Brainstorming vs. Ideation

Brainstorming and ideation are different tools for different purposes.

You’ve undoubtedly been in brainstorming sessions. Some of these sessions have likely been fruitful, others disappointing. I often get asked how ideation is different from brainstorming. A very smart and talented friend of mine, Matt Phillips distinguished the two types of sessions by asserting most brainstorms are simply “meetings… with better food.” But beyond that perhaps undeserved jab at brainstorming, there are several aspects that separate brainstorms from formal ideation.

First, what is an ideation session, anyway?

Before I jump into the difference between a brainstorm and an ideation session, I should provide some context for anyone unfamiliar with this process. In traditional design-thinking, the ideation phase is often the most exciting step within the process. The ideation session itself is the organized gathering of minds within that step where the litany of ideas is generated against some highly defined problems or desired outcomes. These ideas range from the possible to the seemingly impossible given current organizational constraints.

A time and a place.

For what it’s worth, I love a good brainstorm. They’re fun, engaging and often produce creative ideas. They are collaborative and aid in generating new ideas to improve internal processes, develop creative campaigns, share ideas, etc. This is all important work.

But let’s remember that ideation is the third step in a more formal design-thinking process and should be treated as such. It should be informed by learnings emerging from the Empathize stage, address specific challenges outlined in the Define phase and, finally, create a starting point for the Prototype and Test phases.

Ideation is about not only generating ideas but also systematically upending and exploring the mental models surrounding those ideas, assessing recurring themes, evaluating ideas through a variety of lenses and, ultimately, converging and consolidating various branches of thought into manageable future areas of innovation. Ideation, to that point, also requires more time, commitment, homework and buy-in from stakeholders. 

Ideation may be utilized for a multitude of business challenges. Some examples include:

• Developing new product or service directions

• Exploring new business strategies and revenue streams

• Finding new business angles by solving complex customer-centric challenges

Leave it to a professional.

When led by a trained moderator, ideation sessions get users beyond the myriad obvious solutions often generated in traditional brainstorming sessions. The session moderator leads participants through a series of carefully structured exercises designed to create an abundance of ideas and then explore, build on and refine the most viable. There is a substantial amount of exercises out there (this site is a nice repository for a number of tools and methods), but understanding which exercises are best suited to address your particular challenge is a skill honed through repetition and experience. Having a moderator who can teach or lead your team through the effective use of these tools is equally as critical as wielding them in the first place. 

A successful session leader will help you:

• Ask—and answer—the right questions

• Break through organizational constraints to view challenges in a new light

• Keep your “hero” user’s needs and behaviors at the foundation of your innovation

• Rise above the obvious solutions to increase innovation potential

• Identify and leverage different perspectives to uncover unexpected angles for innovation

There’s definitely a team in “I.”

In ideation, fielding the right team is critical. Sure, brainstorms usually include teams. But, yet again, ideation is different. It’s important to bring in the right expertise and perspectives to maximize the value of a session. A diverse group of resources is the most effective, from internal subject matter experts and designers to trend experts and sometimes potential customers. The diversity of expertise within the group can be critical in creating and enhancing groundbreaking ideas, ensuring all angles have been explored, examined or exhausted.

It’s always a matter of time.

In addition to being internally focused with little structure or outside perspectives, most teams dedicate an hour or two for a brainstorm. Little thought or prep work is required. Ideation, on the other hand, is a commitment—session preparation, session execution and idea refinement. To be successful, most sessions require a time commitment of one to two business days.   

Just interesting people kicking back, sharing a beer and developing a breakthrough innovation?

If only it were that easy! The truth is, while they may be fun and stimulating, ideation sessions are hard work. When done right, most participants leave both stimulated and exhausted.

TL:DR?

Here’s a quick snapshot of the difference between a brainstorm and an ideation session.

