Shipulski On Design

Archive for the ‘Seeing Things As They Are’ Category

Innovation is a journey, and it starts from where you are.  With a systematic approach, the right information systems are in place and are continuously observed, decision makers use the information to continually orient their thinking to make better and faster decisions, actions are well executed, and outcomes of those actions are fed back into the observation system for the next round of  orientation.  With this method, the organization continually learns as it executes – its thinking is continually informed by its environment and the results of its actions.

To put one of these innovation systems in place, the first step is to define the group that will make the decisions. Let’s call them the Decision Group, or DG for short. (By the way, this is the same group that regularly orients itself with the information steams.) And the theme of the decisions is how to deploy the organization’s resources.  The decision group (DG) should be diverse so it can see things from multiple perspectives.

The DG uses the company’s mission and growth objectives as their guiding principles to set growth goals for the innovation work, and those goals are clearly placed within the context of the company’s mission.

The first action is to orient the DG in the past.  Resources are allocated to analyze the product launches over the past ten years and determine the lines of ideality (themes of goodness, from the customers’ perspective).  These lines define the traditional ideality (traditional themes of goodness provided by your products) are then correlated with historical profitability by sales region to evaluate their importance. If new technology projects provide value along these traditional lines, the projects are continuous improvement projects and the objective is market share gain. If they provide extreme value along traditional lines, the projects are of the dis-continuous improvement flavor and their objective is to grow the market.  If the technology projects provide value along different lines and will be sold to a different customer base, the projects could be disruptive and could create new markets.

The next step is to put in place externally focused information streams which are used for continuous observation and continual orientation.  An example list includes: global and regional economic factors, mergers/acquisitions/partnerships, legal changes, regulatory changes, geopolitical issues, competitors’ stock price and quarterly updates, and their new products and patents.  It’s important to format the output for easy visualization and to make collection automatic.

Then, internally focused information streams are put in place that capture results from the actions of the project team and deliver them, as inputs, for observation and orientation.  Here’s an example list: experimental results (technology and market-centric), analytical results (technical and market), social media experiments, new concepts from ideation sessions (IBEs), invention disclosures, patent filings, acquisition results, product commercialization results and resulting profits.  These information streams indicate the level of progress of the technology projects and are used with the external information streams to ground the DG’s orientation in the achievements of the projects.

All this infrastructure, process, and analysis is put in place to help the DG make good (and fast) decisions about how to allocate resources. To make good decisions, the group continually observes the information streams and continually orients themselves in the reality of the environment and status of the projects.  At this high level, the group decides not how the project work is done, rather what projects are done.  Because all projects share the same resource pool, new and existing projects are evaluated against each other.  For ongoing work the DG’s choice is – stop, continue, or modify (more or less resources); and for new work it’s – start, wait, or never again talk about the project.

Once the resource decision is made and communicated to the project teams, the project teams (who have their own decision groups) are judged on how well the work is executed (defined by the observed results) and how quickly the work is done (defined by the time to deliver results to the observation center.)

This innovation system is different because it is a double learning loop.  The first one is easy to see – results of the actions (e.g., experimental results) are fed back into the observation center so the DG can learn.  The second loop is a bit more subtle and complex.  Because the group continuously re-orients itself, it always observes information from a different perspective and always sees things differently.  In that way, the same data, if observed at different times, would be analyzed and synthesized differently and the DG would make different decisions with the same data. That’s wild.

The pace of this double learning loop defines the pace of learning which governs the pace of innovation.   When new information from the streams (internal and external) arrive automatically and without delay (and in a format that can be internalized quickly), the DG doesn’t have to request information and wait for it. When the DG makes the resource-project decisions it’s always oriented within the context of latest information, and they don’t have to wait to analyze and synthesize with each other.  And when they’re all on the same page all the time, decisions don’t have to wait for consensus because it already has.  And when the group has authority to allocate resources and chooses among well-defined projects with clear linkage to company profitability, decisions and actions happen quickly.  All this leads to faster and better innovation.

