Posts Tagged ‘Lessons Learned’

Don’t trust your gut, run the test.

At first glance, it seems easy to run a good test, but nothing can be further from the truth.

The first step is to define the idea/concept you want to validate or invalidate.  The best way is to complete one of these two sentences: I want to learn that [type your idea here] is true. Or, I want to learn that [enter your idea here] is false.

Next, ask yourself this question: What information do I need to validate (or invalidate) [type your idea here]?  Write down the information you need.  In the engineering domain, this is straightforward: I need the temperature of this, the pressure of that, the force generated on part xyz or the time (in seconds) before the system catches fire.  But for people-related ideas, things aren’t so straightforward. Some things you may want to know are: how much will you pay for this new thing, how many will you buy, on a scale of 1 to 5 how much do you like it?

Now the tough part – how will you judge pass or fail?  What is the maximum acceptable temperature? What is the minimum pressure? What is the maximum force that can be tolerated? How many seconds must the system survive before catching fire?  And for people: What is the minimum price that can support a viable business? How many must they buy before the company can prosper? And if they like it at level 3, it’s a go. And here’s the most importance sentence of the entire post:

The decision criteria must be defined BEFORE running the test.

If you wait to define the go/no-go criteria until after you run the test and review the data, you’ll adjust the decision criteria so you make the decision you wanted to make before running the test. If you’re not going to define the decision criteria before running the test, don’t bother running the test and follow your gut.  Your decision will be a bad one, but at least you’ll save the time and money associated with the test.

And before running the test, define the test protocol.  Think recipe in a cookbook: a pinch of this, a quart of that, mix it together and bake at 350 degrees Fahrenheit for 40 minutes.  The best protocols are simple and clear and result in the same sequence of events regardless of who runs the test.  And make sure the measurement method is part of the protocol – use this thermocouple, use that pressure gauge, use the script to ask the questions about price and the number they’d buy.

And even with all this rigor, good judgement is still part of the equation.  But the judgment is limited to questions like: did we follow the protocol? Did the measurement system function properly? Do the initial assumptions still hold? Did anything change since we defined the learning objective and defined the test protocol?

To create formal learning objectives, to write well-defined test protocols and to formalize the decision criteria before running the test require rigor, discipline, time and money.  But, because the cost of making a bad decision is so high, the cost of running good tests is a bargain at twice the price.

Image credit – NASA Goddard Flight Center

A Barometer for Uncertainty

Novelty, or newness, can be a great way to assess the status of things.  The level of novelty is a barometer for the level of uncertainty and unpredictability.  If you haven’t done it before, it’s novel and you should expect the work to be uncertain and unpredictable. If you’ve done it before, it’s not novel and you should expect the work to go as it did last time. But like the barometer that measures a range of atmospheric pressures and gives an indication of the weather over the next hours, novelty ranges from high to low in small increments and so does the associated weather conditions.

Barometers have a standard scale that measures pressure.  When the summer air is clear and there are no clouds, the atmospheric pressure is high and on the rise and you should put on sun screen.  When it’s hurricane season and super-low system approaches, the drops to the floor and you should evacuate.  The nice thing about barometers is they are objective. On all continents, they can objectively measure the pressure and display it. No judgement, just read the scale. And regardless of the level of pressure and the number of times they measure it, the needle matches the pressure.  No Kentucky windage.  But novelty isn’t like that.

The only way to predict how things will go based on the level of novelty is to use judgement.  There is no universal scale for novelty that works on all projects and all continents.  Evaluating the level of novelty and predicting how the projects will go requires good judgement. And the only way to develop good judgment is to use bad judgment until it gets better.

All novelty isn’t created equal. And that’s the trouble.  Some novelty has a big impact on the weather and some doesn’t.  The trick is to know the difference.  And how to tell the difference? If when you make a change in one part of the system (add novelty) and the novelty causes a big change in the function or operation of the system, that novelty is important. The system is telling you to use a light hand on the tiller. If the novelty doesn’t make much difference in system performance, drive on. The trick is to test early and often – simple tests that give thumbs-up or thumbs-down results.  And if you try to run a test and you can’t get the test to run at all, there’s a hurricane is on the horizon.

When the work is new, you don’t really know which novelty will bite you. But there’s one rule: all novelty will bite you until proven otherwise.  Make a list of the novel elements of the and test them crudely and quickly.