Brainstorm

• Often a standalone meeting based on a singular objective

• Used to generate new ideas

• Good uses of a brainstorm include:

  • Improving internal processes

  • Developing creative campaigns

  • Naming exercises

• Often unstructured with takeaways delineated at the end of the meeting

• Often include homogenous teams

• Time commitment: 1–2 hours

IdeationSession

• The third step in the design-thinking process: informed by gathered insights and defined challenges to solve

• Used to generate ideas and explore what surrounds those ideas, assess themes and evaluate ideas

• Good uses of an ideation session include

  • Developing new product/service directions

  • Exploring new business strategies and revenue streams

  • Finding new business angles

• Highly structured with pre-work and post-session refinement

• Includes diverse perspectives and internal and external resources

• Time commitment: 1–2 days

2018—Disruption Goes Mainstream

I think everyone can agree that innovation and disruption are already two of the top buzzwords in 2018. Companies are increasingly focusing on innovation to hopefully avoid being disrupted by a new technology, market entrant or an existing competitor. It seems if you’re not innovating, disruption is inevitable—forcing innovation in positive or negative ways. Long story short, disruption is the new normal. Constantly driving or increasing value through innovation is table stakes. So, when the RND2018 Innovation Summit hit Chicago, I decided attendance was mandatory.While attending, I witnessed some of the brightest industry leaders coming together to share best practices and new ways to drive value through innovation within enterprise or mid-sized companies. Presenters included VP of Innovation at Johnson and Johnson, Shawn Johnson; VP of Global R&D IT at Monsanto, Qi Wang; Editor in Chief, IEEE Computer Society, Dr. L. Miguel Encarnacao; Director of Innovation Culture and Habits at Maddock Douglas, Diane Kander; CableLabs VP of Market Development and Project Management, Anju Ahuja (co-presenting with Magnani’s own VP of Strategy and Planning, Christy Hutchinson); VP of Innovation at Leo Burnett, Jeff Ponders; and many more.The most significant take-away from RND2018 was that at the core of all innovation is the creation of value, which doesn’t happen overnight (and it certainly isn’t magic). It takes a methodical approach, with key success and failure metrics helping to guide the path. Below are the four themes I saw at the RND2018 Summit.

1.     Put the customer at the center.

Put the customer, who is first and foremost a human, at the center of any innovation strategy or vision. Seems like a no-brainer. Yet, many companies are just now reorganizing their internal structure to accommodate this mentality. As innovators and value creators, we have to understand that everyone, whether you’re B2B, B2C, B2B2C, is a human first. And we need to understand and address the emotional drivers of their decisions.What are those emotional drivers? You can certainly look at the data you’ve been gathering and make a few assumptions, but it’s never that black and white. Humans respond when there’s a need and it’s your job to find out what this problem is. One way to solve for this is through “Narrative-Based Innovation”, which was presented by Anju Ahuja, CableLabs and Christy Hutchinson, Magnani.Narrative based innovation is driven by story, and it’s especially powerful because stories are ingrained in how we collectively understand and transfer complex ideas. Think of the stories passed down through your family, your religion, your favorite movie, your favorite childhood book, etc. Now apply that mentality to your user journey. What is their story? A story works because it connects with people on a deeper level, and it can also be told over and over without memorizing data sets. It can be told internally to secure funding, to your IT/R&D team to understand the ask without handing them the technical answer, your marketing team to frame communications internally/externally, and, ultimately, to the end user to understand the benefits.As Shawn Johnson, VP of Innovation at Johnson and Johnson said in relation to the connection of health and wellbeing, “Your mind doesn’t know if it is imagined or not, it is a subjective experience.”And, I would argue, every innovation project begins with a subjective experience. So, why not convey it in a story, told through the voice of the consumer, about the consumer, to drive a deeper connection and inform your business case?

2.      Always put the R before the D.

Speed is currency at any organization. And as tempting as it is to run full force without doing the proper research, it rarely works. There was use case after use case at the Summit that pointed to failures, with the common learning of always put research before development (not  to say that failure is bad...I’ll get to that in the last section).Why? According to a number of presenters, when you’re leading a project with your team, and everyone on that team has been at your company longer than six weeks, your collective frame of mind is likely tainted by groupthink. You need to bring in outside resources to share new perspectives and engage with your target audience to ensure that your North Star is actually the North Star—not just the brightest star of the night. Diane Kander, Director of Innovation Culture and Habits at Maddock Douglas, made the great point that everyone needs a “Provocateur” to ask all of the questions that you didn’t know you needed to ask.Once you ask the questions and frame the problem, doing the proper qualitative and quantitative research to inform your direction is paramount. But once you have this research and looked at the data, you’re in the clear—right? Try again.Another important perspective presented on this topic came from  Dr. L. Miguel Encarnacao. Even within companies that have big data, data sets that are so voluminous and complex that traditional data-processing application software are inadequate to deal with them, there is often an overall lack of data literacy. If someone presents the same set of data three different ways (for example a spreadsheet, bar graph and pie chart) there are likely going to be three different opinions. It’s of great importance that data literacy be the foundation for any research, data and analytics project. Having more colors and pie charts doesn’t equal successful innovation.

