The Acorn Analytics Origin Story
Comic book fans are familiar with the concept of the origin story. In honor of our two-year anniversary as a company, I decided to share the origin story of Acorn Analytics Inc. This post attempts to explain why Acorn Analytics was started in the first place.
I felt tempted to spin the story and revise history to make it more interesting. Fortunately, I wrote about the reasons for the company’s beginnings in a speech I delivered to my local Toastmasters International club a few months before we filed our organization’s articles of incorporation, and a few months after my role as a full-time employee at another company had ended.
For the remainder of this post, the words you will read are lifted directly from the print-out of the speech I gave in June of 2016 [except for some edits for clarity indicated with brackets].
If there’s one thing you should know about me, it’s my love affair with information. It’s in the air we breathe, in the songs we hear, in our DNA, in every cell phone in our pockets, and every cell of every living thing on the planet. And all of those bytes of information is sent and received 24/7 on every channel and spectrum and frequency in the known galaxy. I’m never bored because I can occupy myself, forever, just thinking about this.
Today, I want to tell you about this passion and how it has transformed my life over the past few months.
At the beginning of , I was happily working at a job where I worked for one company that employed me to sift through mobile and internet data and use it to try to figure out answers to some very specific questions. I started seeing myself as an explorer of a dense and complex forest, perhaps even a jungle with diverse vegetation. Every species of tree and plant represented a unique species of information in the digital world.
But there was a problem. My employer, understandably, was only interested in one type of tree. Even though I was discovering new species of trees every day, trees that had amazing properties to make a difference in the world, I couldn’t do my job properly unless I ignored everything else in that jungle except for this one type of species of tree. I couldn’t quite figure out why this bothered me so much, but it happened that in my free time, I started exploring different parts of the information jungle.
This led me to a non-profit volunteer-led organization named Code for America. I attended meetings hosted by Code For America’s San Francisco chapter, where I met other people who had experiences similar to mine. They were happily employed doing one job, but they wanted more, so they brought that excess energy and enthusiasm to Code for America.
A few of these people teamed up with me on a project I want to tell you about. We heard about successes that other major metropolitan areas had achieved in assessing and predicting 911 calls and fire risk. We got our hands on a specific type of data, which was the record of fires that had broken out in San Francisco. We also pulled other information that had nothing to do with fires, like census data, history of buildings, records on poverty and construction and crime, and found a way to combine that so that fires could be predicted. For example, you can combine 911 call data with weather data, and identify high-risk areas, and like Minority Report, place key emergency service personnel in the likely neighborhoods hours before they happen. Add in traffic pattern data, and you can better predict supply and demand, making staffing more efficient, and get people the help they need in less time. This technology has the potential to identify the highest risk buildings and stop fires before they even happen.
In other words, there was an example of how taking multiple species of trees in this information jungle and using the information across all of them we were able to make a major life-saving difference in the world.
* * *
This experience is part of the reason why on May 10, 2016, a Tuesday afternoon, I left my day job… without any plan to work for one company full time ever again.
Oh, wait, I should tell you what a data scientist is. We humans generate 700 terabytes of data per second, and we store so much of that data, that in the USA alone we are missing the extra 1.5 million data scientists that we need in order to analyze all that data and turn it into insights. That’s what a data scientist does: uses statistics, and technology, and experience with the two, to convert raw information into analytics insights and predictive value.
So I left my day job as a data scientist, and I started the mission I’m on right now, to understand not just my tiny bit of jungle that I discovered with friends at Code for America or at my former day job, but the entire planet. The way I am doing this is state of the union calls.
To me, a “state of the union call” is where I spend 20 minutes with a person, and I start the conversation with a simple question: “What’s going on in your world?” Then I listen, and we converse, and after 20 minutes, we both leave knowing more than we did 20 minutes earlier. Since I quit my full-time data science job, I’ve had over 200 of these state of the union calls. [NOTE: This was 200 calls over a month period. I probably had over 300 before we incorporated, and have had over a thousand such calls as of November 2018.]
I’ve learned LOTS, but here are three key lessons:
- There are more trees in the information forest than we can possibly imagine
- Few people understand what’s in their own jungles of data, or how they can use multiple species of plant life in their jungle to make dramatic new value to their lives and businesses
- Very few people understand what a data scientist is
Because frankly, when people think about a problem, they do not think about the data associated with our understanding of that problem. Instead, they are focused on the pain, the headache itself, and quickly seeking out which pill at the drugstore will cure it quickly. When someone gets a headache, very few people will take the time to collect data—or to stick with our analogy, find which plant in the rainforest has the medicine that will make all headaches obsolete. That’s why data is rarely a word associated with a headache, a problem, a pain—even though it’s frequently where we can go to look to find a more permanent solution.
58 days [after I left my job and giving this speech, and now over two years after that date, I continue to] hesitate to simply call myself a “data scientist.” Instead, I’m an expert, a guide, and through conversations with humans, I help them navigate the information jungle.
But I need your help: I need to connect with more humans to continue my state of the union calls with. If you know of any interesting people who are willing to speak with me for 20 minutes, please put me in touch. This could be someone who is another native guide—another expert on some part of the information jungle—or it could be someone who wants to understand the data wilderness a little better. Alternatively, it could simply be someone who is in very different territory and has a story to tell. Not of the jungle, but the desert, or the tundra, or some other terrain. Conversations like this allow me to make a bigger difference in the world. They also allow me to work on a shared map for our entire digital, data-rich world—regardless of sector, or industry, or background, or ambitions.
By helping me with the next 100 state of the union calls, I am confident we will all finally be able to better see the forest for the trees.