Technology & Performance Management

I am these days reading a book about Big Data, and going through some of the applications of the technology, I was thinking about some of the ways Big Data can be applied in people matters. I tried to google about usage of Big Data for Performance Management, and didnt quite find much (or maybe thats because the search terms show results for application performance management). One aspect of using technology in HR, I feel, is in the realm of Performance Management.

Today, appraisals are done in an objective manner, with ratings which try to capture achivements and performance. However, as we know, these are a sort of force-fit. What does a rating of “Exceeds Expectation” mean? Does this mean, for instance, that performance is high, or does this mean that expectations are low? Somehow, this seems to be like fitting a square peg in a round hole, or a round peg in a square hole, if you prefer it that way.

An alternative to this could be the usage of technologies like Big Data to handle this. To begin with, managers could have the option of writing their observations, along with specific examples or scenarios as part of the appraisal process. This kind of input gives us rich information about people performance. Instead of trying to fit performance into a quantitative scale, this has the possibility of giving us qualitative inputs into performance.

Add to this the fact that plenty of business-related data is available from finance, sales, and operations, and we have immense data, both quantitative and qualitative, with which to work. Using this data as the starting point, Big Data technologies could be used to build correlation between manager comments and business performance, and deriving employee performance based on this correlation. This has the benefit of giving a descriptive picture of performance, one which describes achievements in a more meaningful way which can be used to drive talent processes.

Theres much more that Big Data can be used for, as this post by @josh_bersin describes.


Big Data Analytics

For quite a while, I have been thinking that maybe I am the only one who doesnt understand what these words mean. I mean, with the buzz around these concepts (and here I mean the concepts, not the technology), these must be complex concepts to define, but the definitions that I was able to understand were all quite simple.

Big data is just that … BIG! There are essentially 3 things which define it:

1. Theres lots of it! Much more than we had imagined maybe even a couple of years ago.

2. The form of this data is too diverse. There text, images, videos, and what have you. Theres structured data and unstructured data, and data comes with its own context which makes it even more complex to handle.

3. Its being generated at a very fast pace. In fact, writing this blog is adding to this big data, as is your tweet, and those pictures you post on facebook, or those status updates that you like.

I was looking for whether this definition is correct or not, and I came across this video from Ericsson Research, which describes it quite simply with an example. If you want to get past the buzz and get to understand the concept, I would suggest you watch this.

So where does analytics come into the picture? Well, if theres so much of data, theres also the fact that its very difficult to build any coherent picture from this mass of data, and this problem is addressed by the analytics domain. Analytics helps us make sense of big data!

So what does Big Data Analytics need?

1. It requires infrastructure which is able to scale up or down based on the demands of the those who are generating this data, and those who are analyzing it. This means that the infrastructure needs to be flexible, and this can be handled much more easily with cloud solutions, and this is where cloud comes into the picture of big data and analytics.

2. It requires the applications which gather this data. A lot of this data is being generated by automated systems like sensors, and through mobile devices. With the scenario of equipment communicating with other equipment, the concept of the internet of things comes into the picture. Also, with the mobile device explosion, the importance of mobile applications and mobility solutions as an integral part of the picture also becomes apparent.

3. It requires the statistical and technology foundation which will help users or systems to make sense of this data. This is the analytics piece of the picture.

Heres a nice video about an IBM study on analytics.

This is how the picture gets a little clearer, and we can see how the cloud, internet of things, mobility, big data, and analytics are coming together to create a whole new technology paradigm.