Welcome!

Who is Robert Schlaff?

I’m a devoted husband and father to an awesome family who works at AIG as Head of Commercial Digital Product. For more information about what I do at work, please visit my LinkedIn profile.

What is a Digital Raconteur?

Throughout the 1920s, some friends would meet daily for lunch at the Algonquin Hotel in New York. They included the founding editor of the New Yorker Harold Ross, the playwright George S. Kaufmann and the writer Dorothy Parker. This group, called The Algonquin Round Table,  would meet to tell stories and share quips in a bustling city that was finding its place on the world stage. They were the original raconteurs of New York, getting together to share stories that would enlighten and entertain. In an age when we no longer have two martini lunches, I wanted humbly bring that sensibility online.

Highlights

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Math and Logic

The Mother-in-Law’s Guide to Cloud Computing

This is part of my “Mother-in-Law’s Guide to Technology.” My Mother-in-Law is a very smart woman even if she isn’t a “computer person.” The goal of this post is to take a very big and treacherous sounding idea and bring it down to earth. I tried this before in a post which I’ve now renamed The Mother-In-Law’s Guide to Chaos Engineering.

Dearest Mother-in-Law,

You know when we visit a Target or a Wal-Mart in the suburbs and they have 30 checkout lanes and only 3 are open at any time? I always wondered why that happens. It even sparked someone to write a funny blog post about the phenomenon: Target Store Opens More than Three Checkout Lanes; Shoppers Confused.

On a Normal Day, the Store Has Full Time Cashiers to Manage the Base Volume. When More People Come In, Part-Time Cashiers Will Be Engaged.

How many checkout lanes should Target build? At first, I thought about how many customers Target has on an average day and that they built that number of cash registers. If they have 300 customers in a day they would need enough cashiers to serve 300 people. The problem is that the flow of people into the store isn’t constant. For example, if the peak time of day is at 4PM and there are 10 people in line, Target can’t tell those people to come back at a less busy time. So on a daily basis, they need to plan for this by making sure they have enough checkout counters (and cashiers) available to keep the lines down to a reasonable level even when it gets busy. The way most retailers do this is to have only a few full-time dedicated as cashiers for the slow times and some other part-time cashiers that mainly do another job but can jump in when the store gets busy.

But that doesn’t answer the question of how many checkout lanes they need to build. Target needs to have enough checkout lanes so that even on the busiest days, they can hire enough part-time cashiers to keep lines relatively short. This means that Target needs to build the number of checkout lanes that they need for the busy time of the year, not for the peak time of day. At Target, this is the Christmas shopping season starting with Black Friday. On Black Friday the store is filled with shoppers struggling to check out. This is the day that Target opens up all their checkout lanes. So even though they’re not used a good portion of the year, Target still needs to build the number of checkout lanes they need for Black Friday.

The Number of People on Black Friday is Much Greater Than That of a Normal Day. This Drives the Total Number of Checkout Lanes.

So what does this have to do with cloud computing? Cloud computing is like Target having these checkout lanes only where they’re needed, like on Black Friday. They wouldn’t have to pay for the cost of having these checkout lanes at less busy times of the year. They would be able to create new ones during the Christmas season and get rid of them at other times of the year. How does this work? Instead of buying checkout lanes (or in the case of cloud computing, computers), they just rent what you need. This means that Target can increase or decrease their capacity based on the actual need from your customers.

Now let’s make the jump from Target to Cloud Computing by defining a few Let’s define a few things:

  • Servers: These are computers that “serve up” the information you need. Just like the cashiers at Target, if a server isn’t available you’re going to have to wait in line.
  • Server Capacity: This is the total number of servers that can be available to provide information. Just like the number of checkout lanes at Target, once you’re out of checkout lanes, you can’t have any more cashiers.
  • Peak Request times: This is your Black Friday time when you the most requests.

Now you can understand one of the key benefits of cloud computing:

Cloud computing provides flexible server capacity to meet demand during peak request times and release that capacity at during other periods.

