Innovation is about good judgement.

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

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

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

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

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

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

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

Image credit – Michael Coghlan

What’s an innovator to do?

Disruption, as a word, doesn’t tell us what to do or how to do it.  Disruption, as a word, it’s not helpful and should be struck from the innovation lexicon.  But without the word, what’s an innovator to do?

If you have a superpower, misuse it. Your brand’s special capability is well known in your industry, but not in others. Thrust your uniqueness into an unsuspecting industry and provide novel value in novel ways. Take it by storm. Contradict the established players. Build momentum quickly and quietly.  Create a step function improvement. Create new lines of customer goodness. Do things that haven’t been done. Turn no to yes.

Don’t adapt your special capability, use it as-is. Adaptation is good, but it’s better to flop the whole thing into the new space.  Don’t think graft, think transplant.  Adaptation brings only continuous improvement.  It’s better to serve up your secret sauce uncut and unfiltered because that brings discontinuous improvement.

Know the needs your product fulfills and meet those needs in another industry.  Some say it’s better to adapt your product to other industries, and to achieve a reasonable CAGR, adaptation is good.  But if you’re looking for an unreasonable CAGR, if you’re looking to stand things on their head, try to use your product as-is. When you can use your product as-is in another industry, you connect dots only you can connect and meet needs in ways only you can.  You bring non-intuitive solutions. You violate routines of accepted practice and your trajectory is not limited by the incumbents’ ruts of success. You’ll have a whole new space for yourself. No sharing required.

But how?

Simply and succinctly, define what your product does.  Then, make it generic and look to misapply the goodness in a different application. For example, manufacturers of large and expensive furniture wrap their products in huge plastic bags to keep the furniture dry and clean during shipping. Generically, the function becomes: use large plastic bags to temporarily protect large and expensive products from becoming wet.  Using that goodness in a new application, people who live in flood areas use the large furniture bags to temporarily protect their cars from water damage.  Just before the flood arrives, they drive their cars into large plastic bags and tie them off.  The bags keep their car dry when the water comes.  Same bag, same goodness, completely unrelated application.

And there’s another way.  Your product has a primary function that provides value to your customers. But, there is unrealized value in your product that your existing customers don’t value. For example, if your company has a proprietary process to paint products in a way that results in a high gloss finish, your customers buy your coating because it looks good. But, the coating may also create a hard layer and increase wear resistance that could be important in another application. Because your coating is environmentally friendly and your process is low-cost, new customers may want you to coat their parts so they can be used in a previously non-viable application.  There is unrealized value in your products that new customers will pay for.

To see the unrealized value, use the strength-as-a-weakness method.  Define two constraints: you must sell to new customers in a new industry and the primary goodness, why people buy your product, must be a weakness.  For example, if your product is fast, you’ve got to use unrealized value to sell a slow one. If it’s heavy, the new one must be light. If small, the new one must be large.  In that way, you are forced to rely on new lines of goodness and unrealized value to sell your product.

Don’t stop continuous improvement and product adaptation.  They’re valuable. But, start some discontinuous improvement, step function increases and purposeful misuse.  Keep selling to the same value to the same customers, but start selling to new customers with previously unrealized value that has been hiding quietly in your product for years.

Evolution is good, but exaptation is probably better.

Image credit – Sor Betto

How To Reduce Innovation Risk

The trouble with innovation is it’s risky.  Sure, the upside is nice (increased sales), but the downside (it doesn’t work) is distasteful. Everyone is looking for the magic pill to change the risk-reward ratio of innovation, but there is no pill.  Though there are some things you can do to tip the scale in your favor.

All problems are business problems.  Problem solving is the key to innovation, and all problems are business problems.  And as companies embrace the triple bottom line philosophy, where they strive to make progress in three areas – environmental, social and financial, there’s a clear framework to define business problems.

Start with a business objective.  It’s best to define a business problem in terms of a shortcoming in business results. And the holy grail of business objectives is the growth objective.  No one wants to be the obstacle, but, more importantly, everyone is happy to align their career with closing the gap in the growth objective.  In that way, if solving a problem is directly linked to achieving the growth objective, it will get solved.

Sell more.  The best way to achieve the growth objective is to sell more. Bottom line savings won’t get you there.  You need the sizzle of the top line. When solving a problem is linked to selling more, it will get solved.

