First Do Your Homework, Then You Can Play Ball

Posted on by Stuart Murray
Shane Battier. Courtesy of Keith Allison.
Shane Battier. Courtesy of Keith Allison.

What impact does analytics have on teamwork?  Plenty, it turns out.

I happened upon an interesting blog post by Thomas Marsden of Saberr, a team-development firm.  Marsden was fascinated by a session with Shane Battier at the Wharton People Analytics Conference.  Battier is a basketball player with many distinctions.

One distinction is that Battier won a team-player award because he served as his team’s data translator.  Players on his basketball team were handed massive statistics packs about the opposing team’s behavior.  He actually read them, a behavior that was rare.  I often wonder what happens when I produce a ream of analysis and send it off to a client.  Sometimes (but not always) someone comes back to me with tough questions, follow-up inquiries, and demands for deeper dives.  In those cases I have struck upon an expert consumer.  They are like wine experts, indie rock snobs, or film buffs.  They don’t produce the product; they just really know how to consume it.

Battier is an expert consumer.  He did his homework and made interpretations in order to play better.  Other players had not done this, so he would help teammates and “drip feed information at the right moment through the game.”  He was acting as the intermediary between the statistical analysts and the front-line players.  This is a key bridging link between two cliques.  In network theory the person who causes information to jump from one crowd to the next becomes a go-to person for both cliques.

For some people, they see the shots being made.  For me, one of the greatest games on earth is watching the information pass from one person to the next.  There is a bounce, a spin, a clever move, a change of play.  I watch big people, breaking a sweat, moving my data across the court.  And when they score, it’s fist-pumps and high-fives.  Good game.

Long Service, Secret Edge

Posted on by Stuart Murray
lockers-attributed-to-flattop341
Lockers, attributed to flattop341.

After many years in one job, little things can become easy.  Amongst the things that give you an advantage are small tips from colleagues about the way things really work.  For instance, I once worked in an office adjacent to a swimming pool.  At lunch, I would swim at the pool, and return to work relaxed and productive.  At this pool, there were coin-operated lockers that cost fifty cents.

I would frequently run into colleagues at the pool during lunch hour.  On one occasion, a long-service colleague attempted to use the same locker as me, locker #51.  He said “oh you go ahead and use the free locker.”  Free locker?  “Yes, the coin slot is broken but the lock works, so there’s no charge.”

This colleague showed me how.  Put your clothes in, close the door, skip the step where you put money in, then turn the key and pull it from the keyhole.  Lo and behold, there was a locked locker and a key in hand.  He handed me the key and said, “enjoy.”

In most workplaces, there are small advantages everywhere, just like locker #51.  An undiscovered staircase, prior versions of the report you’re working on, and contacts who can answer your question in one minute.  These are not always things that you find on the web site or in training materials.  These tips are not a result of having rank, data access, or an advanced degree.  They are just little tips that favor those who have been around for a few years and listened to their peers.

There are many twists and turns in our careers, things that make us energetic or complacent or curious or mad.  In the middle of these many changes, things get a little easier every year.  If we leave, we will lose this advantage.  I think it’s a secret reason why people stick around.

Can you think of the last time you found a locker #51 in your workplace?  What are some of the tips or tricks that you have learned from others?

Data Tastes Better With Ice Cream

Posted on by Stuart Murray
staunton-cherry-pie-attributed-to-tom-feary-no-mods-permitted
Staunton Cherry Pie.  Photo courtesy of Tom Feary.

One day, years ago, I was picking up my children from school. My son, who was in Kindergarten, said “it’s pie week.” I thought about it, and yes, we were approaching March 14th, which numerically is 3.14, also known as Pi Day. I knew about this event, but I didn’t know they were celebrating it in schools. Presumably, my son’s teacher had mentioned it in class. I asked my kids if we should buy pies and share with the class on March 14th? Yes! The children were all in favour of this. How could they say no?

The night before Pi Day I brought home four pies, two for each class of kids. I had forgotten to tell my wife, and she asked “What are these for?” I told her. She said Pi Day was not a thing, and besides, she added, the teachers won’t take time away from teaching to serve pie. I put one pie in the fridge for ourselves, and I took the other three pies to work the next day.

Although Pi Day had been celebrated before, it didn’t elicit excitement. To change this, I put the pie in the coffee room and sent out a pithy email at 1:59 pm. You know, 3.14159, get it? It has well received.

That night I asked the kids what they did at school for Pi Day. Nothing, it turned out. I asked my son, why did he say it was Pie Week? “I just wanted to eat some pie.” My wife gave me that look again, and shook her head. “Pi Day is not a thing” she repeated.  Her disbelief sent me online. Yes, there was such a thing as Pi Day. But my jaw dropped when I saw the photograph on the Wikipedia page, showing the founder of Pi Day at an event. I experienced a startling déjà vu.

