Archive for the ‘Manufacturing Competitiveness’ Category

The Most Important People in Your Company

When the fate of your company rests on a single project, who are the three people you’d tap to drag that pivotal project over the finish line? And to sharpen it further, ask yourself “Who do I want to lead the project that will save the company?” You now have a list of the three most important people in your company.  Or, if you answered the second question, you now have the name of the most important person in your company.

The most important person in your company is the person that drags the most important projects over the finish line.  Full stop.

When the project is on the line, the CEO doesn’t matter; the General Manager doesn’t matter; the Business Leader doesn’t matter.  The person that matters most is the Project Manager.  And the second and third most important people are the two people that the Project Manager relies on.

Don’t believe that? Well, take a bite of this. If the project fails, the product doesn’t sell. And if the product doesn’t sell, the revenue doesn’t come. And if the revenue doesn’t come, it’s game over. Regardless of how hard the CEO pulls, the product doesn’t launch, the revenue doesn’t come, and the company dies.  Regardless of how angry the GM gets, without a product launch, there’s no revenue, and it’s lights out.  And regardless of the Business Leader’s cajoling, the project doesn’t cross the finish line unless the Project Manager makes it happen.

The CEO can’t launch the product. The GM can’t launch the product. The Business Leader can’t launch the product.  Stop for a minute and let that sink in.  Now, go back to those three sentences and read them out loud. No, really, read them out loud.  I’ll wait.

When the wheels fall off a project, the CEO can’t put them back on. Only a special Project Manager can do that.

There are tools for project management, there are degrees in project management, and there are certifications for project management.  But all that is meaningless because project management is alchemy.

Degrees don’t matter. What matters is that you’ve taken over a poorly run project, turned it on its head, and dragged it across the line. What matters is you’ve run a project that was poorly defined, poorly staffed, and poorly funded and brought it home kicking and screaming. What matters is you’ve landed a project successfully when two of three engines were on fire. (Belly landings count.) What matters is that you vehemently dismiss the continuous improvement community on the grounds there can be no best practice for a project that creates something that’s new to the world. What matters is that you can feel the critical path in your chest. What matters is that you’ve sprinted toward the scariest projects and people followed you. And what matters most is they’ll follow you again.

Project Managers have won the hearts and minds of the project team.

The Project manager knows what the team needs and provides it before the team needs it. And when an unplanned need arises, like it always does, the project manager begs, borrows, and steals to secure what the team needs.  And when they can’t get what’s needed, they apologize to the team, re-plan the project, reset the completion date, and deliver the bad news to those that don’t want to hear it.

If the General Manager says the project will be done in three months and the Project Manager thinks otherwise, put your money on the Project Manager.

Project Managers aren’t at the top of the org chart, but we punch above our weight. We’ve earned the trust and respect of most everyone. We aren’t liked by everyone, but we’re trusted by all. And we’re not always understood, but everyone knows our intentions are good. And when we ask for help, people drop what they’re doing and pitch in. In fact, they line up to help. They line up because we’ve gone out of our way to help them over the last decade. And they line up to help because we’ve put it on the table.

Whether it’s IoT, Digital Strategy, Industry 4.0, top-line growth, recurring revenue, new business models, or happier customers, it’s all about the projects. None of this is possible without projects. And the keystone of successful projects?  You guessed it.  Project Managers.

Image credit – Bernard Spragg .NZ

The Five Hardships of Success

Everything has a half-life, but we don’t behave that way.  Especially when it comes to success.  The thinking goes – if it was successful last time, it will be successful next time.  So, do it again. And again.  It’s an efficient strategy – the heavy resources to bring it to life have already been spent. And it’s predictable – the same customers, the same value proposition, the same supply base, the same distribution channel, and the same technology. And it’s dangerous.

