Posts Tagged ‘Competitiveness’

The Slow No

When there’s too much to do and too few to do it, the natural state of the system is fuller than full.  And in today’s world we run all our systems this way, including our people systems.

A funny thing happens when people’s plates are full – when a new task is added an existing one hits the floor.  This isn’t negligence, it’s not the result of a bad attitude and it’s not about being a team player.  This is an inherent property of full plates – they cannot support a new task without another sliding off.  And drinking glasses have this same interesting property – when full, adding more water just gets the floor wet.

But for some reason we think people are different.  We think we can add tasks without asking about free capacity and still expect the tasks to get done.  What’s even more strange – when our people tell us they cannot get the work done because they already have too much, we don’t behave like we believe them.  We say things like “Can you do more things in parallel?” and “Projects have natural slow phases, maybe you can do this new project during the slow times.”  Let’s be clear with each other – we’re all overloaded, there are no slow times.

For a long time now, we’ve told people we don’t want to hear no.  And now, they no longer tell us.  They still know they can’t get the work done, but they know not to use the word “no.”  And that’s why the Slow No was invented.

The Slow No is when we put a new project on the three year road map knowing full-well we’ll never get to it.  It’s not a no right now, it’s a no three years from now.  It’s elegant in its simplicity.  We’ll put it on the list; we’ll put it in the queue; we’ll put it on the road map.  The trick is to follow normal practices to avoid raising concerns or drawing attention.  The key to the Slow No is to use our existing planning mechanisms in perfectly acceptable ways.

There’s a big downside to the Slow No – it helps us think we’ve got things under control when we don’t.  We see a full hopper of ideas and think our future products will have sizzle.  We see a full road map and think we’re going to have a huge competitive advantage over our competitors. In both situations, we feel good and in both situations, we shouldn’t.  And that’s the problem. The Slow No helps us see things as we want them and blocks us from seeing them as they are.

The Slow No is bad for business, and we should do everything we can to get rid of it.  But, it’s engrained behavior and will be with us for the near future.  We need some tools to battle the dark art of the Slow No.

The Slow No gives too much value to projects that are on the list but inactive.  We’ve got to elevate the importance of active, fully-staffed projects and devalue all inactive projects.  Think – no partial credit.  If a project is active and fully-staffed, it gets full credit.  If it’s inactive (on a list, in the queue, or on the road map) it gets zero credit.  None.  As a project, it does not exist.

To see things as they are, make a list of the active, fully-staffed projects. Look at the list and feel what you feel, but these are the only projects that matter.  And for the road map, don’t bother with it.  Instead, think about how to finish the projects you have.  And when you finish one, start a new one.

The most difficult element of the approach is the valuation of active but partially-staffed projects.  To break the vice grip of the Slow No, think no partial credit. The project is either fully-staffed or it isn’t   And if it’s not fully-staffed, give the project zero value.  None.  I know this sounds outlandish, but the partially-staffed project is the slippery slope that gives the Slow No its power.

For every fully-staffed project on your list, define the next project you’ll start once the current one is finished.  Three active projects, three next projects.  That’s it.  If you feel the need to create a road map, go for it.  Then, for each active project, use the road map to choose the next projects.  Again, three active projects, three next projects.  And, once the next projects are selected, there’s no need to look at the road map until the next projects are almost complete.

The only projects that truly matter are the ones you are working on.

Image credit – DaPuglet

For top line growth, think no-to-yes.

Bottom line growth is good, but top line growth is better.  But if you want to grow the bottom line, ignore labor costs and reduce material costs. Labor cost is only 5-10% of product cost. Stop chasing it, and, instead, teach your design community to simplify the product so it uses fewer parts and design out the highest cost elements.

Where the factory creates bottom line growth, top line growth is generated in the market/customer domain. The best way I know to grow the top line is to broaden the applicability of your products and services. But, before you can broaden applicability, you’ve got to define applicability as it is.  Define the limits of what your product can do – how much it can lift, how fast it can run a calculation and where it can be used.  And for your service, define who can use it, where it can be used and what elements without customer involvement. And with the limits defined, you know where top line growth won’t come from.

Radical top line growth comes only when your products and services can be used in new applications.  Sure, you can train your sales force to sell more of what you already have, but that runs out of gas soon enough. But, real top line growth comes when your services serve new customers in new ways.  By definition, if you’re not trying to make your product work in new ways, you’re not going to achieve meaningful top line growth.  And by definition, if you’re not creating new functionality for your services, you might as well be focusing on bottom line growth.