When I was in my twenties, I took a trip to San Francisco. At the end of each day I would meet a family friend at his workplace, and he would drive us home. One day I stopped in, and he offered a slice of pie. Their office celebrated Pi Day on March 14. “It’s just a little thing I started up around the Exploratorium,” he said. The man who handed me that pie was Larry Shaw. He was the founder of Pi Day, he was on the photo on Wikipedia, and he had handed one of the earliest slices of Pi Day pie. I had completely forgotten this random moment, until my son reminded me by accident. I never knew that Larry started this tradition until I saw it online.

I have been organizing Pi Day events at my workplace ever since. It’s a time to pause and reflect on how math that has improved our lives in the past year. As we stand there eating pie, my math-y colleagues talk about the great work we have done around the office. We seal the deal with food which, research shows, improves the likelihood that people will agree.

Disrupt an MBA Class by Inventing Spreadsheets

Posted on by Stuart Murray
idea-cropped-by-katie-tegtmeyer
Idea.  By Katie Tegtmeyer.  Cropped.

This is a great TED talk by Dan Bricklin, the inventor of the electronic spreadsheet.  The application he created – VisiCalc – is the original precursor to Excel, one of the easiest to use number-crunching tools when doing workforce analysis and just about everything else.  He tells a great story of the disruption that his new tool caused its first audience, the MBA class he attended at Harvard, and the first conference where he revealed it.

This is a story of invention, so watch for key words like error, daydream, magic, imagine, prototype, feedback, find solutions, new capabilities, and marketing.  This is a story of iterative design, where they figured out what they were creating part-way through the exploration.

The Soil Cultivation Metaphor

Posted on by Stuart Murray
hand-1-by-david-pacey
Hand 1.  Attributed to David Pacey.

One of the greatest pleasures of home ownership is the opportunity to work in the garden.  Gardening is fulfilling for several reasons.  The accomplishment is satisfying and tangible, unlike a lot of office work.  Gardening is great physical exercise, involving a range of low-impact and core-intensive body movements.  Gardeners get time outdoors, bolstering vitamin D intake and exposure to fresh air.  By handling soil, our body develops a resistance to the germs and bacteria, or so rumor has it.  The work is solitary and meditative, improving mindfulness.  The home-grown and fresh-picked produce tastes better and is higher in nutrients.  Gardening is a kind of cure-all for wellbeing.

Soil cultivation is extremely similar to the practice of cleaning a data set.

My first round of soil cultivation was a patch of land that previously had a garden shed sitting on top of it.  There was no organic matter in the soil at all; just a dense patch of dust.  The soil required a major intervention to become useful.  This is also true about a new data set.  It’s great to have new data, but I just know it’s going to require a lot of attention before I can use it properly.  The data will lack clear labels, there will be columns or fields that are useless in some way, and some data points need to be converted.  Sometimes it simply arrives in the wrong format, such as on paper or ascii, or built around a different software environment.  The certainty that I must put work into it in order to get something back, turns this into “real” work.

With data I typically find that some fields are all wrong, and I need to track down or create “lookup” tables that convert the raw data into something that I know is accurate.  I don’t like throwing out data.  I prefer to just keep the dirty data on the left hand side of a spreadsheet, and to the right of a thick, vertical line, create a modified column or field.  The raw data is black, and the modified data is has color, so I know what I’m working with.  I also give the modified data more explicit labels, in succinct but plain English.  Many dubious data fields are suddenly rendered “accurate” by a good label.

As with my fully-remediated soil, my fully-amended data set means that I am ready-to-roll.  I can work with a converted and color-coded batch of cultivated data, culled of garbage and meaningless fields, and turned into something useful.

I know that some people think of a garden as a place where plants grow.  And some people think of data as something that is capable of producing analytic insights.  In both cases, there is something deeply human about taking a mess – soil or data – and turning it into something more.  We advance civilization one step at a time, one cubic foot at a time, one data point at a time.  Sometimes we just need to break a sweat, get some sun, work our bodies, and build immunity.

The Mathematics of Love

Posted on by Stuart Murray
coffee-hearts-photo-attributed-to-peter-burka
Photo by Peter Burka.

In this fascinating TED talk by Hannah Fry, the speaker describes three mathematical algorithms that explain love.  One of her findings was that the number of romantic advances someone receives is improved if there are polarized views of whether they are attractive.  That is, you will approach someone if you think that many people other than you will think they are unattractive.  How would we apply this to human resources?  I would point out that the Oakland Athletics baseball team was successful at snapping-up rookies that they knew were great and everyone else had passed over.  Using better metrics, the team found high-performers who seemed wrong, but were factually very good.  In many cases the Oakland A’s got first dibs on diamonds-in-the-rough.  Can you apply this insight to your own workplace?