There’s a hierarchical set of these double learning loops, and I’ve described only the one at the highest level.  Each project is a double learning loop with its own group of deciders, information streams, observation centers, orientation work and actions.  These lower level loops are guided by the mission of the company, goals of the innovation work, and the scope of their projects.  And below project loops are lower-level loops that handle more specific work.  The loops are fastest at the lowest levels and slowest at the highest, but they feed each other with information both up the hierarchy and down.

The beauty of this loop-based innovation system is its flexibility and adaptability.  The external environment is always changing and so are the projects and the people running them.  Innovation systems that employ tight command and control don’t work because they can’t keep up with the pace of change, both internally and externally.  This system of double loops provides guidance for the teams and sufficient latitude and discretion so they can get the work done in the best way.

The most powerful element, however, is the almost “living” quality of the system.  Over its life, through the work itself, the system learns and improves.  There’s an organic, survival of the fittest feel to the system, an evolutionary pulse, that would make even Darwin proud.

But, really, it’s Colonel  John Boyd who should be proud because he invented all this.  And he called it the OODA loop. Here’s his story – Boyd: The Fighter Pilot Who Changed the Art of War.

Where possible, I have used Boyd’s words directly, and give him all the credit. Here is a list of his words: observe, orient, decide, act, analyze-synthesize, double loop, speed, organic, survival of the fittest, evolution.

Image attribution – U.S. Government [public domain]. by wikimedia commons.

It all starts and ends with clarity.  There’s not much to it, really.  You strip away all the talk and get right to the work you’re actually doing.  Not the work you should do, want to do, or could do.  The only thing that matters is the work you are doing right now.  And when you get down to it, it’s a short list.

There’s a strong desire to claim there’s a ton of projects happening all at once, but projects aren’t like that.  Projects happen serially.  Start one, finish one is the best way.  Sure it’s sexy to talk about doing projects in parallel, but when the rubber meets the road, it’s “one at time” until you’re done.

The thing to remember about projects is there’s no partial credit.  If a project is half done, the realized value is zero, and if a project is 95% done, the realized value is still zero (but a bit more frustrating).  But to rationalize that we’ve been working hard and that should count for something, we allocate partial credit where credit isn’t due.  This binary thinking may be cold, but it’s on-the-mark.  If your new product is 90% done, you can’t sell it – there is no realized value.  Right up until it’s launched it’s work in process inventory that has a short shelf like – kind of like ripe tomatoes you can’t sell.  If your competitor launches a winner, your yet-to-see-day light product over-ripens.

Get a pencil and paper and make the list of the active projects that are fully staffed, the ones that, come hell or high water, you’re going to deliver.  Short list, isn’t it?  Those are the projects you track and report on regularly.  That’s clarity. And don’t talk about the project you’re not yet working on because that’s clarity, too.

Are those the right projects?  You can slice them, categorize them, and estimate the profits, but with such a short list, you don’t need to.  Because there are only a few active projects, all you have to do is look at the list and decide if they fit with company expectations.  If you have the right projects, it will be clear.  If you don’t, that will be clear as well.  Nothing fancy – a list of projects and a decision if the list is good enough.  Clarity.

How will you know when the projects are done?  That’s easy – when the resources start work on the next project.  Usually we think the project ends when the product launches, but that’s not how projects are.  After the launch there’s a huge amount of work to finish the stuff that wasn’t done and to fix the stuff that was done wrong.  For some reason, we don’t want to admit that, so we hide it.  For clarity’s sake, the project doesn’t end until the resources start full-time work on the next project.

How will you know if the project was successful?  Before the project starts, define the launch date and using that launch data, set a monthly profit target.  Don’t use units sold, units shipped, or some other anti-clarity metric, use profit.  And profit is defined by the amount of money received from the customer minus the cost to make the product.  If the project launches late, the profit targets don’t move with it.  And if the customer doesn’t pay, there’s no profit.  The money is in the bank, or it isn’t.  Clarity.

