Archive for the ‘New Thinking’ Category

The zero-sum game is a choice.

With a zero-sum game, if you eat a slice of pie, that’s one less for me; and if I eat one, that’s one less for you. A simple economic theory, but life isn’t simple like that. Here’s how life can go.

Get with expectation – I expect you to give, and you do.

Get without expectation – I don’t expect you to give, but you do. I’m indifferent.

Get with thanks – I don’t expect you to give, and when you do, I thank you graciously.

Get then give – I get from you, then a couple weeks later, I think of you and give back.

Get and give – I get from you, and I give back immediately. I choose what I give.

Give and get – I give to you, and you give back immediately. You chose what you give.

Give as get – I give to you so I can feel the joy of giving.

Give – I give because I give.

The zero-sum game is a choice. Which game will you chose to play?

Image credit – Mark Freeth

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

Diabolically Simple Prototypes

Ideas are all talk and no action.  Ideas are untested concepts that have yet to rise to the level of practicality.  You can’t sell an idea and you can’t barter with them. Ideas aren’t worth much.

A prototype is a physical manifestation of an idea. Where ideas are ethereal, prototypes are practical. Where ideas are fuzzy and subject to interpretation, prototypes are a sledge hammer right between the eyes.  There is no arguing with a prototype. It does what it does and that’s the end of that. You don’t have to like what a prototype stands for, but you can’t dismiss it. Where ideas aren’t worth a damn, prototypes are wholly worth every ounce of effort to create them.

If Camp A says it will work and Camp B says it won’t, a prototype will settle the disagreement pretty quickly.  It will work or it won’t.  And if it works, the idea behind it is valid.  And if it doesn’t, the idea may be valid, but a workable solution is yet-to-be discovered.  Either way, a prototype brings clarity.

Prototypes are not elegant.  Prototypes are ugly. The best ones do one thing – demonstrate the novel idea that underpins them. The good ones are simple, and the best ones are diabolically simple. It is difficult to make diabolically simple prototypes (DSPs), but it’s a skill that can be learned.  And it’s worth learning because DSPs come to life in record time. The approach with DSPs is to take the time up front to distill the concept down to its essence and then its all-hands-on-deck until it’s up and running in the lab.

But the real power of the DSP is that it drives rapid learning.  When a new idea comes, it’s only a partially formed.  The process of trying to make a DSP demands the holes are filled and blurry parts are brought into focus.  The DSP process demands a half-baked idea matures into fully-baked physical embodiment.  And it’s full-body learning.  Your hands learn, your eyes learn and your torso learns.

If you find yourself in a disagreement of ideas, stop talking and start making a prototype. If the DSP works, the disagreement is over.

Diabolically simple prototypes end arguments. But, more importantly, they radically increase the pace of learning.

Image credit – snippets101

Moving Away from Best Practices

rotten-appleIf the work is new, there is no best practice.

When you read the best books you’ll understand what worked in situations that are different than yours.  When you read the case studies you’ll understand how one company succeeded in a way that won’t work in yours.  The best practices in the literature worked in a different situation, in a different time and a under different cultural framework.  They won’t work best for you.

Just because a practice worked last time doesn’t mean it’s a best practice this time.  More strongly, just because it worked last time doesn’t mean it was best last time. There may have been a better way.

When a problem has high urgency it should be solved in a fast way, but if urgency is low, the problem should be solved in an efficient way. Which way is best? If the consequences of getting it wrong are severe, analyses and parallel solutions are skillful, but if it’s not terribly important to get it right, a lower cost way is better.  But is either the best way?

The best practices found in books are usually described a high level of abstraction using action words, block diagrams and arrows.  And when described at such a high level, they’re not actionable.  You may know all the major steps, but you won’t know how each step should be done.  And if the detail is provided, the context of your situation is different and the prescriptive steps don’t apply.

Instead of best practices, think effective practices.  Effective because the people doing the work can do it effectively.  Effective because it fits with the capability and capacity of the people doing the work.  Effective because it meshes with existing processes and projects.  Effective because it fits with your budget, timeline and risk profile.  Effective because it fits with your company values.

