How Are Those Long Range Scanners Working Out?

Are You Looking Far Enough Into The Future? Since our earliest days as primitive savannah wanderers, we humans have had a natural tendency to prioritize immediate gratification above achieving more far-reaching goals. Along with the capacity for thought and reason, human beings are the only animals that are capable of planning and thinking ahead to…

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Banish Failure! Did You Win Or Did You Learn?

Ah, failure. Are there still people out there who feel that it is a bad thing? I know of very few cases where, barring a life and death struggle, failure does not produce a positive effect. Failure does teach, and it teaches a great lesson.

It’s time to retire the word. For everything.

Read an article the other day in one of my favorite magazines – the New Philosopher (yes, as an innovator, you should read broadly too – just reading HBR and innovation tomes doesn’t open your mind like philosophy and great, far future sci-fi do) where a father was urging on this son to excel at chess. To keep from hurting his feelings, he never used the word “lose”, as in “Did you win or lose?” when he came back from his matches – but the phrase “Did you win, or did you learn?” Of course, there is learning in winning as well, but who can argue that we learn more than we lose. In fact, isn’t it true that we learn more when we lose because we hate feeling pain worse than love feeling pleasure?

Either way, note that the dad specifically did not say “lose” but “learn”. In the same say, can we not constantly attribute failing startups or losing market share to a solid lesson learned? If we slam our innovation initiatives every time they fail, do you think you’ll see your people continuing to take risks?

No, you’ll never get the kind of disruptive innovation that you need, you’ll get the same incremental stuff that might help a little – but won’t lead you to those unicorns you love so much.

We need to recast the concept of failure, eliminate the word as much as we can. Didn’t Thomas Edison say that he never failed, just came up with hundreds of ways that didn’t work? We need to look at risk-taking anew and realize that without risk of “finding ways things don’t work” then we rarely get to the way that does work.

If startups and projects don’t gain traction, they pivot or shut down. The lessons learned from these moves into the founders next startup or the project teams next project or company. Instead of saying “a string of failed startups” you should be thinking “a string of educational experiences”

We had a very long string of inventions, from the Renaissance to the jet engine, truly disruptive concepts which dented the human universe and changed humanity for the better. Even those concepts which were tried and didn’t fly taught us what not to do or educated us that this was the wrong time and place for this concept (so many businesses start too far ahead of the world and are unable to pivot to product/market fit).

But should we slow down, should we stop trying, just because it might cost us to learn? If you ask me it costs us more when we don’t take the risk, when we are afraid to fail.

When you are afraid to fail, then you never do, and without doers, where would we be?

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Timing Is Everything. Get That Right and You Win.

Everything that we’ve come up with will happen. We just don’t know when.

I’ve said before many times that the biggest issue with being a futurist is that you are a lot like a weatherperson – usually right, but at the wrong time. Another corollary to that is that everything that has been imagined happening, within reason, will happen, and the only question is when.

Basically, if it is physically possible to do something, then it will probably happen at some point. It may be soon, it may be 5-10 years, or it may be even further out. The trick is trying to figure out when.

In our futurist programs, we ask our clients to imagine what the world will be like 10 years out. We ask them to imagine what they will be like, what their customers will be like, what their products and services will be like, as well. We get them to project into this, for some people, far future (remember that many people can hardly think even a quarter or two out, concerned that there are massive technological and cultural shifts just around the corner.

In these exercises, we usually get many excellent ideas which are natural extensions or combinations of current thinking. We get many incremental ideas. Sometimes, we really get some groundbreaking ideas, and for those, depending on if they can be currently implemented, we take them to a proof-of-concept (which is much more easily done these days due to the frameworks, systems, and tools available), then present them directly to small subsets of users. If they like the idea, we then move it to the next step.