If your product couldn’t do it and now it can, you’re doing it right. If your service couldn’t be used by people that speak Chinese and now it can, you’re on your way.  If your product couldn’t be used in applications without electricity and now it can, you’re on to something.  If your service couldn’t run on a smartphone and now it can, well, you get the idea.

For the acid test, think no-to-yes.

If your product can’t work in application A, you can’t sell it to people who do that work. If your service can’t be used by visually impaired people, you’re not delivering value to them and they won’t buy it. Turning can’t into can is a big deal. But you’ve got to define can’t before you can turn it into can. If you want top line growth, take the time to define the limits of applicability.

No-to-yes is powerful because it creates clarity. It’s easy to know when a project will create no-to-yes functionality and when it won’t.  And that makes it easy to stop projects that don’t deliver no-to-yes value and start projects that do.

No-to-yes is the key element of a compete-with-no-one approach to business.

image credit – liebeslakritze

How to Avoid a Cliff

Much like living organisms continually evolve to secure their place in the future, technological systems can be thought to display similar evolutionary behavior.  Viruses mutate so some of them can defeat the countermeasures of their host and live to fight another day. Technological systems, as an expression of a company’s desire to survive, evolve to defeat the competition and live to pay another dividend.

There are natural limits to evolutionary success in any single direction.  When one trait is improved it pushes on the natural limits imposed by the environment.  For example, a bacterium let loose in a friendly Petri dish will replicate until it eats all the food in the dish. Or, on a longer timescale, if the mass of a bird increases over generations when its food source is plentiful, the bird will get larger but will also get less agile. The predators who couldn’t catch the fast, little bird of old can easily catch and eat the sluggish heavyweight. In that way, there’s an edge condition created by the environmental Petri dishes and predators.  And it’s the same with technological systems.

Companies and their technological systems evolve within their competitive environment by scanning the fitness landscape and deciding where to try to improve.  The idea is to see preferential lines of improvement and create new technologies to take advantage of them.  Like their smaller biological counterparts, companies are minimum energy creatures and want to maximize reward (profit) with minimum effort (expense) and will continue to leverage successful lines of evolution until it senses diminishing returns.

The diminishing returns are a warning sign that the company is approaching an edge condition (a Petri dish of a finite size). In landscape lingo, there’s a cliff on the horizon. In technology lingo, the rate of improvement of the technology is slowing.  In either language, the edge is near and it’s time to evolve in a new direction because this current one is out of gas.

Like the bird whose mass increases over the generations when food is readily available, companies also get fat and slow when they successfully evolve in a single direction for too long.  And like the bird, they get eaten by a more agile competitor/predator. And just as the replication rate of the bacterium accelerates as the food in the Petri dish approaches zero, a company that doesn’t react to a slowing rate of technological improvement is sure to outlive its business model.

Biology and technology are similar in that they try new things (create variants of themselves) in order to live another day.  But there’s a big difference – where biology is blind (it doesn’t know what will work and what won’t), technology is sighted (people that create use their understanding to choose the variants they think will work best).  And another difference is that biological evolution can build only on viable variants where technology can use mental models as scaffolds to skip non-viable embodiments to cross a chasm.

There’s no need to fall off the cliff.  As a leading indicator, monitor the rate of improvement of your technology.  If its rate of improvement is still accelerating, it’s time to develop the next line of evolution. If its rate is declining, you waited too long. It’s time to double down on two new lines of evolution because you’re behind the curve. And remember, like with the population of bacteria in the Petri dish, sales will keep growing right up until the business model runs out of food or a competitor eats you.

Image credit — Amanda

Thoughts on Selling

Like most things, selling is about people.

The hard sell has nothing to do with selling.

Just when you think you’re having the least influence, you’re having the most.

When – ready, sell, listen – has run its course, try – ready, listen, sell.

Regardless of how politely it’s asked, “How many do you want?” isn’t selling.

If sales people are compensated by sales dollars, why do you think they’ll sell strategically?

The time horizon for selling defines the selling.

When people think you’re selling, they’re not thinking about buying.

Selling is more about ears than mouths.

Selling on price is a race to the bottom.

Wanting sales people to develop relationships is a great idea; why not make it worth their while?

Solving customer problems is selling.

Making it easy to buy makes it easy to sell.

You can’t sell much without trust.

Sell like you expect your first sale will happen a year from now.

Selling is a result.

I’m not sure the best way to sell; but listening can’t hurt.

Over-promising isn’t selling, unless you only want to sell once.

Helping customers grow is selling.

Delaying gratification is exceptionally difficult, but it’s wonderful way to sell.

Ground yourself in the customers’ work and the selling will take care of itself.

People buy from people and people sell to people.

