a fairly common innovation framework developed originally by McKinsey I believe.

In speaking with a prospect recently who has been in the innovation space for close to five years, I referenced the three horizons model.  Even though my prospect was using language like "incremental" innovation, he had never heard of the three horizons model.  What some of us take for granted as a proven and useful model, others who have been in the innovation space for some period of time have never heard of!

Common language simplifies communication and improves meaning, shortening work and improving understanding.  Where innovation is concerned, none of that statement above is true.  We lack standard definitions and labels, because we lack agreed standards.  Some of this is because innovation is a cottage industry.  Some of it is because different organizations want to own certain language or terms, while others don't want to use a competitor's language or framework.  Others try to over complicate innovation by introducing new, complex language and frameworks that make clients dependent on consultants.  The industry itself is guilty for some of the language issues.

Uncommon and infrequent

However, corporations also bear part of the blame.  Just like my Spanish usage comes and goes based on my trips to Cancun, many corporations have occasional visits to innovation land and need to learn the unusual jargon, then quickly forget it once they leave.  Since innovation is uncommon and infrequent, different teams in companies pick up different language or jargon based on who read what book or which team used which consulting partner.  Several times I've been in innovation meetings in corporations where different teams were arguing about the same thing, just giving it different titles or labels.

The tower of Babel had nothing on modern innovation speak.  Between competing frameworks and consultants with their own branded solutions and infrequent usage by internal teams, we spend far too much time on any innovation activity simply trying to arrive at a common language when we all happen to speak English.  But what we say, what we frame and what we define matters.

Disruptive or Transformational

One of my favorite definitional debates was in a corporation where the CEO wanted disruptive innovation and the team settled on performing transformational innovation.  To this day I'm not sure what the difference was, because disruptive means disrupting an existing market with a new offer, and it would seem transformational would "transform" a market or product, but the time spent getting the language right was, for the most part, time wasted because everyone eventually fell back on whatever labels and language they were comfortable with, which meant that we eventually adopted operational language, which narrowed the scope of work.

If you can't define something in a way that everyone understands exactly what you mean, you'll create confusion and others will rush in to create clarity based on their own understanding or biases.  That's what happens when the CEO requests innovation and gets small changes to existing products.

Nothing more important, nothing more trivial

However, not matter how important the right labels and language are to innovation work, trying to get teams to do this work and share their definitions is almost impossible.  First, you are trying to define something that people may believe is already defined.  Second, you were hired to create new products, not tinker with definitions.  Working on internal communications and language doesn't seem to create a new revenue producing product, so let's move on.

However, if you can't agree on "what" the outcome should be, you can't agree on "how" to do what you need to do and more importantly "why" you should do it.  Getting the language right, creating shared definitions and vocabulary doesn't seem important, but it is.
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posted by Jeffrey Phillips at 6:59 AM 0 comments

Thursday, June 20, 2019

Ideas are easy, good ideas are hard

I'm writing a series of posts that examine some of my lessons learned after over 15 years of corporate innovation consulting.  Past posts have included the concept of needing a why and a how for innovation, why ideas need a sponsor and how to understand the range of innovation options your company will consider.  In this post I want to discuss the proliferation of ideas and their relationship to innovation. 

Ideas are easy

Ideas are the raw material of innovation.  There can be little doubt about that.  Whether your innovation process is need driven (finding a need and then finding a solution) or emergent technology or idea driven (having a technology or idea and seeking a market) ideas represent a recurring theme.  And the fact is, ideas are easy.  If you doubt this, ask a five year old about their ideas for their bedtime, what to have for dinner or any other situation.  Everyone has ideas, some have better ideas than others, but we are awash in ideas.

The fact that so many people are spending so much time generating ideas creates a problem.  There is only so much bandwidth to review, evaluate and process ideas, so many ideas never get reviewed or considered.  And, since many ideas carry the idea generator's hope and dreams, it's really easy for cynicism to creep in to any idea generation or innovation process.  After all, hundreds or thousands of ideas could be generated, but only a handful will be selected.  There's only so much resource availability in any business to consider and manage ideas.  Many will never be selected.

Good ideas are hard

Few ideas ever reach the point where they are carefully considered, evaluated and moved on to become new products and services.  As an example, I used to have a sticky note on my PC to remind me of the rather fatal statistics.  ABC once published the number of show ideas they received in a year, the number of pilots they made and the number of shows they actually premiered.  I no longer have the data but it was approximately 800 show ideas, 50 pilots and 5 premiers.  Or, a little less than a 1% return on ideas.  Which seems about right given other statistics on new idea generation and conversion I've seen.

Does this mean all the other ideas (785 in the case of TV shows) were terrible?  No, it just says that the producers and sponsors felt the five were the best at that time.  Ideas have moments when they are more compelling or less compelling.  You don't want to be too early or too late with an idea.  An idea can be a "good" idea for a certain setting, or for a particular demographic but not for everyone.  Ideas may be "good" or "bad" based on their ability to generate revenue or profits (or not).  In other words, there's a lot that goes into determining whether or not an idea is good or bad, some qualitative, some quantitative, and some simply in the eye of the beholder.