Because all our systems are people systems, there are no best practices.

image credit — johnwayne2006

When doing new work, you’ll be wrong.

OOPSWhen doing something from the first time you’re going to get it wrong.  There’s no shame in that because that’s how it goes with new work. But more strongly, if you don’t get it wrong you’re not trying hard enough.  And more strongly, embrace the inherent wrongness as a guiding principle.

Take Small Bites. With new work, a small scope is better than a large one.  But it’s exciting to do new work and there’s a desire to deliver as much novel usefulness as possible.  And, without realizing it, the excitement can lead to a project bloated with novelty.  With the best intentions, the project team is underwater with too much work and too little time.  With new work, it’s better to take one bite and swallow than three and choke.

Ratchet Thinking. With new work comes passion and energy.  And though the twins can be helpful and fun to have around, they’re not always well-behaved.  Passion can push a project forward but can also push it off a cliff. Energy creates pace and can quickly accelerate a project though the milestones, but energy can be careless and can just as easily accelerate a project in the wrong direction.  And that’s where ratchet thinking can help.

As an approach, the objective of ratchet thinking is to create small movements in the right direction without the possibility of back-sliding.  Solve a problem and click forward one notch; solve a second problem and click forward another notch.  But, with ratchet thinking, if the third problem isn’t solved, the project holds its ground at the second notch.  It takes a bit more time to choose the right problem and to solve it in a way that cannot unwind progress, but ultimately it’s faster.  Ratchet thinking takes the right small bite, chews, swallows.

Zero Cost of Change. New work is all about adding new functions, enhancing features and fixing what’s broken.  In other words, new work is all about change. And the faster change can happen, the faster the product/service/business model is ready for sale.  But as the cost of change increases the rate of changes slows.  So why not design the project to eliminate the cost of change?

To do that, design the hardware with a bit more capability and headroom so there’s some wiggle room to handle the changes that will come.  Use a modular approach for the software to minimize the interactions of software changes and make sure the software can be updated remotely without customer involvement.  And put in place a good revision control (and tracking) mechanism.

Doing new work is full of contradictions: move quickly, but take the time to think things through; take on as much as you can, but no more; be wrong, but in the right way; and sometimes slower is faster.

But doing new work you must.

image credit – leasqueaky

How To Learn Quickly

ProblemsWhen the work is new, it all comes down to learning.  And with learning it all comes down to three questions:

  • What do you want to learn?
  • What actions will take to learn what you want to learn?
  • How will you decide if you learned what you wanted to learn?

There are many definitions of learning.  To me, when your beliefs change, that’s learning.  If your hunch moves to a validated idea, that’s learning.  If your understanding of a system moves from “I don’t know” to “I know a little bit.”, that’s learning.  If you believed your customers buy your product for Feature A and now you know they really buy it because of Feature B, that’s learning.

What do you want to learn? The best place to start is to clearly define what you want to learn.  Sounds easy, but it’s not. Some of the leading thinking recommends you define a formal hypothesis.  I don’t like that word.  It’s scary, intimidating and distracting.  It’s just not helpful.  Instead, I suggest you define a Learning Objective.  To do that, complete this sentence:

I want to learn if the customer ____________________.

It may take several iterations/meetings to agree on a Learning Objective, but that’s time well spent.  It’s faster to take the time to define what you want to learn than to quickly learn something that doesn’t matter.  And define the Learning Objective as narrowly as possible.  The tighter the Learning Objective, the faster you can learn it.

What actions will you take to learn what you want to learn? In other words, for every Learning Objective create a Learning Plan.  Use the Who, What, When format.  Define Who will do What and When they’ll be done.  To increase the learning rate, define the minimum work to fulfill the narrowly-defined Learning Objective.  Just as you defined the Learning Objective narrowly, define the Learning Plan narrowly.  And to further speed the learning, set constraints like – no one can travel to see customers; no more than five customers can be contacted; and the Learning Plan must be completed in two days.  You’re not looking for large sample sizes and statistical significance; you’re looking to use your best judgement supported by the minimum learning to create reasonable certainty.

