Posts tagged: Why Can’t You Just Give Me the Number

My Favorite Business Books of the Year

“I am learning all the time.  The tombstone will be my diploma.” ~Eartha Kitt

“Books are the bees which carry the quickening pollen from one to another mind.” ~James Russell Lowell

And my all-time favorite quote about reading…

“Outside of a dog, a book is man’s best friend.  Inside of a dog it’s too dark to read.” ~Groucho Marx

I love to read books and absorb new information and ideas. In this final post of the year, I thought I would share some of the books that most inspired me this year. I hope you might also get great value from them. Some of them aren’t exactly business books, but I got business value from them and I thought you might benefit similarly.

Without further ado, and in no particular order, here are my favorite books of the year:

Customer Culture bookCustomer Culture: How FedEx and Other Great Companies Put the Customer First Every Day
by Michael D. Basch

This one was recommended to me by Anna Barcelos after I wrote my post on the 4 Keys to a Customer Centric Culture. Luckily, I think I was largely on the same page as Michael Basch, but I learned so much more about company cultures after reading his tome. Basch was a co-founder of FedEx and their initial SVP of Sales and Customer Service. He relays plenty of his learnings at FedEx, but he also relates the stories of other customer focused businesses small and large. He even covers an incredibly innovative Australian dentist office! Many of the stories sparked plenty of ideas in my mind, and I even excerpted one to highlight in my blog post on the power of naivete. Basch gives some very specific and easy-to-follow advice on creating the types of customer-focused cultures that drive businesses that simply succeed more because of their focus on their customers.

Why Can't You Just Give me the Number

Why Can’t You Just Give Me the Number? An Executive’s Guide to Using Probabilistic Thinking to Manage Risk and Make Better Decisions
by Patrick Leach

Every manager and executive should read this book. Patrick Leach does an excellent job explaining the concepts of probabilistic thinking and decision making, and he does it in everyday language that is easy to consume for business people who don’t necessarily have advanced degrees in mathematics. He makes a very compelling case for using probabilistic thinking to greatly improve the bottom line. This book, more than any other, was the inspiration for some of my posts on Monte Carlo simulations.

Hidden BrainThe Hidden Brain: How Our Unconscious Brains Elect Presidents, Control Markets, Wage Wars and Save Our Lives
by Shankar Vedantam

This is a book that I actually didn’t love immediately after reading it. However, the concepts I got from it kept creeping back into my brain, and maybe that’s an even better way to value a book. I excerpted a bit of it in my most recent blog post on the power of our hidden brains to dominate our decision making in ways we don’t consciously realize. Author Shankar Vedantam deftly manages to explain complicated brain inner workings through easy-to-read stories that illustrate the concept and leave lasting memories.

Upside of IrrationalityThe Upside of Irrationality: The Unexpected Benefits of Defying Logic at Work and at Home
by Dan Ariely

I included Dan Ariely’s first book, Predictably Irrational: The Hidden Forces That Shape Our Decisions, as an all-time favorite in last year’s list of best business books. While the experiments and ideas in that book were probably more useful in the marketing and merchandising functions, I would say this book is much more about human interactions and general management and leadership. Ariely focuses on topics such as the effect of pay on performance, the motivational value of creating things, and the high addiction of our own ideas. As you might guess from the title, Ariely’s conclusions are not often what we’d expect but extremely beneficial.

SwitchSwitch: How to Change Things When Change is Hard
by Dan and Chip Heath

Anyone who’s attempted to implement major change in an organization knows how difficult it can be. This book is an excellent guide for how to implement and encourage change in business and in life. I loved not only the tips but the explanations about why we humans have such a difficult time with change. The Heath brothers use a metaphor of the Rider and the Elephant to describe the rational and emotional parts of our brains that are so fundamental to accepting and embracing change (and making decisions of any kind). It’s an excellent way to visualize the concept and a concept that I’ll not likely forgot.

