On Reading: Second Year DMBA

As I wrap my head around the topics we covered throughout the DMBA, I’ve found it helpful to remember and assess the materials we used, including books. It should be noted that many of the courses heavily used articles and HBR case studies, which I’m not going to endeavor to list. Perhaps there will be a “best of” article list someday. Here’s the comprehensive book list from year two:

Brand Strategy:

Managerial Finance:

  • Financial Management, 13th Edition, Eugene F. Brigham, Michael C. Ehrhardt
  • Various HBR case studies


Experience Studio:

Venture Studio:

Strategic Management:

Strategic Foresight: (Full reading list is too long to post, so I’m just posting the ones I selected or have read.)

Some of the books were wonderful, some forgettable, and there are a few books that I would never recommend. Books I have gone back to for reference include the Marty Neumeier selections, Blue Ocean Strategy (more the toolset than the book), Strategy Safari, and Kellogg on Branding.

A Natural History of the Senses and most of the strategic foresight books were enjoyable to read and provided a good sense of a field or concept, but haven’t been useful as references.

The concepts in The Lean Startup and Tribes have been useful and commonly referred to by practitioners I’ve spoken with, but both books could probably express their ideas in a few pages.

In my opinion, don’t bother with Operations Strategy or Experience Design 1.1. These books were not helpful, interesting, or useful. There are other, better ways to explore the content.

Second semester, I started to use Audible.com for some books, and would highly recommend listening to books at high speed. This method takes advantage of time running errands, baking, or cleaning. Good candidates for listening are books where the concept is more important than the prose, where storytelling isn’t key, and you won’t want to take copious notes. There’s a lot of stopping and starting involved in consuming books this way, and the high speed tends to lose nuance in the reader’s inflection. Although note taking isn’t super intuitive, I take notes on books in Audible through bookmarks and their speech recognition software. Because you can’t read the text, it’s harder to note specific sentences.


Summary: The Signal and the Noise

By exploring prediction methodologies as they pertain to events ranging from earthquakes to chess, The Signal and the Noise by Nate Silver offers insights on the art of prediction. As the title suggests, a central theme is separating signals (underlying truths), from the noise (the plethora of available data that forms meaningless patterns that can be mistaken for signals). The book makes a case for using Bayesian logic, thinking probabilistically, for better predictions. The premise is that by using information gathered from past events, you can predict future events.

Rather than read the physical copy, I listened to it at 2.5x the recorded speed. It was an interesting method to try.

Rather than read the physical copy, I listened to it at 2.5x the recorded speed. It was an interesting method to try.

Bayes’ theorem is an equation that takes multiple factors, expressed as probabilities, into account. Both general probabilities, things that are generally true, and conditional probabilities, probabilities based on if-then situations are used. For example, I eat hummus for lunch 50% of the time. (Probability.) If it’s raining, I only eat hummus 10% of the time. (Conditional probability.) The result of the equation is a likelihood of the event occurring. If you used the equation to evaluate whether or not I am likely to have hummus for lunch next Tuesday (using more information than I provided here) you may determine that there’s a 20% chance that I’ll have hummus, which does not rule out the possibility of a hummus lunch, but indicates that it is less likely than my having something else. For more information on Bayes’ theorem, check here.

Silver also addresses the value of the human versus computer in prediction. Despite a computer’s ability to sort and process massive amounts of data, humans sometimes have an edge, at least for now. In baseball, for example, the book examines predictions of player performance down the line. Computer programs made a list of players they predicted would do well, and human scouts made predictions. When the predictions were examined years later, the human scouts were more accurate. They were able to take in less quantifiable data that the computer did not consider, like personality.

Qualitative data plays a role in certain  types of predictions, although it is difficult, perhaps impossible, to take personal bias out of it, which may lead to error. Personal bias may lead us to over-emphasize certain information, while disregarding other data. The predictions that most obviously benefit from qualitative data involve human behavior. For example, predictions around poker, chess, basketball, and politics fit this category.