Success is successful right up until it isn’t. It will go away. But it will take time.  A successful product line won’t fall off the face of the earth overnight. It will deliver profits year-over-year and your company will come to expect them.  And your company will get hooked on the lifestyle enabled by those profits. And because of the addiction, when they start to drop off the company will do whatever it takes to convince itself all is well.  No need to change.  If anything, it’s time to double-down on the successful formula.

Here’s a rule: When your successful recipe no longer brings success, it’s not time to double-down.

Success’s decline will be slow, so you have time.  But creating a new recipe takes a long time, so it’s time to declare that the decline has already started. And it’s time to learn how to start work on the new recipe.

Hardship 1 – Allocate resources differently. The whole company wants to spend resources on the same old recipes, even when told not to.  It’s time to create a funding stream that’s independent of the normal yearly planning cycle.  Simply put, the people at the top have to reallocate a part of the operating budget to projects that will create the next successful platform.

Hardship 2 – Work differently. The company is used to polishing the old products and they don’t know how to create new ones. You need to hire someone who can partner with outside companies (likely startups), build internal teams with a healthy disrespect for previous success, create mechanisms to support those teams and teach them how to work in domains of high uncertainty.

Hardship 3 – See value differently. How do you provide value today? How will you provide value when you can’t do it that way? What is your business model? Are you sure that’s your business model? Which elements of your business model are immature? Are you sure? What is the next logical evolution of how you go about your business? Hire someone to help you answer those questions and create projects to bring the solutions to life.

Hardship 4 – Measure differently. When there’s no customer, no technology and no product, there’s no revenue.  You’ve got to learn how to measure the value of the work (and the progress) with something other than revenue.  Good luck with that.

Hardship 5 – Compensate differently. People that create something from nothing want different compensation than people that do continuous improvement. And you want to move quickly, violate the status quo, push through constraints and create whole new markets. Figure out the compensation schemes that give them what they want and helps them deliver what you want.

This work is hard, but it’s not impossible. But your company doesn’t have all the pieces to make it happen.  Don’t be afraid to look outside your company for help and partnership.

Image credit — Insider Monkey

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

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

Established companies must be startups, and vice versa.

oppositesFor established companies, when times are good, it’s not the right time to try something new – the resources are there but the motivation is not; and when times are tough it’s also the wrong time to try something new – the motivation is there but the breathing room is not.  There are an infinite number of scenarios, but for the established company it’s never a good time to try something new.

For startup companies, when times are good, it’s the right time to try something new – the resources are there and so is the motivation; and when times are tough it’s also the right time to try something new – the motivation is there and breathing room is a sign of weakness.  Again, the scenarios are infinite, but for the startup is always a good time to try something new.

But this is not a binary world. To create new markets and new customers, established companies must be a little bit startup, and to scale, startups must ultimately be a little bit established. This ambidextrous company is good on paper, but in the trenches it gets challenging. (Read Ralph Ohr for an expert treatment.)  The establishment regime never wants to do anything new and the startup regime always wants to.  There’s no middle ground – both factions judge each other through jaded lenses of ROI and learning rate and mutual misunderstanding carries the day.  Trouble is, all companies need both – established companies need new markets and startups need to scale. But it’s more complicated than that.

As a company matures the balance of power should move from startup to established.  But this tricky because the one thing power doesn’t like to do is move from one camp to another. This is the reason for the “perpetual startup” and this is why it’s difficult to scale.  As the established company gets long in the tooth the balance of power should move from the establishment to the startup.  But, again, power doesn’t like to change teams, and established companies squelch their fledgling startup work. But it’s more complicated, still.

The competition is ever-improving, the economy is ever-changing and the planet is ever-warming.  New technologies come on-line, and new business models test the waters. Some work, some don’t.  Huge companies buy startups just to snuff them out and established companies go away.  The environment is ever-changing on all fronts.  And the impermanence pushes and pulls on the pendulum of power dynamics.

All companies want predictability, but they’ll never have it.  All growth models are built on rearward-looking fundamentals and forward-looking conjecture.  Companies will always have the comfort of their invalid models, but will never the predictability they so desperately want.  Instead of predictability, companies would be better served by a strong sense of how it wants to go about its business and overpowering genetics of adaptability.

