Here’s a plug for a practice I’ve leaned on more and more to make sure I’m getting things done, particularly those important-but-hard-to-sit-down-and-do things.
I experience the textbook case of procrastination due to perfectionism. When I have a vision for how I want something to turn out, it’s often overwhelming for me to start or at least keep it going. The Pomodoro technique totally wipes this out.
Here’s a summary of the Pomodoro technique. Many advocates advise not using the timer on your phone but I always have with no issue. I also don’t stick to the rules about how many Pomodoros to do before taking a break. It’s rare that I find a block of clear time longer than 1-2 hours in my day.
This is why the Pomodoro technique works so well for me:
Offers a low barrier-to-entry to just getting started. Rather than clearing my desk, reaching inbox zero and having a snack before starting a project (all sneaky ways to procrastinate!), I just start the timer and work. It’s only 25 minutes!
Captures actual effort exerted. Recently I lamented that a project was taking the whole day. Then I realized I had only done two Pomodoros, with the rest of my time going to two phone meetings, a coffee and lunch. So in reality I had only worked on that thing for less than one hour. A much needed reality check!
I recommend trying it out, especially if you’re prone to procrastination.
I’m fresh off what was probably my 20th+ family trip to Walt Disney World, and as always it was such a magical time. After so many visits, it’s fun to experience the parks with a first-timer. and this time it was my sister’s boyfriend, Frank.
The Carousel of Progress sparked a great lunchtime discussion about what technology will look like at the end of this century. The Carousel of Progress is an animatronic stage show that shows an American family at four points in the 20th century, highlighting technology innovations in the home. It kicks off at the turn of the century, showing electric lights and cast iron stoves, and the “future” scene takes places in the 1990s, highlighting virtual reality games, self-flushing toilets and voice-activated appliances. After the ride, we all dreamed up what a 2000s Carousel of Progress would contain. Here in 2016 we’d be the very first scene of the show.
We didn’t have to stretch too far to imagine what that scene would contain – we were wearing it. Disney World has integrated wearable technology into its parks with the Magic Bands. We all had a Magic Band in a chosen color with our name printed on the inside and used it as our hotel key, our park ticket, our credit card… It was everything. Meanwhile, all my ride photos popped up immediately in my Disney mobile app, presumably linked through my Magic Band.
Working in analytics, I am curious about the other side of the Band – the big data side. I would love to get a glimpse at what the data scientists at Disney are conjuring up with all the movement and spending data they get through the Magic Bands. Disney has spent over $1 billion on the MyMagic+ program so it’s clear they have big plans for ROI. So far reception has been positive, and the overall creepy factor I felt when my face first magically appeared on my Disney app – screaming on the new Seven Dwarves Mine attraction – was quickly replaced by joy when watching the two-minute video of my family’s reactions at various points on the new ride. From Wired:
No matter how often we say we’re creeped out by technology, we tend to acclimate quickly if it delivers what we want before we want it.
Just like the Carousel of Progress, technological innovation moves fast, and even now Magic Bands are moving to the past. The next scene takes place in Shanghai Disney, where everything will happen seamlessly through a smartphone. I’m adding Shanghai Disney to the bucket list!
As a kid, I had a wooden piggy bank and loved dropping any spare change into it (and later sorting it with the plastic coin sorter on my mom’s desk). I have found the digital equivalent in Digit.
I joined Digit on January 30 after reading this post on Lifehacker. It has a great premise: link it to your bank account and it applies its special algorithm to find untapped savings. As a personal finance hobbyist, I was happy to take the bait.
In the first month, I saved over $100 with Digit and have since saved about $650. I recommend it, as long as you understand a few things about its operating model (or what I’ve gleaned from Google searches).
First, Digit holds your “savings” in an interest-free account. I’ll come back to this because it’s a key to the Digit business. But for the consumer, that means my “savings” are essentially stuffed under a digital mattress until I’ve moved the money out of my Digit account and into an interest-bearing savings account or investment. The catch to this is that so far, Digit only links to one account, meaning to “save” the $100 Digit pulled aside in month 1, I had to transfer that money back into my checking account and then into my savings account. I’m fine with this as an experiment, but this would get really annoying over time.