Image credit – Kevin Dooley

Mapping the Future with Wardley Maps

How do you know when it’s time to reinvent your product, service or business model? If you add ten units of energy and you get less in return than last time, it’s time to work in new design space.  If improvement in customer goodness (e.g., miles per gallon in a car) has slowed or stopped, it’s time to seek a new fuel source.  If recent patent filings are trivial enhancements that can be measured only with a large sample sizes and statistical analysis, the party is over.

When there’s so many new things to work on, how do you choose the next project? When you’re lost, you look at a map. And when there is no map, you make one.  The first bit of work is defined by the holes in the first revision of your map.  And once the holes are filled and patched, the next work emerges from the map itself. And, in a self-similar way, the next work continually emerges from the previous work until the project finishes.

But with so much new territory, how do you choose the right new territory to map?  You don’t.  Before there’s a need to map new territory, you must map the current territory.  What you’ll learn is there are immature areas that, when made mature, will deliver new value to customers.  And you’ll also learn the mature areas that must be blown up and replaced with infant solutions that will ultimately create the next evolution of your business.  And as you run thought experiments on your map – projecting advancements on the various elements – the right new territory will emerge.  And here’s a hint – the right new solutions will be enabled by the newly matured elements of the map.

But how do you predict where the right new solutions will emerge?  I can’t tell you that.  You are the experts, not me.  All I can say is, make the maps and you’ll know.

And when I say maps, I mean Wardely Maps – here’s a short video (go to 4:13 for the juicy bits).

Image credit – Simon Wardley

Too Many Balls in the Air

In today’s world of continuous improvement, everything is seen as an opportunity for improvement. The good news is things are improving. But the bad news is without governance and good judgement, things can flip from “lots of opportunity for improvement” to “nothing is good enough.”  And when that happens people would rather hang their heads than stick out their necks.

When there’s an improvement goal is propose like this “We’ve got to improve the throughput of process A by 12% over the next three months.” a company that respects their people should want (and expect) responses like these:

As you know, the team is already working to improve processes C, D, and E and we’re behind on those improvement projects. Is improvement of process A more important than the other three? If so, which project do you want to stop so we can start work on process A? If not, can we wait until we finish one of the existing projects before we start a new one?  If not, why are you overloading us when we’re making it clear we already have too much work?

Are we missing customer ship dates on process A? If so, shouldn’t we move resources to process A right now to work off the backlog? If we have no extra resources, let’s authorize some overtime so we can catch up. If not, why is it okay to tolerate late shipments to our customers? Are you saying you want us to do more improvement work AND increase production without overtime?

That’s a pretty specific improvement goal. What are the top three root causes for reduced throughput? Well, if the first part of the improvement is to define the root causes, how do you know we can achieve 12% improvement in 3 months? We learned in our training that Deming said all targets are artificial. Are you trying to impose an artificial improvement target and set us up for failure?

Continuous improvement is infinitely good, but resources are finite.  Like it or not, continuous improvement work WILL be bound by the resources on hand. Might as well ask for continuous improvement work in a way that’s in line with the reality of the team’s capacity.

And one thing to remember for all projects – there’s no partial credit.  When you’re 80% done on ten projects, zero projects are done.  It’s infinitely better to be 100% done on a single project.

Image credit – Gabriel Rojas Hruska

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

Additive Manufacturing’s Holy Grail

The holy grail of Additive Manufacturing (AM) is high volume manufacturing.  And the reason is profit. Here’s the governing equation:

(Price – Cost) x Volume = Profit

The idea is to sell products for more than the cost to make them and sell a lot of them.  It’s an intoxicatingly simple proposition. And as long as you look only at the volume – the number of products sold per year – life is good. Just sell more and profits increase.  But for a couple reasons, it’s not that simple. First, volume is a result. Customers buy products only when those products deliver goodness at a reasonable price.  And second, volume delivers profit only when the cost is less than the price.  And there’s the rub with AM.

Here’s a rule – as volume increases, the cost of AM is increasingly higher than traditional manufacturing. This is doubly bad news for AM. Not only is AM more expensive, its profit disadvantage is particularly troubling at high volumes. Here’s another rule – if you’re looking to AM to reduce the cost of a part, look elsewhere. AM is not a bottom-feeder technology.

If you want to create profits with AM, use it to increase price. Use it to develop products that do more and sell for more.  The magic of AM is that it can create novel shapes that cannot be made with traditional technologies. And these novel shapes can create products with increased function that demand a higher price. For example, AM can create parts with internal features like serpentine cooling channels with fine-scale turbulators to remove more heat and enable smaller products or products that weigh less.  Lighter automobiles get better fuel mileage and customers will pay more. And parts that reduce automobile weight are more valuable.  And real estate under the hood is at a premium, and a smaller part creates room for other parts (more function) or frees up design space for new styling, both of which demand a higher price.