I was attracted to Silver’s assertion that there are uncertainties in prediction, and there always will be. There is no way to have access to all pertinent data relevant to a prediction.  Nor is it possible to un-biasedly and correctly analyze all available pertinent data. In part, this is because it is difficult to correctly discern which data is relevant. Otherwise stated: it is difficult to tell what is noise and what is signal. Silver asserts that it is important to accurately represent uncertainties, even when it makes the prediction less useful. For example, rather than stating that population growth will be P% in 30 years, it would be better to state that “pending X and Y conditions, if Z holds steady, population growth is projected to be between P% and Q% in 30 years.”

Silver also cites a Donald Rumsfeld quote: “…there are known knowns; there are things we know that we know. There are known unknowns; that is to say, there are things that we now know we don’t know. But there are also unknown unknowns – there are things we do not know we don’t know.” “Unknown unknowns” present the greatest chance for introducing danger or inaccuracy into predictions. In representing uncertainty accurately, it is important to take this under consideration. To combat unknown unknowns, Silver suggests absorbing as much data as possible by reading avidly. The more prediction-makers know, and the more they know that they don’t know, the more accurate they will be. The book asserts that most predictions go wrong due to human error, and the more data prediction-makers collect, the more human error is reduced.

When considering more data, though, there is potential to get caught up in “noise.” Rather than take “more data” as a net positive at face value, I believe there are criteria that data should meet before having equal consideration. Silver does not address this extensively in his book. The basic premise of the book is that there is so much data out there that it is easy to get stuck in the weeds, and so if we are supposed to absorb everything we can, without extensively filtering it, we are likely to become overwhelmed and confused. While I believe Silver understands this, it is not addressed and the basic idea of “get as much data as possible” is expressed throughout the book.

The concepts above were the ones that most interested me, although other gems are strewn throughout the book. Silver touches on betting strategy (always go for it if the likelihood greater than projected), poker strategy (learn the behavior of your opponents), and the relationship between extreme and non-extreme instances of events. After listening to the book, I feel much better informed about prediction strategy and am planning to incorporate representation of uncertainty into my predictions from here on out.

The Design Journal: Getting it Started Again

I’m a notoriously bad journaler. I love having journals, and have a collection of empty ones. Often I start a diary or journal, only to stop a few days later, and tear out the pages and shred/recycle them when I read them a few years later in mortification.

Last year one of our first assignments as first-year DMBA students was to keep a design journal. Not only would we need to keep a design journal, we needed to turn it in on occasion. Terrifying, true, but also a great opportunity to build a good habit.


First page of my first design journal. Note the cut-out pages from a prior journaling attempt.

Most people want to be the kind of person that keeps a sketch notebook, design journal, writing journal, or diary. Keeping a written or sketch journal is purported to increase creativity, release stress, enable us to better understand our thoughts, and to explore ideas in a non-threatening way. Carrying a small journal with you enables spontaneity and encourages us to be thoughtful of our surroundings, finding inspiration unexpectedly. I found, however, that owning a blank notebook and calling it a “design journal” did not immediately confer these benefits. Journaling/sketching/keeping a diary must be cultivated, like any other habit.

At first, I stuck with word maps, process diagrams, keeping notes on readings and lectures, and occasionally forcing myself to make small sketch accompaniments. As this was an assignment, we needed to make entries at least once a week. Sometimes the entries were uninspired, and sometimes I was enthusiastic about it. Sometimes I could barely manage to make one entry a week, and sometimes it was easy and natural to make several. As time went on, I incorporated colors and visual diagrams. By the end of second semester, I graduated to a new journal.

It's not pretty, but I even started more sketch-heavy entries.

It’s not pretty, but I even started more sketch-heavy entries.

When my journal had a more defined focus– exploring ideas, not trying to be brilliant, it became very comfortable. It was helpful to think of the journal as a personal tool, not intended for public consumption and recognize that not every note made in a journal offers insight or inspiration, and that it’s okay. My journals became lighter and smaller so that I could carry them everywhere and inconspicuously get them out to make a note/observation. Unfortunately, I fell off the design journal bandwagon this summer, but am hopping right back on. Although new habits are hard to build, or even re-build, this one is worth it. Virginia Woolfe puts it well:

“I got out this diary and read, as one always does read one’s own writing, with a kind of guilty intensity. I confess that the rough and random style of it, often so ungrammatical, and crying for a word altered, afflicted me somewhat. I am trying to tell whichever self it is that reads this hereafter that I can write very much better; and take no time over this; and forbid her to let the eye of man behold it. And now I may add my little compliment to the effect that it has a slapdash and vigour and sometimes hits an unexpected bull’s eye.”