How will you decide if you learned what you wanted to learn? Learning requires decisions, decisions require judgement and judgement requires supporting information.  As part of the Learning Plan, define the Learning Information you’ll collect/capture/record to support your decisions.  Audio recordings are good and video is better.  For fast learning, you can record a phone call with a customer or ask them to share their webcam (and record the feed) as you talk with them.  Or you can ask them to shoot some video with their smart phone to provide the information needed to achieve you Learning Objective.

To analyze the data, it’s best to review the audio/video as a group and talk about what you see.  You should watch for body language as well as listen to the words.  Don’t expect complete agreement among your team and expect to create follow-on Learning Objectives and Learning Plans to answer the open questions.  Repeat the process until there’s enough agreement to move forward, but don’t wait for 100% consensus.

When you present your learning to company leadership, show the raw video data that supports your learning.  Practically, you’ll connect company leaders to customers and let the customers dispel long-held biases and challenge old thinking.

There’s nothing more powerful than a customer telling your company leaders how things really are.

Image credit – Thomas Hawk

Quantification of Novel, Useful and Successful

lets roll the diceIs it disruptive? Is it innovative? Two meaningless questions. Two questions to stop asking. More strongly, stop using the words “disruptive” and “innovative” altogether. Strike them from your vocabulary and replace them with novel, useful, and successful.

Argument is unskillful but analysis is skillful. And what’s needed for analysis is a framework and some good old-fashioned quantification. To create the supporting conditions for an analysis around novelty, usefulness, and successfulness, I’ve created quantifiable indices and a process to measure them. The process starts with a prototype of a new product, service or business model which is shown to potential customers (real people who do work in the space of interest.)

The Novelty Index. The Novelty Index measures the difference of a product, service or business model from the state-of-the-art. Travel to the potential customer and hand them the prototype. With mouth closed and eyes open, watch them use the product or interact with the service. Measure the time it takes them to recognize the novelty of the prototype and assign a value from 0 to 5. (Higher is better.)
5 – Novelty is recognized immediately after a single use (within 5 seconds.)
4 – Novelty is recognized after several uses (30 seconds.)
3 – Novelty is recognized once a pattern emerges (10-30 minutes.)
2 – Novelty is recognized the next day, once the custom has time to sleep on it (24 hours.)
1 – A formalized A-B test with statistical analysis is needed (1 week.)
0 – The customer says there’s no difference. Stop the project and try something else.

The Usefulness Index. The Usefulness Index measures the level of importance of the novelty. Once the customer recognizes the novelty, take the prototype away from them and evaluate their level of anger.
5 – The customer is irate and seething. They rip it from your arms and demand to place an order for 50 units.
4 – The customer is deeply angry and screams at you to give it back. Then they tell you they want to buy the prototype.
3 – With a smile of happiness, the customer asks to try the prototype again.
2 – The customer asks a polite question about the prototype to make you feel a bit better about their lack of interest.
1 – The customer is indifferent and says it’s time to get some lunch.
0 – Before you ask, the customer hands it back to you before you and is happy not to have it. Stop the project and try something else.

The Successfulness Index. The Successfulness Index measures the incremental profitability the novel product, service or business model will deliver to your company’s bottom line. After taking the prototype from the customer and measuring the Usefulness Index, with your prototype in hand, ask the customer how much they’d pay for the prototype in its current state.
5 – They’d pay 10 times your estimated cost.
4 – They’d pay two times your estimated cost.
3 – They’d pay 30% more than your estimated cost.
2 – They’d pay 10% more than your estimated cost.
1 – They’d pay you 5% more than your estimated cost.
0 – They don’t answer because they would never buy it.

The Commercialization Index. The Commercialization Index describes the overall significance of the novel product, service or business model and it’s calculated by multiplying the three indicies. The maximum value is 125 (5 x 5 x 5) and the minimum value is 0. Again, higher is better.

The descriptions of the various levels are only examples, and you can change them any way you want. And you can change the value ranges as you see fit. (0-5 is just one way to do it.) And you can substitute actual prototypes with sketches, storyboards or other surrogates.

Modify it as you wish, and make it your own. I hope you find it helpful.