So there you have it. In the real world, Target needs to build enough capacity (checkout lanes)  to meet demand during peak request times (Black Friday). But the cloud computing model allows companies to greatly reduce their capacity during non-peak times because they can easily turn on or turn off this capacity.

Note: You can actually see a checkout model like this (sans the physical checkout lanes) at Apple stores. They can easily increase or decrease capacity because they don’t have any physical checkout aisles. This allows for flexibility by just adding or removing salespeople to the store with their mobile checkout devices. 

Additional Resources: For more information on managing lines check out this quick overview from FiveThirtyEight. For more on Cloud Computing, take a look at Google Cloud Platform training or Amazon Web Services training. You can audit classes for free.

 

 

The Value of Big Data: Why It’s Difficult to Monetize and How Google Does It

I recently attended a session on Autonomous Cars at the law firm Herbert Smith Freehills. It was an insightful session where the lawyers gave great presentations on legal issues they advise on, like M&A, regulatory and product liability. However, one non-legal item they talked about was the ability for car manufacturers to “monetize data.” The idea of monetizing data comes up often but it’s a lot harder than it sounds.

A decade ago, I was working for a large credit card company looking at new growth opportunities. We were convinced that we could become the most valuable company in the world. Our reasoning went like this. Google was worth billions of dollars. But Google’s value was based on what web links people clicked. We, as a credit card company, had data on what people actually bought. Because our data was more relevant to advertisers than Google’s data, we should clearly have been worth more than Google.

There was just one problem. While we had this data, so did Bank of America, Capital One, JP Morgan and every other bank. And everyone was looking to monetize their data.

Did I say one problem? It wasn’t just financial services companies looking to out-Google Google. The phone companies were in this game too. They were saying, “Hey, we should be the most valuable companies in the world. Google has data on where people go on the web, but we have data on where people actually are in the real world.” Suffice it to say, there was a lot of data around.

This reminded me of an article written about undersea cable capacity in the days of the telegraph. Andy Kessler shared the following cautionary tale:

After undersea telegraph messages were first sent between Newfoundland and Ireland in 1886, a half-dozen companies sprang up to relay messages between London and Paris and New York. Half the traffic was for stock trading. These companies charged up to $5 per word and could transmit 15 to 17 words per minute. Each thought it could generate revenues of $5 million dollars or more per year. It was easy to raise the $2 million it took to lay undersea cable and investors, who constantly dashed off telegrams themselves, were all too happy to lend money.

Each of these companies assumed that they’d have a monopoly on the market. But when many companies entered the market based on that same assumption, all of the excess capacity created a race to the bottom for telegraph message pricing, forcing many of the companies into bankruptcy.

So what makes Google different? I remember a discussion with stock analysts around that time. I had written a paper on Mobile Payments along with Citi’s Equity Analysts. The topic of data was very hot and various analysts asked me, “Who’s going to win the data game? Who has the best data?” I explained that the real differentiator, and what people will pay for, isn’t the data itself but what you can do with the data.

As the famous Harvard Marketing professor, Theodore Levitt said, “People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!” In the data space, this would be, “People don’t want to buy data, they want to buy results!”

How Google Uses Big Data

The goal of a search engine is to find the most relevant documents. In the early days of search engines, things were relatively easy. You could:

  1. Examine Web Pages: Early search engines like Lycos and Altavista would look at web pages and determine which ones were the most relevant. They would do this by looking at factors like the number of times a word was repeated or whether the search term was in the title of the document.
  2. Curated Directory: Yahoo, on the other hand, had humans hand-curating the web into a giant directory. This was relatively easy when the web only had a few thousand pages.
My Interpretation of the Early Web. With Only a Few Pages, Choosing a Winner Wasn’t That Difficult.  

However, as the web grew, it became more and more difficult to manage search with these methods. Lycos and Altavista were overwhelmed. Not only was it difficult to distinguish between multiple similar pages based on the text in the page but there was also web spam that was trying to fool the search engines into promoting their pages. Yahoo had a problem hiring enough people to keep up with the quickly growing web. Both had doomed strategies.