ClickClick: The Magic of Instant Connections
by Ram and Ori Brafman

I actually dedicated a post to this book. This is a fascinating look at the reasons people click with each other. The authors really break it all down and in the process provide an excellent roadmap for creating better connections between people. Used in a business environment, this knowledge can help up create better functioning, happier and more productive teams.

design of everyday thingsThe Design of Everyday Things
by Don Norman

This is not a new book by any means, but I somehow never read it until this year. I found this book to be extremely eye opening and completely fascinating. Don Norman spends a lot of time talking about the design of objects like doors and faucets, yet the design principles he discusses and the human psychology learnings that go into those design principles are absolutely relevant to usable designs of things that didn’t even exist in the time he wrote this (the ’80s) — like websites. I explored just a couple of these concepts, and how they apply to retail websites,  in a post earlier this year.

And just for kicks, since I’m a music nut, here are my top 10 albums of the year:

  1. Trombone ShortyBackatown
    A great combination of jazz, funk, hip-hop and rock. Trombone Shorty rips on both the trombone and the trumpet. Standout track: “Hurricane Season.”
  2. Florence + the MachineLungs
    Technically, this record came out in 2009, but the Grammys have nominated them for Best New Artist this year I think I get to include the record in my list. Great vocals from Florence and the drums in particular are amazing on this record. The sound is powerful, a bit dark and different from anything I’ve ever heard. Standout track: “Dog Days are Over”
  3. Grace Potter & the NocturnalsGrace Potter & the Nocturnals
    Grace Potter can flat out sing, and the songs on this record are top-notch. This is just good, ol’ rock ‘n’ roll and a rollicking good time. Standout track: “Paris (Ooh la la)”
  4. The Gaslight AnthemAmerican Slang
    Gaslight Anthem are kind of a Green Day meets with Replacements and (not surprisingly since they are from New Jersey) jams with Bruce Springsteen. Standout track: “The Spirit of Jazz
  5. Mumford and SonsSigh No More
    The bluegrass tinted pop from British newcomers Mumford and Sons is highly infectious. Very impressive vocal harmonies as well. Standout track: “Winter Winds”
  6. Sons of SylviaRevelation
    A band of brothers (I assume their mother is named Sylvia), these guys have put together what I guess could be called an alt-country record because it’s basically pop music with country instruments. Lead singer Ashley Clark can flat out wail, and the band certainly holds their own. Standout track: “50 Ways.”
  7. Sharon Jones and the Dap KingsI Learned the Hard Way
    Sharon Jones and the Dap Kings are the best of the new wave of R&B retro, and this record does not disappoint. Standout track: “Money”
  8. OzomatliFire Away
    I’ve been an Ozomatli fan for a long time, but I think this is their best record since 2001’s Embrace the Chaos. Great combination of Latin, hip-hop and rock, and the songs are lots of fun. Standout track: “Yeah, Yeah, Yeah, Yeah”
  9. Aloe BlaccGood Things
    I suppose Aloe Blacc is a bit of an R&B retro artist, but he’s got a sound that feels both contemporary and throwback at the same time — and he’s very smooth. Standout track: “I Need a Dollar”
  10. SantanaGuitar Gods: The Greatest Guitar Classics of All-Time
    Carlos Santana teaming up with a bunch of guest vocalists to record some of rock’s all-time great guitar songs (sort of — I’m not sure Dance the Night Away would be my choice for a Van Halen song). Artistically, this is not particularly impressive. However, it’s a lot of fun to just listen to Carlos Santana wail away — even when he’s stepping all over the melodies. Standout track: “Back in Black”

What were your favorite business books of the year (and music, too)?

11 Ways Humans Kill Good Analysis

Failure to CommunicateIn my last post, I talked about the immense value of FAME in analysis (Focused, Actionable, Manageable and Enlightening). Some of the comments on the post and many of the email conversations I had regarding the post sparked some great discussions about the difficulties in achieving FAME. Initially, the focus of those discussions centered on the roles executives, managers and other decisions makers play in the final quality of the analysis, and I was originally planning to dedicate this post to ideas decision makers can use to improve the quality of the analyses they get.

But the more I thought about it, the more I realized that many of the reasons we aren’t happy with the results of the analyses come down to fundamental disconnects in human relations between all parties involved.

