How do you define "innovation"?

Scott Berkun: I strongly recommend people use this word as little as possible. It’s mostly a distraction. Many great ideas and breakthroughs were achieved without people worrying if they were innovative enough or not. They simply chose to try and solve a problem they or their customers cared about. And then later on, after the hard work was done, they were called "innovators." It’s a good word to let other people say about you, rather than use it in reference to yourself.

His book, The Myths of Innovation is a sharp, if short read. This quote encourages me to re-read it.

I have been speaking to a lot of HR audiences lately, and sometimes they get a little uncomfortable when I bring up the analytics topic. Most HR departments don’t do a good job at analytics, and then hey wonder why they don’t get the budgets to make an impact on the business.

One of my suggestions to HR is to hire a good numbers person, someone with strong undergraduate or preferably graduate statistics.

Looks like this is exactly how the Evil HR lady got her start.

I had a master’s degree in political science, with a strong emphasis in statistics.  Since you never see a “Help wanted:  Political Scientist” sign in the window, I knew I needed to look outside my field of study.  What I really wanted to be was a trainer.  I knew that trainers often work in Human Resources departments, but how in in the heck was I going to get a job in HR?

Well, first, I went to a temp agency and asked to work in an HR department.  “I’ll do anything!” I said, and I meant it.  If the temp agency had sent me to wash windows in an HR department, I would have done it.  Instead, they placed me as an admin (I can type!), and for 6 months in a couple of different assignments I worked as an HR admin.  Then, I saw a job posting.  Job title?  HR Metrics Specialist.

What on earth does an HR Metrics Specialist do?  Well, I didn’t know, but one of the qualifications was the ability to do statistics.  That, I had.  So, I applied, interviewed and was hired.  My boss told me flat out that the only reason they had hired me is that I appeared to be the only person in the universe with a modicum of HR experience and the ability to do statistics.

I’ve been ranting on about this topic for ages, here are a few.

http://blogs.gartner.com/thomas_otter/2009/09/07/scrabble-and-hr/

http://blogs.gartner.com/thomas_otter/2009/06/08/via-a-comment-via-a-link-the-three-sexy-skills-of-data-geeks/

http://blogs.gartner.com/thomas_otter/2009/02/23/accountings-big-problem-according-to-archibald/

http://blogs.gartner.com/thomas_otter/2009/02/19/banging-on-about-hr-analytics/

http://blogs.gartner.com/thomas_otter/2008/12/06/measuring-twice-cutting-once/

so it is nice to see some validation…

Mathematics is a beautiful thing. Spend 20 minutes in the company of Benoit Mandelbrot. (click here if you can’t see the video)

If Hans Rosling can do this with demographics on a global scale, why can’t HR do it with their data? (click here if you can’t see the video)

By the way: Jim Holincheck and I recently published quite a bit of research on workforce analytics, and there is buckets of cool stuff on pattern based strategy on Gartner.com

Photo via the cc of sgt. PepperedJane. thanks!

To score well at Scrabble, you need to look at the score, not the just word. Long words across the board might look good, but unless they land on double or triples, you simply waste letters and open up the board for the others to score. Literary types like to think that they are good at Scrabble because they know lots of words and are well read, but Qi or QANAT aren’t something that even the most literary of souls come across in literature. To win at Scrabble you need to look at the numbers and the odds, know what letters have gone already, and have a mental database of short nasty words like ZO and XU. Sure, a love of words helps with Scrabble, but to score well, you need to engage the numeric side of your brain.

It may be stretching it a bit, but I think HR has a similar challenge.

To be a top HR professional, you do need to have empathy for people. It is probably what attracted you to the job in the first place. But if you are going to succeed you need to be analytical too. HR professionals that can see patterns beyond the incident, abstract the problems from the personal, and make the best move given the constraints  they have been dealt with, will have a real impact on shaping the business and their careers.

We are doing a lot of work at the moment on pattern based strategy here at Gartner (clients see this). I’m going to be exploring this is in an HR context later this year.  Extracting and analysing patterns out of the mass of data sources and conflicting signals. HR is going to get a lot more analytical.

Tony Hirst, who I linked to the other day about the UK politics mashup, came back and commented on my blog, so I followed a couple of his links and I ended up at the delightful Dataspora blog.

The post the three sexy skills of data geeks is excellent. Here is the concluding paragraph, but read all of it.

Put All Three Skills Together: Sexy. Thus with the Age of Data upon us, those who can model, munge, and visually communicate data — call us statisticians or data geeks — are a hot commodity.  I grew up before the age of geek chic, when the computer wizzes were social pariahs, and feature-length movies were dedicated to nerds seeking revenge.  But in the last decade, Steve Jobs became an icon, the Internet became cool, and an entire generation of tech kids grew up well adjusted.  They even built the social web to prove it.   I believe the same could happen to statistics and data geeks too.

I spent Friday night on the phone with a large company asking about how to sort out their HR analytics issues. My advice was to hire such a person, and not worry too much about whether you need to do the charts on tool a or b. I didn’t put it quite as eloquently as model and munge though.

Bowman, Archibald 1938. “Reporting on the Corporate Investment” Journal of Accountancy, May 1938 p. 39

This one of my favourite business related quotes. I’ve quoted it many times, but I figured it is well worth repeating here. I’m planning to use it in Vienna tomorrow when I talk about workforce analytics.

And now for my little Monday rant.

It is high time that HR analytics moved up a gear. Too many HR leaders are sitting on a pile of data and doing very little with it. Also I would like to see a lot more collaboration between HR and Finance on management measurement.

Currently both disciplines talk a lot about performance management, and even the competition for ownership of the acronyms is fierce. Is EPM Employee Performance Management or Enterprise Performance Management? Surely it is hard to do one without the other?

Yet I don’t see much collaboration, either from the vendors or departments, but I would love to be corrected.