Striking Datapoint from Mary Meeker’s Internet Trends 2015 Report

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May 29th, 2015

I spoke this morning with an operations executive at a large insurer which distributes personal lines products through independent agents. He said that they are working feverously to deliver digital service tools to the customer service representatives (CSRs) at agents because they know that the average CSR is now 19 to 26 years old. This insurer is transitioning from a telephony-centered approach to one which includes chat, secure messaging, and intelligent avatars in order to meet CSRs’ expectations about how service should be done. As any insurer distributing through the independent channel knows, the company that keeps the CSRs happy wins!

In our innovation research, we repeatedly see the influence of Millennials’ expectations around the consumer experience, but a datapoint from Mary Meeker’s Internet Trends 2015 report http://www.kpcb.com/internet-trends identifies an equal, if not higher, motivator for change from workers. Millennials now represent the largest percentage of the U.S. workforce.

Take a close look at Slide 109. It shows that in 2015, for the first time, Millennials make up 35% of U.S. workers. Gen X and Boomers represent 31% each. The data signals a tipping point and it is pretty clear which way this trend is going to continue.

Watch as the buzzword “Worker Experience” is added to the already well-worn “Consumer Experience”. For insurers that want to gain an advantage with their own workers, and with their distributors’ CSRs, the field is wide-open. All they need to do is innovate, experiment, put some funds at risk, and transition to digital working.

KPCB

A four year old’s employment records (or How not to handle a data breach)

Tom Scales

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May 28th, 2015

Yesterday one of my four year old twins received a letter from a major health insurance carrier (we’ll leave them nameless, tempting as it is). The letter states that the carrier had a data breach and that his information may have been included. The list was pretty extensive, including name, address, telephone number, email address, date of birth, social security number and employment history.

That’s a pretty big list and everything you need to steal an identity. They assure me that no health information was shared, but I think they have their priorities wrong. I don’t care if the thief knows I have high cholesterol, but I do care that they have my social security number. I admit I am curious about the employment history of my four year old – I think he has been holding out on me. I wondered how he had so many Legos.

The challenge? We’ve never had a policy from this particular carrier. Their FAQ site (a whopping four pages of minimal information) says it could have been because they process for other carriers, but nope, none of them either.

So I set out to find out more information, particularly whether others in the family were affected, since we are all on the same policy (Mom, Dad and five small kids).

I started my quest at 8:45am, on the website, and then the phone center opened at 9am. What a frustrating two hours. After talking to 11 people, from 4 different companies, do I know the answer to any of the questions? Not a single one. It all started with the vendor that the problem was outsourced too. I feel for those phone clerks, as they were provided almost no information. I then found a way to the carrier (a blog post in its own right), who didn’t know any more, but managed to transfer me to two other insurance companies, neither of whom had a clue why as they didn’t have a breach and I was never their customer.

My concern is that this means they don’t even know what was stolen, where it was stolen, who’s information was stolen and more. If they don’t know that about me, what about you?

I honestly don’t know how you protect yourself. You can’t really go off the grid. I could do without credit cards, and go to cash, but I can’t do without utilities or health insurance. I also understand that identity theft is big business, but the protections taken by major companies feel so lax. This is the FIFTH major breach of our family in less than 18 months. My credit card, from a major bank, has been replaced three times (only one breach was their own).

So to the point of the post, for those still with me:

If I was responsible for data security at any of these firms, I’d fire myself. There are solid, dependable companies doing security work. If you r company has not hired one to test your security, do it. Do it today. You should be doing penetration tests, at least annually. You should have solid company policies on data access, and that access should be extremely limited. People need information to do their jobs, but they don’t need all the information. Does your company have a data governance policy? If not, start today. We all know that IT budgets are limited and that our user communities, including our customers, want more and broader access. I just caution that you move with speed, but not without safeguards. Everything can be breached. Your firewalls, your apps, your website and even, as in the case of one breach, your cash registers.