Image credit – Nisarg Lakhmani

Creating a brand that lasts.

chillinOne of the best ways to improve your brand is to improve your products.  The most common way is to provide more goodness for less cost – think miles per gallon.  Usually it’s a straightforward battle between market leaders, where one claims quantifiable benefit over the other – Ours gets 40 mpg and theirs doesn’t.   And the numbers are tied to fully defined test protocols and testing agencies to bolster credibility.  Here’s the data.  Buy ours

But there’s a more powerful way to improve your brand, and that’s to map your products to reliability.  It’s far a more difficult game than the quantified head-to-head comparison of fuel economy and it’s a longer play, but done right, it’s a lasting play that is difficult to beat.  Run the thought experiment:  think about the brands you associate with reliability.  The brands that come to mind are strong, lasting brands, brands with staying power, brands whose products you want to buy, brands you don’t want to compete against.  When you buy their products you know what you’re going to get.  Your friends tell you stories about their products.

There’s a complete a complete tool set to create products that map to reliability, and they work.  But to work them, the commercialization team has to have the right mindset.  The team must have the patience to formally define how all the systems work and how they interact. (Sounds easy, but it can be painfully time consuming and the level of detail is excruciatingly extreme.)  And they have to be willing to work through the discomfort or developing a common understanding how things actually work. (Sounds like this shouldn’t be an issue, but it is – at the start, everyone has a different idea on how the system works.)  But more importantly, they’ve got to get over the natural tendency to blame the customer for using the product incorrectly and learn to design for unintended use.

The team has got to embrace the idea that the product must be designed for use in unpredictable ways in uncontrolled conditions. Where most teams want to narrow the inputs, this team designs for a wider range of inputs.  Where it’s natural to tighten the inputs, this team designs the product to handle a broader set of inputs.  Instead of assuming everything will work as intended, the team must assume things won’t work as intended (if at all) and redesign the product so it’s insensitive to things not going as planned.  It’s strange, but the team has to design for hypothetical situations and potential problems.  And more strangely, it’s not enough to design for potential problems the team knows about, they’ve got to design for potential problems they don’t know about. (That’s not a typo.  The team must design for failure modes it doesn’t know about.)

How does a team design for failure modes it doesn’t know about? They build a computer-based behavioral model of the system, right down to the nuts, bolts and washers, and they create inputs that represent the environment around the system.  They define what each element does and how it connects to the others in the system, capturing the governing physics and propagation paths of connections. Then they purposefully break the functions using various classes of failure types, run the analysis and review the potential causes.  Or, in the reverse direction, the team perturbs the system’s elements with inputs and, as the inputs ripple through the design, they find previously unknown undesirable (harmful) functions.

Purposefully breaking the functions in known ways creates previously unknown potential failure causes.  The physics-based characterization and the interconnection (interaction) of the system elements generate unpredicted potential failure causes that can be eliminated through design.  In that way, the software model helps find potential failures the team did not know about.  And, purposefully changing inputs to the system, again through the physics and interconnection of the elements, generates previously unknown harmful functions that can be designed out of the product.

If you care about the long-term staying power of your brand, you may want to take a look at TechScan, the software tool that makes all this possible.

Image credit — Chris Ford.

Selling New Products to New Customers in New Markets

yellow telephoneThere’s a special type of confusion that has blocked many good ideas from seeing the light of day.  The confusion happens early in the life of a new technology when it is up and running in the lab but not yet incorporated in a product.  Since the new technology provides a new flavor of customer goodness, it has the chance to create incremental sales for the company.  But, since there are no products in the market that provide the novel goodness, by definition there can be no sales from these products because they don’t yet exist.  And here’s the confusion.  Organizations equate “no sales” with “no market”.

There’s a lot of risk with launching new products with new value propositions to new customers.  You invest resources to create the new technologies and products, create the sales tools, train the sales teams, and roll it out well. And with all this hard work and investment, there’s a chance no one will buy it.  Launching a product that improves on an existing product with an existing market is far less risky – customers know what to expect and the company knows they’ll buy it.  The status quo when stable if all the players launch similar products, right up until it isn’t.  When an upstart enters the market with a product that offers new customer goodness (value proposition) the same-old-same-old market-customer dynamic is changed forever.