The State of Web Search When Google Entered the Game. As the Web Started Exploding, Finding the Best Pages Became Increasingly More Difficult.
Google went down a different path. By using an algorithm called PageRank (after Larry Page), formerly called BackRub (oh those Googlers and their funny names), Google was able to make use of data that everyone else was overlooking. The links between pages were just as valuable as the data in the pages themselves. For example, any page can claim to be the authoritative page of IBM. But if 100 people point to IBM.com as the right answer, it’s easy to lift that one to the top.
Google Changed the Game by Using Links from Other Sites as a Measure of Quality

There are a few things to realize about Google’s use of data:

1.  Google didn’t have the “best” data. Yahoo had a more accurate method for categorizing the web. Having humans look at content gave better results for each individual page. Unfortunately for Yahoo, that method was too slow and expensive to sustain.

2.  The data didn’t cost Google anything. At the time, everyone was concentrating on the web pages themselves — not the linkages between the pages. This kind of information is often called “information exhaust” — information that’s a by-product of what you’re really looking for. It was already out there, free for anyone to use.

3.  It’s the capability that made the difference. While the data was free, it was up to Google to organize the data and make it useful. Going back to the jobs to be done metaphor, Google put this data to work solving a problem for users.

4.  More data is better. While other search engines were getting overwhelmed by the torrent of data from an explosion of web content, Google’s product actually benefited: The more links that can point to a quality web page, the better search results Google produces.

Google has been using this template for various other projects since they were founded. They can leverage data in some very creative and useful ways. Take location data for example. If you have an Android phone or Google Maps on your phone, Google is keeping track of your location data. You can take a look at your data here. The data is useful to me but it’s a bit odd seeing that Google holds a record of everywhere I’ve been.

An Example of Google Tracking Me Through the Day.

So how can Google use your location, along with that of others, to create value? Well, one way is to aggregate this data to show where there’s road traffic. If you have a lot of phones not moving, then you can flag that road as congested. But where else could Google use this data? Google added a feature to Google Maps that let you see how crowded a restaurant was at different times of day based on how many cell phones they found at the restaurant.

A Graph of Popular Times at Bubby’s Restaurant Compiled Through Location Data. Note the Popularity of Sunday Brunch.

It’s important to remember that Google did not have the best data to determine busy times at restaurants. Telephone companies and restaurant sites (e.g., Yelp, OpenTable) likely had better data. For example, OpenTable manages the reservations systems for many restaurants and actually knows how busy they are. But yet again, Google was the best at putting the data to work at solving this problem.

So let’s sum up. People still talk about monetizing data but their data isn’t as valuable as they think it is. There’s a lot of data out there that can solve problems and generate value. The tricky part is extracting the value from the data. Google did this in search and continues to do so in lots of other ways.

Note: Ben Thompson from Stratechery gave a similar talk about how Google works last week to kick off the University of Chicago Antitrust and Competition Conference.

The Hidden Thirteenth Floor

In my apartment building, like many others, there’s no 13th floor. The floors go right from 12 to 14.

Some people in our building thought it would be funny to tell the boys that they lived on 13. The boys would look between 12 and 14 and say “But there is no 13.” Then they discovered something very interesting. The designers of the elevator pattern needed to make a “B” for the basement. In order to make the circles in the middle of the “B” they decided to make the design into a 13.

This isn’t an accident and is done with other logos and graphic designs. Take the FedEx logo for example.

I bet you never noticed the arrow.

Or the Amazon arrow that tells you that they sell everything from “A” to “Z.”

And there’s many more.

Now the boys ask everyone where the 13 is on the elevator panel. Boy are the adults surprised.

In Praise of Humility — The Forgotten Story of Edward S. Harkness

The Residential Colleges were created 85 years ago. Though they have the names of many famous Yalies, the donor of these colleges is nowhere to be seen. Why?

