Archive for the ‘Technology’ Category

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

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

What if it works?

jumping-dogWhen money is tight, it’s still important to do new work, but it’s doubly important not to waste it.

There are a number of models to increase the probability of success of new work.  One well known approach is the VC model where multiple projects are run in parallel.  The trick is to start projects with the potential to deliver ultra-high returns.  The idea isn’t to minimize the investment but to place multiple bets.  When money’s tight, the VC model is not your friend.

Another method to increase the probability of success is to increase the learning rate.  The best known method is the Lean Startup method.  Come up with an idea, build a rough prototype, show it to potential customers and refine or pivot.  The process is repeated until a winning concept finds a previously unknown market segment and the money falls from the sky.   In a way, it’s like the VC Model, but it’s not a collection of projects run in parallel, it’s a sequential series of high return adventures punctuated by pivots. The Lean Startup is also quite good when money’s tight.  A shoe string budget fosters radical learning strategies and creates focus which are both good ideas when coffers are low.

And then there’s the VC/Lean Startup combo. A set of high potential projects run in parallel, each using Lean’s build, show, refine method to learn at light speed.  This is not the approach for empty pockets, but it’s a nice way to test game changing ideas quickly and efficiently.

Things are different when you try to do an innovation project within a successful company. Because the company is successful, all resources are highly utilized, if not triple-booked.  On the balance sheet there’s plenty of money, but practically the well is dry.  The organization is full up with ROI-based projects that will deliver marginal (but predictable) top line growth, and resources are tightly shackled to their projects.  Though there’s money in the bank, it feels like the account is over drawn.  And with this situation there’s a unique and expensive failure mode lurking in the shallows.

The front end of innovation work is resource light. New prototypes are created quickly and inexpensively and learning is fast and cheap.  Though the people doing the work are usually highly skilled and highly valuable, it doesn’t take a lot of people to create a functional prototype and test it with new customers.  And then, when the customers love it and it’s time to commercialize, there’s no one home. No one to do the work. And, unlike the relatively resource light front end work, commercialization work is resource heavy and expensive. The failure mode – the successful front end work is nothing but pure waste.  All the expense of creativity with none of innovation’s return.  And more painful, if the front end was successful the potential failure mode was destined to happen. There was no one to pick it up from the start.

The least expensive projects are the ones that never start. Before starting a project, ask “What if it works?”

image credit – jumping lab

Make it work.

square-pegIf you think something can’t be done, it won’t get done.  And if you think it may be possible, or is possible, it may get done.  Those are the rules.

If an expert says it will work, it will work.  If they say it won’t work, it might.  Experts can tell you will work, but can’t tell you what won’t.

If your boss tells you it won’t work, it might. Give it a try.  It will be fun if it works.

If you can’t make it work, make it worse and then do the opposite.

If you can’t explain the problem to your young kids, you don’t understand the situation and you won’t make it work.

If something didn’t work ten years ago, it may work now. Technology is better and we’re smarter.  More likely it would have worked ten years ago if they ran more than one crude experiment before they gave up.

If you can’t draw a one page sketch of the problem, it may never work.

If you can’t make it work, put it down for three days. Your brain may make it work while you’re sleeping.

If you don’t know the problem, you can’t make it work.  Be sure you’re trying to solve the right problem.

If your boss tells you it will work, it might.  If they tell you how to make it work, let them do it.

If none of your attempts have been fruitful and you’re out of tricks, purposely make one performance attribute worse to free up design space. That may work.

If you don’t know when the problem occurs, you don’t know much. Your solutions won’t work.

If you tried everything and nothing worked, ask someone for help whose specialty in an unrelated area.  They may have made it work in a different domain.

If you think everyone in the group understands the problem the same way, they don’t.  There’s no way they’ll agree on the best way to make it work. Don’t wait for consensus.

If you don’t try, that’s the only way to guarantee it won’t work.

Image credit – Simon Greig



Be done with the past.

graspThe past has past, never to come again.  But if you tell yourself old stories the past is still with you.  If you hold onto your past it colors what you see, shapes what you think and silently governs what you do.  Not skillful, not helpful.  Old stories are old because things have changed.  The old plays won’t work. The rules are different, the players are different, the situation is different.  And you are different, unless you hold onto the past.

As a tactic we hold onto the past because of aversion to what’s going on around us. Like an ostrich we bury our head in the sands of the past to protect ourselves from unpleasant weather buffeting us in the now.  But there’s no protection. Grasping tightly to the past does nothing more than stop us in our tracks.

If you grasp too tightly to tired technology it’s game over.  And it’s the same with your tired business model – grasp too tightly and get run through by an upstart.  But for someone who wants to make a meaningful difference, what are the two things that are sacred? The successful technology and successful business model.