Customers are the only people that buy things.  If you want to sell more, you’ve got to sell it to customers. And customers buy novel usefulness.  When solving a problem creates novel usefulness that customers like, the problem will get solved.  However, before trying to solve the problem, verify customers will buy what you’re selling.

No-To-Yes.  Small increases in efficiency and productivity don’t cause customers to radically change their buying habits.  For that your new product or service must do something new. In a No-To-Yes way, the old one couldn’t but the new one can. If solving the problem turns no to yes, it will get solved.

Would they buy it? Before solving, make sure customers will buy the useful novelty. (To know, clearly define the novelty in a hand sketch and ask them what they think.) If they say yes, see the next question.

Would it meet our growth objectives? Before solving, do the math. Does the solution result in incremental sales larger than the growth objective? If yes, see the next question.

Would we commercialize it? Before solving, map out the commercialization work. If there are no resources to commercialize, stop.  If the resources to commercialize would be freed up, solve it.

Defining is solving. Up until now, solving has been premature. And it’s still not time. Create a functional model of the existing product or service using blocks (nouns) and arrows (verbs). Then, to create the problem(s), add/modify/delete functions to enable the novel usefulness customers will buy.  There will be at least one problem – the system cannot perform the new function. Now it’s time to take a deep dive into the physics and bring the new function to life.  There will likely be other problems.  Existing functions may be blocked by the changes needed for the new function. Harmful actions may develop or some functions will be satisfied in an insufficient way.  The key is to understand the physics in the most complete way.  And solve one problem at a time.

Adaptation before creation. Most problems have been solved in another industry. Instead of reinventing the wheel, use TRIZ to find the solutions in other industries and adapt them to your product or service.  This is a powerful lever to reduce innovation risk.

There’s nothing worse than solving the wrong problem.  And you know it’s the wrong problem if the solution doesn’t: solve a business problem, achieve the growth objective, create more sales, provide No-To-Yes functionality customers will buy, and you won’t allocate the resources to commercialize.

And if the problem successfully runs the gauntlet and is worth solving, spend time to define it rigorously.  To understand the bedrock physics, create a functional of the system, add the new functionality and see what breaks.  Then use TRIZ to create a generic solution, search for the solution across other industries and adapt it.

The key to innovation is problem solving. But to reduce the risk, before solving, spend time and energy to make sure it’s the right problem to solve.

It’s far faster to solve the right problem slowly than to solve the wrong one quickly.

Image credit – Kate Ter Haar

Before you can make a million, you’ve got to make the first one.

With process improvement, the existing process is refined over time.  With innovation, the work is new. You can’t improve a process that does not yet exist.  Process creation, yes.  Process improvement, no.

Standard work, where the sequence of process steps has proven successful, is a pillar of the manufacturing mindset.  In manufacturing, if you’re not following standard work, you’re not doing it right.  But with innovation, when the work is done for the first time, there can be no standard work. In that way, if you’re following the standard work paradigm, you are not doing innovation.

In a well-established manufacturing process, problems are tightly scoped and constrained. There can be several ways to solve it and one of the ways is usually better than the others. Teams are asked to solve the problem three or four ways and explain the rationale for choosing one solution over the other. With innovation it’s different.  There may not be a solution, never mind three.  With innovation, it’s one-in-a-row solution.  And the real problem is to decide which problem to solve.  If you’re asked to use Fishbone diagrams to solve the problem three or four ways, you’re not doing innovation. Solve it one way, show a potential customer and decide what to do next.

With manufacturing and product development, it’s all about Gantt charts and hitting dates.  The tasks have a natural precedence and all of them have been done before.  There are branches in the plan, but behind them is clear if-then logic.  With innovation, the first task is well-defined.  And the second task – it depends on the outcome of the first.  And completion dates?  No way. If you can predict the completion date, you’re not doing innovation.  And if you’re asked for a fully built-out Gantt chart, you’re in trouble because that’s a misguided request.