More important than all of this, though, is how you handle the breach when it occurs. Even with the most amazing safeguards, some pretty smart people, and governments, are hacking into private data. When it occurs, it should not be a shock to your company. You shouldn’t mobilize a task force after it happens. You should never consider this an IT problem – it is a major problem for the most senior levels of your company, and your reputation. Your company probably has, I hope, an IT Disaster Recovery (DR) plan. Does it include a data breach? Many don’t. They worry about floods, power outages, even pandemics, but not a data breach. Even if your DR plan does include data breach, are the actions your company will take fully laid out? If you are going to use a vendor, have they been chosen and briefed and is the conduit of key information already prepped? Is the spokesman for your company prepared and ready to speak publicly immediately? In my case, the time between the public announcement of the breach and the time we received the letter was over three months. Three months!

Hopefully this post will cause at least one reader to start asking questions in their company and that those questions will be well received.

You don’t want to be the next company in the news, do you?

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Your Natural Best Friend will certainly know that you are sad. But will your customer service chat bot know?

Donald Light

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May 27th, 2015

AI and machine learning things are moving right along.

A few months ago, in a Celent report, I predicted the emergence of a “Natural Best Friend,” a term combining “natural language” and “best friends forever.” However, there is nothing organic about the Natural Best Friend; it is completely a product of technology.

The Natural Best Friend will at some point pass the Turing Test (interacting with a person in a way that is indistinguishable from how another person would interact). Natural Best Friends will become sources of not only trusted information and advice, but also of companionship, friendship, and perhaps even some form of wisdom and intimacy.

The use of the Natural Best Friend has obvious applications in throughout the entire insurance life cycle: from underwriting to service to claims. Even the possible characteristics of companionship, friendship, wisdom, and intimacy may be of use to insurers. Consider insurers’ brands, built over decades, which stand for trust, reliability, and succor. Once it becomes socially normal to have a personal relationship with the Natural Best Friend, insurers’ (and many other service industries’) sales and service processes will change dramatically.

IBM has just announced it is developing customer service software that can interpret the customer’s emotional state by the content and pattern of the customer’s chat messages. Somewhere in the future, the software may be able to analyze a customer’s voice to determine the emotional playing field. Here’s a link to the WSJ story (warning: this might be behind a paywall).

The family tree that will produce a baby boom of Natural Best Friends now has a new branch.

The critical importance of testing

Tom Scales

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May 26th, 2015

It should go without saying, but good testing is absolutely critical to producing technology that benefits your organization. As a former insurer CIO, I can attest that the group most often squeezed to meet a deliverable date is the quality assurance team that has the incredible responsibility to ensure accuracy.

Perhaps our organization was unique, but having also spent years at vendors, doing implementations, I see it happen over and over. Projects run late and rather than adjusting the date, or the project content, testing gets squeezed, often with unintended consequences.

The corollary to poor testing is “Day 2.” This is code in the IT community for “we didn’t get it done, but will let someone else worry about it later.” This is compounded in the Life insurance industry, as “later” can sometimes be measured in years. This means that the team that built the code may be long gone by the time Day 2 rolls around, or worse, the fact that there are open items will be lost in the history or lore of the organization.

The reason I bring this topic up is an article I read recently that dramatically shows the challenges of inadequate testing. For the nerds amongst our readership, one of the classic fails of programming is an overflow. For the non-nerds, this just means you have a counter in your program that isn’t big enough. Rather than continuing to count up, it wraps back to zero and starts over. The results can be major to a program and it is an error that might not be discovered for years. Remember, you’re counting something, so reaching this limit can take a long time.

The latest programming error to experience an overflow? The Boeing 787 Dreamliner.

It seems that you need to reboot the plane every 248 days or risk the plane falling from the sky. 248 days, measured differently, 2^31 one-hundredths of a second. Now I have no idea what they’re counting, but apparently it is pretty important.

Should testing have caught this? Of course. Did it? Apparently not.

So the next time you want to cut short testing, remember this post and ask yourself “should we?” You may not have a plane falling from the sky, but you could have a hidden calculation error that could cost your company. Take a small error and multiply it over time and it quickly becomes a very, very large error. A potentially catastrophic financial error.

The rise and fall (and rise) of Artificial Intelligence

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May 21st, 2015

Artificial intelligence has been around nearly as long as humans have been able to think about themselves, about thought and what they do. Empathy is wired into us – some more than others but we are all capable of thinking from another’s point of view. This capacity leads us to anthropomorphize things that aren’t human, to imbue things in our daily lives with human qualities like moods, characteristics and personality. When we build puppets, robots, models that look sort of human it is easy to for us to assign it with greater power, ability and promise than is really there. For marketers in other fields, to have consumers attribute their products with ‘magical’ properties would be a dream come true but for artificial intelligence it is a nightmare – one the industry has expended funds marketing against.

