Most of us use online driving apps like Waze.

If so – this probably looks pretty familiar.  Note in the bottom left corner of the image that it has your speed.

These apps let us tell it all sorts of interesting things like whether there is a hidden police car, or an accident, even a pothole. It also let’s us tell them if we think there’s a traffic jam.

To do that, you can choose one of these three options, Moderate, Heavy, or Standstill.

Every time you report something – anything, you get six points.  Now these points aren’t useful for anything other than comparing yourself with other drivers, but I suspect this gamification helps Waze collect a lot more data about everything.

Waze is wildly popular.  There are Waze users everywhere.  And since they know your speed, and they have years of historical data, they already know when there is a Traffic Jam.  They can’t infer too many of the other things I mentioned above (an accident or other hazard could be the cause of a slowdown, but it’s still a Traffic Jam).

So if they know how fast you are going and what’s normal, why do they even bother to let you report it?  Is it to give you something to do when you are sitting in traffic?  Maybe.  But there are no rules around when you submit one of these (as I have learned).  I can be at zero on my speedometer and report any one of the three Traffic Jam values. I can even report all three of them in succession if I want to and I will get six points for every time.

So what are they really doing?

They are calibrating us – our feedback and how we judge things.

If they know you will report 6 MPH traffic as Moderate, and I consistently report that as Standstill – they have learned something about how we are different.  Maybe we just want the six points, but knowing that it doesn’t matter which of the three levels we choose, they learn a little bit about us every time.

It has been reported that the same thing happens in the long surveys we see in places like Facebook.  It’s partly to learn our answers to the questions, but it’s also to calibrate our willingness to answer 5 or 50 questions.  So before you fill in surveys, or tell Waze something they already know, think about your privacy and what you want to share.

If you watch this TEDx talk, it gets into the ability to get smarter about people and their data patterns.

It will be very interesting to see what Waze and other apps do with us now that we have been calibrated.

I am a loyal reader of anything from Farhad Manjoo and this piece in The New York Times today is no exception.

The gist of it is that while marketing used to be as non-targeted as carpet bombing (not his expression), but now, because so much is known about on online user contextually, ads can be much more targeted, a point made in some detail in this TEDx talk.

The problem I have with Manjoo’s column today is that it overlooks a key piece in the path.  Our privacy.  It’s a sadly one-sided argument to talk about how awesome it will be when marketers know so much more about us that they can put just the right razor blade ad at the right person at the right time to sell the right product.  What we really need is user control of our bio and data so we can decide when we want those sorts of ads.  It won’t be until we have a better balance between privacy and marketing that we will really achieve progress in digital marketing.

Everyone seems to be into journey mapping these days.

It looks pretty easy to lay out the steps, discover, enroll, plan, arrive, experience, remember are common groupings that people use.  One extreme case is this one from the San Francisco airport that has 16 steps.  Adding personas to the journeys also looks pretty easy (and it is).  All of that is easy but most of the journey maps I have seen recently from banks to agriculture stop well short of being actionable, and thus they don’t add much value.

Remember in the 1990s when process reengineering was a big thing?  After Michael Hammer and James Champy published their Reengineering the Corporation which sold millions of copies.  Companies from Accenture to Accelare built large and successful businesses around that very practice.  But over time – people saw the shapes and arrows on the page and thought “how hard can that be” and started doing their own process mapping.  That ended up being a lot of work without a lot of value – and if I knew how to graph the popularity of the word “Process” in titles in LinkedIn, my bet is that the line would point pretty sharply downward over the last 15 years.

Unless people start to figure out how to cross over the line into adding value, my guess is that journey mapping will have a similar fate.

There is good news.

Adding value in journey mapping isn’t impossible.  It’s not always easy, but it’s also not always hard.

Here are five things that can be done to flip journey maps from just being interesting – to actually adding value.

1. Add value.  Literally tag each element/capability/step with a value contribution marker.  Do this also for the customer personas.  Whether it’s data driven or just a red/yellow/green assertion for high value/low value, that’s important.  For example, using the steps mentioned above (discover, enroll, plan, arrive, experience, remember) most organizations assume that the “experience” step is their core value – but what if people never get to the discovery step or what if after discovery they don’t enroll?  It’s important to know where the value is, and isn’t, in each step, so when you talk about a performance change, whether it’s a lift in customer satisfaction, or revenue, or more of a certain type of customer, you have started with a notion of where the value is.
2. Map revenue and cost.  Know where you have revenue by step and persona. Some theme parks recognize revenue once people go through their turnstile, but booking the revenue is also critical – and knowing not only where the booking happens, from where, and how much you spent in marketing or sales to get that booked revenue is key.  This is one that is easy if you already track and store this information or use a system like Acxiom for that – start work because this is critical.  Cost is linked to effort an operations and there’s more about that in #5 below.
3. Map current state / future state.  It’s interesting to understand where you are today with journeys, and technology and revenue and value, but if you don’t have a specific end state or direction in mind, you really don’t have any way to know if you are on the right path – and it makes it really hard to build trust and confidence with leadership.  Have a future state, and map the work needed to get there, have success measures, document the risks.  Treat it like a mathematical model such that if one of your numbers is different from plans/expectations, you should know which one of your assumptions to change.
4. Compare them to other familiar experiences.  This one is fun and easy and hugely valuable.  A few years ago I was working for a big global coffee company who wanted to open a big building near their headquarters that would showcase several of the things they do really well.  Their leader kept saying it would be a “Willy Wonka”-like experience.  The good news was that everyone knew what he meant.  The bad news was that the experience journey didn’t resemble the Willy Wonka Experience at all.  In the enroll/plan steps you had to get a golden ticket to do to Willy Wonka, not so with this coffee experience.   Willy Wonka offered a guided tour, not so with this coffee experience.  Everything was free in Willy Wonka, not so with the coffee experience.  And so on.  But instead of telling the coffee boss that he was wrong, we listed a number of familiar examples to be specific about which ones the journey experiences should be like – at every step along the way (discover, enroll, plan, arrive, experience, remember).  We used Nike Town, a popular local restaurant, a wine tour, Disney World and some others.  That made the discussion both fun and productive.  It also got the coffee boss to stop talking about Willy Wonka.  You should do this as well – and you ought to include some of your brand people from marketing because they will have some assertions about which brands you are like – and which ones you aspire to be more like (Apple, Nordstrom, and Amazon often come up as the best experience brands in the world) but remember that experience is just one of the steps in the journey  Expedia is one that often comes up as the best for the discover step, as one example of hundreds we have come up with over the years.
5. Don’t forget operations.  It’s very common for people to do the customer experience journey map and stop there.  That’s just the yin without the yang.  At every step of the way, there’s something going on operationally (it might be automated today, but it’s still there) behind the scenes.  Knowing where the operations cost, effort, and complexity is (and don’t forget regulations/compliance) so when you start to model the future state of an experience – be clear and specific about whether you are creating or removing operational work on the back end (it’s rarely neutral).  If you create work as you increase customer satisfaction, you may be lowering employee satisfaction and that can be as deadly as bad customer satisfaction.