For a strong definition of how to go about business, a simple declaration does nicely. “We want to spend 80% of our resources on established-company work and 20% on startup-company work.” (Or 90-10, or 95-5.)  And each quarter, the company measures itself against its charter, and small changes are made to keep things on track.  Unless, of course, if the environment changes or the business model runs out of gas.  And then the company adapts.  It changes its approach and it’s projects to achieve its declared 80-20 charter, or, changes the charter altogether.

A strong charter and adaptability don’t seem like good partners, but they are.  The charter brings focus and adaptability brings the change necessary to survive in an every-changing environment.  It’s not easy, but it’s effective.  As long as you have the right leaders.

Image credit – Rick Abraham1

Purposeful Violation of the Prime Directive

Live Long and ProsperIn Star Trek, the Prime Directive is the over-arching principle for The United Federation of Planets.  The intent of the Prime Directive is to let a sentient species live in accordance with its normal cultural evolution.  And the rules are pretty simple – do whatever you want as long as you don’t violate the Prime Directive.   Even if Star Fleet personnel know the end is near for the sentient species, they can do nothing to save it from ruin.

But what does it mean to “live in accordance with the normal cultural evolution?” To me it means “preserve the status quo.”  In other words, the Prime Directive says – don’t do anything to challenge or change the status quo.

Though today’s business environment isn’t Star Trek and none of us work for Star Fleet, there is a Prime Directive of sorts.  Today’s Prime Directive deals not with sentient species and their cultures but with companies and their business models, and its intent is to let a company live in accordance with the normal evolution of its business model.   And the rules are pretty simple – do whatever you want as long as you don’t violate the Prime Directive.  Even if company leaders know the end is near for the business model, they can do nothing to save it from ruin.

Business models, and their decrepit value propositions propping them up, don’t evolve.  They stay just as they are.  From inside the company the business model and value proposition are the very things that provide sustenance (profitability).  They are known and they are safe – far safer than something new – and employees defend them as diligently as Captain Kirk defends his Prime Directive.  With regard to business models, “to live in accordance with its natural evolution” is to preserve the status quo until it goes belly up. Today’s Prime Directive is the same as Star Trek’s – don’t do anything to challenge or change the status quo.

Innovation brings to life things that are novel, useful, and successful.  And because novel is the same as different, innovation demands complete violation of today’s Prime Directive.  For innovators to be successful, they must blow up the very things the company holds dear – the declining business model and its long-in-the-tooth value proposition.

The best way to help innovators do their work is to provide them phasers so they can shoot those in the way of progress, but even the most progressive HR departments don’t yet sanction phasers, even when set to “stun”.  The next best way is to educate the company on why innovation is important.  Company leaders must clearly articulate that business models have a finite life expectancy (measured in years, not decades) and that it’s the company’s obligation to disrupt and displace it.them.

The Prime Directive has a valuable place in business because it preserves what works, but it needs to be amended for innovation.  And until an amendment is signed into law, company leaders must sanction purposeful violation of the Prime Directive and look the other way when they hear the shrill ring a phaser emanating  from the labs.

Image credit – svenwerk

To make the right decision, use the right data.

wheels fall offWhen it’s time for a tough decision, it’s time to use data.  The idea is the data removes biases and opinions so the decision is grounded in the fundamentals.  But using the right data the right way takes a lot of disciple and care.

The most straightforward decision is a decision between two things – an either or – and here’s how it goes.

The first step is to agree on the test protocols and measure systems used to create the data.  To eliminate biases, this is done before any testing.  The test protocols are the actual procedural steps to run the tests and are revision controlled documents.  The measurement systems are also fully defined.  This includes the make and model of the machine/hardware, full definition of the fixtures and supporting equipment, and a measurement protocol (the steps to do the measurements).

