Try Did You?

This afternoon, I got to my meeting a bit early and noticed that there was a still a crowd of people in the conference room that I was scheduled to be meeting in.  So, I waited in the hallway for a few minutes.  It wasn't long until the crowd of what seemed like fifty people started filing out of a conference room designed for fifteen!  I didn't notice anything in particular about them, but when I walked into the room they had all vacated, I noticed a bit of their presence remaining.  The room was definitely warmer than the hallway and had a touch of body odor.

I thought that maybe I could cool the room down before my meeting started.  I assumed the thermostat would be covered by a clear locked box and wasn't surprised when I found it that way.  The counter-culture hacker in me said, "maybe you can pry it off or pick the lock."  So, I figured I should at least give it try and wiggle the plastic cover.

It came right off the wall.

And I turned the thermostat down a few degrees.

And everyone in my meeting was happier for the not-so-stuffy-anymore room.

All because I questioned my assumptions and ignored my expectations of failure.  Or maybe it was my Jedi mind-powers that unlocked the plastic cover over the thermostat.  Who knows.

Data Modelers Model, What do Data Scientists Do?

Steve Hoberman (of various forms of data modeling fame) had an article on Information Management recently that poses the question: "what is the difference between a data modeler and a data scientist?"  I think that most people who have been hearing the term "data scientist" going around realize there are certainly differences, but the article does a nice job spelling that out in a gap analysis.

This got me thinking, though, about how rarely people on BI projects play multiple roles.  It's been one of the biggest challenges we've had adopting an agile methodology, I think.  The data modeler becomes a bottleneck for developers.  Analysts have to finish mapping documents before data modelers can finalize attribute names.  If a user decides that something really needs to be many-to-many instead of one-to-many, it trickles down through data modeler, developer, reporting, and testing.

Why don't we put stronger emphasis on one person having the breadth of skills to play multiple roles on a given project?  If a requirement changes, the number of system components impacted may not be any less, but the number of people who have to understand the nature of the change could be significantly reduced.  I'm not saying that business analyst, data modeler, ETL developer, and UI developer aren't different and equally valuable skills to develop; but I am suggesting that a single person should be able to play more than one role on any given project.  I think the result would usually be leaner and more efficient projects.

The challenges - leadership trusting that team members can take on multiple roles and develop those skills, and helping team members break out of their shell and prioritize the development of new skills.

Back to Steve Hoberman's discussion -- can we change it to "what's the difference between data modeling and data science?"

Macrowikinomics

I've been reading Macrowikimomics by Don Tapscott. Great read.

One of my favorite things is the connection I see between his description of "platforms" that people are building to leverage and focus social collaboration and the Unix Philosophy of 40 years ago. Where I am in the book, he's only just now started to reference Linux and the Open Source movement. (Shocking realization: I got into Linux in year 1996 when it was only 5 years old. Now Linux in 22 years old.)

I'm starting to draw connections into my own professional life in healthcare. I think there are home opportunities to leverage "the commons" to improve the business of healthcare. My opinion: healthcare technology and business services vendors are a huge part of the inefficiency and cost of healthcare. If we take their value proposition and make it deliver it through open collaboration instead, we have the opportunity to eliminate that waste, improve the value being delivered, and extend that value beyond only those health systems that can afford the exorbitant fees.

Let's give that a try and see how it goes. Watch for updates...