Big data is the current hot topic, but is it a case of “Here we go again?” The next learning and development bandwagon is up and rolling and this time the wheels have been attached to big data. We’re being told that we’ve got to concentrate on big data; we’ve got to learn about it and we’ve got to embrace it (so some would say), but what’s the point of trying to grapple with big data when most of the people profession can’t really get their heads around small data!
In this post I want to be challenging – as always – but I also wanted to offer some advice and learning as a way of ensuring that you glean something useful from this post, rather than it just being some random rant . . so that’ll make a change then 😉
Do we know data from big data
The Learning and Performance Institute recently released the first six months of data from their innovative Capability Map. Of the 983 people who took this personal assessment, only 32% felt able to assess themselves against the capability of ‘data interpretation’ and only 12% of this elite band scored themselves at the highest level. This demonstrates that – for whatever reason – 68% of respondents felt unable to assess their data interpretation capabilities and only a rather lowly 3.7% of all respondents felt able to indicate that they excel at this skill. Whichever way you look at it the picture is poor. I appreciate that this is a generalisation, but as learning and development professionals we just don’t get data. Given these facts it would seem rather foolish to rush off into the areas of big data when we hardly seem at ease with simple numbers.
What would we do with big data anyway?
But let’s say we did get data – which we don’t. What on earth would we do with big data anyway? In his excellent post about big data Sukh Pabial is exceptionally honest when he discusses the benefits or otherwise of big data, saying: “So where does HR fit into all of this? Well, I’m not entirely sure.” And perhaps that’s it – we know it’s out there but we’re unsure of how to deal with it. As Craig Taylor (@CraigTaylor74) tweeted beautifully: “I’m not so sure I’m that interested in BIG data, I’m more interested in using the (small) data that I already have, to better effect.” Spot on, Craig!
What the heck is big data?
The term ‘big data’ is misleading because ‘big’ is a fuzzy term. Let me explain . . . as someone who stands 6’6” tall, most people would consider me to be ‘big’ – yet in 1999 the average height of the Cambridge Boat Race crew was 6’9”, which would make me ‘below average’ and a veritable dwarf when compared to some professional basketball players. Big can mean many things to many people and so ‘big data’ needs some further explanation.
According to Wikipedia “Big data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualisation. As of 2012, limits on the size of data sets that are feasible to process in a reasonable amount of time were on the order of exabytes of data.” The definition continues, “Big data is difficult to work with using most relational database management systems and desktop statistics and visualization packages, requiring instead massively parallel software running on tens, hundreds, or even thousands of servers.”
So that’s useful. Big data isn’t the stuff you’ve got in your average Excel spreadsheet or Access database, it’s the data that your entire organisation may hold. It’s BIG data with the emphasis on BIG!
Let’s not get too carried away though; we’ve been looking at big data for a while now. If you’re in the UK and have a store loyalty card – which, according to the BBC, 85% of UK households do – then you’ll definitely be adding to the massive pool of data retailers already hold about you as this article from the Guardian explains. It’s been suggested that big data allows retailers to know when you’re planning to start a family. Big data has been helping credit card companies for years in their effort to detect fraud, and if you think that the recent revelations surrounding the PRISM ‘scandal’ are scary then think again – security services have been using big data for years in their constant effort to keep us safe.
Here are some useful links which provide further insights into big data:
But what if it’s not big?
As we can see, big data really is BIG – massive in fact – probably more massive than most of us will ever come across. To be honest, for most of us I guess we think that data is little more than a collection of numbers. Perhaps it’s the pass marks from tests, perhaps it’s the location of learners, perhaps it’s the length of service of a learner – or perhaps it’s all three. Perhaps it’s the ability to assess whether location and length of service has an impact on test scores and therefore potentially performance. Well no. That’s just data.
Returning to the top of this story, the problem is – and is likely to remain – that we just don’t understand data. Perhaps then, instead of being wooed by big data, we should spend some time getting to know data, what it is, how it works and how it relates to other data.
Here are some questions all about data. Feel free to use the feedback option of the blog to share your thoughts and discuss what you think the answers are. This isn’t intended to show people up – it’s a real opportunity to share and learn.
Question 1: A meeting of entrepreneurs contains 100 people. Data shows that the average net worth of each of the entrepreneurs is £100 million. List as many things as possible you can determine from this data.
Question 2: It is war time. You are tasked with reviewing damaged planes coming back from sorties over enemy territory to see which areas of the plane should be protected further. You find that 70% of the fuselage and 30% of the fuel system of returned planes are much more likely to be damaged by bullets or flak than any other part of the planes. Which single area of the plane would you reinforce – assuming there is no difference in cost or performance?
Question 3: A study is looking at the success rates of two different approaches to teaching people to drive – called Approach A and Approach B. The success rates for both male and female learners over a four month period are as follows:
- Month 1 – Approach A: 93% success, 81 out of 87 passed first time
- Month 2 – Approach B: 87% success, 234 out of 270 passed first time
- Month 3 – Approach A: 73% success, 192 out of 263 passed first time
- Month 4 – Approach B: 69% success, 55 out of 80 passed first time
You have to select one approach to be used across the country. Which one do you choose, Approach A or Approach B?
Get to know data before you try and get to grips with big data. The truth is that if you don’t understand the former then you’ll never understand the latter. Although for many learning and development professionals data is a horrible thing to think about, challenge your fears and learn to love data – because if you do then you’ll make far better decisions in the long run.
Call to action
A great starting point for getting to know and love data is the BBC’s More or Less radio programme.