What is a Yalie? When I think of the archetypical Yalie, I think of two things. First, a Yalie is someone who will do great things and change the world. Second, a Yalie has great human qualities of humility, philanthropy and caring for others.  While Yalies are always reminded of our great alumni plastered across campus, we rarely see the humbler and more human side. That’s why it’s important to remember Edward S. Harkness. Continue reading “In Praise of Humility — The Forgotten Story of Edward S. Harkness”

Design Challenge: Makeup Kits for Female Astronauts

It’s always hard to design products that you are never going to use yourself.  One of the most interesting design challenges in history was the equipment for the first astronauts. And once the women went up in space,  the problem for the (mostly) male engineers only got worse. Take the example of the makeup kit.

As you can see in the above tweet, Sally Ride and other female astronauts were offended that makeup kits would even be considered on the shuttle. Dr. Ride didn’t even wear makeup on earth — she was a hardcore physicist.

If you look at the responses to the Tweet the story is clear. “What stupid engineers. Don’t they understand that these are scientists, not women?” There’s even a Quartz article titled NASA Engineers Thought Female Astronauts Needed A Full Face Of Makeup.

But that’s not the real reason that makeup kits were put onboard. Astronauts had always had a set of personal hygiene products onboard like shampoo, nail clippers,  toothbrushes, dental floss and lotion. While Ride didn’t care about the makeup kit, other astronauts did. Rhea Seddon, was the one that spoke up. She writes in her blog:

After a little of the usual small talk, they came to the point. Did we want to have makeup in flight?

Some of the women Astronauts never wore makeup anyway, so they said adamantly “NO!” Some of us did. Was this to be a majority rule decision?

I spoke up for the minority. If there would be pictures taken of me from space, I didn’t want to fade into the background so I requested some basic items. All agreed that a small kit with items of our choosing would be a “preference item,” that is, stowed only if requested.

(It was interesting to me that that I wasn’t the sole space traveler whose in-flight pictures showed a bit of lipstick and blush.)

As it turns out, when you ask an astronaut, “Do you need makeup to do your job?” The answer is of course, “No.” But remember that astronauts aren’t just scientists, they’re public figures. If you ask the question differently, “Do you want makeup when pictured on newscasts around the world?” the answer is quite different. It reminded me of the Amy Schumer parody You Don’t Need Makeup.

In summary, as a designer, you need to do your best. Ask the questions you need to ask, even if it makes you look silly. And make sure that you’re taking into account the needs of all your users, not just the most vocal ones.

 

The Future of Payments

When I was working at Citi Cards, I was under the impression that people were spending a lot of time figuring out what credit cards they should have. Were they going to get points or miles? Weren’t they going to be so excited that they could redeem their points with Amazon? Of course, working in a credit card company I was thinking about this all day and I lost sight of the fact that my customers had far better things to do with their time.

That’s why the Pymnts.com study on How We Will Pay caught my eye. The study highlighted a couple of key numbers I hadn’t thought about:

  • 61% of shoppers don’t enjoy the act of shopping
  • 66% of consumers would use a connected device to enable a seamless shopping experience

In short, most people don’t like shopping and find payments an even worse pain to deal with. The future of payments isn’t about making payments cooler (a la Venmo) it’s making them invisible. My friend Ashwin Shirvaikar described this as Internet of Things Payments in his section of Disruptive Innovations V.

But what does a future of transparent payments look like? Some examples are:

  • Uber already integrates payments seamlessly into its app. You don’t think about “paying” for an Uber. You think about booking a trip and the payment is part of that. It’s like express check out at a hotel.
  • Slice On-demand Insurance is an insurance platform for the “Gig Economy.” Slice provides insurance to Airbnb hosts and Uber drivers only when they are providing services. It integrates seamlessly into the buying transaction by providing insurance any time the host takes a reservation.
  • Parkmobile, a leader in mobile parking, has developed an integrated parking solution with BMW.  When parking at a Parkmobile enabled location, drivers will be able to begin a parking session directly from their dashboards without leaving their car to pay a meter. The parking session is terminated once the driver leaves the spot. 

But who should develop the future of payments? The Pymnts’ How Will We Pay survey asked this question to consumers. Interestingly enough, the top named company was Amazon.

The Pymnts’ How Will We Pay Survey. Note: Super Connected Consumers Have 6+ Devices That are Not Laptops, Smartphones or Tablets

So why does Amazon come up so high on this list? Because customers want an innovative shopping experience, not an innovative payments experience.