It’s difficult for an organization to decide if the successful technology should be reused or replaced.  The easy decision is to reuse it.  New products come faster, fewer resources are needed because the hard engineering work has been done and the technical and execution risks are lower.  The difficult decision is to scrap the old and develop the new.  The smart decision is to do both.  Launch products with the old technology while working feverishly to obsolete it.  These days the half-life of technology is short.  It’s always the right time to develop new technology.

The business model is even more difficult to scrap. It cuts across every team and every function.  It’s how the company did its work.  It’s how the company made its name. It’s how the company made its money.  It’s how families paid their mortgages.  It’s grasping to the past success of the business model that makes it almost impossible to obsolete.

People grasp onto the past for protection and companies are nothing more than a loosely connected network of people systems.  And these people systems have a shared past and a good memory.  It’s no wonder why old technologies and business models stick around longer than they should.

To let go of the past people must see things as they are.  That’s a slow process that starts with a clear-eyed assessment today’s landscapes. Make maps of the worldwide competitive landscape, intellectual property, worldwide regulatory legislation, emergent technologies (search YouTube) and the sea of crazy business models enabled by the cloud.

The best time to start the landscape analyses was two years ago, but the next best time to start is right now.  Don’t wait.

Image credit – John Fife

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

If you don’t know the critical path, you don’t know very much.

ouija queenOnce you have a project to work on, it’s always a challenge to choose the first task.  And once finished with the first task, the next hardest thing is to figure out the next next task.

Two words to live by: Critical Path.

By definition, the next task to work on is the next task on the critical path.  How do you tell if the task is on the critical path?  When you are late by one day on a critical path task, the project, as a whole, will finish a day late.  If you are late by one day and the project won’t be delayed, the task is not on the critical path and you shouldn’t work on it.

Rule 1: If you can’t work the critical path, don’t work on anything.

Working on a non-critical path task is worse than working on nothing.  Working on a non-critical path task is like waiting with perspiration.  It’s worse than activity without progress.  Resources are consumed on unnecessary tasks and the resulting work creates extra constraints on future work, all in the name of leveraging the work you shouldn’t have done in the first place.

How to spot the critical path? If a similar project has been done before, ask the project manager what the critical path was for that project.  Then listen, because that’s the critical path.  If your project is similar to a previous project except with some incremental newness, the newness is on the critical path.

Rule 2: Newness, by definition, is on the critical path.

But as the level of newness increases, it’s more difficult for project managers to tell the critical path from work that should wait.  If you’re the right project manager, even for projects with significant newness, you are able to feel the critical path in your chest.  When you’re the right project manager, you can walk through the cubicles and your body is drawn to the critical path like a divining rod.   When you’re the right project manager and someone in another building is late on their critical path task, you somehow unknowingly end up getting a haircut at the same time and offering them the resources they need to get back on track.  When you’re the right project manager, the universe notifies you when the critical path has gone critical.

Rule 3: The only way to be the right project manager is to run a lot of projects and read a lot.  (I prefer historical fiction and biographies.)

Not all newness is created equal.  If the project won’t launch unless the newness is wrestled to the ground, that’s level 5 newness. Stop everything, clear the decks, and get after it until it succumbs to your diligence.  If the product won’t sell without the newness, that’s level 5 and you should behave accordingly.  If the newness causes the product to cost a bit more than expected, but the project will still sell like nobody’s business, that’s level 2.  Launch it and cost reduce it later.  If no one will notice if the newness doesn’t make it into the product, that’s level 0 newness. (Actually, it’s not newness at all, it’s unneeded complexity.)  Don’t put in the product and don’t bother telling anyone.

Rule 4: The newness you’re afraid of isn’t the newness you should be afraid of.

A good project plan starts with a good understanding of the newness.  Then, the right project work is defined to make sure the newness gets the attention it deserves.  The problem isn’t the newness you know, the problem is the unknown consequence of newness as it ripples through the commercialization engine. New product functionality gets engineering attention until it’s run to ground.  But what if the newness ripples into new materials that can’t be made or new assembly methods that don’t exist?  What if the new materials are banned substances?  What if your multi-million dollar test stations don’t have the capability to accommodate the new functionality?  What if the value proposition is new and your sales team doesn’t know how to sell it?  What if the newness requires a new distribution channel you don’t have? What if your service organization doesn’t have the ability to diagnose a failure of the new newness?

Rule 5: The only way to develop the capability to handle newness is to pair a soon-to-be great project manager with an already great project manager. 

It may sound like an inefficient way to solve the problem, but pairing the two project managers is a lot more efficient than letting a soon-to-be great project manager crash and burn.  After an inexperienced project manager runs a project into the ground, what’s the first thing you do?  You bring in a great project manager to get the project back on track and keep them in the saddle until the product launches.  Why not assume the wheels will fall off unless you put a pro alongside the high potential talent?