Second, Digit operates primarily through SMS. This feels like a novelty these days, and the simplicity makes it so enjoyable to use. Every day I get a text with my checking account balance and then I get texts when Digit makes a withdraw. I also got some gif action when I hit $50 and $100 in my account. All in all, a very pleasant and simple user experience.
I was hooked after using it just a few days. I’ve noticed the amounts drawn taper off – sometimes to <$1 – as my checking account lowers with bills, rent, etc. It hasn’t landed me any overdraft fees and even if it did, if offers a guarantee to repay them.
And now Digit: the startup. I am intrigued by this company. The founder, Ethan Bloch, has started a few other companies and the last one, Flowtown, was acquired by Demandforce. Why is this company so interested in helping little ol’ me save some bucks? Which brings us back to the no-interest point at the top. Your miniscule interest on your checking interest (mine is 0.05%) is Digit’s gain. When I defer my money to a Digit account instead of my checking, I forfeit only pennies in interest earnings, if that. This becomes a win for Digit if they put everybody’s money together to collect the interest or invest or do whatever they want to do.
For now, I’ve put a reminder on my calendar to transfer my Digit account back into my checking account the first of each month so that I actually put the money into an interest-bearing savings account. I’ve automated a lot of savings already – I have a set amount pull out of my checking account the day after my paycheck hits each pay cycle. It feels good to use Digit because I feel like it’s a little bonus, finding incremental savings where I thought there was none. But if it ends up being a similar amount each month, I’ll just up my savings rate and deactivate my Digit account.
If you have trouble automating savings, Digit could be for you. I’m enjoying it so far.
This week I saw a demo of Watson Analytics, IBM’s new natural language-based analytics tool. It was presented at the New York Strategic HR Analytics Meetup, though the tool itself is not specialized to any one business function – and that is a big part of its appeal.
My initial thought was, “Uh oh, there goes the boom in data analyst jobs!” I also felt really excited at the idea of analytics operating like a Google search bar. Number crunching for the masses!
The past few years have been an exciting time to be following data and analytics. With market intelligence startups like Food Genius getting regular mentions in the press and tools like Qlik and Tableau entering the common language of non-data heads in the business, it’s cool to see where analytics is going next.
Here are the top five reasons to get excited about Watson Analytics (and one reason to be weary):
You’re no longer at the mercy of your IT team.
You can pull in data from Excel spreadsheets, Oracle, Salesforce, etc. The data has to be uploaded to IBM’s cloud in order to use it in Watson, but data selection and clean-up takes place as a step in the analysis. Current solutions on the market try to approach this by doing transfers and loads on their own, but there’s a lot of planning ahead – and partnering with the data managers in IT – required before you can move data into any system for analysis.
Data clean-up is a cinch.
In the demo, after the rep chose a question, the next page guided clean-up, the process of organizing and formatting the data. IBM estimates that data preparation can take 50-70% of the completion time of a data mining project. To be fair, Excel does this pretty well but has its limits with huge data sets.
The data looks pretty!
Any analyst worth her salt knows that getting the right data story is only half the battle. No one cares about a pivot table – they want to see cool graphics. Compelling visualizations are the vehicle for getting data into viewers’ heads. The visualizations in the Watson demo look good – they have lots of information without looking too busy, they connect well to the data they’re showing and the colors and shapes are bold and appealing.
It’s not relegated to a single business function.
There are great analytics tools for marketing, great analytics tools for operations, great (or at this stage, maybe just good?) analytics tools for human resources. The beauty of Watson Analytics is that it doesn’t specialize. I hope movement towards tools like this leads to asking deeper questions of the data, like how do disparate business functions work together and drive productivity, sales, etc.
Analytics is no longer the domain of analysts.
This tool doesn’t require a PhD to understand a multivariate regression. Analytics and data storytelling are now in the hands of anyone with a question that can be answered with the data on hand.
And my bonus point, one reason to be weary:
Data analysis is only as good as the people communicating it.
A huge job in building good data stories is communicating the finer points of the analysis to those less data-savvy. A difference of 2% can mean nothing or so much depending on the sample size. A regression is only as good as the variables you’re putting into it. These basic statistical concepts may be lost with easy-access analysis. Data is powerful, and it should be wielded wisely!
Ultimately, I am excited to get my mitts on a trial and signed up at IBM’s site. You can too here.
So what do you think? Is natural language analytics the next big thing? Will we all be data analysts in the near future?