The best example of this is Amazon Go. Amazon Go is a prototype payments experience of the future. Customers go into an Amazon Go store, pick up their items and leave. Checkout is performed automatically when the customer leaves the store. While there are currently some issues around the price to create these stores (automation being more pricey than human labor) and theft due to shoplifting, this is a good view of the future of payments.

While those working in the payments industry think about payments all day, consumers see payments as an inconvenience. Some services like Parkmobile and Slice are already providing great payments integration. In the future, companies will be providing truly integrated services like Amazon Go.

Growing Up Alexa

A few months ago, I wrote about how Alexa and Google Home are used in our house. In my experience, these devices are a better way for kids to use the internet than a mobile phone. A phone becomes an extension of a person, isolating her from the group. Interacting with Alexa is more of a family activity with Alexa acting like another person in the room.

Some people think it’s odd to treat Alexa humanely. As a machine, she doesn’t have any feelings. But think about the way we refer to Alexa. It feels more natural to refer to Alexa as a “her” than an “it” because that’s the way we interface with her. And if we interface with her as a person, we should be polite and say please and thank you. Continue reading “Growing Up Alexa”

Almanac – Some Random Rules of Thumb I Like

In ancient times, people had wisdom, aphorisms and rules of thumb they would put into Almanacs. In the current lingo, they’re called mental models.  Here’s a list of some of my favorite bits of knowledge from around the web — some because they are useful, others because they are just fun.

  • Baader-Meinhof Phenomenon — The feeling that something you just learned about seems to appear everywhere
  • Bechdel Test — A method for evaluating the portrayal of women in fiction taken from a comic from Alison Bechdel from 1985. The test states that the movie has to have at least two women in it who talk to each other about something besides a man
  • Betteridge’s Law — Any headline that ends in a question mark can be answered by the word no. There’s a great Betteridge’s Law Twitter feed
  • Dunning-Kruger Effect — The term comes from the article “Unskilled and Unaware of It: How Difficulties in Recognizing One’s Incompetence Lead to Inflated Self-Assessments.” It’s a scientific description of someone who is too dumb to know it. Here’s John Cleese with a video explanation
  • Godwin’s Law — As an online discussion grows longer, the probability of a comparison involving Hitler approaches 1. Said differently, if an online discussion (regardless of topic or scope) goes on long enough, sooner or later someone will compare someone or something to Adolf Hitler. The corollary is that the thread immediately ends and this person loses the argument
  • Goodhart’s Law — When a measure becomes a target, it ceases to be a good measure. Anytime a metric becomes a target, people will try to game it
  • Hanlon’s Razor — Never attribute to malice that which is adequately explained by stupidity
  • Occam’s Razor — In short, Occam’s Razor says that the simplest solution is most likely correct. Formally it says, “When presented with competing hypotheses to solve a problem, one should select the solution with the fewest assumptions.” Though they’re historically unrelated, I tend to think of Occam’s Razor with the Gordian Knot. This was the story of Alexander the Great who untangled an impossible knot by cutting it with his sword. I always think of Occam’s razor as the act of cutting the Gordian Knot

How to be Happy — Yale’s Most Popular Class

This year Professor Laurie Santos created Yale’s most popular class of all time. The class is titled Psychology and the Good Life but it’s really a course on how to be happy both in the short and long term. I was excited to hear that Yale was offering the course but even more excited to see that the class is available online. While there’s little I hadn’t heard before, it did a great job of focusing me on what’s important and helped me get into the practice of being happier.

Continue reading “How to be Happy — Yale’s Most Popular Class”

As You Wish — Watching the Princess Bride With Kids

I keep trying to find great movies to watch with my 8 and 5-year-old sons that are fun for all of us. The Princess Bride is one of the best. It’s a great movie for adults and it even has Peter Falk as the narrator grandfather to keep the kids engaged.