Systems in manufacturing can be complicated, with lots of moving parts.  And the problems can be complicated. But given enough time, the experts can methodically figure it out. But with innovation, the systems can be complex, meaning they are not predictable.  Sometimes parts of the system interact strongly with other parts and sometimes they don’t interact at all. And it’s not that they do one or the other, it’s that they do both.  It’s like they have a will of their own, and, sometimes, they have a bad attitude. And if it’s a new system, even the basic rules of engagement are unknown, never mind the changing strength of the interactions.  And if the system is incomplete and you don’t know it, linear thinking of the experts can’t solve it.  If you’re using linear problem solving techniques, you’re not doing innovation.

Manufacturing is about making one thing a million times. Innovation is about choosing among the million possibilities and making one-in-a-row, and then, after the bugs are worked out, making the new thing a million times.  But one-in-a-row must come first.  If you can’t do it once, you can’t do it a million times, even with process improvement, standard work, Gantt charts and Fishbone diagrams.

Image credit jacinta lluch valero

See differently to solve differently.

There are many definitions for creativity and innovation, but none add meaningfully to how the work is done. Though it’s clear why the work is important – creativity and innovation underpin corporate prosperity and longevity – it’s especially helpful to know how to do it.

At the most basic level, creativity and innovation are about problem solving.  But it’s a special flavor of problem solving.  Creativity and innovation are about problems solving new problems in new ways.  The glamorous part is ‘solving in new ways’ and the important part is solving new problems.

With continuous improvement the same problems are solved over and over. Change this to eliminate waste, tweak that to reduce variation, adjust the same old thing to make it work a little better.  Sure, the problems change a bit, but they’re close cousins to the problems to the same old problems from last decade. With discontinuous improvement (which requires high levels of creativity and innovation) new problems are solved.  But how to tell if the problem is new?

Solving new problems starts with seeing problems differently.

Systems are large and complicated, and problems know how to hide in the nooks and crannies. In a Where’s Waldo way, the nugget of the problem buries itself in complication and misuses all the moving parts as distraction. Problems use complication as a cloaking mechanism so they are not seen as problems, but as symptoms.

Telescope to microscope. To see problems differently, zoom in.  Create a hand sketch of the problem at the microscopic level.  Start at the system level if you want, but zoom in until all you see is the problem.  Three rules: 1. Zoom in until there are only two elements on the page. 2. The two elements must touch. 3. The problem must reside between the two elements.

Noun-verb-noun. Think hammer hits nail and hammer hits thumb.  Hitting the nail is the reason people buy hammers and hitting the thumb is the problem.

A problem between two things. The hand sketch of the problem would show the face of the hammer head in contact with the surface of the thumb, and that’s all.  The problem is at the interface between the face of the hammer head and the surface of the thumb. It’s now clear where the problem must be solved. Not where the hand holds the shaft of the hammer, not at the claw, but where the face of the hammer smashes the thumb.

Before-during-after. The problem can be solved before the hammer smashes the thumb, while the hammer smashes the thumb, or after the thumb is smashed.  Which is the best way to solve it? It depends, that’s why it must be solved at the three times.

Advil and ice. Solving the problem after the fact is like repair or cleanup. The thumb has been smashed and repercussions are handled in the most expedient way.

Put something between. Solving the problem while it happens requires a blocking or protecting action. The hammer still hits the thumb, but the protective element takes the beating so the thumb doesn’t.

Hand in pocket. Solving the problem before it happens requires separation in time and space. Before the hammer can smash the thumb it is moved to a safe place – far away from where the hammer hits the nail.

Nail gun. If there’s no way for the thumb to get near the hammer mechanism, there is no problem.

Cordless drill. If there are no nails, there are no hammers and no problem.

Concrete walls. If there’s no need for wood, there’s no need for nails or a hammer. No hammer, no nails, no problem.

Discerning between symptoms and problems can help solve new problems. Seeing problems at the micro level can result in new solutions. Looking closely at problems to separate them time and space can help see problems differently.

Eliminating the tool responsible for the problem can get rid of the problem of a smashed thumb, but it creates another – how to provide the useful action of the driven nail.  But if you’ve been trying to protect thumbs for the last decade, you now have a chance to design a new way to fasten one piece of wood to another, create new walls that don’t use wood, or design structures that self-assemble.

Image credit – Rodger Evans

Put Yourself Out There

If you put yourself out there and it doesn’t go as you expect, don’t get down.  All you are responsible for is your effort and your intentions.  You’re not responsible for the outcome. Intentions don’t drive outcomes. In fact, be prepared for your work to bring out the opposite of your intentions.

