In The News : Why I Love Data

Probably the question I hate the most when meeting someone for the first time is, “What do you do for a living?”

I add weight to when the question first appears in a conversation because work isn’t everything to me and, while I know some people are genuinely lucky enough to make a passion their job, I’m more interested in knowing what people do for a fun.  There’s a time and a place for talking about work in a relationship, and within 10 minutes of it starting probably isn’t it.

The main reason I hate the question, though, is that I don’t find it easy to tell people what I do.  I’ve had friends for years not able to explain it to soon to be mutual acquaintances.  I usually prefer to answer it in four stages.  I start by saying who I work for.  If pressed, I’ll then say that I work in IT which is loosely correct.  When they assume I fix the office printer (as part of my day-to-day duties) I attempt to explain to them what I really do, which is working with master data.  When they don’t get it, I tell them that I count the components of our products which is, again, loosely correct.

The problem with trying to talk to people about master data is that those that know about it don’t need to ask, and those that need to ask will inevitably find it as dull as dish water, hence why I don’t flaunt it.  For the sake of this post, I’ll have to explain it, so I’ll do it quickly.

Master data is data that drives all the other business processes and which should not change (although it will invariably age and become obsolete).  In the industry I work in, this comprises data on our customers, vendors, banks, materials and products, including other secondary and tertiary objects such as bills of materials.  By way of comparison, non-master data would something like a contract or pricing information.

Got it? Good.  So something else I used to do was develop on-system workflows – a set of steps that ensured that the right work was with the right person at the right time.

In a kind of metaphor for my life, which is possibly why I enjoy my work, what I do enables other things to work properly.  The problem with computer systems and processes though, is that they’re only as good as the data you input.

This is why I always find it amusing (obviously only in the one sense) when I read stories about how computers got something wrong.  One such news item recently was when NHS computers failed to invite an estimated 450,000 women between the ages of 68 and 71 to their final screening for breast cancer.

The health secretary, Jeremy Hunt, made a statement last Wednesday apologising for what he termed a “computer algorithm failure dating back to 2009”.  Another part of the statement referred to “issues with the system’s IT and how age parameters are programmed into it”.

I should imagine that this is as outrageous to a lay person as it is to me, to get something so simplistic wrong.  In my world, I further see a lack of testing, governance, data standards and regular quality and integrity checks.  Oh, and a human able to understand exactly what it is that the system was designed to do.

Because any good computer process needs to work offline before it can be made to work online.  It’s then scaled up.  So, with sending letters to women of a particular age group, someone would physically look down a list, fold a letter in to an envelope, address it, lick a stamp and post it.  Mistakes are possible, especially in great repetition, which is where computers help.  They’ll follow the rules they’re given to the letter over and over and over and over again and they only go wrong when they’re not told clearly what to do or the data that they’re given to work with is not complete and correct.

We have a lot to be thankful to technology for.  Ironically, it was a new IT system that first spotted the failure in the NHS’s algorithm nearly a decade a go.  As with everything, though, it’s only as good as what you put in to it.  Perhaps I need to put more effort in to telling people what I do for a living.

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