Groups of people with disparate backgrounds, training and experiences gather in a room to “review the numbers.” We each bring our own sets of assumptions, biases and expectations, and we generally fail to establish common sets of understanding before digging in. It’s the type of Communication Illusion I’ve written about previously. And that failure to communicate tends to kill a lot of good analyses.

Establishing common understanding around a few key areas of focus can go a long way towards facilitating better communication around analyses and consequently developing better plans of action to address the findings.

Here’s a list of 11 key ways to stop killing good analyses:

  1. Begin in the beginning. Hire analysts not reporters.
    This isn’t a slam on reporters, it’s just recognition that the mindset and skill set needed for gathering and reporting on data is different from the mindset and skill set required for analyzing that data and turning it into valuable business insight. To be sure, there are people who can do both. But it’s a mistake to assume these skill sets can always be found in the same person. Reporters need strong left-brain orientation and analysts need more of a balance between the “just the facts” left brain and the more creative right brain. Reporters ensure the data is complete and of high quality; analysts creatively examine loads of data to extract valuable insight. Finding someone with the right skill sets might cost more in payroll dollars, but my experience says they’re worth every penny in the value they bring to the organization.
  2. Don’t turn analysts into reporters.
    This one happens all too often. We hire brilliant analysts and then ask them to spend all of their time pulling and formatting reports so that we can do our own analysis. Everyone’s time is misused at best and wasted at worst. I think this type of thing is a result of the miscommunication as much as a cause of it. When we get an analysis we’re unhappy with, we “solve” the problem by just doing it ourselves rather than use those moments as opportunities to get on the same page with each other. Web Analytics Demystified‘s Eric Peterson is always saying analytics is an art as much as it is a science, and that can mean there are multiple ways to get to findings. Talking about what’s effective and what’s not is critical to our ultimate success. Getting to great analysis is definitely an iterative process.
  3. Don’t expect perfection; get comfortable with some ambiguity
    When we decide to be “data-driven,” we seem to assume that the data is going to provide perfect answers to our most difficult problems. But perfect data is about as common as perfect people. And the chances of getting perfect data decrease as the volume of data increases. We remember from our statistics classes that larger sample sizes mean more accurate statistics, but “more accurate” and “perfect” are not the same (and more about statistics later in this list). My friend Tim Wilson recently posted an excellent article on why data doesn’t match and why we shouldn’t be concerned. I highly recommend a quick read. The reality is we don’t need perfect data to produce highly valuable insight, but an expectation of perfection will quickly derail excellent analysis. To be clear, though, this doesn’t mean we shouldn’t try as hard as we can to use great tools, excellent methodologies and proper data cleansing to ensure we are working from high quality data sets. We just shouldn’t blow off an entire analysis because there is some ambiguity in the results. Unrealistic expectations are killers.
  4. Be extremely clear about assumptions and objectives. Don’t leave things unspoken.
    Mismatched assumptions are at the heart of most miscommunications regarding just about anything, but they can be a killer in many analyses. Per item #3, we need to start with the assumption that the data won’t be perfect. But then we need to be really clear with all involved what we’re assuming we’re going to learn and what we’re trying to do with those learnings. It’s extremely important that the analysts are well aware of the business goals and objectives, and they need to be very clearly about why they’re being asked for the analysis and what’s going to be done with it. It’s also extremely important that the decision makers are aware of the capabilities of the tools and the quality of the data so they know if their expectations are realistic.
  5. Resist numbers for number’s sake
    Man, we love our numbers in retail. If it’s trackable, we want to know about it. And on the web, just about everything is trackable. But I’ll argue that too much data is actually worse than no data at all. We can’t manage what we don’t measure, but we also can’t manage everything that is measurable. We need to determine which metrics are truly making a difference in our businesses (which is no small task) and then focus ourselves and our teams relentlessly on understanding and driving those metrics. Our analyses should always focus around those key measures of our businesses and not simply report hundreds (or thousands) of different numbers in the hopes that somehow they’ll all tie together into some sort of magic bullet.
  6. Resist simplicity for simplicity’s sake
    Why do we seem to be on an endless quest to measure our businesses in the simplest possible manner? Don’t get me wrong. I understand the appeal of simplicity, especially when you have to communicate up the corporate ladder. While the allure of a simple metric is strong, I fear overly simplified metrics are not useful. Our businesses are complex. Our websites are complex. Our customers are complex. The combination of the three is incredibly complex. If we create a metric that’s easy to calculate but not reliable, we run the risk of endless amounts of analysis trying to manage to a metric that doesn’t actually have a cause-and-effect relationship with our financial success. Great metrics might require more complicated analyses, but accurate, actionable information is worth a bit of complexity. And quality metrics based on complex analyses can still be expressed simply.
  7. Get comfortable with probabilities and ranges
    When we’re dealing with future uncertainties like forecasts or ROI calculations, we are kidding ourselves when we settle on specific numbers. Yet we do it all the time. One of my favorite books last year was called “Why Can’t You Just Give Me the Number?” The author, Patrick Leach, wrote the book specifically for executives who consistently ask that question. I highly recommend a read. Analysts and decision makers alike need to understand the of pros and cons of averages and using them in particular situations, particularly when stacking them on top of each other. Just the first chapter of the book Flaw of Averages does an excellent job explaining the general problems.
  8. Be multilingual
    Decision makers should brush up on basic statistics. I don’t think it’s necessary to re-learn all the formulas, but it’s definitely important to remember all the nuances of statistics. As time has passed from our initial statistics classes, we tend to forget about properly selected samples, standard deviations and such, and we just remember that you can believe the numbers. But we can’t just believe any old number. All those intricacies matter. Numbers don’t lie, but people lie, misuse and misread numbers on a regular basis. A basic understanding of statistics can not only help mitigate those concerns, but on a more positive note it can also help decision makers and analysts get to the truth more quickly.