If you put yourself out there and it goes poorly, don’t judge yourself negatively. Sometimes, things go that way. It’s not a problem, unless you make it one. So, don’t make it one. Just put yourself out there.

The clothes don’t get clean without an agitator. Hold onto that, and put yourself out there.

How do you know you’ve put yourself out there? The status quo is angry with you. The people in power want you to stop. The organization tries to scuttle your work. And the people that know the truth take you out to lunch.

If you put yourself out there and your message is met with 100% agreement, you didn’t put yourself out there. You may have stepped outside the lines, but you didn’t put your whole self on the line. You didn’t splash everyone with a full belly flop. There wasn’t enough sting and your belly isn’t red enough.

You won’t get it right, but put yourself out there anyway. You can’t predict the outcome, but take a run at the status quo. You don’t know how it will turn out, but that’s not a reason to hold back, it’s objective evidence it’s time to take a run at it.

Don’t put yourself out there because it’s the right thing to do, put yourself out there because you have an emotional connection.  Put yourself out there because it’s time to put yourself out there. Put yourself out there because you don’t know what else to do.

Be prepared to be misunderstood, but put yourself out there. Expect to be laughed at and talked about behind your back, but put yourself out there. And expect there will be one or two people who will have your back.  You know who they are.

No sense holding back. Get over the fear and put yourself out there.

The only one holding you back is you.

Image credit – Mark Bonica

Success – the Enemy of New Work

Success is the enemy of new work. Past success blocks new work out of fear it will jeopardize future success, and future success blocks new work out of fear future success will actually come to be.

Either way you look at it, success gets in the way of doing new work.

Success itself has no power to block new work.  To generate its power, past success creates the fear of loss in the people doing today’s work. And their fear causes them to block new work.  When we did A we got success, and now you are trying to do B.  B is not A, and may not bring success. I will resist B out of fear of losing the goodness of past success.

As a blocking agent, future success is more ethereal and more powerful because it prevents new work from starting. Future success causes our minds to project the goodness and glory the new work could bring and because our small sense of self doesn’t think we’re worthy, we never start. Where past success creates an enemy in the status quo, future success creates an enemy within ourselves.

But if we replace fear with learning, the game changes.

I’m not trying to displace our past success, I’m trying to learn if we can use it as springboard and back flip into the deep end of our future success. If it works, our learning will refine today’s success and inform tomorrow’s. If it doesn’t work, we’ll learn what doesn’t work and try something else. But not to worry, we’ll make small bets and create big learning. That way when we jump in the puddle, the splash will be small. And if the water’s cold, we’ll stop. But if it’s warm, we’ll jump into a bigger puddle. And maybe we’ll jump together. What do you think? Will you help me learn?

Yes, it’s scary to think about running this small experiment. Not because it won’t work, but because it might. If we learn this could work it would be a game-changer for the company and I’m afraid I’m not worthy of the work. Can you help me navigate this emotional roller coaster? Can you help me learn if this will work?  Can you review the results privately and help me learn what’s going on?  If we don’t learn how to do it, our competitors will. Can you help me start?

Success blocks, but it also pays the bills. And, hopefully it’s always part of the equation. But there are things we can do to take the edge of its blocking power. Acknowledge that new work is scary and focus on learning.  Learning isn’t threatening, and it moves things forward. Show results and ask for comments from people who created past success. Over time, they’ll become important advocates. And acknowledge to yourself that new work creates internal fear, and acknowledge the best way to push through fear is to learn.

Be afraid, make small bets and learn big.

Image credit – Andy Morffew

The Effective Expert

What if you’re asked to do something you know isn’t right? Not from an ethical perspective, but from a well-read, well-practiced, world-thought-leader perspective? What if you know it’s a waste of time? What if you know it sets a dangerous precedent for doing the wrong work for the right reason? What if the person asking is in a position of power? What if you know they think they’re asking for the right work?

Do you delay and make up false reasons for the lack of progress? Do you get angry because you expect people in power know what they’re doing? Does your anger cause you to double-down on delay?  Or does it cause you to take a step back and regroup? Or do you give them what they ask for, knowing it will make it clear they don’t know what they’re doing?

