Shipulski On Design

Posts Tagged ‘Competitiveness’

There’s a lot of stress in the working world these days, and to me, it all comes down to our blatant disrespect of uncertainty.

In today’s reality, we ask for plans then demand strict adherence to the deliverables – on time, on budget, or else. We treat plans like they’re chiseled in granite, when really it should be more like dry erase markers and a whiteboard. Our markets are uncertain; customers’ behaviors are uncertain; competitors’ actions are uncertain; supply chains are uncertain, yet our plans are plans don’t reflect that reality. And when we expect absolute predictability and accountability, we create stress and anxiety and our people don’t want to try new things because that adds another level of uncertainty.

With a flexible, rubbery plan the first step informs the second, and this is the basis for the logical shift from robust plans to resilient ones. Plans should be less about forcing adherence and more about recognizing deviation. Today’s plans demand early recognition of something that did follow the plan and today’s teams must have the authority to respond quickly. However, after years of denying the powerful force of uncertainty and shooting the messenger, we’ve trained our people to hide the deviations. And, with our culture of control and accountability, our teams require our approval before any type of change, so their response time is, well, not timely.

At our core, we know uncertainty is a founding principle in our universe, and now it’s time to behave that way. It’s time to look inside and decide to embrace uncertainty. Accept it or not, acknowledge it or not, uncertainty is here to stay. Here are some words to guide your journey:

• Resilient not robust.
• Early detection, fast response.
• Many small plans, done in parallel.
• Do more of what works, and less of what doesn’t.
• Plans are meant to be re-planned.

And if you’re into innovation, this applies doubly.

Image credit – dfbphotos.

Big Data is powerful – measure what people do on the web, summarize the patterns, and use the information for good. These data sets are so powerful because they’re bigger than big; there’s little bias since the data collection is automatic; and the analysis is automated. There’s huge potential in the knowledge of what people click, what pages they land on, and what place the jump from.

It’s magical to think about what can be accomplished with the landing pages and click-through rates for any demographic you choose. Here are some examples:

• This is the type of content our demographic of value (DOV) lands on, and if we create more content like this we’ll get more from them to land where we want.
• These are the pages our DOV jump from, and if we advertise there more of our DOV will see our products.
• This is the geographic location of our DOV when they land on our website, and if we build out our sales capacity in these locations we’ll sell more.
• This is the time slot when our DOV is most active on their smart phones, and if we tweet more during that time we’ll reach more of them.

But just as there’s immense power knowing the actions of your DOV (what they click on), there are huge assumptions on what it all means. Here are two big ones:

1. All clicks are created equal.
2. When more see our content, more will do what we want.

Here is an example of three members (A, B, C) of your demographic of interest who take the same measurable action but with different meaning behind it:

Member A, after four drinks, speeds home recklessly; loses control of the car; crashes into your house; and parks the car in your living room.

Member B, after grocery shopping, drives home at the speed limit; the front wheel falls off due to a mechanical problem; loses control of the car; crashes into your house; and parks the car in your living room.

Member C, after volunteering at a well-respected non-profit agency, drives home in a torrential rain 15 miles per hour below the speed limit; a child on a bicycle bolts into the lane without warning and C swerves to miss the child; loses control of the car; crashes into your house; and parks the car in your living room.

All three did the same thing – crashed into your house – but the intent, the why, is different. Same click, but not equal. And when you put your content in front of them, regardless of what you want them to do, A, B, and C will respond differently. Same DOV, but different intentions behind their actions.

Big Data, with its focus on the whats, is powerful, but can be made stereoscopic with the addition of a second lens that can see the whys. Problem is, the whys aren’t captured in a clean, binary way – not transactional but conversational – and are subject to interpretation biases where the integers of the whats are not.

With people, action is preceded by intent, and intent is set by thoughts, feelings, history, and context. And the best way to understand all that is through their stories. If you collect and analyze customer stories you’ll better understand their predispositions and can better hypothesize and test how they’ll respond.

In the Big Data sense, Nirvana for stories is a huge sample size collected quickly with little effort, analysis without biases, and direct access to the stories themselves.

New data streams are needed to collect the whys in a low overhead way, and new methods are needed to analyze them quickly and without biases. And a new perspective is needed to see not only the amazing power of Big Data (the whats), but the immense potential of seeing the what’s with one eye and the whys with the other.

