When to Stop Dreaming?

When inventing pathfinding technology (something that has never been done) you have to ignore reality. Steve Jobs called it “reality distortion.”

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To create, you must refuse to accept current thinking that what you are doing can’t be done. You are told that there are laws of physics, principles of chemistry and material science that should inform you that your problem can’t be solved. You are told you don’t have enough time or money and to accept the reality of your business and technical constraints. The people that conform to this thinking rarely make anything new.

Of course if every inventor/invention team listened to this advice then nothing new would ever be invented. All invention is impossible, until it is done, then it was obvious. The only way to move forward is to ignore the risks and the obvious funding and time-line gaps you face. Ignoring reality is an art that is practiced by everyone that has created something new. It is at once terrifying and exhilarating, which is why people do it.

So if we consider a typical “invent/create and then monetize” development life cycle, about one-third of the time is spent breaking new ground in order to prove that the concept will work. The rest of the time (2/3’s) is spent trying to monetize it.

The successful people/organizations have the presence of mind to know where they are in this life cycle. They know how to transition from ignoring their constraints (time, money, skills, and what is unknown) to acknowledging reality. They know when to stop dreaming and to start converging.

The “thought transition point” is critical to grasp and see it in the context of the overall effort to take an idea and turn it into a product that can be made, so that you make money and your investors recover their capital and realize the expected return.

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The dreamer, on the other hand, goes on dreaming and ignoring reality. Living in the dreamworld is like a drug that is hard to kick. When you are dreaming you can pretend that the risks ahead aren’t real and you can make up stories to prove that they will never happen, so why worry… “We are almost there, one last spin, one last build, one more prototype and we are ‘done’ and we can turn it over to the next group of people to do the easy part and make lots of them.” And, “We need a little bit more money and then we will be done, trust me.”

The inventor that recognizes that critical transition point knows how to switch gears to a new way of thinking. No more dreaming, it is time for reality. These teams consider risk and face it head on.

During the “monetize-phase” all potential risks must be identified and assessed. The mitigation actions are integrated into the planning. They consider the possible number of learning cycles they will need and these get added into the plan. If it will take three cycles (do-it, try-it, fix-it) based on what is unknown and the degree of difficulty, then they assume 4-5 cycles to be safe. They can always remove a cycle if they get a breakthrough. Why pretend they can do someone faster than they have ever done it before.

Of course if there are dreamers on the team they can object to this kind of “pessimistic” planning, thinking that if they just all believe that one cycle is all that is needed then somehow it will materialize - and for all those potential risks, they will become self-fulling if we focus on them too much… Better to ignore them and charge ahead.

Reality-based planning during the “monetize-phase” is the key to being able to more accurately predict when a product can be produce in volume. When the gap is known and embraced, efforts can be made to narrow the product focus around what customers most value. But you can’t get a realistic prediction if it is based on “right the first time” thinking that clouds traditional “optimistic” top-down planning. Better predictions means that required financing can be secured for the full “real” duration, not a fake-duration that is based on everything going perfectly.

The more advanced the technology and more cutting-edge, the harder it is to predict. Pathfinding research (it really is research and not development for most of these teams) used to take between 5-10 years. This is when large corporations had expansive research laboratories and lots of time and resources. Once the fundamental research was done it was handed to a product development team to commercialize, since the basic research had already been proven. The next step was to turn it into a product over a 1-3 year time frame (after a research team had already spent 5 years doing the basing learning).

Today it is different. R&D is now one thing. R is done while doing D. No time is allocated for the R part. One client we worked with had an advanced technology that pushed the limits of physics and material science. It had only been demonstrated in a lab in a very controlled experiment. Lots of papers were written, but no one had really proven it would work and no one knew of how manufacture it if they could get it to work.

The competitor had already invested 5 years and $500M in their own research project and was close to demonstrating a prototype (they’re press release said). Our client had only been working a year and had made a limited investment. They started late. They were more of an “execution” company and thought that all that research money was not a good way to spend money. Their strategy was to be a fast follower. They had succeeded in gaining the most market share with this strategy.