Allocating resources as if people and planet mattered.

Business is about allocating resources to achieve business objectives.  And for that, the best place to start is to define the business objectives.

First – what is the timeframe of the business objectives? Well, there are three – short, medium and long.  Short is about making payroll, shipping this month’s orders and meeting this year’s sales objectives.  Long is about the existence of the company over the next decade and happiness of the people that do the work along the way. And medium – the toughest – is in-between.  It’s neither short nor long but bound by both.

Second – define business objectives within the three types: people, planet and profit.

People. Short term: pay them so they can eat, pay the mortgage and fund their retirement, provide healthcare, provide a safe workplace, give them work that fits their strengths and give them time to improve their community. Medium: pay them so they can provide for their family and fund their retirement, provide healthcare, provide a safer workplace, give them work that requires them to grow their strengths and give them time to become community leaders. Long: pay them so they can pay for their kids’ college and know they can safely retire, provide the safest workplace, let them choose their own work, and give them time to grow the next community leaders.  And make it easy.

Planet. Short term: teach Life Cycle Assessment,  Buddhist Economics and TRIZ and create business metrics for them to flourish. Medium: move from global sourcing to local sourcing, move to local production, move from business models based on non-renewable resources to renewable resources. Long: create new business models that are resource neutral. Longer: create business models that generate excess resources. Longest: teach others.

Profit. Short, medium and long – focus on people and planet and the profits will come. But also focus on creating new value for new customers.

For business objectives, here’s the trick on timeframe – always work short term, always work long term and prioritize medium term.

And for the three types of business objectives, focus on people, planet and creating new value for new customers.  Profits are a result.

Image credit – magnetismus

Make It Easy

When you push, you make it easy for people resist. When you break trail, you make it easy for them to follow.

Efficiency is overrated, especially when it interferes with effectiveness.  Make it easy for effectiveness to carry the day.

You can push people off a cliff or build them a bridge to the other side. Hint – the bridge makes it easy.

Even new work is easy when people have their own reasons for doing it.

Making things easier is not easy.

Don’t tell people what to do.  Make it easy for them to use their good judgement.

Set the wrong causes and conditions and creativity screeches to a halt.  Set the right ones and it flows easily. Creativity is a result.

Don’t demand that people pull harder, make it easier for them to pull in the same direction.

Activity is easy to demonstrate and progress isn’t.  Figure out how to make progress easier to demonstrate.

The only way to make things easier is to try to make them easier.

Image credit – Richard Hurd



How to wallow in the mud of uncertainty.

Creativity and innovation are dominated by uncertainty. And in the domain of uncertainty, not only are the solutions unknown, the problems are unknown. And yet, we still try to use the tried-and-true toolbox of certainty even after it’s abundantly clear those wrenches don’t fit.

When wallowing in the mud of uncertainty and company leaders ask, “When will you be done?”, the only real answer is a description of the next thing you’ll try to learn. “We will learn if Step 1 is possible.” And then the predicted response, “Well, when will you be done with that?”  The only valid response is, “It depends.”  Though truthful, this goes over like a lead balloon.  And the dialog continues – “Okay, then, what is Step 2?”  The unpalatable answer, “It depends. If Step 1 is successful, we’ll move onto Step 2, but if Step 1 is unsuccessful, we’ll step back and regroup.” This, too, though truthful, is unsatisfactory.

When doing creative work, there’s immense pressure to be done on time. But, that pressure is inappropriate. Yes, there can be pressure to learn quickly and effectively, but the expectation to be done within an arbitrary timeline is ludicrous.  Managers don’t know this, but when they demand a completion date for a task that has never been done before, the people doing the creative work know the manager doesn’t know what they’re doing.  They won’t tell the manager what they think, but they definitely think it. And when pushed to give a completion date, they’ll give one, knowing full well the predicted date is just as arbitrary as the manager’s desired timeline.

But learning objectives can create common ground. Starting with “We want to learn if…”, learning objectives define what the project team must learn. Though there’s no agreement on when things will be completed, everyone can agree on the learning objectives. And with clearly defined learning objectives and measurable definitions of success, the project can move forward with consensus. There is still consternation over the lack of hard deadlines for the learning objectives, but there is agreement on the sequence of events, tests protocols or analyses that will be carried out to learn what must be learned.