Keep counting the whats with traditional Big Data work – there’s real value there. But also keep one eye on the horizon for new ways to collect and analyze the whys (customer stories) in a Big Data way.

Collection and analysis of customer stories, if the sample size is big enough and biases small enough, is the best way I know to look through the fog and understand emerging customer needs and emerging markets.

If you can figure out how to do it, it will definitely be worth the effort.

The Holy Grail of marketing is to identify emerging customer needs before anyone else and satisfy them to create new markets. It has been a long and fruitless slog as emerging needs have proven themselves elusive. And once candidates are identified, it’s a challenge to agree which are the game-changers and which are the ghosts. There are too many opinions and too few facts. But there’s treasure at the end of the rainbow and the quest continues.

Emerging things are just coming to be, just starting, so they appy to just a small subset of customers; and emerging things are new and different, so they’re unfamiliar. Unfamiliar plus small same size equals elusive.

I don’t believe in emerging customer needs, I believe in emergent customer behavior.

Emergent behavior is based on actions taken (past tense) and is objectively verifiable. Yes or no, did the customer use the product in a new way? Yes or no, did the customer make the product do something it wasn’t supposed to? Did they use it in a new industry? Did they modify the product on their own? Did they combine it with something altogether unrelated? No argument.

When you ask a customer how to improve your product, their answers aren’t all that important to them. But when a customer takes initiative and action, when they do something new and different with your product, it’s important to them. And even when just a few rouge customers take similar action, it’s worth understanding why they did it – there’s a good chance there’s treasure at the end of that rainbow.

With traditional VOC methods, it has been cost prohibitive to visit enough customers to learn about a handful at the fringes doing the same crazy new thing with your product. Also, with traditional VOCs, these “outliers” are thrown out because they’re, well, they’re outliers. But emergent behavior comes from these very outliers. New information streams and new ways to visualize them are needed to meet these challenges.

For these new information streams, think VOC without the travel; VOC without leading the witness; VOC where the cost of capturing their stories is so low there are so many stories captured that it’s possible to collect a handful of outliers doing what could be the seed for the next new market.

To reduce the cost of acquisition, stories are entered using an app on a smart phone; to let emergent themes emerge, customers code their own stories with a common, non-biasing set of attributes; and to see patterns and outliers, the coded stories are displayed visually.

In the past, the mechanisms to collect and process these information streams did not exist. But they do now.

I hope you haven’t given up on the possibility of understanding what your customers will want in the near future, because it’s now possible.

I urge you to check out SenseMaker.

It’s pretty clear that innovation is the way to go. There’s endless creation of new technologies, new materials, and new processes so innovation can create new things to sell. And there are multiple toolsets and philosophies to get it done, but it’s difficult.

When doing new there’s no experience, no predictions, no certainty. But innovation is no dummy and has come up with a way to overcome the uncertainty. It builds knowledge of systems through testing – build it, test it, measure it, fix it. Not easy, but doable. And what makes it all possible is the repeatable response of things like steel, motors, pumps, software, hard drives. Push on them repeatably and their response is repeatable; stress them in a predictable way and their response is predictable; break them in a controlled way and the failure mode can be exercised.

Once there’s a coherent hypothesis that has the potential to make magic, innovation builds it in the lab, creates a measurement system to evaluate goodness, and tests it. After the good idea, innovation is about converting the idea into a hypothesis – a prediction of what will happen and why – and testing them early and often. And once they work every-day-all-day and make into production, the factory measures them relentlessly to make sure the goodness is shipped with every unit, and the data is religiously plotted with control charts.

The next evolution of innovation will come from systematically improving people systems. There are some roadblocks but they can be overcome. In reality, they already have been overcome it’s just that no one realizes it.

People systems are more difficult because their responses are not repeatable – where steel bends repeatably for a given stress, people do not. Give a last minute deliverable to someone in a good mood, and the work gets done; give that same deliverable to the same person on a bad day, and you get a lot of yelling. And because bad moods beget bad moods, people modify each other’s behavior. And when that non-repeatable, one-person-modifying-another response scales up to the team level, business unit, company, and supply chain, you have a complex adaptive system – a system that cannot be predicted. But just as innovation of airliners and automobiles uses testing to build knowledge out of uncertainty, testing can do the same for people systems.