Those are my pointers on journey mapping. Whether you are in agile software development or big data or brand management, these are key to success.

And don’t miss this TEDx talk about how technology is going to improve your quality of life.

Almost a year ago I wrote about how different the use of the expression “customer experience” is from just a short time ago in this blog post.  The gist of it is that it used to be a vague notion that couldn’t be measured and now it can be measured in all sorts of ways.  There’s a reference in that blog to an HBR piece by my friend Ewan Duncan from McKinsey who highlights how they found that the key elements of customer experience were literally between the touch points the client was actually measuring.  So they were literally measuring the wrong things and thus didn’t know when their customers were extremely unhappy.

I recently heard from my friend David Lancashire and his CTO Rob Pierry at Projekt202 – they do interesting work in customer experience and David told me about this piece that came out just yesterday in FastCompany.  There’s so much room for improvement in the airline industry – and with a firm like Projekt202, I am not surprised to see that Southwest has had success with them.

John Hawthorne is someone who got in touch with me and point out this piece about how to really wow customers and John made me realize that my previous blog post only pointed out the opportunity to define and measure customer experience differently – his piece does a great job of highlighting some not-so-obvious ways to go above and beyond in that department.

You MUST see this TEDx talk on customer experience and big data.

 

We continue to do some really groundbreaking work in the realm of customer experience and we look forward to telling you all about it when we can.  So stay tuned.

My friend Lance Knight wrote this very provocative piece recently and I am including both the text and the link.

I have a really deep background in CRM and I have read The Challenger Sale (I did a summary of that book using a new tool that lets you zoom in and zoom out of detail – message me if you are interested in that) and it struck me that what Lance is suggesting is on the one hand kind of obvious, and on the other hand somewhat shocking that no one has done this yet.  So have a read and let us know what you think.

-Ric (see the TEDx Talk on How Technology is Going to Improve Your Quality of Life – FINALLY)

Backlog, Teams, Closed Sales WHAT?  

People are racing to blockchain for some really good reasons – it reduces risk, creates efficiency, and adds transparency for industries as diverse as logistics, banking, and healthcare.  This article from The New York Times is a good explanation about it and what’s good about it.  And this TED talk by Don Tapscott offers a very clear explanation of what blockchain is.

But there’s an issue I haven’t heard people talking about that seems like a “Houston we have a problem” kind of risk – or if you saw the movie Ex Machina – it feels a bit like the AI issue that movie hints at.

This TED talk gets into the patterns that will emerge from Big Data.

If you haven’t seen Ex Machina – it’s an amazing thriller of a movie that suggests that once artificial intelligence gets smarter than we are (in this case in human form) there won’t be anything we can do to stop it – and the implications are pretty scary.

Yes.

If you have an open source platform that can trace the full chain of custody of everything from radishes on a container ship, to heart valves in a hospital, to every transaction in a financial services company – you have transparency into everything.  Part of the backbone of Wall Street and the global stock market is quarterly and annual forecasts and results.

If there is total transparency in all of these systems in real time and the systems are open sourced – even if companies try to make some or all of this data confidential or private – do you really think it won’t be hacked or exposed (if those two things are different)?  That’s the promise of blockchain.

Hacking the personal data of tens or hundreds of thousands of accounts at Target was big news a few years ago.  But hacking your grandmothers target account information is a bogeyman problem compared with gaining transparency to the global markets in real time.

Now one way to look at this is that if all of a sudden we can use machine learning to get predictive about that shipment of radishes to Whole Foods and what that means to their forecasts, and how many new accounts at Wells Fargo will do for their projections, or how many heart valves today will translate into Kaiser Permanente financial results – that real time global transparency will make the world smarter and we can do away with quarterly projections and that every thing will be run like Amazon (everything managed in real time).

But while that may seem like an interesting and viable end state – what seems like a more realistic outcome is that a small number of people will figure this out ahead of everyone (think The Big Short by Michael Lewis – but on a much bigger scale) and they will be able to game the entire global stock market.

That seems like a very big, very real risk and I don’t think we are ready for that.

So as we race to blockchain everything – let’s think through some of the downstream risks before we open up this new floodgate of Big Data.