Some of these ideas are interesting but not radical, and still, others are so radical and out-of-the-box, they are a tough sell to move forward on. Think of it this way – if it’s a good idea, then it will eventually be built by someone. Even if there is no current business model or infrastructure to support building the concept, that will change in the future, when new business models and technologies make it possible.

For example, imagine someone, several years ago, seeing their car sitting on the driveway and thinking “why am I paying a monthly fee for my car to just sit there 80% of the time”, and then thinking, “what if I could give people rides for a fee to help cover my costs, in my spare time”. Without smartphones, Google Maps, inexpensive data plans and GPS, Uber, Lyft, and its counterparts would never have been invented.  I would not be surprised if there were several people who came up with the exact same concept, just lacking the technology, the drive, or the funding to make it happen.

It’s much the same with other ideas. If they are physically possible, they will happen. They just need the right timing: for both the technology, the business model, and the culture to line up at the same time, and boom – you have a billion-dollar business.

How do you determine what will strike? That’s beside the point – because we don’t. The output of a typical ideation session could generate 20-1000’s of concepts, and you may have no idea which will become the big ideas. Or if there even is one in there. Once the idea is created and captured, however, this will trigger “implementation thinking” – now that it’s out there and formed, then someone, most likely the inventor, will drive to see that idea become reality. In this way, all ideas, unless they are fantasy, will happen, the trick is to guess when.

To guess when we need to be highly cognizant of the world. To actively seek signals which match up as precursors to this idea. Things that, when taken to a next logical (or even illogical step) will show us an embryonic version of the idea. Once we see that, it is the best time to start looking at building the capability to deliver that idea, or if that capability is available, then the ability to build those combinations and get to that idea.

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3 Reasons Why Moonshots Make You More Innovative

The Most Disruptive Innovation Can Start With Zero Demand

We hear a lot about profitability and ROI in my business – some of my clients innovation groups need to continually justify their existence day-in and day-out, since, for some reason, every innovation initiative always seems to need to be tied back to some level of profitability – it needs to cut costs or increase revenues out of the gate (or even before the gate) before we can even think about it.

The drum beats for ROI are loud and clear – we get it. No one likes to feel like that they are “wasting money”, which for some reason seems to be the excuse for innovation initiatives which don’t beget at least billion-dollar businesses. However, nothing spent fostering a culture of innovation and creating new products, services, and process improvements is wasted.

Where does innovation come from?

1) Most truly disruptive and incredibly successful innovative new products do not have an ROI, simply because they have zero demand when they launch. The product or service never existed before, and it may not even address a problem. Take, for example, the iPhone. The iPhone may have been the last truly independently generated product, but how can you calculate the ROI of a product which no one has ever seen before, and solves no specific problem? It’s a phone, a mini touchscreen tablet, a camera, and a computing platform all on one, and it sprang forth from Steve Jobs and his team’s imagination. No one knew that they needed one until they saw it, and everyone now needs one. The iPhone was developed secretly, and there were no users studies, there were no focus groups. There was no idea that it would fly and be the success that it was. Steve took a risk, and it paid off.

2) What if you are doing something so out there that you have no idea what will happen? Take something like Twitter – which has rapidly become THE premier communications tool for the US President, and many others. It has become the source for breaking news and crowdsourced reporting. No one had any idea of ROI when Odeo developed and launched Twitter. They thought it might be a cool adjunct for their podcasting service. They had little idea of who would use the service and for what, and its grown from nothing to be one of the powerhouses of social media. Today, you can almost not even imagine a world without Twitter, and its many, many social media variants.

3) No one is saying that the only innovation is innovation without an ROI – we don’t chase fairy dust either. All we are saying is that your innovation team should have a healthy mix of both kinds of initiatives – the solid, pragmatic incremental bread-and-butter stuff which visibly contributes directly to the bottom line, as well as a cool, edgy, interesting stuff which doesn’t have a well-defined market or ROI. There are tons of well established, multi-billion-dollar companies which were based on an untried, untested idea which just captured the hearts and minds of as yet unidentified market. Plus, it has never been easier to spin up and test a quick proof-of-concept with the tools and frameworks of today.