Artificial intelligence has delivered many great tools which today we take for granted. Our phones listen to us and understand our requests in the context of our calendar, our camera’s recognise faces and social networks tell us who those faces belong to, machines translate words from one language to another (although don’t get the translations tattooed just yet) and the list goes on. We chuckle at these mistakes these learning and adaptive systems make, we see the huge strides and investment and we expect a new human like intelligence to emerge in the short term. Around the middle of every decade since the 60’s there has been a peak in excitement for AI, a frustration with it’s lack of progress, and a reduction of funding or AI winters as they are called. In the eighties it was LISP machines, in the nineties it was expert systems. Now in the twenty-tens (I thought it was teenies but that’s a kids show apparently) we are seeing a resurgence of AI, a blending of machine learning, predictive modelling and cognitive computing along with self driving cars.

This raises some rare and interesting questions:

  • Are we headed for a new AI winter?
  • Or an AI apocalypse?
  • Also, will I still be cleaning my home in 2020?

It is certainly true to say the set of tasks we can expect software and physical computing systems to do is vastly increased compared to just a decade ago, and massively so since the 60s.

Doing all the things humans can do and living in our society, empathising and understanding us in that broad context is still well beyond computers – but engaging with us in specific, well-defined domains such as about our calendar or what we would like to buy from the shop is well within their grasp today.

Previously difficult tasks such as searching a database for information, reading that from a screen and keying it into another screen is now entirely possible – see the earlier blog post on bots.

Having a drone fly itself around an obstacle to reach an objective is still very hard. Having a vehicle drive itself on the road is in fact easier, albeit most humans don’t benefit from lidar sensors, ultrasonics and eyes in the back of their head (alright, bumper).

It is good to see AI on the rise again – I loved the topic ever since getting into programming and getting involved in a cognitive psychology course some years ago. I recall writing an expert system in Pascal back in the 90s.

I am concerned, as the insurance industry should be, by a new AI winter. Self driving cars and vehicles have the potential to make the roads safer for all. We will when we see them, imbue them with more power than they have – this is human nature. We will, in the not too distant future, hear people say things like, “the car likes to give cyclists a lot of room on the road” or “the car prefers to take this corner at a fair speed” – imbuing a complex machine with sensors and programming with preferences, desires and likes – human qualities.

When the first death comes we will ask how could it do such a thing. When an automated car is put in a position where it must decide between a set of actions – each leading to injury, we will hear people discuss why it chose to do what it did, people may say, “it did the best it could” or worse, “no person would ever have done that, this is why machines shouldn’t be able to choose.” The latter of course revealing the human construct, an unspoken contract – our expectation that smart or intelligent systems will operate like us, share our values, our culture, that we can predict their actions in our context. This is the greatest threat to AI and always has been – the expectation, the contract that the new intelligence will be like human intelligence. Some winters are due in part to that contract being broken, to these systems not living up to the expectation and making inhuman mistakes.

There are a set of tools available now that are not intelligent but they are smart and they are powerful. We would be remiss in our duty to our customers and shareholders if we do not leverage them. Manage expectations about these powerful tools and understand the very real limits that exist on them. If we can do this we may benefit from the AI boom and avoid another AI Winter.

Will we see an AI apocalypse? Ironically it’s not the human like intelligence that may be our greatest threat but simpler intelligences. A human like intelligence could empathise, could act in acordance with values and could be relatively predictable (in a human way). There are many stories across science fiction of smart robots that act like insects and replicate, in fact that only make copies of themselves, that pose a great threat to any civilisation. They are not intelligent, they don’t want to kill off all life in the galaxy – they just turn all the available resources into copies of themselves which would have that effect. We are much closer to building that threat frankly (with drones, 3d printers, etc.), than a super intelligence that decides all human life is worthless. For now though – I expect these things to stay firmly in the space of science fiction. I include this discussion here because it does demonstrate a key difference between smart with unintended consequences and ‘intelligent’ – a lesson worth bearing in mind for those adopting AI.