Clarity is good for everyone, but we don’t behave that way.  For some reason, we want to claim we’re doing more work than we actually are which results in mis-set expectations.  We all know it’s matter of time before the truth comes out, so why not be clear?  With clarity from the start, company leaders will be upset sooner rather than later and will have enough time to remedy the situation.

Be clear with yourself that you’re highly capable and that you know your work better than anyone.  And be clear with others about what you’re working on and what you’re not.  Be clear about your test results and the problems you know about (and acknowledge there are likely some you don’t know about).

I think it all comes down to confidence and self-worth.  Have the courage wear clarity like a badge of honor.  You and your work are worth it.

Image credit – Greg Foster

If they made innovation fortune cookies, here’s what would be inside:

If you know how it will turn out, you waited too long.

Whether you like it or not, when you start something new uncertainty carries the day.

Don’t define the idealized future state, advance the current state along its lines of evolutionary potential.

Try new things then do more of what worked and less of what didn’t.

Without starting, you never start. Starting is the most important part

Perfection is the enemy of progress, so are experts.

Disruption is the domain of the ignorant and the scared.

Innovation is 90% people and the other half technology.

The best training solves a tough problem with new tools and processes, and the training comes along for the ride.

The only thing slower than going too slowly is going too quickly.

An innovation best practice –  have no best practices.

Decisions are always made with judgment, even the good ones.

image credit – Gwen Harlow

Innovation Excellence announced their top innovation bloggers of 2014, and, well, I topped the list!

The list is full of talented, innovative thinkers, and I’m proud to be part of such a wonderful group.  I’ve read many of their posts and learned a lot.  My special congratulations and thanks to: Jeffrey Baumgartner, Ralph Ohr, Paul Hobcraft, Gijs van Wulfen, and Tim Kastelle.

Honors and accolades are good, and should be celebrated. As Rick Hanson knows (Hardwiring Happiness) positive experiences are far less sticky than negative ones, and to be converted into neural structure must be actively savored.  Today I celebrate.

Writing a blog post every week is challenge, but it’s worth it.  Each week I get to stare at a blank screen and create something from nothing, and each week I’m reminded that it’s difficult.  But more importantly I’m reminded that the most important thing is to try. Each week I demonstrate to myself that I can push through my self-generated resistance.  Some posts are better than others, but that’s not the point. The point is it’s important to put myself out there.

With innovative work, there are a lot of highs and lows.  Celebrating and savoring the highs is important, as long as I remember the lows will come, and though there’s a lot of uncertainty in innovation, I’m certain the lows will find me.  And when that happens I want to be ready – ready to let go of the things that don’t go as expected.  I expect thinks will go differently than I expect, and that seems to work pretty well.

I think with innovation, the middle way is best – not too high, not too low.  But I’m not talking about moderating the goodness of my experiments; I’m talking about moderating my response to them. When things go better than my expectations, I actively hold onto my  good feelings until they wane on their own.  When things go poorly relative to my expectations, I feel sad for a bit, then let it go.  Funny thing is – it’s all relative to my expectations.

I did not expect to be the number one innovation blogger, but that’s how it went. (And I’m thankful.)  I don’t expect to be at the top of the list next year, but we’ll see how it goes.

For next year my expectations are to write every week and put my best into every post.  We’ll see how it goes.

If I was CEO of a company that wanted to do innovation, the one thing I’d strive for is clarity.

For clarity on the innovative new product, here’s what the CEO needs.

Valuable Customer Outcomes – how the new product will be used.  This is done with a one page, hand sketched document that shows the user using the new product in the new way.  The tool of choice is a fat black permanent marker on an 81/2 x 11 sheet of paper in landscape orientation. The fat marker prohibits all but essential details and promotes clarity.  The new features/functions/finish are sketched with a fat red marker.  If it’s red, it’s new; and if you can’t sketch it, you don’t have it. That’s clarity.

The new value proposition – how the product will be sold. The marketing leader creates a one page sales sheet.  If it can’t be sold with one page, there’s nothing worth selling.  And if it can’t be drawn, there’s nothing there.

