Posts Tagged ‘Learning’

Four Questions to Choose Innovation Projects

It’s a challenge to prioritize and choose innovation projects. There are open questions on the technology, the product/service, the customer, the price and sales volume.  Other than that, things are pretty well defined.

But with all that, you’ve still go to choose.  Here are some questions that may help in your selection process

Is it big enough? The project will be long, expensive and difficult. And if the potential increase in sales is not big enough, the project is not worth starting. Think (Price – Cost) x Volume. Define a minimum viable increase in sales and bound it in time. For example, the minimum incremental sales is twenty five million dollars after five years in the market. If the project does not have the potential to meet those criteria, don’t do the project. The difficult question – How to estimate the incremental sales five years after launch? The difficult answer – Use your best judgement to estimate sales based on market size and review your assumptions and predictions with seasoned people you trust.

Why you? High growth markets/applications are attractive to everyone, including the big players and the well-funded start-ups. How does your company have an advantage over these tough competitors? What about your company sets you apart? Why will customers buy from you? If you don’t have good answers, don’t start the project. Instead, hold the work hostage and take the time to come up with good answers. If you come up with good answers, try to answer the next questions. If you don’t, choose another project.

How is it different? If the new technology can’t distinguish itself over existing alternatives, you don’t have a project worth starting.  So, how is your new offering (the one you’re thinking about creating) better than the ones that can be purchased today? What’s the new value to the customer? Or, in the lingo of the day, what is the Distinctive Value Proposition (DVP)? If there’s no DVP, there’s no project. If you’re not sure of the DVP, figure that out before investing in the project. If you have a DVP but aren’t sure it’s good enough, figure out how to test the DVP before bringing the DVP to life.

Is it possible? Usually, this is where everyone starts. But I’ve listed it last, and it seems backward. Would you rather spend a year making it work only to learn no one wants it, or would you rather spend a month to learn the market wants it then a year making it work? If you make it work and no one wants it, you’ve wasted a year. If, before you make it work, you learn no one wants it, you’ve spent a month learning the right thing and you haven’t spent a year working on the wrong thing. It feels unnatural to define the market need before making it work, but though it feels unnatural, it can block resources from working on the wrong projects.

There is no foolproof way to choose the best innovation projects, but these four questions go a long way. Create a one-page template with four sections to ask the questions and capture the answers. The sections without answers define the next work. Define the learning objectives and the learning activities and do the learning. Fill in the missing answers and you’re ready to compare one project to another.

Sort the projects large-to-small by Is it big enough? Then, rank the top three by Why you? and How is it different?  Then, for the highest ranked project, do the work to answer Is it possible?

If it’s possible, commercialize. If it’s not, re-sort the remaining projects by Is it big enough? Why you? and How is it different? and learn if It is possible.

Image credit – Ben Francis

Choosing What To Do

In business you’ve got to do two things: choose what to do and choose how to do it well.  I’m not sure which is more important, but I am sure there’s far more written on how to do things well and far less clarity around how to choose what to do.

Choosing what to do starts with understanding what’s being done now.  For technology, it’s defining the state-of-the-art. For the business model, it’s how the leading companies are interacting with customers and which functions they are outsourcing and which they are doing themselves. In neither case does what’s being done define your new recipe, but in both cases it’s the first step to figuring how you’ll differentiate over the competition.

Every observation of the state-of-the-art technologies and latest business models is a snapshot in time.  You know what’s happening at this instant, but you don’t know what things will look like in two years when you launch. And that’s not good enough. You’ve got to know the improvement trajectories; you’ve got to know if those trajectories will still hold true when you’ll launch your offering; and, if they’re out of gas, you’ve got to figure out the new improvement areas and their trajectories.

You’ve got to differentiate over the in-the-future competition who will constantly improve over the next two years, not the in-the-moment competition you see today.

For technology, first look at the competitions’ websites. For their latest product or service, figure out what they’re proud of, what they brag about, what line of goodness it offers.  For example, is it faster, smaller, lighter, more powerful or less expensive?  Then, look at the product it replaced and what it offered. If the old was faster than the one it replaced and the newest one was faster still, their next one will try to be faster.  But if the old one was faster than the one it replaced and the newest one is proud of something else, it’s likely they’ll try to give the next one more of that same something else.

And the rate of improvement gives another clue.  If the improvement is decreasing over time (old product to new product), it’s likely the next one will improve on a new line of goodness.  If it’s still accelerating, expect more of what they did last time.  Use the slope to estimate the magnitude of improvement two years from now.  That’s what you’ve got to be better than.