A market-busting product is usually launched by an outsider – either a big player moves into a new space or a startup launches its first product.  Both the new-to-market big boy and the startup have a far different risk profile than the market leader, not because their costs to develop and launch a new product are different, but because they have not market share.  For them, they have no market share to protect any new sales are incremental.  But for the established players, most of their resources are allocated to protecting their existing business and any resources diverted toward a new-to-market product is viewed as a loss of protective power and a risk to their market share and profitability.   And on top of that, the incumbent sees sales of the new product as a threat to sales of the existing products.  There’s a good chance that their some of their existing customers will prefer the new goodness and buy the new-to-market product instead of the tried-and-true product.  In that way, sales growth of their own new product is seen as an attack no their own market share.

Business leaders are smart.  Theoretically, they know when a new product is proposed, because it hasn’t launched yet, there can be no sales.  Yet, practically, because their prime directive to protect market share is so all-encompassing and important, their vision is colored by it and they confound “no sales” with “no market”.  To move forward, it’s helpful to talk about their growth objectives and time horizon.

With a short time horizon, the best use of resources is to build on what works – to launch a product that builds on the last one.  But when the discussion is moved further out in time, with a longer time horizon it’s a high risk decision to hold on tightly to what you have as the market changes around you.  Eventually, all recipes run out of gas like Henry Ford’s Model T.  And the best leading indicator of running low on fuel is when the same old recipe cannot deliver on medium-term growth objectives.  Short term growth is still there, but further out they are not.  Market forces are squeezing the juice out of your past success.

Ultimately, out of desperation, the used-to-be market leader will launch a new-to-market product.  But it’s not a good idea to do this work only when it’s the only option left.  Before they’re launched, new products that offer new value to customers will, by definition, have no sales.  Try to hold back the fear-based declaration that there is no market.  Instead, do the forward-looking marketing work to see if there is a market.  Assume there is a market and build some low cost learning prototypes and put them in front of customers.  These prototypes don’t yet have to be functional; they just have to communicate the idea behind the new value proposition.

Before there is a market, there is an idea that a market could exist.  And before that could-be market is served, there must be prototype-based verification that the market does in fact exist.  Define the new value proposition, build inexpensive prototypes and put them in front of customers.  Listen to their feedback, modify the prototypes and repeat.

Instead of arguing whether the market exists, spend all your energy proving that it does.

Image credit — lensletter

Doing New Work

first rideIf you know what to do, do it.  But if you always know what to do, do something else.  There’s no excitement in turning the crank every-day-all-day, and there’s no personal growth.  You may be getting glowing reviews now, but when your process is documented and becomes standard work, you’ll become one of the trivial many that follow your perfected recipe, and your brain will turn soggy.

If you want to do the same things more productively, do continuous improvement.  Look at the work and design out the waste.  I suggest you look for the waiting and eliminate it.  (One hint – look for people or parts queueing up and right in front of the pile you’ll find the waste maker.)  But if you always eliminate waste, do something else.  Break from the minimization mindset and create something new.  Maximize something. Blow up the best practice or have the courage to obsolete your best work.  In a sea of continuous improvement, be the lighthouse of doing new.

When you do something for the first time, you don’t know how to do it. It’s scary, but that’s just the feeling you want.  The cold feeling in your chest is a leading indicator of personal growth.  (If you don’t have a sinking feeling in your gut, see paragraph 1.) But organizations don’t make it easy to do something for the first time.  The best approach is to start small.  Try small experiments that don’t require approval from a budget standpoint and are safe to fail.  Run the experiments under the radar and learn in private.  Grow your confidence in yourself and your thinking.  After you have some success, show your results to people you trust.  Their input will help you grow.  And you’ll need every bit of that personal growth because to staff and run a project to bring your new concept to life you’ll need resources.  And for that you’ll need to dance with the most dangerous enemy of doing new things – the deadly ROI calculation.