What if you asked them why they want what they want? What if when you really listened you heard their request for help? What if you recognized they weren’t comfortable confiding in you and that’s why they didn’t tell you they needed your help? What if you could see they did not know how to ask? What if you realized you could help? What if you realized you wanted to help?

What if you honored their request and took an approach that got the right work done? What if you used their words as the premise and used your knowledge and kindness to twist the work into what it should be? What if you realized they gave you a compliment when they asked you to do the work? Better still, what if you realized you were the only person who could help and you felt good about your realization?

As subject matter experts, it’s in our best interest to have an open mind and an open heart.  Sure, it’s important to hang onto our knowledge, but it’s also important to let go our strong desire to be right and do all we can to improve effectiveness.

If we are so confident in our knowledge, shouldn’t it be relatively easy to give others the benefit of the doubt and be respectful of the possibility there may be a deeper fundamental behind the request for the “wrong work”?

As subject matter experts, our toughest job is to realize we don’t always see the whole picture and things aren’t always as they seem. And to remain open, it’s helpful to remember we became experts by doing things wrong. And to prioritize effectiveness, until proven otherwise, it’s helpful to assume everyone has good intentions.

Image credit — Ingrid Taylar

Innovation and the Mythical Idealized Future State

When it’s time to innovate, the first task is usually to define the Idealized Future State (IFS).  The IFS is a word picture that captures what it looks like when the innovation work has succeeded beyond our wildest dreams. The IFS, so it goes, is directional so we can march toward the right mountain and inspirational so we can sustain our pace over the roughest territory.

For the IFS to be directional, it must be aimed at something – a destination.  But there’s a problem. In a sea of uncertainty, where the work has never been done before and where there are no existing products, services or customers, there are an infinite number of IFRs/destinations to guide our innovation work.  Open question – When the territory is unknown, how do we choose the right IFS?

For the IFS to be inspirational, it must create yearning for something better (the destination). And for the yearning to be real, we must believe the destination is right for us. Open question – How can we yearn for an IFS when we really can’t know it’s the right destination?

Maps aren’t the territory, but they are a collection of all possible destinations within the design space of the map.  If you have the right map, it contains your destination. And for a long time now, the old paper maps have helped people find their destinations. But on their own maps don’t tell us the direction to drive.  If you have a map of the US and you want to drive to Kansas, in which direction do you drive? It depends. If in California, drive east; if in Mississippi, drive north; if in New Hampshire, drive west; and in Minnesota, drive south. If Kansas is your idealized future state, the map alone won’t get your there.  The direction you drive depends on your location.

GPS has been a nice addition to maps. Enter the destination on the map, ask the satellites to position us globally and it’s clear which way to drive. (I drive west to reach Kansas.) But the magic of GPS isn’t in the electronic map, GPS is magic because it solves the location problem.

Before defining the idealized future state, define your location. It grounds the innovation work in the reality of what is, and people can rally around what is. And before setting the innovation direction with the IFS, define the next problems to solve and walk in their direction.

Image credit – Adrian Brady

Forecasting The Next Big Technology

When a hurricane is on the horizon, we are all glued to our TVs. We want to know where it track so we know we’ll be safe.  Will it track north and rumble over the top of us or will it track east and head out to sea?  This is not trivial. In one scenario we lose our house and in the other the crazy surfers get to ride huge waves.

The meteorologist shows us a time-lapse of the storm center hour-by-hour. It was one hundred miles off shore an hour ago, it’s fifty miles off shore now and it will hit the shoreline in an hour. Drawing a line from where it was, through its location in the moment, the meteorologist can extrapolate where it will be an hour from now.  In the short term, the storms trajectory will be unchanged and its momentum will help it maintain its pace.  It’s pretty clear to everyone where the storm will be in an hour. No magic here.

But the good meteorologists can forecast a hurricane’s path days in advance. In a phenomenological way, they use behavior models of past storms, assume this storm is like past storms, turn the crank and forecast its trajectory. And they’re right more times than not. And they’re right enough to determine who should evacuate and who should sit tight. This is borderline magic.

The best meteorologists know where hurricanes want go because they understand hurricanes. They know hurricanes want to run in straight lines, if not follow gentle curves. They know hurricanes get anxious when they hop from sea to land, and they know, given the choice, will skirt the coastline and head back home to the salt water.  Meteorologists know the rules hurricane’s live by and use that knowledge to tighten their forecast of the storm’s path.