Customer classification – who will buy and use the new product.  Using a two column table on a single page, these are their attributes to define: Where the customer calls home; their ability to pay; minimum performance threshold; infrastructure gaps; literacy/capability; sustainability concerns; regulatory concerns; culture/tastes.

Market classification – how will it fit in the market.  Using  a four column table on a single page, define: At Whose Expense (AWE) your success will come; why they’ll be angry; what the customer will throw way, recycle or replace; market classification – market share, grow the market, disrupt a market, create a new market.

For clarity on the creative work, here’s what the CEO needs: For each novel concept generated by the Innovation Burst Event (IBE), a single PowerPoint slide with a picture of its thinking prototype and a word description (limited to 12 words).

For clarity on the problems to be solved the CEO needs a one page, image-based definition of the problem, where the problem is shown to occur between only two elements, where the problem’s spacial location is defined, along with when the problem occurs.

For clarity on the viability of the new technology, the CEO needs to see performance data for the functional prototypes, with each performance parameter expressed as a bar graph on a single page along with a hyperlink to the robustness surrogate (test rig), test protocol, and images of the tested hardware.

For clarity on commercialization, the CEO should see the project in three phases – a front, a middle, and end.  The front is defined by a one page project timeline, one page sales sheet, and one page sales goals. The middle is defined by performance data (bar graphs) for the alpha units which are  hyperlinked to test protocols and tested hardware.  For the end it’s the same as the middle, except for beta units, and includes process capability data and capacity readiness.

It’s not easy to put things on one page, but when it’s done well clarity skyrockets.  And with improved clarity the right concepts are created, the right problems are solved, the right data is generated, and the right new product is launched.

And when clarity extends all the way to the CEO, resources are aligned, organizational confusion dissipates, and all elements of innovation work happen more smoothly.

Image credit – Kristina Alexanderson

There are three prerequisites for greatness.

1. You have to believe greatness is possible.
2. You have to believe greatness is worth it.
3. You have to believe you’re worthy of the journey.

If you can’t see old things in new ways, see new things in new ways, or see what’s missing, you won’t believe greatness is possible.  To believe greatness is possible, you have to change your perspective.

Greatness is an uphill battle on all fronts, and to push through the pain requires weapons grade belief that it’s worth it. But the power isn’t in the payoff.  The power is the personal meaning you attach to the work.  Your slog toward greatness is powered from the inside out.

Here’s the tough one – you’ve got to believe you’re worthy of the journey.  At every turn the status quo will kick you in the shins, and you must strap on your self-worth like shin guards. And when it’s time to conger greatness from gravel, you must believe, somehow, your life force will rise to the occasion. But, to be clear, you don’t have to believe you’ll be successful; you only have to believe you’re worth the bet.

From the outside, greatness is all about the work. But from the inside, greatness is all about you.

Image credit – Dietmar Temps

Mind and body are connected, literally.  It’s true – our necks bridge the gap. Don’t believe me? Locate one end of your neck and you’ll find your head or body; locate the other and you’ll find the other.  And not only are they connected, they interact.  Shared blood flows between the two and that means shared blood chemistry and shared oxygen.  And not only is the plumbing shared, so is the electrical.  The neck is the conduit for the nerves which pass information between the two and each communicate is done in a closed loop way. Because it’s so obvious, it sounds silly to describe the connectedness in this way, yet we still think of them as separate.

When the mind-body is combined into a single element our perspectives change.  For one, we realize the significance of the environment because wherever the body is the mind is. If your body walks your mind to a hot place, your body is hot and so is your mind.  No big deal?  Go to the beach in mid- summer, stand in the 105 degree heat for 1 hour, then do some heavy critical thinking.  Whether the environment is emotionally hot or temperature hot, it won’t go well.  Sit your body in a noisy, chaotic environment for two hours then try to come up with the new technology to keep your company solvent. Keep your body awake for 24 hours and try to solve a fundamental problem to reinvent your business model. I don’t think so.