Here's to new beginnings!

Here’s to new beginnings!

For more on the benefits of journals (the articles are endless, but these are my favorites):

Summer Reading/Personal Leadership Plan

One of the most helpful deliverables we created last semester in our Leadership by Design course was a “Personal Leadership Plan.” This plan analyzed the results of our various assessments (See post titled “You: By the Numbers” for specifics) and identified two areas for growth for us to focus on. For each of these growth areas, we identified specific actions to take, feedback loops, success criteria, and a timeline for the plan. If you’re interested in the exact format, please message me directly.

The two areas I identified for myself were growing my capabilities and confidence as an ideator and better identifying and aligning my actions with my purpose. In addition to identifying actions and activities to support this growth, I’ve curated my summer reading list around these goals. I’d love your comments/feedback on other books that might support this.

Purpose focus: Identify a purpose that may lead to sustained happiness, satisfaction, and success.

Ideation focus: To look at opportunities instead of problems, and to practice letting go of some control to become more agile.

Some of these books are ones I’ve already read for school, and want to re-read on my own time to more fully absorb their lessons. And the journey continues.

Indispensable Interweb Tools: The Study Edition

More learning happens online than ever before, and the trend will continue. I use online tools a ton, as my program accommodates a commuter schedule and involves a ton of online meeting, research, posting, and content generation. These are the tools I’ve found the most helpful this year:

Evernote: This tool has been wonderful. All of your notes for all of your classes and books and anything else…in the same place. You can insert videos, images and audios into your notes, and the search function searches text inside images as well as in your actual notes. You can also access your documents online or offline at any time– on your iPad, phone, or computer. It’s free.

Pandora: Electronic for Studying Mix. Everything you wanted from your study playlist but didn’t have time to curate. Free with commercials.

Zoom: The group video service that doesn’t crash, and connects people quickly. You can invite people via Google Chat or email. Allows for screen sharing, and is far more reliable than anything else I’ve tried. And I’ve tried a lot of services. Unfortunately, the free version only allows for 45 minute meetings before you have to re-connect. The paid version isn’t too expensive though.

Google Docs: When working with groups, Google Docs is a fairly intuitive and easy way to work on documents at the same time. We can take notes, keep track of action items, brainstorm, and generate content during meetings with each team member seeing the same thing. It’s brilliant. I can’t imagine writing a team paper or sharing research without it. Free.

LinkedIn: This tool has been surprisingly useful for connecting with visiting speakers, professors, and classmates. People post useful news articles and groups may offer insight into various industries and trends. Free.

Twitter: Another surprise find– when researching trends or trying to find general consumer data points (to get started in the right direction, not to be taken as a representative sample) Many of my projects involve industries that I haven’t worked in, and it’s been extremely helpful to create lists of key industry players and follow their tweets. Also free.

YouTube: Cute Baby Animal Videos. There’s nothing that’s quite as relaxing, brainless, and uplifting as watching videos of cute baby animals.

Honorable Mentions: Asana and Mural.ly

What are your favorites?

On Reading: First Year DMBA

As you can imagine/have experienced/are experiencing currently, grad school requires a lot of reading. Almost through my first year, I feel ready to recommend some of the best reading we’ve done in the purple track of the DMBA.


Here goes:

The top three on the list were pre-reading before the first semester started, and served to get my head in the game before starting my MBA. The second three were the Bibles of my first semester, and Business Model Generation and Designing for Growth have influenced each project I’ve worked on since meeting them. The last two books are both from my second semester marketing insights course. The Making Meaning book provided a whole new perspective on what needs to design for, and Design Research is full of tools for uncovering those needs.

Finally, cliche I know, but keeping a design journal has been wonderful. If you don’t already think of yourself as a person who draws or maps ideas on paper, having to keep a design journal as an assignment will open doors. I’m not a drawer and I do not sketch for fun. But, let me tell you, putting an idea on paper, literally, is the fastest way to try out a new idea and communicate it to people. Because it was a weekly assignment, I had to get used to it. I loved it when I did.

Anyone else have great grad school reads?