Now, back to cost.  There’s one exception to cost rule.  AM can reduce total product cost if it is used to eliminate high cost parts or consolidate multiple parts into a single AM part.  This is difficult to do, but it can be done.  But it takes some non-trivial cost analysis to make the case.  And, because the technology is relatively new, there’s some aversion to adopting AM.  An AM conversion can require a lot of testing and a significant cost reduction to take the risk and make the change.

To win with AM, think more function AND consolidation.  More (or new) function to support a higher price (and increase volume) and reduced cost to increase profit per part. Don’t do one or the other. Do both. That’s what GE did with its AM fuel nozzle in their new aircraft engines. They combined 20 parts into a single unit which weighed 25 percent less than a traditional nozzle and was more than five times as durable. And it reduced fuel consumption (more function, higher price).

AM is well-established in prototyping and becoming more established in low-volume manufacturing.  The holy grail for AM – high volume manufacturing – will become a broad reality as engineers learn how to design products to take advantage of AM’s unique ability to make previously un-makeable shapes and learn to design for radical part consolidation.

More function AND radical part consolidation.  Do both.

Image credit – Les Haines

To improve productivity, it’s time to set limits.

The race for productivity is on. And to take productivity to the next level, set limits.

To reduce the time wasted by email, limit the number of emails a person can send to ten emails per day. Also, eliminate the cc function. If you send a single email to ten people, you’re done for the day.  This will radically reduce the time spent writing emails and reduce distraction as fewer emails will arrive. But most importantly, it will help people figure out which information is most important to communicate and create a natural distillation of information. Lastly, limit the number of word in an email to 100. This will shorten the amount of time to read emails and further increase the density of communications.

If that doesn’t eliminate enough waste, limit the number of emails a person can read to ten emails per day.  Provide the subject of the email and the sender, but no preview.  Use the subject and sender to decide which emails to read.  And, yes, responding to an email counts against your daily sending quota of ten.  The result is further distillation of communication. People will take more time to decide which emails to read, but they’ll become more productive through use of their good judgement.

Limit the number of meetings people can attend to two per day and cap the maximum meeting length to 30 minutes. The attendees can use the meeting agenda, meeting deliverables and decisions made at the meeting to decide which meetings to attend. This will cause the meeting organizers to write tight, compelling agendas and make decisions at meetings. Wasteful meetings will go away and productivity will increase.

To reduce waiting, limit the number of projects a person can work on to a single project.  Set the limit to one. That will force people to chase the information they need instead of waiting. And if they can’t get what they need, they must wait. But they must wait conspicuously so it’s clear to leaders that their people don’t have what they need to get the project done. The conspicuous waiting will help the leaders recognize the problem and take action.  There’s a huge productivity gain by preventing people from working on things just to look busy.

Though harsh, these limits won’t break the system. But they will have a magical influence on productivity. I’m not sure ten is the right number of emails or two is the right number of meetings, but you get the idea – set limits.  And it’s certainly possible to code these limits into your email system and meeting planning system.

Not only will productivity improve, happiness will improve because people will waste less time and get to use their judgement.

Everyone knows the systems are broken. Why not give people the limits they need and make the productivity improvements they crave?

Image credit –  XoMEoX

The Additive Manufacturing Maturity Model

Additive Manufacturing (AM) is technology/product space with ever-increasing performance and an ever-increasing collection of products. There are many different physical principles used to add material and there are a range of part sizes that can be made ranging from micrometers to tens of meters.  And there is an ever-increasing collection of materials that can be deposited from water soluble plastics to exotic metals to specialty ceramics.

But AM tools and technologies don’t deliver value on their own.  In order to deliver value, companies must deploy AM to solve problems and implement solutions.  But where to start? What to do next? And how do you know when you’ve arrived?

To help with your AM journey, below a maturity model for AM.  There are eight categories, each with descriptions of increasing levels of maturity.  To start, baseline your company in the eight categories and then, once positioned, look to the higher levels of maturity for suggestions on how to move forward.

For a more refined calibration, a formal on-site assessment is available as well as a facilitated process to create and deploy an AM build-out plan.  For information on on-site assessment and AM deployment, send me a note at mike@shipulski.com.