Innovation is like a marathon, and if you treat your body like a marathon runner you’ll be in great shape to innovate.  Get regular physical activity; eat well; get enough sleep; don’t go out and party every night; drink your fluids; don’t get over heated.  If you don’t think any of this matters, do the opposite for a week or two and see how it goes with your innovation.  And as with innovation climate, geography and environment matter.  Train at altitude and sleep in a hypobaric chamber and your mind-body responds differently.  Run up hill and you get faster on the hills and likely slower on the flats.  Run downhill and your legs hurt.  Run in sub-zero temperatures and your lungs burn.

Just as the mind goes with the body, the body follows mind.  If you are anxious about your work, you feel a cold pressure in your chest – a clear example where your mental state influences your body.  If you are depressed, your body can ache – another example where your mind changes your body. But it’s more than unpleasant body sensations.  Your body does far more than move your head place-to-place.  Your body is the antenna for the unsaid, and the unsaid is huge part of innovation.  Imagine a presentation to your CEO where you describe your one year innovation project that came up empty.  When you stop talking and there’s a minute of silent unsaid-ness, your body picks up the signals, not your mind.  (You feel the tightness in your chest before you know why.) But if your mind has been monkeying with your body, your crumpled antenna may receive incorrect signals or may transmit them to your brain improperly, and when the CEO asks the hard question, your mind-body is spongy.

And what fuels the mind-body? Why does it get out of bed? Why does it want to do innovation? Dan Pink has it right – when it comes to tasks with high cognitive load, the mind-body is powered by autonomy, the pursuit of mastery, and purpose.  For innovation, the mind-body is powered intrinsically, not extrinsically.  If your engineers aren’t innovating, it’s because their mind-bodies know there’s no autonomy in the ether.  If they’re not taking on the impossible, it’s because they aren’t given time to master its subject matter or the work they’re given is remedial. If they’re doing what they always did, it’s because their antennas aren’t resonating with the purpose behind the innovation work.

When your innovation work isn’t what you’d like it’s not a people problem, it’s an intrinsic motivation problem.  Innovators’ mind-bodies desperately want to pole vault out of bed and innovate like nobody’s business, but they feel they have too little control over what they do and how they do it; they want to put all their life force into innovation, but they know (based on where their mind-bodies are) they’re not given the tools, time, and training to master their craft; and the rationale you’ve given them – the “WHY” in why they should innovate – is not meaningful to their mind-bodies.

Innovation is a full mind-body sport, and the importance of the body should be elevated.  And if there’s one thing to focus on it’s the innovation environment in which the mind-body sits.

Innovators were born to innovate – our mind-bodies don’t have a choice.  And if innovation is not happening it’s because extrinsic motivation strategies (carrots and sticks) are blocking the natural power of our intrinsic motivation.  It’s time to figure that one out.

Image credit – Eli Duke

If you’re not thinking differently, you’re thinking the same. And if you’re thinking the same, you’re going to get the same. Same may feel safe, and at some level it is. But when sameness festers into staleness, too much of a good thing isn’t wonderful.

In our fast moving Bizzaro World, safe is dangerous; repeatable is out and remarkable is in; improving what is is displaced by creating what isn’t; more capacity is outlawed and new capability is the only way; growing existing markets is wasteful because it gets in the way of creating new ones.

Ask your company leaders if they’re doing innovation, and the answer is yes. It’s a loaded question, and nothing good can come of it. “No, we don’t do innovation.” is a career-limiting response. Here are two better questions: What are you doing that’s different? What are you doing differently? These questions are effective because they require answers that are relative – relative to what you used to do. And because innovation starts with different, these questions are a good start.

Our assembly process is different and we increased productivity 0.3%; our product design is different and we made it stronger by 2.1%; our customer service tools are different and we decrease waiting time by 1.7%; our plastics are different and we reduced product cost by 0.6%. The difference is clear, but it didn’t really make a difference. Innovation starts with different, but all different isn’t created equal. Instead of shades of gray, think binary, think black to white, think no to yes.