And with business models, make a Wardley Map.  On the map, place the elements of the business ecosystem (I hate that word) and connect the elements that interact with each other.  And now the tricky part.  Move to the right the mature elements (e.g., electrical power grid), move to the middle the immature elements (things that are clunky and you have to make yourself) and move to the middle the parts you can buy from others (products).  There’s a north-south element to the maps, but that’s for another time.

The business model is defined by which elements the company does itself, which it buys from others and which new ones they create in their labs.  So, make a model for each competitor.  You’ll be able to see their business model visually.

Now, which elements to work on?  Buy the ones you can buy (middle), improve the immature ones on the far left so they move toward the central region (product) and disrupt the lazy utilities (on the right) with some crazy technology development and create something new on the far left (get something running in the lab).

Choosing what to work on starts with Observation of what’s going on now. Then, that information is Oriented with analysis, synthesis and diverse perspective.  Then, using the best frameworks you know, a Decision is made.  And then, and only then, can you Act.

And there you have it.  The makings of an OODA loop-based methodology for choosing what to do.

 

For a great podcast on John Boyd, the father of the OODA loop, try this one.

And for the deepest dive on OODA (don’t start with this one) see Osinga – Science, Strategy and War.

Validate the Business Model Before Building It.

One of the best ways to learn is to make a prototype.  Prototypes come in many shapes and sizes, but their defining element is the learning objective behind them.  When you start with what you want to learn, the prototype is sure to satisfy the learning objective.  But start with the prototype, and no one is quite sure what you’ll learn.  When prototypes come before the learning objective, prototypes are inefficient and ineffective.

Before staffing a big project, prototypes can be used to determine viability of the project.  And done right, viability prototypes can make for fast and effective learning.  Usually, the team wants to build a functional prototype of the product or service, but that’s money poorly spent until the business model is validated.   There’s nothing worse than building expensive prototypes and staffing a project, only to find the business model doesn’t hold water and no one buys the new thing you’re selling.

There’s no reason a business model can’t be validated with a simple prototype. (Think one-page sales tool.)  And there’s no reason it can’t be done at the earliest stages.  More strongly, the detailed work should be held hostage until the business model is validated.  And when it’s validated, you can feel good about the pot of gold at the end of the rainbow.  And if it’s invalidated, you saved a lot of time, money and embarrassment.

The best way to validate the business model is with a set of one-page documents that define for the customer what you will sell them, how you’ll sell it, how you’ll service it, how you’ll train them and how you’ll support them over the life of your offering.  And, don’t forget to tell them how much it will cost.

The worst way to validate the business model is buy building it.  All the learning happens after all the money has been spent.

For the business model prototypes there’s only one learning objective: We want to learn if the customer will buy what we’re selling.  For the business model to be viable, the offering has to hang together within the context of installation, service, support, training and price.  And the one-page prototype must call out specifics of each element.  If you use generalities like “we provide good service” or “our training plans are the best”, you’re faking it.

Don’t let yourself off the hook.  Use prototypes to determine the viability of the business model before spending the money to build it.

Image credit – Heather Katsoulis

A Little Uninterrupted Work Goes a Long Way

If your day doesn’t start with a list of things you want to get done, there’s little chance you’ll get them done. What if you spent thirty minutes to define what you want to get done and then spent an hour getting them done?  In ninety minutes you’ll have made a significant dent in the most important work.  It doesn’t sound like a big deal, but it’s bigger than big.  Question: How often do you work for thirty minutes without interruptions?

Switching costs are high, but we don’t behave that way.  Once interrupted, what if it takes ten minutes to get back into the groove? What if it takes fifteen minutes?  What if you’re interrupted every ten or fifteen minutes?  Question: What if the minimum time block to do real thinking is thirty minutes of uninterrupted time?

Let’s assume for your average week you carve out sixty minutes of uninterrupted time each day to do meaningful work, then, doing as I propose – spending thirty minutes planning and sixty minutes doing something meaningful every day – increases your meaningful work by 50%.  Not bad.  And if for your average week you currently spend thirty contiguous minutes each day doing deep work, the proposed ninety-minute arrangement increases your meaningful work by 200%.  A big deal.  And if you only work for thirty minutes three out of five days, the ninety-minute arrangement increases your meaningful work by 400%.  A night and day difference.

Question: How many times per week do you spend thirty minutes of uninterrupted time working on the most important things?  How would things change if every day you spent thirty minutes planning and sixty minutes doing the most important work?

Great idea, but with today’s business culture there’s no way to block out ninety minutes of uninterrupted time.  To that I say, before going to work, plan for thirty minutes at home.  And set up a sixty-minute recurring meeting with yourself first thing every morning and do sixty minutes of uninterrupted work.  And if you can’t sit at your desk without being interrupted, hold the sixty-minute meeting with yourself in a location where you won’t be interrupted.  And, to make up for the thirty minutes you spent planning at home, leave thirty minutes early.