Two rules to live by: If you know when you’ll be done, you’re not doing innovation. And if no one is surprised by the solution, you’re not doing creative work.

Image credit – Michael Carian

Wisdom Within Dichotomy

To create future success, you’ve got to outlaw the very thing responsible for your past success.

Sometimes slower is faster and sometimes slower is slower. But it’s always a judgement call.

We bite the bullet and run expensive experiments because they’re valuable, but we neglect to run the least expensive thought experiments because they’re too disruptive.

There’s an infinite difference between the impossible and the almost impossible. And the people that can tell the difference are infinitely important.

If you know how to do it, so does your competition. Do something else.

We want differentiation, but we can’t let go of the sameness of success.

People that make serious progress take themselves lightly.

If you can predict when the project will finish, you can also predict customers won’t be excited when you do.

If you don’t have time to work on something, you can still work on it a little a time.

Perfection is good, but starting is better.

Sometimes it’s time to think and sometimes it’s time to do. And it’s easy to decide because doing starts with thinking.

When your plate is full and someone slops on a new project, there may be a new project on your plate but there’s also another project newly flopped on the floor.

New leaders demand activity and seasoned professionals make progress.

Sometimes it’s not ready, but most of the time it’s ready enough.

There’s no partial credit for almost done. That’s why pros don’t start a project until they finish one.

In this age of efficiency, effectiveness is far more important.

Image credit — Silentmind8

To improve innovation, use fewer words.

Everyone knows innovation is difficult, but there’s no best way to make it easier. And everyone knows there’s plenty of opportunities to make innovation more effective, but, again, there’s no best way.  Clearly, there are ways to improve the process, and new tools can help, but the right process improvements depend on the existing process and the specific project.  And it’s the same for tools – the next tool depends on the existing toolbox and the new work required by the project.  With regard to tools and processes, the right next steps are not universal.

But with all companies’ innovation processes, there is a common factor – the innovation process is run by people. Regardless of process maturity or completeness, people run the process.  And this fundamental cuts across language, geography and company culture.  And it cuts across products, services, and business models.  Like it or not, innovation is done by people.

At the highest level, innovation converts ideas into something customers value and delivers the value to them for a profit. At the front end, innovation is about ideas, in the middle, it’s about problems and at the back end, it’s about execution. At the front, people have ideas, define them, evaluate them and decide which ones to advance. In the middle, people define the problems and solve them. And at the back end, people define changes to existing business process and run the processes in a new way.

Tools are a specialized infrastructure that helps people run lower-level processes within the innovation framework. At the front, people have ideas about new tools, or how to use them in a new way, define the ideas, evaluate them, and decide which tools to advance. In the middle, people define problems with the tools and solve them. And at the back end, they run the new tools in new ways.

With innovation processes and tools, people choose the best ideas, people solve problems and people implement solutions.

In order to choose the best ideas, people must communicate the ideas to the decision makers in a clear, rich, nuanced way. The better the idea is communicated, the better the decision. But it’s difficult to communicate an idea, even when the idea is not new. For example, try to describe your business model using just words. And it’s more difficult when the idea is new. Try to describe a new (untested) business model using just your words. For me, words are not a good way to communicate new ideas.

Improved communication improves innovation. To improve communication of ideas, use fewer words. Draw a picture, create a cartoon, make a storyboard, or make a video.  Let the decision maker ask questions of your visuals and respond with another cartoon, a modified storyboard or a new sketch.  Repeat the process until the decision maker stops asking questions.  Because communication is improved, the quality of the decision is improved.

Improved problem solving improves innovation. To improve problem-solving, improve problem definition (the understanding of problem definition.) Create a block diagram of the problem – with elements of the system represented by blocks and labeled with nouns, and with actions and information flow represented by arrows labeled with verbs. Or create a sketch of the customer caught in the act of experiencing the problem.  Define the problem in time (when it happens) so it can be solved before, during or after. And in all cases, limit yourself to one page. Continue to modify the visuals until there’s a common definition of the problem (the words stop.)  When the problem is defined and communicated in this way, the problem solves itself. Problem-solving is seven-eighths problem definition.