The next step is to create the charts and graphs used to present the data. (Again, this is done before any testing.) The simplest and best is the bar chart – with one bar for A and one bar for B.  But for all formats, the axes are labeled (including units), the test protocol is referenced (with its document number and revision letter), and the title is created.  The title defines the type of test, important shared elements of the tested configurations and important input conditions.   The title helps make sure the tested configurations are the same in the ways they should be.  And to be doubly sure they’re the same, once the graph is populated with the actual test data, a small image of the tested configurations can be added next to each bar.

The configurations under test change over time, and it’s important to maintain linkage between the test data and the tested configuration.  This can be accomplished with descriptive titles and formal revision numbers of the test configurations.  When you choose design concept A over concept B but unknowingly use data from the wrong revisions it’s still a data-driven decision, it’s just wrong one.

But the most important problem to guard against is a mismatch between the tested configuration and the configuration used to create the cost estimate.  To increase profit, test results want to increase and costs wants to decrease, and this natural pressure can create divergence between the tested and costed configurations. Test results predict how the configuration under test will perform in the field.  The cost estimate predicts how much the costed configuration will cost.  Though there’s strong desire to have the performance of one configuration and the cost of another, things don’t work that way.  When you launch you’ll get the performance of AND cost of the configuration you launched.  You might as well choose the configuration to launch using performance data and cost as a matched pair.

All this detail may feel like overkill, but it’s not because the consequences of getting it wrong can decimate profitability. Here’s why:

Profit = (price – cost) x volume.

Test results predict goodness, and goodness defines what the customer will pay (price) and how many they’ll buy (volume).  And cost is cost.  And when it comes to profit, if you make the right decision with the wrong data, the wheels fall off.

Image credit – alabaster crow photographic

Innovation’s Mantra – Sell New Products To New Customers

bull's headThere are three types of innovation: innovation that creates jobs, innovation that’s job neutral, and innovation that reduces jobs.

Innovation that reduces jobs is by far the most common. This innovation improves the efficiency of things that already exist – the mantra: do the same, but with less. No increase in sales, just fewer people employed.

Innovation that’s job neutral is less common. This innovation improves what you sell today so the customer will buy the new one instead of the old one. It’s a trade – instead of buying the old one they buy the new one. No increase in sales, same number of people employed.

Innovation that creates jobs is uncommon. This innovation radically changes what you sell today and moves it from expensive and complicated to affordable and accessible. Sell more, employ more.

Clay Christensen calls it Disruptive Innovation; Vijay Govindarajan calls it Reverse Innovation; and I call it Less-With-Far-Less.

The idea is the product that is sold to a relatively small customer base (due to its cost) is transformed into something new with far broader applicability (due to its hyper-low cost). Clay says to “look down” to see the new technologies that do less but have a super low cost structure which reduces the barrier to entry. And because more people can afford it, more people buy it. And these aren’t the folks that buy your existing products. They’re new customers.

Vijay says growth over the next decades will come from the developing world who today cannot afford the developed world’s product. But, when the price comes down (down by a factor of 10 then down by a factor of 100), you sell many more. And these folks, too, are new customers.

I say the design and marketing communities must get over their unnatural fascination with “more” thinking. To sell to new customers the best strategy is increase the number of people who can afford your product. And the best way to do that is to radically reduce the cost signature at the expense of features and function. If you can give ground a bit on the thing that makes your product successful, there is huge opportunity to reduce cost – think 80% less cost and 20% less function. Again, you sell new product to new customers.

Here’s a thought experiment to help put you in the right mental context: Create a plan to form a new business unit that cannot sell to your existing customers, must sell a product that does less (20%) and costs far less (80%), and must sell it in the developing world. Now, create a list of small projects to test new technologies with radically lower cost structures, likely from other industries. The constraint on the projects – you must be able to squeeze them into your existing workload and get them done with your existing budget and people. It doesn’t matter how long the projects take, but the investment must be below the radar.

The funny thing is, if you actually run a couple small projects (or even just one) to identify those new technologies, for short money you’ve started your journey to selling new products to new customers.