3.      Focus on the value over the innovation.

At the end of the day, innovation is about value for your consumers. Hence, every innovation initiative should be focused on the value provided to the end-customer, but also your company. If you create an amazing product and the end user loves it, but it doesn’t make sense to your company’s bottom line, scratch it.So how do you determine if it’s of shared value? Simple. The value should be tangible for both your end user and your company—it should solve a problem and drive growth. Here are the three things that matter:

• Cost
• Return
• Speed of return

Qi Wang, VP of Global R&D IT at Monsanto, gave great examples of being intentional about driving value and understanding when to invest in driving value to inform the R&D pipeline. For Wang, it’s not how they do science, it’s how they talk about science.

4.      Fail quickly. “Mastery is a journey, not destination.”

Name someone who woke up overnight with a brilliant idea and flawless execution that didn’t fail 1,000+ times before getting there? Any luck? Companies all tend to like to have processes in place that minimize chaos and predict outcomes as much as possible. If you attempt to do this with your innovation team, they won’t be around long.Smart, controlled failure is critical to any successful innovation initiative. Jeff Ponders, VP of Innovation at Leo Burnett, illustrated that mastery is a journey, not a destination. In order to be successful, you and your team need to get comfortable with being uncomfortable and need to realize that understanding how to fail and succeed are one in the same.Another great suggestion by Diane Kander was to put pivot indicators in place. Understand the value created (map on Y-axis) and the effort required (map on X-axis) and assess if the two are in-line or heavily skewed one way or another to determine if you should move forward.Once you have decided to move forward, put failure metrics in place.One of the greatest talents of innovators is knowing when to pivot or change directions altogether, learning when to say no, and understand that “good enough” is not a standard.And the main take-a-way: R&D is to bring the energy and focus, because real innovation is iterative and messy.

Why Should You Care About Deep Learning?

People and patterns and predictions, oh my.

For marketers, a simple way to think about deep learning is that it’s ultimately about presenting customers with exactly what they want, whether or not they know yet that they want it. That could mean an experience, a bit of information, an ad, or a suggestion for a specific product. But what is deep learning?Deep learning is a subset of artificial intelligence (AI) derived from the science of neural networks. And neural networks are simply an attempt to mimic the way scientists think our own brains process and make sense of the world. Basically, a neural network self optimizes its performance on a desired task based on exposure to structure and unstructured data.

I spy with my AI…

For example, let’s imagine we’re creating a deep learning based image recognition system designed to spot a product––a specifically branded can of soda—in photos posted on social media because we’d like to give a shout out, through our own social accounts, to the poster for their brand loyalty.The first thing we would need to do is train the deep learning neural network using a number of verified positive and negative sources—e.g., photos containing said soda can, pre-tagged as a hit as well as photos with no can correspondingly tagged as a non-hit. Next, the system would be fed untagged positive and negative photos. The digital patterns in those photos would be compared to whatever digital patterns emerged from reviewing the initial guided positive and negative inputs.If the system recognizes what it has determined is the pattern for, “branded can,” it marks that photo as a positive hit. At this stage, the system will require human feedback to determine whether that positive hit was, in fact, positive and whether other photos were falsely tagged as hits or non-hits. Each iteration, every data point, refines the neural network to better identify its proper target. And with data sets that span the internet, you can imagine how refined those algorithms can get.But here’s the interesting part. Humans generally can’t read or understand those algorithms. We don’t know what the criteria the network is using, per se. We only know it’s getting better (or worse) at identifying the branded can. And there are plenty of times the technology fails completely, not to mention offensively.

Sidebar:

How this “portrait” was made:

1. generate random polygons
2. feed them into a deep learning, neural net face detector
3. mutate to increase recognition confidence until the neural net is reasonably sure it is “seeing” a face

A synthetic portrait “recognized” among random overlaid polygons by deep learning AI at here, here and here, deep learning AI will likely become increasingly pervasive in marketing and advertising. If you want a far more detailed and thorough primer on the topic, Stanford university has placed online an amazing guide to deep learning.    