Finally – will we see robots cleaning our homes by 2020? Well roomba is out there and sort of does that. Stairs and steps are still a huge challenge to robots. Frankly differentiating furniture, pets, clutter, magazines, rubbish, dust and recycling in a moving environment is still a very complex issue.

As in insurance, I think smart things will make cleaning easier and assist those who invest but there’ll be a role for human intelligence in ensuring the pets aren’t recycled and the customer ultimately gets the service they expect.

Strategic issues in insurance distribution management

Karlyn Carnahan

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May 18th, 2015

Carriers use a variety of techniques for growing the book and most consider distribution management as a key component of their growth strategy. They are expanding channels, adding distributors, moving into new territories, and working to optimize their existing channel to improve customer acquisition and retention. Some carriers are investing in improving the servicing of distribution channels. Others are focused on managing the compliance aspects of distribution management — assuring the distributors have the right licenses, and that state appointments are made in a timely manner. Many carriers are concentrating on using compensation tools and techniques to more effectively stimulate production.

To understand what top carriers are doing in this area, I conducted a survey of carriers around this topic. The goal of the survey was to understand how the carriers are organized to manage the distribution channel, what types of techniques they use, how effective those techniques are, and what challenges they face. Check it out here.

  • In most organizations, a formal Distribution Management organization has primary responsibility for channel management. Managing relationships and compliance are seen as the biggest issues they face.
  • A wide variety of compensation techniques are used by carriers and most say they get value from those programs – although carriers report that it is more important to calculate compensation accurately than to assure compensation is effective at driving desired business. Some techniques such as incentive comp and contests may only be available to top tier or qualifying agents – but receive mixed reviews on their effectiveness. Only 25% of those offering incentive compensation programs see them as effective. “Having an incentive compensation program isn’t highly effective, but not having one would be even worse.”
  • Most carriers rely on a variety of different systems to manage compensation – including Excel and find efficient calculation and distribution of compensation to be quite challenging. For many, the ability to administer a compensation program easily is the key driver as to whether the program will be offered. While they may wish to utilize a particular technique, their technologies create barriers.
  • Compliance is another challenging area with many carriers in the early phase of considering additional automation.  Fewer than half of carriers have automated any of the major processes – validating licenses, processing an appointment or providing self-service to distributors. Those that have automated the processes generally report them as delivering value.

Managing the distribution channel requires discipline in a number of areas – from managing the day-to-day relationship, assuring the distributor is in compliance with the licenses and appointments, and strategically managing compensation. However, carriers face significant challenges in performing these tasks efficiently. Carriers looking to improve distribution effectiveness use technology as a strategic differentiator.

CCC acquires a telematics platform: the story behind the story

Donald Light

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May 12th, 2015

Today CCC announced the acquisition of DriveFactor which provides a device independent platform for telematics data and analysis.

Why is an auto physical damage estimation and analytics firm acquiring a telematics platform provider?

Well, you could say that telematics is hot, and all personal and commercial insurers writing auto insurance are scrambling to build market share. That is true enough.

You could also say that telematics data is going to be increasingly valuable in determining causation and relative responsibility for auto accidents: how fast was each car driving around a corner, who braked first, and how hard, etc.? That is also true.

But that is not the whole story.

The year is 2018. I am driving a new car, and I am in an accident. My car knows it is damaged. It also knows which systems and parts were damaged and need repair or replacement. And it knows the fastest, best, and least expensive way for that to happen. It might even know about the probability of personal injuries among my car’s occupants.

This is all pretty valuable information.

Who is my car going to give this information to?

  • Its manufacturer? My insurance company?  Emergency responders? Towing companies? Auto repair facilities? Or software companies that estimate the cost of repairs?

And what is the value of such data from tens or hundreds of thousands of accidents?

A telematics platform that can order the flow of this information suddenly starts looking quite valuable.

Robotics, bots and chocolate teapots

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May 8th, 2015

Increasingly in operational efficiency and automation circles we’re hearing about bots and robotics. As a software engineer in days past and a recovering enterprise architect I have given up biting my tongue and repeatedly note that, “we have seen it all before.” I’ve written screen scrapers that get code out of screens, written code to drive terminal applications and even hunted around user interfaces to find buttons to press. The early price comparison websites over a decade ago used these techniques to do the comparison. These techniques work for a while but are desperately fragile when someone changes the name of a button, or a screen or a screen flow.