To start, assumptions about how people systems would respond to new input must be hardened into formal hypotheses. And for the killer hypotheses that hang together, an experiment is defined; a small target population is identified; a measurement system created; a baseline measurement is taken; and the experiment is run. Data is then collected, statistical analyses are made, and it’s clear if the hypothesis is validated or not. If validated, the solution is rolled out and the people system is improved. And in a control chart sense, the measurement system is transferred to the whole system and is left to run continuously to make sure the goodness doesn’t go away. If it’s invalidated, another hypothesis is generated and the process is repeated. (It’s actually better to test multiple hypotheses in parallel.)

In the past, this approach was impossible because the measurement system did not exist. What was needed was a simple, mobile data acquisition system for “people data”, a method to automatically index the data, and a method to quickly process and display the results. The experimental methods were clear, but there was no response for the experiments. Now there is.

People systems are governed by what people think and feel, and the stories they tell are the surrogates for their thoughts and feelings. When an experiment is conducted on a people system, the stories are the “people data” that is collected, quantified, and analyzed. The stories are the response to the experiment.

It is now possible to run an experiment where a sample population uses a smart phone and an app to collect stories (text, voice, pictures), index them, and automatically send them to a server where some software groups the stories and displays them in a way to see patterns (groups of commonly indexed stories). All this is done in real time. And, by clicking on a data point, the program brings up the story associated with that data point.

Here’s how it works. The app is loaded, people tell their stories on their phone, and a baseline is established (a baseline story pattern). Inputs or constraints are changed for the target population and new stories are collected. If the patterns change in a desirable way (statistical analysis is possible), the new inputs and constraints are rolled out. If the stories change in an undesirable way, the target population reverts back to standard conditions and the next hypothesis is tested.

Unbiased, real time, continuous information streams to make sense of your people systems is now possible. Real time, direct connection to your employees and your customers is a reality, and the implications are staggering.

Thank you Dave Snowden.

From the outside it’s unclear how things happen; but from the inside it’s clear as day. No, it’s not your bulletproof processes; it’s not your top down strategy; and it’s not your operating plans. It’s your people.

At some level everything happens like this:

An idea comes to you that makes little sense, so you drop it. But it comes again, and then again. It visits regularly over the months and each time reveals a bit of its true self. But still, it’s incomplete. So you walk around with it and it eats at you; like a parasite, it gets stronger at your expense. Then, it matures and grows its voice – and it talks to you. It talks all the time; it won’t let you sleep; it pollutes you; it gets in the way; it colors you; and finally you become the human embodiment of the idea.

And then it tips you. With one last push, it creates enough discomfort to roll over the fear of acknowledging its existence, and you set up the meeting.

You call the band and let them know it’s time again to tour. You’ve been through it before and you all know deal. You know your instruments and you know how to harmonize. You know what they can do (because they’ve done it before) and you trust them. You sing them the song of your idea and they listen. Then you ask them to improvise and sing it back, and you listen. The mutual listening moves the idea forward, and you agree to take a run at it.

You ask how it should go. The lead vocalist tells you how it should be sung; the lead guitar works out the fingering; the drummer beats out the rhythm; and the keyboardist grins and says this will be fun. You all know the sheet music and you head back to your silos to make it happen.
In record time, the work gets done and you get back together to review the results. As a group you decide if the track is good enough play in public. If it is, you set up the meeting with a broader audience to let them hear your new music. If it’s not, you head back to the recording studio to amplify what worked and dampen what didn’t. You keep re-recording until your symphony is ready for the critics.

Things happen because artists who want to make a difference band together and make a difference. With no complicated Gantt chart, no master plan, no request for approval, and no additional resources, they make beautiful music where there had been none. As if from thin air, they create something from nothing. But it’s not from thin air; it’s from passion, dedication, trust, and mutual respect.

The business books over-complicate it. Things happen because people make them happen – it’s that simple.

There’s a natural hierarchy to work.  Your job, if you choose to accept it is to climb the ladder of hierarchy rung-by-rung. Here’s how to go about it:

Level 1. Work you can say no to – Say no to it. Say no effectively as you can, but say it. Saying no to level 1 work frees you up for the higher levels.

Level 2. Work you can get someone else to do – Get someone else to do it. Give the work to someone who considers the work a good reach, or a growth opportunity. This isn’t about shirking responsibility, it’s about growing young talent. Maybe you can spend a little time mentoring and the freed up time doing higher level work. Make sure you give away the credit so next time others will ask you for the opportunity to do this type of work for you.