Three Proven Paths to Disruptive Innovation

[embed]https://soundcloud.com/magnani_brilliant/3-three-proven-paths-to-disruptive-innovation[/embed]

Justin and Justin discuss the myth of overnight success, the three proven paths to disruptive innovation, and how half the Fortune 500 companies listed in 2000 have been replaced by market disruptors. And, as a bonus, they give their subjective opinion of Domino’s pizza.

How to Improve Your Odds of Successfully Innovating? Hint: It’s a Numbers Game.

How many of Edison’s 1,000+ inventions can you name?

There is the electric light bulb, the phonograph, the motion picture camera... and more. And that’s the point. For every notable invention Edison patented, there were dozens more along the lines of his entire post on the value of failure in the innovation process. One way to think about it is to look at a very rough rule of thumb used by many venture capitalists. Among all of the investments they make, they expect:

• One third of investments fail outright
• One third of investments break even
• One third of investments generate 10X returns

If they can stick to that schedule, failures and all, they are generally making better than average returns on the portfolio overall. Granted, it’s not a sound strategy for any normal investor looking for someplace safe to slowly grow their money over time, but it’s perfect if your investments are collectively high risk/high reward endeavors. And if your innovation program doesn’t fit that description, you’re probably not actually innovating.

So, how can you improve your odds?

Reading all of this discussion of failure and risk, one might assume innovation programs are a drawn out roll of the dice. There are, however, proven ways to increase your chances of success, besides simply having the tenacity to ride out the failed iterations along the way.

1. Define your area of focus Try to determine what aspect of your industry or category offers the greatest opportunity for disruptive innovation. Is it in product cost? Performance? Service model? We have another article covering a few approaches to this issue here.
2. Focus your teamCreate a dedicated innovation group. Make sure they’re charged not only with creating new innovation projects, but also shepherding them—both the successes and the failures—through to completion.
3. Know your end userThis may be the most important safeguard of success. Great innovation is about solving for real human needs and challenges. When component bells and whistles drop in price, should you add more bells and whistles or create a cheaper bell and whistle delivery system? Unless you know what truly matters to your existing and potential users, you have no reasonable way to determine which path offers the greatest chance for success.

In other words. Everyone rolls the dice. But smart innovators take the time to figure out where to shave off a corner here and there to make the numbers come up in their favor more often.

Three Proven Paths to Disruptive Innovation

Disruption isn’t magic

The popular mythology is that nobody sees disruption coming. Disruptive businesses, like unicorns, appear as if by magic, to upend the status quo. And the disruptors are mad wizards who somehow see the future no one else could have. But the truth is, most disruptors follow a very linear thought process and those companies being disrupted are more victims of their current successes than they are caught off guard.

Even the best companies are vulnerable

More than half of the companies listed in the Fortune 500 in 2000 have since been removed—dethroned by a more technologically savvy disruptor. And, it is predicted, that between now and 2025, half again will have succumb to a similar fate.In his seminal work, “The Innovator's’ Dilemma.” Harvard professor Clayton Christensen lays out the basic development trajectory of disruptive innovation and provides a myriad of logical reasons why successful companies fail to act when smaller, even less-well-funded, disruptors enter the scene.

It’s an excellent text with innumerable examples that most will read with exquisite hindsight and shake their heads at what seem today to have been myopic management decisions. But how do you know you’re not following the same path today in your own industry—great at the game you’re playing, but not realizing the game itself is about to change?

1. Launch tomorrow’s market offering, today

Is your target segment a growing or shrinking demographic? Are there macroeconomic trends that will have any major impact on the size of your current markets? Are there any shifting  generational or social norms that could affect perceptions of your brand or your offering?Choosing which trends might materially affect your markets one day is an art form, to be sure. But the idea here is to scour secondary research sources and glean from that data the most relevant bits to help model a snapshot of your market at some specific point in the future—two years, five years—when you believe those trends will converge to a tipping point for the current market.

For a relevant example, we can look at the hospitality industry. In it, there are any number of examples of companies using this type of analysis to shift their offering to meet future demand. Case in point, while Generation X may currently represent the largest segment of business travelers, many of the leading hoteliers have focused their innovation teams on changing their room and common space designs to address the impending market dominance of Millennial business travelers.

Watch a Gen-X-aged business traveller enter a recently renovated room at a Marriott and you’ll likely see them looking all around the room for a desk that isn’t there. Watch a Millennial business traveller enter the same room and they’ll sit on the bed and pull out their laptop without a second glance for a desk they’d likely never use anyway. Common areas are being similarly transformed. Where once hotels created separate lobby, work and dining areas with nationally recognized eateries, current renovations are delivering integrated common rooms and unique culinary options derived from local influences.