What's needed is more context

For companies to innovate successfully and continually, they don't need more ideas, they need better ideas more attuned to current and emerging needs and opportunities that align with corporate strategies.  To get those ideas, companies need to do a better job educating their people about what matters in an idea, why it matters, and what key issues, opportunities or strategies good ideas must solve or address.  This means that strategy must be clear, goals and needs carefully defined and emerging opportunities constantly identified and communicated.  When companies do a better job of identifying emerging needs, markets and opportunities, people can do a better job creating ideas that match those opportunities, reducing ideas that are interesting distractions.  Fewer, better ideas reduces the number of ideas that can't be reviewed, increases the probability of success and build confidence in the entire team.

This observation means that there is actually more pressure on senior executives and product and service leaders to get their strategies right, to identify emerging opportunities and communicate them, and to tell people what ideas they actually want and need, and to act when their teams provide the ideas that meet those needs.  Good innovation is rarely a failure of the masses of people trying to generate ideas, it is a failure to provide the best context and identify needs and opportunities that are worth solving.
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posted by Jeffrey Phillips at 7:37 AM 0 comments

Monday, June 17, 2019

Understanding the innovation options in your business

I'm writing a series of blog posts to document some of the things I've learned in innovation along the way, over 15 years of leading corporate innovation work.  So far I've written several blogs, the first about the importance of defining a why and a how for innovation, the second about the importance of an idea sponsor.

Today I'm going to focus on the key drivers for innovation and explain what drives innovation in many organizations.  And in doing so I'm going to revert to a bit of probability and statistics, using a normal distribution curve.

Which firms innovate and why

Before we go deeply into the analysis, let me first say that most firms innovate, occasionally and sporadically, so to be fair, innovation is often happening in many organizations.  That's important, but what's more important is the nature and type of innovation.  For the vast majority of companies, the vast majority of innovation work is incremental at best, adding a new feature or capability to an existing product.

Now, incremental innovation isn't necessarily easy and it is important.  Incremental innovation is what ensures you have something new and attractive to provide to customers three to six months from now.  It's a new flavoring in an existing soft drink or a new feature for an electronics device.  Incremental innovation is relatively safe, and usually returns a small value for the investment, but rarely fails to flop.  That's why incremental innovation is so valued, and also why it is so dangerous.

Interesting and disruptive innovation

More valuable and far more risky are different types of innovation, those that achieve true breakthroughs or disrupt existing markets or industries, or create something really new and different.  The investments are often higher, and the risks of failure are often far higher with this type of innovation.  This could include innovating to offer a physical product as a service, or introducing an entirely new relationship or business model (ala Airbnb).  Disruptive innovation often originates from outside the standard players in an industry, because most of the existing players have too much to lose to make a significant transformation in their existing industry.

This leads back to the normal distribution curve

All of this leads back to the normal distribution curve.  If we assume that in every industry, companies are distributed across the risk and success curve in a normal (bell shaped) distribution, then the companies in the middle (moderately successful) are likely to conduct incremental innovation.  It's the firms two or three standard distributions away from the mean (industry leaders and industry laggards) which are most likely to conduct interesting, disruptive innovation, for two different rationales:

  • Industry leaders can afford to make big bets and investments, to try to keep a significant differentiation between themselves and the second tier competitors.  The leaders will double down, introducing new capabilities and features at an increasing rate, and will expand the definition of innovation beyond purely product features and shift into channels, service and experience innovation.
  • Industry laggards, falling behind the leaders and the second tier competitors, have no choice but to swing for the fences.  They will conduct disruptive innovation activities because they need to become relevant again to customers and to do that they must change the nature of competition.  These companies are more likely to conduct disruptive innovation that changes offerings and especially business models.
Which company are you?

From this simple analysis we can see there are three categories of companies within an industry (note I am not considering new entrants because they typically try to disrupt the industry or offer a significantly new business model, channel or experience).  Leaders will attempt to reshape the industry with new products, new services and new experiences to lock in their advantage.  Second tier competitors will fiddle around the edges and respond to innovations that the leaders introduce, but most of the second tier competitors will conduct incremental innovation.  Industry laggards, more desperate for attention and needing to change the nature of competition are more willing to take risks and conduct disruptive innovation.

Knowing which kind of company you are in, and the stomach for risk and change in your company and in your industry, will tell you a lot about the potential for the different forms and types of innovation.  Doing incremental innovation in a laggard is whistling past the graveyard.  Most second tier companies prefer to wait to see what the leaders do and then follow those actions, rather than define a new course for the industry.  Leaders lead, until like Apple they no longer innovate and simply rest on their laurels and watch their share get taken away.