Can It Grow?

Retired SunflowerIf you’re working in a company you like, and you want it to be around in the future, you want to know if it will grow.  If you’re looking to move to a new company, you want to know if it has legs – you want to know if it will grow. If you own stock, you want to know if the company will grow, and it’s the same if you want to buy stock.  And it’s certainly the case if you want to buy the whole company – if it can grow, it’s worth more.

To grow, a company has to differentiate itself from its competitors.  In the past, continuous improvement (CI) was a differentiator, but today CI is the minimum expectation, the cost of doing business.  The differentiator for growth is discontinuous improvement (DI).

With DI, there’s an unhealthy fascination with idea generation.  While idea generation is important, companies aren’t short on ideas, they’re short on execution.  But the one DI differentiator is the flavor of the ideas.  To do DI a company needs ideas that are radically different than the ones they’re selling now.  If the ideas are slightly twisted variants of today’s products and business models, that’s a sure sign continuous improvement has infiltrated and polluted the growth engine. The gears of the DI engine are gummed up and there’s no way the company can sustain growth.  For objective evidence the company has the chops to generate the right ideas, look for a process that forces their thinking from the familiar, something like Jeffrey Baumgartner’s Anticonventional Thinking (ACT).

For DI-driven growth, the ability to execute is most important.  With execution, the first differentiator is how the company investigates radically new ideas.  There are three differentiators – a focus on speed, a “market first” approach, and the use of minimum viable tests (MVTs).  With new ideas, it’s all about how fast you can learn, so speed should come through loud and clear.  Without a market, the best idea is worthless, so look for “market first” thinking.  Idea evaluation starts with a hypothesis that a specific market exists (the market is clearly defined in the hypothesis) which is evaluated with a minimum viable test (MVT) to prove or disprove the market’s existence.  MVTs should error on the side of speed – small, localized testing.  The more familiar minimum viable product (MVP) is often an important part of the market evaluation work.  It’s all about learning about the market as fast as possible.

Now, with a validated market, the differentiator is how fast company can rally around the radically new idea and start the technology and product work.  The companies that can’t execute slot the new project at the end of their queue and get to it when they get to it.  The ones that can execute stop an existing (lower value) project and start the new project yesterday.  This stop-to-start behavior is a huge differentiator.

The company’s that can’t execute take a ready-fire-aim approach – they just start.  The companies that differentiate themselves use systems thinking to identify gaps in resources and capabilities and close them. They do the tough work of prioritizing one project over another and fully staff the important ones at the expense of the lesser projects.  Rather than starting three projects and finishing none, the companies that know how to do DI start one, finish one, and repeat.  They know with DI, there’s no partial credit for a project that’s half done.

All companies have growth plans, and at the highest level they all hang together, but some growth plans are better than others.  To judge the goodness of the growth plan takes a deeper look, a look into the work itself.  And once you know about the work, the real differentiator is whether the company has the chops to execute it.

Image credit – John Leach.

A Singular Pillar of Productivity

human pillar of productivityProductivity generates profit.  No argument.  But it has two sides – it can be achieved through maximization by increasing output with constant resources (machines and people) or through minimization with constant output and decreasing machines and people.  And the main pillars of both flavors are data, tools, and process.

Data is used to understand how things are going so they can be made more productive.  Process output is measured, yields are measured, and process control charts are hung on the wall like priceless art.  Output goes up and costs go down.  And the two buckets of cost – people and machines – are poured out the door.  But data on its own doesn’t know how to improve anything.  The real heroes are the people that look at the data and use good judgment to make good decisions.

You can pull the people out of the process to reduce costs, but you can’t pull the judgment out productivity improvement work.  And here’s the difference – processes are made transactional and repetitive so people can be removed, and because judgment can’t be made into a transactional process, people are needed to do productivity improvement work.  People and their behavior – judgment – are the keys.