For the Adults

It has great writing from William Goldman and a superb cast including Wallace Shawn, Mandy Patinkin, Robin Wright, and Andre the Giant. You also might remember some great lines like:

  • VIZZINI: Inconceivable!
    INIGO MONTOYA: You keep using that word. I do not think it means what you think it means.
  • INIGO MONTOYA: My name is Inigo Montoya, you killed my father, prepare to die!
  • PRINCE HUMPERDINCK:  Please consider me as an alternative to suicide.
  • MIRACLE MAX AND VALERIE: Have fun stormin’ da castle.

Explanations for the Kids

Most of the time when watching a movie with kids you have to answer questions like “Is this going to be a BORING MOVIE” from your kids. However, in The Princess Bride, the movie has included the characters Grandfather (Peter Falk) and Kid (Fred Savage) to step in for you and your kid and answer any questions, like…

Starting the Movie

GRANDFATHER: I brought you a special present.
KID: A book?
GRANDFATHER: That’s right. When I was your age, television was called books. And this is a special book. It was the book my father used to read to me when I was sick, and I used to read it to your father. And today, I’m gonna read it to you.
KID: Does it got any sports in it?
GRANDFATHER: Are you kidding? Fencing, fighting, torture, revenge, giants, monsters, chases, escapes, true love, miracles…

When Kissing Appears

KID:  — Hold it, hold it— What is this? Are you trying to
trick me? —  Where’s the sports? — Is this a kissing book?
GRANDFATHER: — Wait, just wait —
KID:  Well, when does it get good?
GRANDFATHER: Keep your shirt on. Let me read.

At the Scary Part when the Giant Eel Attacks

GRANDFATHER: She doesn’t get eaten by the eels at this time.
KID: What?
GRANDFATHER: The eel doesn’t get her. Now, I’m explaining to you because you look nervous.
KID: I wasn’t nervous. Well, maybe I was a little bit concerned, but that’s not the same thing.

As You Wish

And if you’re looking for more, Wesley (Cary Elwes) wrote a wonderful behind the scenes tribute to the movie called As You Wish: Inconceivable Tales from the Making of The Princess Bride (with audio that he narrates). This is literally a love letter to the movie. In the movie, “As You Wish” means “I Love You.” It’s a special movie as Cary writes in the introduction:

Over the past three decades, I’ve appeared in nearly a hundred movies and television shows. I’ve been a leading man and a supporting actor and worked in almost every genre. But whatever else I’ve done or whatever else I might do, The Princess Bride will always be the work with which I am most closely associated; and Wesley, with his wisp of a mustache and ponytail, the character with whom I will be forever linked.

 

These are a Few of My Favorite Words

To start with I found an amazing etymological podcast called The Allusionist by Helen Zaltzman. She has some great episodes on cursing [NSFW], Mountweazels (fictional words used in dictionaries for copyright purposes), portmanteaus (combination words like “brunch”) and eponyms (words named after people). She also had a great TED talk on how the letter i got a dot on top of it. Continue reading “These are a Few of My Favorite Words”

Why Do People Think That Wearing a Hoodie to Work is a Status Symbol?

I spotted a technology executive walking down the street. He used to wear expensive tailored suits. Now he’s coming to work in high-end jeans and a polo shirt. Then it hit me. Jeans and a turtleneck or jeans and a polo shirt (or really jeans and anything) is the new innovation wardrobe. On one level, it makes sense because everyone wants to dress like Steve Jobs. But when you dig a little bit deeper, using Silicon Valley clothes as a status symbol doesn’t make any sense at all.  Continue reading “Why Do People Think That Wearing a Hoodie to Work is a Status Symbol?”

How Strawberry Ice Cream Got the Short End of the Stick

In the class The Science of Well-Being, Professor Santos focuses on how we often look at our happiness not in an absolute way but by comparing ourselves to those around us. These thoughts about absolute vs. relative comparisons got me thinking about strawberry ice cream.

Whenever I eat strawberry ice cream, I think is pretty wonderful. It’s light, sweet, and just a little bit tangy. If I like strawberry ice cream so much, why am I surprised at this fact every time I eat it. I feel like I’m carrying some sort of bias against strawberry ice cream — but why?

Continue reading “How Strawberry Ice Cream Got the Short End of the Stick”