Rule 6: When your best project managers tell you they need resources, give them what they ask for.

If you want to deliver new value to new customs there’s no better way than to develop good project managers.  A good project manager instinctively knows the critical path; they know how the work is done; they know to unwind situations that needs to be unwound; they have the personal relationships to get things done when no one else can; because they are trusted, they can get people to bend (and sometimes break) the rules and feel good doing it; and they know what they need to successfully launch the product.

If you don’t know your critical path, you don’t know very much.  And if your project managers don’t know the critical path, you should stop what you’re doing, pull hard on the emergency break with both hands and don’t release it until you know they know.

Image credit – Patrick Emerson

Patents are supposed to improve profitability.

wrong AnswerEveryone likes patents, but few use them as a business tool.

Patents define rights assigned by governments to inventors (really, the companies they work for) where the assignee has the right to exclude others from practicing the concepts described in the patent claims.  And patent rights are limited to the countries that grant patents.  If you want to get patent rights in a country, you submit your request (application) and run their gauntlet.  Patents are a country-by-country business.

Patents are expensive.  Small companies struggle to justify the expense of filing a single patent and big companies struggle to justify the expense of their portfolio.  All companies want to reduce patent costs.

The patent process starts with invention.  Someone must go to the lab and invent something.  The invention is documented by the inventor (invention disclosure) and the invention is scored by a cross-functional team to decide if it’s worthy of filing.  If deemed worthy, a clearance search is done to see if it’s different from all other patents, all products offered for sale, and all the other literature in the public domain (research papers, publications).   Then, then the patent attorneys work their expensive magic to draft a patent application and file it with the government of choice. And when the rejection arrives, the attorneys do some research, address the examiner’s concerns and submit the paperwork.

Once granted, the fun begins.  The company must keep watch on the marketplace to make sure no one sells products that use the patented technology.  It’s a costly, never-ending battle.  If infringement is suspected, the attorneys exchange documents in a cease-and-desist jousting match.  If there’s no resolution, it’s time to go to court where prosecution work turns up the burn rate to eleven.

To reduce costs, companies try to reduce the price they pay to outside law firms that draft their patents.  It’s a race to the bottom where no one wins.  Outside firms get paid less money per patent and the client gets patents that aren’t as good as they could be.  It’s a best practice, but it’s not best.  Treating patent work as a cost center isn’t right.  Patents are a business tool that help companies make money.

Companies are in business to make money and they do that by selling products for more than the cost to make them.  They set clear business objectives for growth and define the market-customers to fuel that growth.  And the growth is powered by the magic engine of innovation.  Innovation creates products/services that are novel, useful and successful and patents protect them.  That’s what patents do best and that’s how companies should use them.

If you don’t have a lot of time and you want to understand a patent, read the claims.  If you have less time, read the independent claims.  Chris Brown, Ph.D.

Patents are all about claims.  The claims define how the invention is different (novel) from what’s tin the public domain (prior art).  And since innovation starts with different, patents fit nicely within the innovation framework. Instead of trying to reduce patent costs, companies should focus on better claims, because better claims means better patents.  Here are some thoughts on what makes for good claims.

Patent claims should capture the novelty of the invention, but sometimes the words are wrong and the claims don’t cover the invention.   And when that happens, the patent issues but it does not protect the invention – all the downside with none of the upside.  The best way to make sure the claims cover the invention is for the inventor to review the claims before the patent is filed.  This makes for a nice closed-loop process.

When a novel technology has the potential to provide useful benefit to a customer, engineers turn those technologies into prototypes and test them in the lab.  Since engineers are minimum energy creatures and make prototypes for only the technologies that matter, if the patent claims cover the prototype, those are good claims.

When the prototype is developed into a product that is sold in the market and the novel technology covered by the claims is what makes the product successful, those are good claims.

If you were to remove the patented technology from the product and your customer would notice it instantly and become incensed, those are the best claims.

Instead of reducing the cost of patents, create processes to make sure the right claims are created.  Instead of cutting corners, embed your patent attorneys in the technology development process to file patents on the most important, most viable technology.  Instead of handing off invention disclosures to an isolated patent team, get them involved in the corporate planning process so they understand the business objectives and operating plans.  Get your patent attorneys out in the field and let them talk to customers.  That way they’ll know how to spot customer value and write good claims around it.

Patents are an important business tool and should be used that way.  Patents should help your company make money.  But patents aren’t the right solution to all problems.  Patent work can be slow, expensive and uncertain.  A more powerful and more certain approach is a strong investment in understanding the market, ritualistic technology development, solid commercialization and a relentless pursuit of speed.  And the icing on the top – a slathering of good patent claims to protect the most important bits.

Image credit – Matthais Weinberger

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

Mike Shipulski Mike Shipulski
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