Here are some better questions:

• Have we stopped distracting ourselves by focusing on growth of our biggest markets?
• Did we change the value proposition with our new product?
• Have we increased sales people in the undeveloped markets at the expense of sales people in our biggest markets?
• Do our new technologies change the argument?
• Are we working on the new products that will obsolete our most profitable product?
• Does the new product do less of anything so it can do more of something else?
• Are we working on the technologies so we can sell into Africa?
• Are we hiring experts in mobile technology?
• How about experts in data science?

There’s no hard and fast definition of what makes for the right no-to-yes thinking but their telltale sign is their wake of oblique problems. If your organization doesn’t know how to do something, then it could be an indication of powerful no-to-yes behavior. For example, if your translations group doesn’t know how to translate into a new language requested by sales, it could be because a new region of the world is now important. If your sales managers want to use a new search firm because your longstanding one can’t find the right new candidates, it may be because your new product demands a new flavor of sales people. If your compensation structure doesn’t let you make an acceptable offer to an engineer you really need, it could be because you need to hire for new specialties from different industries with radically different compensation norms.

“Are you doing innovation?”, as a question, is not skillful.  Instead, do the work so you must sell where you haven’t sold; use materials you’ve never used; use technologies you’ve never heard of; hire people you never had to hire; and create problems related to new geographies and new languages.  And when someone asks “Are you doing innovation?”, tell them you used to, but you’ve found something better.

Image credit – JD HANCOCK PHOTOS

Here’s how innovation goes:
(Words uttered. // Internal thoughts.)

That won’t work. Yes, this is a novel idea, but it won’t work. You’re a heretic. Don’t bring that up again. // Wow, that scares me, and I can’t go there.

Yes, the first experiment seemed to work, but the test protocol was wrong, and the results don’t mean much. And, by the way, you’re nuts. // Wow. I didn’t believe that thing would ever get off the ground.

Yes, you modified the test protocol as I suggested, but that was only one test and there are lots of far more stressful protocols that surely cannot be overcome. // Wow. They listened to me and changed the protocol as I suggested, and it actually worked!

Yes, the prototype seemed to do okay on the new battery of tests, but there’s no market for that thing. // I thought they were kidding when they said they’d run all the tests I suggested, but they really took my input seriously. And, I can’t believe it, but it worked. This thing may have legs.

Yes, the end users liked the prototypes, but the sample size was small and some of them don’t buy any of our exiting products. I think we should make these two changes and take it to more end users. // This could be exciting, and I want to be part of this.

Yes, they liked the prototypes better once my changes were incorporated, but the cost is too high. // Sweet! They liked my design! I hope we can reduce the cost.

I made some design changes that reduce the cost and my design is viable from a cost standpoint, but manufacturing has other priorities and can’t work on it. // I’m glad I was able to reduce the cost, and I sure hope we can free up manufacting resources to launch my product.

Wow, it was difficult to get manufacturing to knuckle down, but I did it, and my product will make a big difference for the company. // Thanks for securing resources for me, and I’m glad you did the early concept work when I was too afraid.

Yes, my product has been a huge commercial success, and it all strarted with this crazy idea I had. You remember, right? // Thank you for not giving up on me. I know it was your idea. I know I was a stick-in-the-mud. I was scared. And thanks for kindly and effectively teaching me how to change my thinking. Maybe we can do it again sometime.
________________

There’s nothing wrong with this process; in fact, everything is right about it because that’s what people do. We’ve taught them to avoid risk at all costs, and even still, they manage to walk gingerly toward new thinking.

I think it’s important to learn to see the small shifts in attitude as progress, to see the downgrade from an impossible problem to a really big problem as progress.

Instead of grabbing the throat of radical innovation and disrupting yourself, I suggest a waterfall approach of a stepwise ratchet toward problems of a lesser degree. This way you can claim small victories right from the start, and help make it safe to try new things. And from there, you can stack them one on top of another to build your great pyramid of disruption.

And don’t forget to praise the sorceres and heretics who bravely advance their business model-busting ideas without the safety net of approval.

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.