Tools are productivity’s golden children.  Better tools speed up the work so more can get done.  In the upswing, output increases to get more work done; in the downturn, people leave to reduce cost.  Tools can increase the quality (maximize) or reduce the caliber of the people needed to do the work (minimize).  But the tools aren’t the panacea, the real panacea are the people that run them.

Any analytical tool worth its salt requires judgment by the person that runs it.  And here’s where manufacturing’s productivity-through-process analogy is pushed where it doesn’t belong.  Companies break down the process to run the tools into 6000 to 7000 simple steps, stuff them into a 500 page color-coded binder, provide a week of training and declare standard work has saved the day because, now that the process has been simplified and standardized, everyone can run the tool at 100% efficiency.  But the tool isn’t the important part, neither is the process of using it. The important part is the judgment of the people running it.

Productivity of tools is not measured in the number of design cycles per person or the number of test cases run per day.  This manufacturing thinking must be banished to its home country – the production floor.  The productivity of analytical tools is defined by the goodness of the output when the time runs out.  And at the end of the day, measuring the level of goodness also requires judgment – judgment by the experts and super users.   With tools, it’s all about judgment and the people exercising it.

And now process.  When the process is made repetitive, repeatable, and transactional, it brings productivity.  This is especially true when the process lets itself to being made repetitive, repeatable, and transactional.  Here’s a good one – step 1, step 2, step 3, repeat for 8 hours.  Dial it in and watch the productivity jump.  But when it’s never been done before, people’s judgment governs productivity; and when the process has no right answer, the experts call the ball. When processes are complex, undefined, or the first of their kind, productivity and judgment are joined at the hip.

Processes, on their own, don’t rain productivity from the sky; the real rainmakers are the people that run them.

Today’s battle for productivity is overwhelmingly waged in the trenches of minimization, eliminating judgment skirmish by skirmish. And productivity’s “more-with-less” equation has been toppled too far toward “less”, minimizing judgment one process at a time.

Really, there’s only one pillar of productivity, and that’s people.  As everyone else looks to eliminate judgment at every turn, what would your business look like if you went the other way?  What if you focused on work that demanded more judgment?  I’m not sure what it would look like, other than you’d have little competition.

Tracking Toward The Future

Rusty TrainIt’s difficult to do something for the first time. Whether it’s a new approach, a new technology, or a new campaign, the mass of the past pulls our behavior back toward itself.  And sadly, whether the past has been successful or not, its mass, and therefore it’s pull, are about the same.  The past keeps us along the track of sameness.

Trains have tracks to enable them to move efficiently (cost per mile), and when you want to go where the train is heading, it’s all good. But when the tracks are going to the wrong destination, all that efficiency comes at the expense of effectiveness.  Like we’re on rails, company history keeps us on track, even if it’s time for a new direction.

The best trains run on a ritualistic schedule.  People queue up at same time every morning to meet their same predictable behemoth, and take comfort in slinking into their regular seats and turning off their brains.  And this is the train’s trick. It uses its regularity to lull riders into a hazy state of non-thinking – get on, sit down, and I’ll get your there – to blind passengers from seeing its highly limited timetable and its extreme inflexibility.  The train doesn’t want us to recognize that it’s not really about where the train wants to go.

Trains are powerful in their own right, but their real muscle comes from the immense sunk cost of their infrastructure. Previous generations invested billions in train stations, repair facilities, tight integration with bus lines, and the tracks, and it takes extreme strength of character to propose a new direction that doesn’t make use of the old, tired infrastructure that’s already paid for. Any new direction that requires a whole new infrastructure is a tough sell, and that’s why the best new directions transcend infrastructure altogether.  But for those new directions that require new infrastructure, the only way to go is a modular approach that takes the right size bites.

Our worn tracks were laid in a bygone era, and the important destinations of yesteryear are no longer relevant. It’s no longer viable to go where the train wants; we must go where we want.

Mike Shipulski Mike Shipulski
Subscribe via Email

Enter your email address:

Delivered by FeedBurner

Archives