Just as hurricanes have a desire to follow their hearts, technologies have a similar desire climb the evolutionary ladder. Just as hurricanes behave like their predecessors, technologies behave like their grandparents, aunts and uncles. And just as a meteorologist, using their knowledge of  historical patterns and an understanding of hurricane genetics can forecast the path of a hurricane, technologists can forecast the path of technologies using historical patterns and an understanding of what technologies want.

And like with hurricanes, the best way to forecast the path of a technology is to define where it was, draw a line through where it is and project its trajectory into the future.  Like hurricanes, technologies move in straight lines or gentle S-curves, so their next move is easy to forecast. If a technology has improved year-over-year, it will likely continue to improve. And if this year’s performance is the same as last year, it’s behavior will remain unchanged going forward.  That’s how it goes with technologies.

The best technologists are like horse whisperers in that they can hear the inner voice of technologies. They know when a technology is ready to grow from infant to adolescent and know when a technology is ready to retire. The best technologists can read the tea leaves of the patent landscape and, knowing the predisposition of technologies, can forecast the next evolution.  But just as some ranch owners don’t believe in horse whisperers, some company leaders don’t believe technology whisperers can forecast technologies.

But for believers and non-believers alike, it’s more effective to compare forecasting capabilities of technologists with the forecasting capabilities of meteorologists.  The notions of trajectory and momentum have clear physical interpretations for hurricanes and technologies, and historical models of storm trajectories map directly to evolutionary paths of technologies.

If you’re looking to forecast where the next big storm will make landfall, hire a great meteorologist. But if you’re looking to forecast when the next technology will rip the roof off your business model, hire a great technology whisperer.

Image credit – NASA

Maximize The Learning Ratio

As creatures of habit, we like to do what we did last time. Outcomes match expectations and things go as planned – no surprises, no delays, no problems. But as creatures swimming in an evolutionary soup, doing what we did last time leads to extinction. Customers’ expectations multiply and competitors mutate into a higher performing organism and eat us. There are two competing functions – do what we did last time to minimize energy and try new things to harden ourselves for the ever more competitive future.

You can’t reinvent yourself at every turn or your brain will run out of glucose and you’ll pass out. And you can’t always lounge on the couch or you’ll get out of shape and become a slow-moving snack for the new T-Rex on the block.  If the endpoints lead to our demise, the solution must be something like the middle way.

If you can get away with it, do what you did last time – minimum energy living is a good gig if you can get it. With little investment and lots of return, there’s enough for everyone.  Plenty to eat and some left over to put in stores for the winter. But plenty to eat and plenty of time to goof off may make for lazy (but happy) tribe members who may be of little use when it’s time to defend the business model against hostile species.

Live frugally to develop a surplus and spend some of it trying new things. Improved fitness is the best way to navigate the landscape, even the landscape still beyond the horizon.  More than physical fitness, improved mental fitness is the dominant trait that leads to survival. But doing new work is energy intensive and must be done skillfully.

The primary reason we try new things is to learn. In that way, the new things we try are a means to an end – improved mental fitness. But because doing new is expensive from an energy perspective, the learning ratio (new learning divided by the energy to learn) must be high. First, be clear about what you want to learn because learning the wrong thing costs more energy than resting on the couch. Second, maximize the learning of your experiments.

If you run an experiment where you are 100% sure of the outcome, your learning is zero. You already knew how it would go, so there was no need to run the experiment. The least costly experiment is the one you didn’t have to run, so don’t run experiments when you know how they’ll turn out.  If you run an experiment where you are 0% sure of the outcome, your learning is zero. These experiments are like buying a lottery ticket – you learn the number you chose didn’t win, but you learned nothing about how to choose next week’s number.  You’re down a dollar, but no smarter.

The learning ratio is maximized when energy is minimized (the simplest experiment is run) and probability the experimental results match your hypothesis (expectation) is 50%.  In that way, half of the experiments confirm your hypothesis and the other half tell you why your hypothesis was off track.

We can argue about the energy balance between leveraging best practices and creating new recipes. But, when you want to learn, there can be no argument – maximize the learning ratio.

Image credit – Craig Sunter

Mike Shipulski Mike Shipulski
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