However, they can help. I recall a while ago a manager lamenting ‘the solution’ was about as useful as a chocolate teapot. A useful 10 minutes hunting for this video of a chocolate teapot holding boiling water for one whole pot of tea made the point for me. Sometimes all you need is one pot of tea.

Tea poured from a chocolate tea pot

Tea poured from a chocolate tea pot

So it’s not new, some bots may be fragile and with my “efficiency of IT spend” hat on (the one typically worn by enterprise architects) stitching automation together by having software do what people do is an awful solution – but as a pragmatist sometimes it’s good enough.

Things have moved on. Rather than a physical machine running this with a ghost apparently operating mouse and keyboard we have virtual machines and monitoring of this is a lot better than it used to be. Further machine learning and artificial intelligence libraries are now getting robust enough to contribute meaningfully smart or learning bots into the mix that can do a bit more than rote button pressing and reading screens.

In fact this is all reminiscent of the AI dream of mutli-agent systems and distributed artificial intelligence where autonomous agents collaborated on learning and problem solving tasks amongst other things. The replacement of teams of humans working on tasks with teams of bots directly aligns with this early vision. The way these systems are now stitched together owes much to the recent work on service oriented architecture, component orchestration and modern approaches to monitoring distributed Internet scale applications.

For outsourcers it makes a great deal of sense. The legacy systems are controlled and unlikely to change, the benefits are quick and if these bots do break they can have a team looking after many bots across their estate and fix them swiftly. It may not be as elegant as SOA purists would like but it helps them automate and achieve their objectives. The language frustrates me though, albeit bots is better than chocolate teapots. I’ve heard bot referred to as a chunk of code to run, a machine learning model and a virtual machine running the code. I’ve even heard discussion comparing the number staff saved to the number of bots in play – I can well imagine operations leads in the future including bot efficiency in their KPIs. Personally, I’d rather we discussed them for what they are – virtual desktops, screen scraper components, regression models, decision trees, code, bits of SQL were appropriate, etc. rather than bucket them together but perhaps I’m too close to the technology.

In short bots may not be a well-defined term but the collection it describes is another useful set of tools, that are becoming increasingly robust, to add to the architects toolkit.

Smartwatch adoption: Don’t end up as a laggard

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May 7th, 2015

Timex-DataLink_04LLet me present you my first smart watch: Timex Datalink. My mom gave me this as a present when I was 23, back in 1995 (Oh my, I just gave out my age!).

For those that haven’t seen one of these, it was the first watch capable of downloading information from a computer. Co-developed by Timex and Microsoft it was capable of data transferring from outlook calendar and tasks, No email, no voice unfortunately.

It didn’t look very different than any other digital watches from that time (did I mention they were water resistant?), but they were unique because they could synchronise wirelessly through light (using the monitor screen) with the computer and data was transferred from the computer to the watch quickly and easily.

It seemed revolutionary those days. Nevertheless, it was a complete failure (do you see them somewhere today?) While the concept was fine, they were too ahead in time so the functionality was very limited, and there was no integration with mobile devices and apps (they didn’t exist!).

So when everyone started talking about smart watches (again) I remembered my old Timex Datalink. I don’t use watches anymore (smart watch or not), but back then I did. So this triggered my curiosity as what are the chances for smart watches to succeed. I decided to run a small poll between my friends and asked:

  1. Would you use a smart watch?
  2. Why?
  3. Under what circumstances would you consider using one?

This is what I discovered:

  • Some people (10%) don’t know what a smart watch is.
  • 10% said no, my smartphone provides me all I need plus if smart watches connect through Bluetooth they make batteries die fast. They would only consider using a smart watch if it is free (as part of a smartphone purchase for example) and technology improves (and battery life becomes a non-issue).
  • 40% said they don’t use watches today so why start using it now? They recognize that it needs to have a compelling advantage over the other devices we use today (mobile, tablet, laptop, etc.). If it is about health monitoring there are a plenty of devices in the format of wristbands that they would use instead. Video streaming would be another good reason to adopt it.
  • 10% answered that a watch is something related to fashion (and in some cases luxury) so unless an established well recognized fashion/luxury watch maker brand enters into the segment and makes them attractive, there is no way they would use it. Clearly this segment of consumers wouldn’t buy it from Apple, even if they come in gold and with diamonds, but they would buy it from Rolex for example. The good news for them is that Rolex is launching one.
  • 10% said they would use it out of curiosity (this reminds me myself back then with the Timex Datalink smart watch). If smart watches provide much more functionality and convenience than they did before, there is a chance that this segment may continue to use them after the “trial” period.
  • 20% said definitely they would use a smart watch. Even more, they believe that it will become an accessory required for many daily tasks and interaction with business as in health for example. If you get a discount in health insurance (or life insurance) associated to a healthy lifestyle, a smart watch seems an ideal device to combine the monitoring capacity with other daily activities as talking and mailing. For those that today carry a watch it will be a seamless experience compared to when we moved from landlines to mobiles. Insurers moving into the use of wearables, including smartphones, to monitor lifestyle and provide benefits associated to it, will encourage adoption by people in this segment.

Some conclusions around this small and targeted survey are that smart watches don’t escape to the same logic of any other product market introduction. There are clearly some early adopters (30%) but with risk of some dropping out if the product does not convince (those that would use it out of curiosity). Pragmatists, that would only use it if provides a clear advantage (40%). Some of these will fall into laggards (or not adopt it) if they don’t see a real benefit. Conservatives, more reluctant to change as they perceive watches to have a different meaning (and use) than smart watches. Finally, laggards that will see how everything evolvers before jumping in (20%).

Bell curve

We need to see what happens with wearables in general, as there may be other devices and interfaces better than a watch? In my opinion there is still a long way to go before having all the ducks in a row, but no doubt that if linked to real benefits such as savings and convenience the chances of smart watches to succeed increases. Insurers, if not doing it yet, should be considering smart watches and wearables in general as part of its products and its customer experience. Don’t wait to see who the winner is in the wearables segment of the IoT, or you may end on team laggard.

Pushing beyond apps

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Apr 30th, 2015

It struck me while I was driving this morning: First-gen mobile apps are fine, but virtually everyone is missing high-volume opportunities to engage with their customers.

Allow me to back up a step. I was stuck in traffic. Not surprisingly, that gave me some time to ponder my driving experience. I found myself thinking: Why can’t I give my car’s navigation system deep personalizations to help it think the way I do? And how do I get around its singular focus on getting from Point A to Point B?

I explored the system while at a red light. It had jammed me onto yet another “Fastest Route,” disguised as a parking lot. My tweaks to the system didn’t seem to help.

I decided what I’d really like is a Creativity slider so I could tell my nav how far out there to be in determining my route. Suburban side streets, public transportation, going north to eventually head south, and even well-connected parking lots are all nominally on the table when I’m at the helm. So why can’t I tell my nav to think like me?

I’d also like a more personal, periodic verbal update on my likely arrival time, which over the course of my trip this morning went from 38 minutes to almost twice that due to traffic.

The time element is important, of course. But maybe my nav system should sense when I’m agitated (a combination of wearables and telematics would be a strong indicator) and do something to keep me from going off the deep end. Jokes? Soothing music? Directions to highly-rated nearby bakeries? Words of serenity? More configurability is required, obviously, or some really clever automated customization.

Then an even more radical thought struck. Why couldn’t my nav help me navigate not only my trip but my morning as well? “Mr. Weber, you will be in heavy traffic for the next 20 minutes. Shall I read through your unopened emails for you while you wait?” Or, “Your calendar indicates that you have an appointment before your anticipated arrival time. Shall I email the participants to let them know you’re running late?” Or (perhaps if I’m not that agitated), “While you have a few minutes would you like to check your bank balances, or talk to someone about your auto insurance renewal which is due in 10 days?”

What I’m describing here is a level of engagement between me and my mobile devices which is difficult to foster, for both technical and psychological reasons. And it doesn’t work if a nav system is simply a nav system that doesn’t have contextual information about the user. But imagine the benefits if the navigation company, a financial institution, and other consumer-focused firms thought through the consumer experience more holistically. By sensibly injecting themselves into consumers’ daily routines—even when those routines are stressful—companies will have a powerful connection to their customers that will be almost impossible to dislodge. Firms like Google have started down this path, but financial institutions need to push their way into the conversation as well.