Improved execution improves innovation. To improve execution, improve clarity of the definition of success.  And again, minimize the words. Draw a picture that defines success using charts or graphs and data. Create the axes and label them (don’t forget the units of measure). Include data from the baseline product (or process) and define the minimum performance criterion in red.  And add the sample size (number of tests.) Use one page for each definition of success and sequence them in order of importance. Start with the work that has never been done before.  And to go deeper, define the test protocol used to create the data.

For a new business model, the one-page picture could be a process diagram with new blocks for new customers or partners or new arrows for new information flows. There could be time requirements (response time) or throughput requirements (units per month). Or it could be a series of sketches of new deliverables provided by the business model, each with clearly defined criteria to judge success. When communicated clearly to the teams, definitions of success are beacons of light that guide the boats as the tide pulls them through the project or when uncharted rocks suddenly appear to starboard.

Innovation demands communication and communication demands mechanisms. In the domain of uncertainty, words are not the best communicators.  Create visual communication mechanisms that distill and converge on a common understanding.

A picture isn’t worth a thousand words, it gets rid of a thousand.

Image credit – Michael Coghlan

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

Companies don’t innovate, people do.

Big companies hold tightly to what they have until they feel threatened by upstarts, and not before. They mobilize only when they see their sales figures dip below the threshold of tolerability, and no sooner. And if they’re the market leaders, they delay their mobilization through rationalization.  The dip is due to general economic slowdown that is out of our control, the dip is due to temporary unrest from the power structure change in government, or the dip is due to some ethereal force we don’t yet fully understand. The strength of big companies is what they have, and they do what it takes only when what they have is threatened.  But once they’re threatened, watch out. But, the truth is, big companies don’t make change, people within big companies make change.

Start-ups want to change everything. They reject what they don’t have and threaten the status-quo at every turn.  And they’re always mobilized to grow sales.  Every new opportunity brings an opportunity to change the game. In a ready-fire-aim way, every phone call with a potential customer is an opportunity to dilute and defocus. Each new opportunity is an opportunity to create a mega business and each new customer segment is an opportunity to pivot. The strength of start-ups is what they don’t have. No loyalty to an existing business model, no shared history with other companies, and no NIH (not invented here). But, once they focus and decide to converge on an important market segment, watch out.  But, truth is, start-ups don’t make change, people within start-ups make change.

When you work in a big company, if your idea is any good the established business units will try to stomp it into oblivion because it threatens their status quo.  In that way, if your idea is dismissed out of hand or stomped on aggressively, you are likely onto something worth pursuing. If you’re told by the experts “It will never work.” that’s a sign from the gods that your idea has strong merit and deserves to be worked. And this is where it comes down to people. The person with the idea can either pack it in or push through the intellectual inertia of company success.  To be clear – it’s their choice. If they pack it in, the idea never sees the light of day. But if they decide, despite the fact they’re not given the tools, time, or training, to build a prototype and show it to company leadership, your company has a chance to reinvent itself. What causes and conditions have you put in place for your passionate innovators to choose to do the hard work of making a prototype?

When you work at a start-up the objective is to dismantle the status quo, and all ideas are good ideas. In that way, your idea will be praised and you’ll be urged to work on it. If you’re told by the experts “That could work.” it does not mean you should work on it. Since resources are precious, focus is mandatory. The person with the idea can either try to convert their idea into a prototype or respect the direction set by company leadership. To be clear – it’s their choice. If they work on their new idea they dilute the company’s best chance to grow. But if they decide, despite their excitement around their idea, to align with the direction set by the company, your startup has a chance to deliver on its aggressive promises. What causes and conditions have you put in place for your passionate innovators to choose to do the hard work of aligning with the agreed upon approach and direction?

When no one’s looking, do you want your people to try new ideas or focus on the ones you already have? When given a choice, do you want them to focus on existing priorities or blow them out of the water? And if you want to improve their ability to choose, what can you put in place to help them choose wisely?

To be clear, a formal set of decision criteria and a standardized decision-making process won’t cut it here. But that’s not to say decisions should be unregulated and unguided. The only thing that’s flexible and powerful enough to put things right is the good judgment of the middle managers who do the work.  “Middle managers” is not the best words to describe who I’m talking about. I’m talking about the people you call when the wheels fall off and you need them put back on in a hurry. You know who I’m talking about.  In start-ups or big companies, these people have a deep understanding of what the company is trying to achieve, they know how to do the work and know when to say “give it a try” and when to say “not now.” When people with ideas come to them for advice, it’s their calibrated judgement that makes the difference.