2. Expose your industry’s deepest darkest secret

In most industries, there’s some fact about the standard business model that no one really wants to talk about because, though it may be inconvenient for the customer, it drives significant revenue. Take for example the insurance industry. Everyone in the industry would tell you that it is, by necessity, a relationship business. To get insured properly, you need a guy or gal in the business who knows the business, because every customer is unique, getting the best premium is math intensive, and the process is too arcane for the issuance of a policy to happen any other way.On top of that, once you were insured, having a claim processed and (hopefully) paid was often a weeks-long undertaking.

Customer complaints about that extended time span were met with explanations that processing a claim required multiple checks and balances and a great deal of necessary paperwork.Though, as proven by industry upstart Lemonade, it is likely more accurate to say the deepest darkest secret of the insurance industry was that most customers fall into common risk profiles, adding obfuscation and complexity in how premiums are calculated reduces price comparison opportunities, and that claim delays were more about earning a greater amount of interest on cash reserves than it was about extensive investigations.

Lemonade began providing renters and home insurance for urban dwellers through an A.I. fueled mobile app, in a process that takes less than two minutes. And claims processing and payment? Three minutes. Further, instead of paying annually, Lemonade customers can “subscribe” to their coverage on a monthly basis.The innovation here doesn’t appear to have stemmed from a single a-ha moment. It seems the product of a systematic, cumulative uncovering of all of the ways the insurance industry intentionally complicates the offering to protect existing revenue streams.

3. Create a future where your industry’s greatest strength is a weakness

This has demonstrably been the most fruitful path to success for disruptive businesses in the past decade. Just look at Alibaba, Uber or AirBnB. Prior to Alibaba, retailers professed their strength by touting the depth and scale of their inventory. Nothing could compare to, “everything, in stock!” Alibaba became the largest retailer in the world expressly by creating a business model where they carry no inventory. Love them or hate them, the same approach was quite successfully taken by Uber.

They have grown to be the world’s largest taxi company, expanding rapidly in more than 80 countries and they own no taxis. AirBnb? The fastest growing hotelier in the world because they explicitly own no property. Ironically, the most current example of this might be Amazon’s recent push to open physical storefronts—differentiating themselves from increasing online retail competition by creating enhanced opportunities for more personal interactions as well as faster local deliveries.

Innovators understand that if you can envision a way to threaten the value of an industry’s greatest asset, the industry will instinctively apply resources to protect that asset, temporarily giving the innovator plenty of runway upon which to gather momentum.

Pick a path. Now act like, or fund, a startup

Technology, machine learning and automation is lowering barriers to entry in every industry. Emerging generations expect better solutions. Disruption is imminent. If you’re charged with improving the long-term competitiveness of your business you have two main choices. Disrupt, or be disrupted. The point here, is that it doesn’t take a massive spark of genius to spot the next disruptive opportunity. It only takes commitment to taking the path.

How to Develop an Innovation Strategy

The myth in popular culture is that innovation is the byproduct of a random spark of inspiration. Lightning strikes. Someone has a eureka moment. The world is forever changed. Sounds quite easy, if mostly unachievable by mere mortals.The truth is that innovation is more often the result of a resolute commitment of time and resources—and a solid innovation process. Committing the resources is simply a matter of availability and will. Creating a strategy can be more complicated. There are, however, some basic questions that every company should ask and answer to begin solidifying a viable innovation strategy that the entire company can rally around.

What would change the value equation of our industry and our customers?

This is an intentionally broad question, but it is at the root of any successful innovation strategy. For a business, innovation isn’t about change for change’s sake, it’s about taking steps today to secure the greatest share of revenues and profits in the future. And the first step gaining a glimpse of what that future looks like is to imagine what the market would look like if you, through your product development efforts, could radically alter the cost structures for the business or its customers, or both. What would the market look like if you could radically alter the product lifespan? What if you radically changed the scale of your solution? Delivery times?It’s not that you need to answer exactly how you will accomplish this, for now. But rather, you need to decide, as a company, what of those changes could have the greatest impact on the landscape of your industry. Further, whatever you choose to focus on needs to be something you believe is at least somewhat achievable with the application of time and resources.

How could our business model be disrupted?