The R is for return.  To calculate the return for the new concept you need to know: how many you’ll sell, how much you’ll sell them for, how much it will cost, and how well it will work.  All this must be known BEFORE resources can be allocated. But that’s not possible because the new thing has never been done before.  Even before talking about investment (I), the ROI calculation makes a train wreck of new ideas.  To calculate investment, you’ve got to know how many person-hours will be needed, the cost of the materials to make the prototypes and the lab resources needed for testing.  But that’s impossible to know because the work has never been done before.  The ROI is a meaningless calculation for new ideas and its misapplication has spelled death for more good ideas than anything else known to man.

Use the best practice and standardize the work. There’s immense pressure to repeat what was done last time because our companies prefer incremental growth that’s predictable over unreasonable growth that’s less certain.  And add to that the personal risk and emotional discomfort of doing new things and it’s a wonder how we do anything new at all.

But magically, new things do bubble up from the bottom. People do find the courage to try things that obsolete the business model and deliver new lines of customer goodness.  And some even manage survive the run through the ROI gauntlet.  With odds stacked against them, your best people push through their fears cut through the culture of predictability.

Imagine what they will do when you demand they do new work, give them the tools, time and training to do it, and strike the ROI calculation from our vocabulary.

Image credit – Tony Sergo

Serious Business

Looking serious in a hatIf you’re serious about your work, you’re too serious.  We’re all too bound up in this life-or-death, gotta-meet-the-deadline nonsense that does nothing but get in the way.

If you’re into following recipes, I guess it’s okay to be held accountable to measuring the ingredients accurately and mixing the cake batter with 110% effort.  When your business is serious about making more cakes than anyone else on the planet, it’s fine to take that seriously.  But if you’re into making recipes, serious doesn’t cut it.  Coming up with new recipes demands the freedom of putting together spices that have never been combined.  And if you’re too serious, you’ll never try that magical combination that no one else dared.

Serious is far different than fully committed and “all in.”  With fully committed, you bring everything you have, but you don’t limit yourself by being too serious.  When people are too serious they pucker up and do what they did last time.  With “all in” it’s just that – you put all your emotional chips on the line and you tell the dealer to “hit.”  If the cards turn in your favor you cash in in a big way.  If you bust, you go home, rejuvenate and come back in the morning with that same “all in” vigor you had yesterday and just as many chips.  When you’re too serious, you bet one chip at a time.  You don’t bet many chips, so you don’t lose many.  But you win fewer.

The opposite of serious is not reckless.  The opposite of serious is energetic, extravagant, encouraging, flexible, supportive and generous.  A culture of accountability is serious.  A culture of creativity is not.

I do not advocate behavior that is frivolous.  That’s bad business.  I do advocate behavior that is daring.  That’s good business.  Serious connotes measurable and quantifiable, and that’s why big business and best practices like serious.  But measurable and quantifiable aren’t things in themselves.  If they bring goodness with them, okay.  But there’s a strong undercurrent of measurable for measurable’s sake.  It’s like we’re not sure what to do, so we measure the heck out of everything.  Daring, on the other hand, requires trust is unmeasurable.  Never in the history of Six Sigma has there been a project done on daring and never has one of its control strategies relied on trust.  That’s because Six Sigma is serious business. Serious connotes stifling, limiting and non-trusting, and that’s just what we don’t need.

Let’s face it, Six Sigma and lean are out of gas.  So is tightening-the-screws management.  The low hanging fruit has been picked and Human Resources has outed all the mis-fits and malcontents.  There’s nothing left to cut and no outliers to eliminate.  It’s time to put serious back in its box.

I don’t know what they teach in MBA programs, but I hope it’s trust.  And I don’t know if there’s anything we can do with all our all-too-serious managers, but I hope we put them on a program to eliminate their strengths and build on their weaknesses.  And I hope we rehire the outliers we fired because they scared all the serious people with their energy, passion and heretical ideas.

When you’re doing the same thing every day, serious has a place.  When you’re trying to create the future, it doesn’t.  To create the future you’ve got to hire heretics and trust them.  Yes, it’s a scary proposition to try to create the future on the backs of rabble-rousers and rebels.  But it’s far scarier to try to create it with the leagues of all-too-serious managers that are running your business today.

Image credit — Alan

Mike Shipulski Mike Shipulski
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