There’s no excuse – your lab needs a good mix of grounded stuff and moonshots to be as effective as they can be.

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How To Recognize The Future Even When Its Hard

Recognizing the future is tough but not impossible.

Many people say that predicting the future is hard. It is – there are few of us who can take the myriad signals and drivers of today and successfully map them to a tomorrow which may happen.

Although, personally I believe that everything that we have envisioned will happen (no matter how crazy it might seem right now), we just don’t know when. As I’ve said, being a futurist is like being a meteorologist, you are usually always right, just at the wrong time.

For example, I made several predictions as part of a futurist program at one of our major clients 10 years ago. About half of them have already happened (although they are not called the same thing), some are in progress, and others have yet to begin happening. For the half which is happening today, most are not named anywhere near the same, and while some map to the spirit of the original prediction, they may be implemented in a completely different way.

So how do you recognize the future? How can you look around, or come across these clues which will lead to major changes? How will you know which of these truly have long lasting staying power, and should be invested in, where others are just fads which will fade?

There are certain attributes which these signals have which help to indicate that they will be something which may become the future.

For example, who could have predicted that the e-commerce industry would be as big as it is today, compared to Amazon of 1999, which looked like a guy behind a makeshift desk at a single computer with an “” banner over his head (I’m sure that you’ve seen the picture)?

How To Review The Clues.

You must look at these clues with both your heart and your head.

Start with instinct – take the clue in front of you and think about it. Can you project it into the future? Can you see it evolving into something, new, different, important, powerful? What does your gut say?

Next, can this thing become a platform? Can it turn into something that others can use as a tool to do other things, beyond its original intent?

Next, think about what a future version of this signal will solve. Is there a current problem it’s addressing, or is it like most innovations, solving a problem which we did not know was there? Does it seem like a doorway to a whole new ecosystem of some still undefined other place?

Next, does it make you feel a little queasy? Is it unsettling or “creepy”? Does it sit on (or over) the edge of acceptability? Then it may be truly innovative, and therefore, part of the future.

Identifying clues to the future will now let you address them – if this future is going to happen (and it may) then what steps should you be taking to ensure your companies continued survival. Recognizing the future is not easy, but its also essential for you the survive and thrive.

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How To Pick Winning Ideas For Your Innovation Lab

Your innovation labs existential question: which idea is the billion-dollar idea?

The biggest problem I’ve seen companies struggle with, once they have launched a futurist innovation program, is not a low number of ideas. In fact, it’s usually the opposite.

After possible years of not providing any kind of systematized institutional method of capturing, collecting, reviewing, voting on, providing feedback on, and deciding on the fate of an idea, innovation labs are usually swamped with ideas once an effective program is launched.

Some ideas are slightly incremental, and may already be on the roadmap, unbeknownst to the inventor. Others are a bit too far out and may not be in a space that the company wishes to invest in, or are currently not possible, due to technological capability or the culture of the company not being ready for it.

Even after adding those filters, there are still usually a ton of really good ideas in that sweet spot – great ideas which could be implemented today and could grow your revenues or cut your costs by a substantial amount.

But which will have the most impact?

You can take a wild guess and use your gut instinct to figure out the winners, or get a team together on a regular basis of the brightest minds in the company and filter and prioritize, but in the end, you really don’t know which of these ideas are the winners.

What do you do? Do you come up with complicated schemes, using various metrics which may or may not reveal the most profitable ideas, do you throw it back out to the crowd again by allowing those with the top votes become your prioritized list, or do you randomly select a subset of ideas to focus your efforts on? In our view, none of these are the best course of action.

It may sound obvious, but you need to lift a page from the venture capital playbook and simply fund all of them.