Execution

  1. Specify AM machine – There a many types of AM machines. Learn to choose the right machine.
  2. Justify AM machine – Define the problem to be solved and the benefit of solving it.
  3. Budget for AM machine – Find a budget and create a line item.
  4. Pay for machine –  Choose the supplier and payment method – buy it, rent to own, credit card.
  5. Install machine – Choose location, provide necessary inputs and connectivity
  6. Create shapes/add material – Choose the right CAD system for the job, make the parts.
  7. Create support/service systems – Administer the job queue, change the consumables, maintenance.
  8. Security – Create a system for CAD files and part files to move securely throughout the organization.
  9. Standardize – Once the first machines are installed, converge on a small set of standard machines.
  10. Teach/Train – Create training material for running AM machine and creating shapes.

 

Solution

  1. Copy/Replace – Download a shape from the web and make a copy or replace a broken part.
  2. Adapt/Improve – Add a new feature or function, change color, improve performance.
  3. Create/Learn – Create something new, show your team, show your customers.
  4. Sell Products/Services – Sell high volume AM-produced products for a profit. (Stretch goal.)

 

Volume

  1. Make one part – Make one part and be done with it.
  2. Make five parts – Make a small number of parts and learn support material is a challenge.
  3. Make fifty parts – Make more than a handful of parts. Filament runs out, machines clog and jam.
  4. Make parts with a complete manufacturing system – This topic deserves a post all its own.

 

Complexity

  1. Make a single piece – Make one part.
  2. Make a multi-part assembly – Make multiple parts and fasten them together.
  3. Make a building block assembly – Make blocks that join to form an assembly larger than the build area.
  4. Consolidate – Redesign an assembly to consolidate multiple parts into fewer.
  5. Simplify – Redesign the consolidated assembly to eliminate features and simplify it.

 

Material

  1. Plastic – Low temperature plastic, multicolor plastics, high performance plastics.
  2. Metal – Low melting temperature with low conductivity, higher melting temps, higher conductivity
  3. Ceramics – common materials with standard binders, crazy materials with crazy binders.
  4. Hybrid – multiple types of plastics in a single part, multiple metals in one part, custom metal alloy.
  5. Incompatible materials – Think oil and water.

 

Scale

  1. 50 mm – Not too large and not too small. Fits the build area of medium-sized machine.
  2. 500 mm – Larger than the build area of medium-sized machine.
  3. 5 m – Requires a large machine or joining multiple parts in a building block way.
  4. 0.5 mm – Tiny parts, tiny machines, superior motion control and material control.

 

Organizational Breadth

  1. Individuals – Early adopters operate in isolation.
  2. Teams – Teams of early adopters gang together and spread the word.
  3. Functions – Functional groups band together to advance their trade.
  4. Supply Chain – Suppliers and customers work together to solve joint problems.
  5. Business Units – Whole business units spread AM throughout the body of their work.
  6. Company – Whole company adopts AM and deploys it broadly.

 

Strategic Importance

  1. Novelty – Early adopters think it’s cool and learn what AM can do.
  2. Point Solution – AM solves an important problem.
  3. Speed – AM speeds up the work.
  4. Profitability – AM improves profitability.
  5. Initiative – AM becomes an initiative and benefits are broadly multiplied.
  6. Competitive Advantage – AM generates growth and delivers on Vital Business Objectives (VBOs).

Image credit – Cheryl

Leadership isn’t binary, and that’s why judgement is important.

100% of the people won’t like your new idea, even if it’s a really good one like the airplane, mayonnaise or air conditioning.

I don’t know the right amount of conflict, but I know it’s not 0% or 100%.

If 100% is good, 110% isn’t better. Percentages don’t work that way.

100% alignment is not the best thing. Great things aren’t built on the back of consensus.

100% of the problems shouldn’t be solved.  Sometimes it’s best to let the problem blossom into something that cannot be dismissed, denied or avoided.

Fitting in can be good, but not 100% of the time. Sometimes the people in power need to hear the truth, even if you know they’ll choke on it.

If the system is in the way, work the rule. Follow it 100%, follow it to the letter, follow it until it’s absurd. But, keep in mind the system isn’t in the way 100% of the time.

Following the process 100% eliminates intellectual diversity. And, as Darwin said, that leads to extinction.  I think he was onto something.

Trying to fix 100% of the problems leads to dilution. Solve one at a time until you’re done.

The best tool isn’t best 100% of the time. Here’s a rule: If the work’s new, try a new tool. You can’t cut a board with a hammer.

I don’t know how frequently to make mistakes, but I know it’s not 0% or 100% of the time.

As a sport, leadership isn’t binary. That’s why we’re paid to use our good judgement.

Image credit – Joe Dyer

Mike Shipulski Mike Shipulski
Subscribe via Email

Enter your email address:

Delivered by FeedBurner

Archives