Level 3. Work you’ve done before, but can’t wiggle out of – Do it with flair, style, and efficiency; do it differently than last time, then run away before someone asks you to do it again. Or, do it badly so next time they ask someone else to do it. Depending on the circumstance, either way can work.

Level 4. Work you haven’t done before, but can’t wiggle out of – Come up with a new recipe for this type of work, and do it so well it’s unassailable. This time your contribution is the recipe; next time your contribution is to teach it to someone else. (See level 2.)

Level 5. Work that scares others – Figure out why it scares them; break it into small bites; and take the smallest first bite (so others can’t see the failure).  If it works, take a bigger bite; if it doesn’t, take a different smallest bite.  Repeat, as needed. Next time, since you’ve done it before, treat it like level 3 work. Better still, treat it like level 2.

Level 6. Work that scares you – Figure out why it scares you, then follow the steps for level 5.

Level 7. Work no one knows to ask you to do – You know your subject matter better than anyone, so figure out the right work and give it a try.  This flavor is difficult because it comes at the expense of work you’re already signed up to do and no one is asking you to do it. But you should have the time because you followed the guidance in the previous levels.

Level 8. Work that obsoletes the very thing that made your company successful – This is rarified air – no place for the novice. Ultimately, someone will do this work, and it might as well be you.  At least you’ll be able to manage the disruption on your own terms.

In the end, your task, if you choose to accept it, is to migrate toward the work that obsoletes yourself. For only then can you start back at level 1 on the ladder of your own making.

If 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.

Things are cyclic, but there seems to be no end to the crusade of continuous improvement. (Does anyone remember how the Crusades turned out?) If only to take the edge off, there needs to be an injection of absurdity.

There’s no pressure with absurdity – no one expects an absurd idea to work.  If you ask for an innovative idea, you’ll likely get no response because there’s pressure from the expectation the innovative idea must be successful. And if you do get a response, you’ll likely get served a plain burrito of incremental improvement garnished with sour cream and guacamole to trick your eye and doused in hot sauce to trick your palate. If you ask for an absurd idea, you get laughter and something you’ve never heard before.

When drowning in the sea of standard work, it takes powerful mojo to save your soul.  And the absurdity jetpack is the only thing I know with enough go to launch yourself to the uncharted oasis of new thinking.  Immense force is needed because continuous improvement has serious mass – black hole mass. Like with light, a new idea gets pulled over the event horizon into the darkness of incremental thinking.  But absurdity doesn’t care.  It’s so far from the center lean’s pull is no match.

But to understand absurdity’s superpower is to understand what makes things absurd.  Things are declared absurd when they cut against the grain of our success.  It’s too scary to look into the bright sun of our experiences, so instead of questioning their validity and applicability, the idea is deemed absurd.  But what if the rules have changed and the fundamentals of last year’s success no longer apply?  What if the absurd idea actually fits with the new normal?  In a strange Copernican switch, holding onto to what worked becomes absurd.

Absurd ideas sometimes don’t pan out.  But sometimes they do.  When someone laughs at your idea, take note – you may be on to something.  Consider the laughter an artifact of misunderstanding, and consider the misunderstanding a leading indicator of the opportunity to reset customer expectations.  And if someone calls your idea absurd, give them a big hug of thanks, and get busy figuring out how to build a new business around it.

Every day is a meeting-to-meeting sprint with no time for some of the favorite fundamentals like the bathroom and food.  Though crazy, it’s the norm and no longer considered crazy.   But it is crazy.  When you’re too busy to answer emails that’s one thing, but when you’re too busy to realize answering email isn’t progress, that’s a problem.

Our in-boxes are full; our plates are full; our calendars are full. But our souls are empty.

You’re clear on what must get done over the next 48 hours, but the pace is too fast to know why the work is important in the first place. (One of the fastest way to complete a task is to deem it unimportant and don’t do it – all of the done with none of the work.) But it’s worse.  It’s too fast to do the work no one is asking you to do, and it’s too fast to do the work you were born to do.

We have confused activity with progress; and with all the activity, we’ve forgotten what it feels like to think.  We need a retreat.

The perfect retreat eliminates distractions and gives people time to think.  After a nice Sunday flight into Boston, it’s a calm two hour coach ride to rural New Hampshire. (Done right, a coach is soothing.)  After pickup it’s a fifteen minute drive to a remote trail head.  With a pack on your back, it’s a five minute walk to a big, remote cabin.  No cell service, no power, no interruptions.