No way.  Can’t do it.  Won’t work.

It will work.  Here’s why.  Over the course of a month, you’ll have done at least 50% more real work than everyone else.  And, because your work time is uninterrupted, the quality of your work will be better than everyone else’s.  And, because you spend time planning, you will work on the most important things.  More deep work, higher quality working conditions, and regular planning.  You can’t beat that, even if it’s only sixty to ninety minutes per day.

The math works because in our normal working mode, we don’t spend much time working in an uninterrupted way.  Do the math for yourself.  Sum the number of minutes per week you spend working at least thirty minutes at time.  And whatever the number, figure out a way to increase the minutes by 50%.  A small number of minutes will make a big difference.

Image credit – NASA Goddard Space Flight Center

Innovation – Words vs. Actions

Innovation isn’t a thing in itself.  Companies need to meet their growth objectives and innovation is the word experts use to describe the practices and behaviors they think will maximize the likelihood of meeting those growth objectives. Innovation is a catchword phrase that has little to no meaning.  Don’t ask about innovation, ask how to meet your business objectives. Don’t ask about best practices, ask how has your company been successful and how to build on that success.  Don’t ask how the big companies have done it – you’re not them.  And, the behaviors of the successful companies are the same behaviors of the unsuccessful companies. The business books suffer from selection bias. You can’t copy another company’s innovation approach. You’re not them.  And your project is different and so is the context.

With innovation, the biggest waste of emotional energy is quest for (and arguments around) best practices.  Because innovation is done in domains of high ambiguity, there can be no best practices. Your project has no similarity with your previous projects or the tightest case studies in the literature. There may be good practice or emergent practice, but there can be no best practice. When there is no uncertainty and no ambiguity, a project can use best practices.  But, that’s not innovation.  If best practices are a strong tenant of your innovation program, run away.

The front end of the innovation process is all about choosing projects. If you want to be more innovative, choose to work on different projects. It’s that simple. But, make no mistake, the principle may be simple the practice is not. Though there’s no acid test for innovation, here are three rules to get you started. (And if you pass these three tests, you’re on your way.)

  • If you’ve done it before, it’s not innovation.
  • If you know how it will turn out, it’s not innovation.
  • If it doesn’t scare the hell out of you, it’s not innovation.

Once a project is selected, the next cataclysmic waste of time is the construction of a detailed project plan.  With a well-defined project, a well-defined project plan is a reasonable request.  But, for an innovation project with a high degree of ambiguity, a well-defined project plan is impossible.  If your innovation leader demands a detailed project plan, it’s usually because they are used running to well-defined continuous improvement projects.  If for your innovation projects you’re asked for a detailed project plan, run away.

With innovation projects, you can define step 1.  And step 2? It depends.  If step 1 works, modify step 2 based on the learning and try step 2.  And if step 1 doesn’t work, reformulate step 1 and try again. Repeat this process until the project is complete.  One step at a time until you’re done.

Innovation projects are unpredictable.  If your innovation projects require hard completion dates, run away.

Innovation projects are all about learning and they are best defined and managed using Learning Objectives (LOs). Instead of step 1 and step 2, think LO1 and LO2.  Though there’s little written about LOs, there’s not much to them.  Here’s the taxonomy of a LO: We want to learn if [enter what you want to learn].  Innovation projects are nothing more than a series of interconnected LOs.  LO2 may require the completion of LO1 or L1 and LO2 could be done in parallel, but that’s your call. Your project plan can be nothing more than a precedence diagram of the Learning Objectives.  There’s no need for a detailed Gantt chart. If you’re asked for a detailed Gantt chart, you guessed it – run away.

The Learning Objective defines what you learn, how you want to learn, who will do the learning and when they want to do it.  The best way to track LOs is with an Excel spreadsheet with one tab for each LO.  For each LO tab, there’s a table that defines the actions, who will do them, what they’ll measure and when they plan to get the actions done. Since the tasks are tightly defined, it’s possible to define reasonable dates.  But, since there can be a precedence to the LOs (LO2 depends on the successful completion of LO1), LO2 can be thought of a sequence of events that start when LO1 is completed.  In that way, an innovation project can be defined with a single LO spreadsheet that defines the LOs, the tasks to achieve the LOs, who will do the tasks, how success will be determined and when the work will be done. If you want to learn how to do innovation, learn how to use Learning Objectives.

There are more element of innovation to discuss, for example how to define customer segments, how to identify the most important problems, how to create creative solutions, how to estimate financial value of a project and how to go to market.  But, those are for another post.

Until then, why not choose a project that scares you, define a small set of Learning Objectives and get going?

Image credit – JD Hancock

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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