What kind of innovation you want to do, and perhaps can do, is to some degree dictated by what kind of firm you work for, its position in the competitive pecking order and the amount of risk it is willing to undertake.
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posted by Jeffrey Phillips at 10:20 AM 0 comments

Wednesday, June 12, 2019

Every idea needs a sponsor

As I noted yesterday, I'm writing a series of posts about what I've learned over the last 15 years of corporate innovation work.  Yesterday I wrote about needing a "why and a how" rather than a "what" for innovation.  Today, I'd like to write about sponsorship, and why it is critical to have engaged sponsors for ideas and for innovation.

This idea is important enough that I took the extra 30 seconds and looked up the definition of sponsor.  The definition that I felt was appropriate for this discourse was "one who assumes responsibility for some other person or thing".  I think this is as close as we can get to what an innovation or idea sponsor is.  Now we just need to understand how this fits into innovation, and why I think it is so important.

Free radicals

Most ideas are free radicals - that is, they don't necessarily "belong" to anyone, and if they are interesting or have real potential impact they are probably a bit dangerous or radical.  Since it is easy to generate lots of ideas, every business has plenty of incremental and disruptive ideas floating around.  It's not hard to generate ideas, obviously, but much more difficult to decide which ideas to test and validate, and even more difficult to convert an idea into a new product or service.  To test and convert ideas successfully and consistently, you'll need to match an idea to a sponsor.  Otherwise, ideas will remain free and interesting, but they won't be implemented.

I've used the term "free radicals" intentionally.  Ideas themselves are necessarily dangerous the way free radicals in our bodies are dangerous, yet ideas left unaccounted for tend to hang around and become the subject of discussion and debate, leading to skepticism and cynicism about innovation.  So over time ideas without sponsors can become like a free radical in the human body, doing unintended damage.


An idea sponsor is simply an individual with enough seniority to ensure that an idea receives the attention, funding and resources it needs to be carefully considered and promoted to a stage where it has a chance to enter new product or service development.  Idea sponsors typically don't sponsor ideas out of the goodness of their hearts - this isn't a charitable exercise - but for purposes of advancing a new opportunity that has value to them or to their business.

This means that ideas need to be matched with people who have enough power or clout to move them ahead, and also matched with people who have an opportunity or need that the idea addresses.  No matter how good an idea is, if there isn't a person who has the need or understands the opportunity and is willing to invest in the idea and push it forward, it will remain a free radical.

There's a potential downside to sponsorship, which we must also consider.  Sometimes "pet" ideas or concepts that aren't really interesting or innovative have sponsors.  Projects or ideas that could not receive investment or funding under other mechanisms will be relabeled as "innovative" and pushed through an innovation process.  That's why every good innovation process has a gating function or steering committee to determine if the idea has real value and impact, as well as having a sponsor.

What do sponsors do for ideas?

Ideas may be free, but managing, evaluating, testing and validating ideas isn't free.  These activities require investment of time and money, and that's where sponsors come in handy.  Given that many organizations have lots of ideas and few resources, resource allocation and prioritization is in order.  For ideas to succeed - moving from the "front end" to product or service development and on to launch, a lot of investment, focus and pressure must be applied.  That only happens when someone takes an interest in an idea and helps focus attention and resources on the idea.

Sponsors help build a business case for the idea, provide resources to shape and vet the idea, encourage the innovation teams when obstacles occur and make the case for the idea to bridge the gap from a concept in the front end to a defined project in product or service development processes.  Sponsors keep attention on an idea, ensure funding flows to critical ideas even when other projects are getting sidelined or killed.

What happens without sponsorship?

When we make a case for a specific course of action - such as assigning sponsorship to ideas - we ought to demonstrate that the course of action has merit over a 'do nothing' or status quo activity.  So let's imagine what happens to ideas in a front end funnel without any sponsorship.

Teams or individuals will generate ideas, and will seek funds to test and validate ideas.  They will have to ascertain what ideas are most valuable and important based on corporate or business unit strategy, since no one will forcefully argue for an idea.  They will have to prioritize a handful of ideas - because they can't work on more than a few at a time - based on their own judgement, since no one is placing emphasis on a specific idea.  The team will have to negotiate for funds to prototype, test or license ideas or conduct research from a funding source who isn't necessarily keen on any specific idea or course of action.  All this time ideas are free radicals, not aligned to any product group or business function, and therefore not receiving any input or shaping by a potential adoptee.

Any idea that must go through a front end process, that must bridge the gap from the front end to product or service development, that must go through a marketing and launch cycle and have an impact on its market needs a sponsor, ideally the same one throughout.  We can debate whether or not small, incremental ideas need sponsorship, but anything reasonably new of different simply cannot run this gauntlet without the careful attention of someone with enough need, vision and clout to make it happen.

How does your organization decide who sponsors ideas?  How do you avoid the pet idea practice?
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posted by Jeffrey Phillips at 7:14 AM 0 comments