As you enter the cabin, you unload all your electronics into bin (Yes, your smart phone goes in the bin.) which is locked away for the remainder of the retreat.  You race to get the best bunk, drop your gear, and share a meal with your fellow over achievers. (Y es, the non-disclosures are signed so you can actually talk to each other.)

The first day is all about recognizing the discomfort that comes with no distractions and your natural tendency to create distraction to sooth your discomfort.  The objective is to help you remember what if feels like to have more than 30 seconds of uninterrupted time.  Then, once you remember, it’s time to actually think.

There are no video conferencing capabilities (or electricity) in the cabin, so all work is done the old-fashioned way – face-to-face.  The objective is to help you remember the depth, complexity, and meaning that come when working with actual faces.  Yes, there’s good facilitated discussion, but the topics aren’t as important as remembering how to share and trust.

There is ritualistic work of cooking, cleaning, splitting the wood, and stoking the fire.  The objective is to remember what it feels like to connect the mind to the body and to connect with others.  And, there’s a group hike every day to remember what it feels like to be grounded in the natural world.  (Sometimes we forget the business world is actually part of the natural world.)

After the rituals and hikes have done their magic, the right discussions start to emerge, and deep contemplation dances with deep conversation.  Though there’s a formal agenda, no matter.  With the group’s awaking, the right agenda emerges.

At the end of the retreat, there’s immense sadness.  This is a sign of importance and deep learning.  And after the hugs and tears, there’s a spontaneous commitment to do it next year.  With eyes dried, it’s off the bus station and then to the airport.

You don’t have to wait for the perfect retreat to start your journey.  Start your practice by carving out an hour a day and set a recurring meeting with yourself and turn off your email. And start by asking yourself why.  Those two tricks will set you on your way.

And if you’re interested in a real retreat, let me know.

Productivity 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.

The early explorers had maps, but they were wrong – sea monsters, missing continents, and the home country at the center.  Wrong, yes, but the best maps of their day.  The early maps weren’t right because the territory was new, and you can expect the same today. When you work in new territory, your maps are wrong.

As the explorers’ adventures radiated further from home, they learned and their maps improved.  But still, the maps were best close to home and diverged at the fringes.  And over the centuries the radius of rightness grew and the maps converged on the territory.  And with today’s GPS technology, maps are dead on.  The system worked – a complete map of everything.

Today you have your maps of  your business environment and the underlying fundementals that ground them.  Like the explorers you built them over time and checked them along the way.  They’re not perfect (more right close to home) but they’re good.  You mapped the rocks, depths, and tides around the trade routes and you stay the course because the routes have delivered profits and they’re safe. You can sail them in your sleep, and sometimes you do.

But there’s a fundamental difference between the explorers’ maps and yours – their territory, the physical territory, never changed, but yours is in constant flux.  The business trade winds shift as new technologies develop; the size of continents change as developing countries develop; and new rocks grow from the sea floor as competitors up their game.  Just when your maps match the territory, the territory changes around you and diverges from your maps, and your maps become old.  The problem is the maps don’t look different.  Yes, they’re still the same maps that guided you safely along your journey, but they no longer will keep you safely off the rocks and out of the Doldrums.

But as a new age explorer there’s hope.  With a healthy skepticism of your maps, frequently climb the mast and from the crow’s nest scan the horizon for faint signs of trouble.  Like a thunder storm just below the horizon, you may not hear trouble coming, but there’ll be dull telltale flashes that flicker in your eyepiece.  Not all the crew will see them, or want to see them, or want to believe you saw them, so be prepared when your report goes unheeded and your ship sales into the eye of the storm.

Weak signals are troubling for several reasons.  They’re infrequent and unpredictable which makes them hard to chart, and they’re weak so they’re tough to hear and interpret.  But worst of all is their growth curve.  Weak signals stay weak for a long time until they don’t, and when they grow, they grow quickly.  A storm just over the horizon gives weak signals right up until you sail into gale force winds strong enough to capsize the largest ships.

Maps are wrong when the territory is new, and get more right as you learn; but as the territory changes and your learning doesn’t, maps devolve back to their natural wrongness.  But, still, they’re helpful.  And they’re more helpful when you remember they have a natural half-life.

My grandfather was in the Navy in World War II, though he could never bring himself to talk about it. However, there was one thing he told me, a simple saying he said kept him safe:

Red skies at night, sailor’s delight; red skies in morninng, sailor takes warning.

I think he knew the importance of  staying aware of the changing territory.