But this new technology was a strategic category for them that they had to win. They must respond with their own version of the technology to maintain their lead. The first planning they showed us predicted a product in low volume in a year.

And why a year? Well, that was how much time they thought they had to announce and demo their technology in order to hold their key customers. If they demoed then they could hold on to them. The 12 months, to essentially prove the concept, was totally top-down driven from when they thought they had to do it and it had nothing to do with how long it was actually going to take to do it. We put that plan aside.

Using our planning process, ignoring constraints, we mapped out the incremental learning steps they needed to achieve and then built a more traditional product development plan (EVT, DVT, PVT) on the back end of the learning cycles. We asked the scientists and engineers to tell us how long it would really take, not how long they thought they had.

There was one critical failure point in the project, that at the time, no one on the team knew how to solve. They had about 10% of the information, yet had to predict the number of learning cycle they would need to solve it, we told them to error on the conservative side. They did and this blew out the schedule, way past the target.

The plan came out to about 5+ years, >4 years late (against the arbitrary target they were given). But when you consider that they had only been working on it for 1-year, knew very little, and only experienced failure conditions on the project (i.e. they could not get it to work), and that this type of new technology usually needed 2-5 years to create, then their 5-year plan was realistic if not optomistic.

Except it totally missed the expected market window. Reality forced a few things to happen; they had to narrow the scope of the project to one market segment (not >5), they had to reuse more existing technology than they had wanted to, they isolated and focused resources on the problem they couldn’t solve (dedicated team of the best experts in the field), and they went back to customers to really find out when the market expected it. It was not in 1-year as they learned.

Turned out they had some flexibility in the market window. Rather than being driven by competition, they let their customers tell them when they really needed it. All this combined with an aggressive weekly Refresh Planning Process caused the schedule to accelerate to 3-years. This was 2 more than they started with and 2 less than they initially thought it would be.

The point here is that they looked reality in the face, rather than pretend that it was not there.

We frequently get called into projects that missed the “thinking change” point and are will into their development cycle, and everyone is still dreaming. In fact they convince large groups of people to “drink the cool-aid” and they all pretend that the cliff they are approaching isn’t there or if it was, they could stop before it, or if they went over it they would all have parachutes and no one would get hurt. Anyone that disagreed was fired a long time ago, so group-think is the dominating thought process. We’ve seen spectacular and expensive failures when this happens.

The trick is to break the dream-cycle, even if it was missed the first time around. It is never too late if there is still money left to continue to fund the project and if you have customers that want and value what you are making, and are willing to assume some risk.

This is very hard to do when the environment is pushing back hard against the pragmatist that wants to consider potential risks before they happen and try to mitigate them. The pragmatist is viewed as negative and not a “team player” if he/she pushes too hard. You will never get a real forecast of completion until you factor in those risks, mitigation actions, and truly understand the gap between when it is expected and when a team can deliver it. The real number of potential learning cycles have to get into the plan.

When you know when something is more likely to be ready to monetize, you can do proper business and product portfolio planning. Can existing technology be extended to fulfill near term customer needs, can new approaches to how the product is packaged, marketed, or licensed be used to gain time, will customers settle for less now if they know they get more later, and so on. These are all possible solutions when reality is factored into the planning. The trick is to know when to transition from the dream-state to the real world.

This is especially required for pathfinding technology. The ratio of invention to reuse drives the schedule’s duration. The more the invention, then the more learning cycles you will have, and the more time it will take. Our example above, that created breakthrough technology in three years, beat the time it should have taken them.

They did it by making the 5-year plan which factored risk in, then used a creative thinking process (called Challenge) to change how they approach the problem and come up with new ideas. Reality is a sobering tool that can be used to drive innovative thinking. People only innovate when press up against the wall of failure.

Transitioning from the dream-phase to the reality-phase was how they did it. We are certain that if they had stuck to the 1-year top-down plan, they would have failed and in the end it would have taken them 5-years plus, with lots of dead bodies along the way. But to do this, you need to set up the right environment that permits reality to surface and then have the intestinal fortitude to deal with what comes out.