    Analysts should learn the language of the business and work hard to better understand the nuances of the businesses of the decision makers. It’s important to understand the daily pressures decision makers face to ensure the analysis is truly of value. It’s also important to understand the language of each decision maker to shortcut understanding of the analysis by presenting it in terms immediately identifiable to the audience. This sounds obvious, I suppose, but I’ve heard way too many analyses that are presented in “analyst-speak” and go right over the heard of the audience.

  9. Faster is not necessarily better
    We have tons of data in real time, so the temptation is to start getting a read almost immediately on any new strategic implementation, promotion, etc. Resist the temptation! I wrote a post a while back comparing this type of real time analysis to some of the silliness that occurs on 24-hour news networks. Getting results back quickly is good, but not at the expense of accuracy. We have to strike the right balance to ensure we don’t spin our wheels in the wrong direction by reacting to very incomplete data.
  10. Don’t ignore the gut
    Some people will probably vehemently disagree with me on this one, but when an experienced person says something in his or her gut says something is wrong with the data, we shouldn’t ignore it. As we stated in #3, the data we’re working from is not perfect so “gut checks” are not completely out of order. Our unconscious or hidden brains are more powerful and more correct than we often give them credit for. Many of our past learnings remain lurking in our brains and tend to surface as emotions and gut reactions. They’re not always right, for sure, but that doesn’t mean they should be ignored. If someone’s gut says something is wrong, we should at the very least take another honest look at the results. We might be very happy we did.
  11. Presentation matters a lot.
    Last but certainly not least, how the analysis is presented can make or break its success. Everything from how slides are laid out to how we walk through the findings matter. It’s critically important to remember that analysts are WAY closer to the data than everyone else. The audience needs to be carefully walked through the analysis, and analysts should show their work (like math proofs in school). It’s all about persuading the audience and proving a case and every point prior to this one comes into play.

The wealth and complexity of data we have to run our businesses is often a luxury and sometimes a curse. In the end, the data doesn’t make our businesses decisions. People do. And we have to acknowledge and overcome some of our basic human interaction issues in order to fully leverage the value of our masses of data to make the right data-driven decisions for our businesses.

What do you think? Where do you differ? What else can we do?

Retail: Shaken Not Stirred by Kevin Ertell


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