One of the best ways to start answering this question is to look at your own and the market leader’s greatest strengths and start to ask how a new entrant might turn that into a weakness. 10 years ago, few would have predicted that the world’s largest taxi company (Uber) would own no taxis, or that the world’s largest retailer (Alibaba) would hold no inventory, or that the world’s fastest growing hotelier wouldn’t own or manage a single room (Airbnb). But those companies looked at the market leader’s greatest strength and made it a weakness.

What parts of today’s business are we willing to sacrifice for tomorrow’s innovation?

In his seminal work, “The Innovator’s Dilemma”, Harvard Business School professor, Clayton Christensen, outlines the ways highly successful companies end up ceding markets to disruptors they could have easily stopped in their tracks had the company been willing to suffer through the opportunity costs of innovation. The point being, sometimes you innovate and sometimes you have innovation thrust upon you. And it pays to understand in advance how the business could function, thrive or survive with various lines of business or product lines removed.

What capital are we willing to invest/risk?

It should come as no surprise, but innovation is rarely inexpensive. In fact, it’s usually costly, even comparatively wasteful by normal business investment standards. Where investments in the day-to-day operations are expected to produce standard linear returns, investments in innovation should be thought of more like a venture capital model—most of them will return nothing, but the home run ideas deliver 10X returns. It’s not math most companies are used to or comfortable with. But failures are as much or more a part of fruitful innovation programs as the successes. A great example of this mentality is Apple. It is widely reported that Apple kills off far more of its R&D projects than it ever sends to market. And that willingness to experiment has obviously served them well.

If it ain’t broke, why fix it?

It’s tempting to think that wildly successful businesses are somehow immune to radical disruption, but none truly are. Traditional relationship businesses could be easily overwhelmed by conversational AI. Delivery, distribution and logistics are in the crosshairs of self-driving vehicles. Accounting, auditing and title insurance businesses could suddenly find themselves anachronistic leftovers by blockchain technology. Just as traditional media planning and strategy has succumbed to programmatic models, even formerly technology-resistant creative professions will find themselves pressured by bots that can literally start running the infinite monkey’s algorithm until they hit upon the marketing equivalent of Shakespeare. This is not a gloom and doom prophecy. It’s the call of opportunity resulting from new disruptive technologies. We just have to keep open minds.

Riding the Wave of AI

The wave of automation and AI disruption is coming. Is your business ready to ride?

We see new advances in digital automation and artificial intelligence (AI) nearly every day. Much like industrial robot technology reduced the number of available manufacturing jobs in the U.S. in the 1980s, the combination digital automation and AI is poised to disrupt virtually every industry at some point in the coming decade. The question is how can you position your company to be the disruptor, not the disrupted? 

Ask how a competitor using advanced AI could beat you at your own game.

Diagram your complete path to purchase on a white board. Evaluate every part of your business for any moment along that path where automation or AI facilitated decision-making could reduce process time, costs and user frustrations. Also look for any part of your path to purchase where customers drop off or fail to convert, and try to re-imagine those points with AI or automation assist. Take time to explore emerging technologies that could directly or indirectly affect your market, long term.Now, look at your market and ask, regardless of organizational, technical or monetary constraints. What would the ideal experience for the majority of your customer look like? What do your customers value/like/dislike about everyone’s current offerings?Finally, get your smartest people—from operations, sales, marketing, admin et al—and design your worst competitive nightmare. What special expertise would they offer? What advantages would they have over your business? How would they price? What capital expenditures would they need to build their infrastructure, I.T. or facilities? 

Figure out what it would take for them to get off the ground.

Once you decide how your new competitor would operate differently to steal your business, try to document what it might take to get a company like this going. What resources would be needed? What infrastructure would be required? What would the employee mix look like? How quickly would they be able to steal your business? How could they offer a parity or better product or service than you do now, cheaper than you can? 

Create a script outlining what they would say to sell against you.

Be brutally honest. Talk about where your business is vulnerable. Ask what potential benefits of this new competitive offering that your customers would respond to that you aren’t able to match. 

Surprise, you just outlined a business plan.

In those three (obviously multifaceted) steps, you’ve outlined the product/service design. You’ve begun to outline a viable financial model. And you’ve laid the foundation for marketing and sales messaging. 

Remember: if you can imagine this, so too can a real competitor.

With every new technology, it’s only disruption when you’re the incumbent. For everyone else, it’s simply opportunity.