VCs have huge floods of ideas coming into their businesses, which they do filter for all kinds of fit, type of business, knowledge of space etc. Even then, they still end up with many supposedly great ideas, but even they, with their in-depth knowledge of what a winner may be, still have very little idea which of their businesses will truly fly. They do the same – they take their pre-vetted short list and fund them all.

The key thing to remember here is that they don’t just fund all of them the same amount, they fund each of them just enough to take them to the next “proof step”, just enough to further test the idea.

These days, with the frameworks and infrastructure available to a typical lean startup, it takes very little time and effort to build a version of the business which is “testable” – enough to drop in front of real possible future users and get an idea of whether it will take off. These testable versions could be as simple as some wireframes whipped out over a few days by a UX designer, all the way to a working non-scalable simplistic prototype rapidly cranked out by a small team of designers and engineers.

Any of these variants are many times less expensive and resource intensive than they used to be. You can now quickly stand up a proof of concept within weeks or day, and quickly get something in front of real users for a thumb up or down.

With the costs of building these proofs of concept plummeting, there is no excuse – there is no reason you can’t at least afford a small amount of time and effort on each pre-vetted idea, to ensure its viability. Once its passed successfully into the testable stage and tested well, you can then move on to a more fully developed prototype.

Remember, your company is an innovation lab. Think of these as experiments. The more experiments you do, the better chance one will be a huge winner. Experiment early and often, kill the unsuccessful experiments as soon as they fail and nurture the successful into massively profitable new businesses, and possibly billion dollar ones.

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I Can’t Wait To Meet My Digital Twin!

While most people think of “digital twins” as the virtual version of an asset, processor or system that can be used to emulate a real-world object in a virtual world, I personally can’t wait until we have digital twins of ourselves.

Like the digital twin in that “Greta cookie” episode of Black Mirror (great series although a bit pessimistic about the future), you know the one, where they use a technology called a “cookie”, which is implanted in your head and creates a digital copy of you over time, learning about the way you act based on observing your actions over time. Of course, the episode gets dark after that, but I see no ethical downside to creating a digital version of yourself, designed to act in a similar way to you, and setting it to task performing all the dull stuff you’d rather not do, or aren’t very good at.

I’ve said before that we all spend a lot of our days doing mundane things that barely tax our amazing human brains. Would it not be great that something like a digital twin – which acts like our own personal virtual assistant – could take care of all of the boring stuff we have to do in our days, thus freeing us up to think the big thoughts?

Sure, maybe a full-on replica of ourselves might be too much to ask for right now, but what about creating a sub-set of ourselves? We could spin off various sub-selves to do all manner of things to save us time – creating these intelligent virtual versions of ourselves focused on a single task or two.

For example, let’s say that I’m terrible at remembering birthdays and anniversaries. would it be so terrible to create a sub-set personality bot of myself which remembers dates, and selects and sends proper greetings and gifts when required? Maybe you create the bot online and like the cookie or Nest – it self-learns my communication patterns – when and how I connect and communicate with people, how I remember things and send gifts etc. After a few days or weeks, it’s become a version of me, but only in regard to dates, messages, and gifts.

Once its more or less defined my actions, I then go in and “revise” it to be better than me. I tell it what dates to remember (and it never forgets as it’s not a fallible human) and what kind of messages to send, and what price range of gifts to get depending on the social strength of the connection. It then goes off and remembers dates, and after researching awesome messages and gifts that the recipient would appreciate, sends them or has them delivered. All under my name, of course.

My bot makes me a better human, friend, relative and spouse, and it frees me up to spend time with other things. Sure, maybe this example is a little creepy, (and probably better suited for pure introverts) but think of the 100s of mundane things you’d prefer to have someone else do for you.

Wouldn’t you prefer that a part of you – as a sub-set digital twin – be doing it? It’s not so different than delegating an autonomous vehicle to drive for you, or a human virtual assistant to book your meetings and do your internet research for you.

I, for one, welcome our new digital underlings. ?

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