Calibrated judgement of respected leaders is not usually called out as a make-or-break element of innovation, growth and corporate longevity, but is just that.  But good judgement around new ideas are the key to all three.  And it comes down to a choice – do those ideas die in the trenches or are they kindly nurtured until they can stand on their own?

No getting around it, it’s a judgment call whether an idea is politely put on hold or accelerated aggressively. And no getting around it, those decisions make all the difference.

Image credit Mark Strozier

Working with uncertainty

Try – when you’re not sure what to do.

Listen – when you want to learn.

Build – when you want to put flesh on the bones of your idea.

Think – when you want to make progress.

Show a customer – when you want to know what your idea is really worth.

Put it down – when you want your subconscious to solve a problem.

Define – when you want to solve.

Satisfy needs – when you want to sell products

Persevere – when the status quo kicks you in the shins.

Exercise – when you want set the conditions for great work.

Wait – when you want to run out of time and money.

Fear failure – when you want to block yourself from new work.

Fear success – when you want to stop innovation in its tracks.

Self-worth – when you want to overcome fear.

Sleep – when you want to be on your game.

Chance collision – when you want something interesting to work on.

Write – when you want to know what you really think.

Make a hand sketch – when you want to communicate your idea.

Ask for help – when you want to succeed.

Image credit – Daniel Dionne

Rule 1: Allocate resources for effectiveness.

We live in a resource constrained world where there’s always more work than time.  Resources are always tighter than tight and tough choices must be made. The first choice is to figure out what change you want to make in the world. How do you want put a dent in the universe? What injustice do you want to put to rest? Which paradigm do you want to turn on its head?

In business and in life, the question is the same – How do you want to spend your time?

Before you can move in the right direction, you need a direction. At this stage, the best way to allocate your resources is to define the system as it is. What’s going on right now? What are the fundamentals? What are the incentives? Who has power?  Who benefits when things move left and who loses when things go right?  What are the main elements of the system? How do they interact? What information passes between them? You know you’ve arrived when you have a functional model of the system with all the elements, all the interactions and all the information flows.

With an understanding of how things are, how do you want to spend your time? Do you want to validate your functional model? If yes, allocate your resources to test your model. Run small experiments to validate (or invalidate) your worldview.  If you have sufficient confidence in your model, allocate your resources to define how things could be.  How do you want the fundamentals to change? What are the new incentives? Who do you want to have the power? And what are the new system elements, their new interactions and new information flows?

When working in the domain of ‘what could be’ the only thing to worry about is what’s next. What’s after the next step?  Not sure. How many resources will be required to reach the finish line? Don’t know. What do we do after the next step? It depends on how it goes with this step. For those that are used to working within an efficiency framework this phase is a challenge, as there can be no grand plan, no way to predict when more resources will be needed and no way to guarantee resources will work efficiently. For the ‘what could be’ phase, it’s better to use a framework of effectiveness.

In a one-foot-in-front-of-the-other way, the only thing that matters in the ‘what could be’ domain is effectively achieving the next learning objective. It’s not important that the learning is done most efficiently, it matters that the learning is done well and done quickly.  Efficiently learning the wrong thing is not effective. Running experiments efficiently without learning what you need to is not effective. And learning slowly but efficiently is not effective.

Allocate resources to learn what needs to be learned. Allocate resources to learn effectively, not efficiently. Allocate your best people and give them the time they need.  And don’t expect an efficient path. There will be unplanned lefts and rights. There will be U-turns. There will times when there’s lots of thinking and little activity, but at this stage activity isn’t progress, thinking is. It may look like a drunkard’s walk, but that’s how it goes with this work.

When the objective of the work isn’t to solve the problem but to come up with the right question, allocate resources in a way that prioritizes effectiveness over efficiency. When working in the domain of ‘what could be’ allocate resources on the learning objective at hand. Don’t worry too much about the follow-on learning objectives because you may never earn the right to take them on.

In the domain of uncertainty, the best way to allocate the resources is to learn what you need to learn and then figure out what to learn next.

Image credit – John Flannery

Mike Shipulski Mike Shipulski
Subscribe via Email

Enter your email address:

Delivered by FeedBurner