10 Small Tips on Big Data – Don’t bite off more than you can chew

By definition, it is more bits and bites, mega- and giga-, than we can get our heads around. The idea is that technology these days – with few professions excepted and for sure not HR – can make pattern sense where we cannot by working through the enormous volume of information that modern life accidentally collects.

The big data consequence is the challenge to us to make good sense of how to use it. I have struggled with the volume of material, the glossy showcasing, the new buzzwords. So, I have struggled to find relevance for the real-life people in my network of colleagues, clients and associate partners.

Daunting for all no doubt and many don’t dare start.
I very much like the People Science concepts, as emphasised for example by Sage People [i], global HR and people system. Look out for this. Find a close correlation between this and equally impressive academic research work for HR on Evidence-based HR Management (EBHR) [ii].
Here I’d like to consolidate and digest into some manageable tips. They may not be big but they may be where you’re at:

Read on for 10 clear and practical points to help you make big data bite-sized [iii].

• HR must recognise and learn about a new set of skills associated with big data –for example the Data Scientist or the People Analyst, but variously termed so far. We have to work out the specification and recruit to it.
• We are wise to focus our data outside of HR, looking to measures that are about our organisation and our clients (and I don’t mean our employees but those who pay our employee bills!) Traditional HR measures take us little forward where there is new potential.
• This means using more than one data set. Expect big data to expect you to work out different sources of relevant information to pull together in drawing insights. For example, writing on EBHR points to 4 sources to seek to triangulate.
• Cross-functional working (and see tip no. 3) is key on people data. Be ready to work closely with Finance, IT, Sales, risk functions for starters. Big data requires thinking around as many verticals as you suspect create limits.
• As human thinkers look for blind spots in our ask of big data – thinking laterally will help us “mine” for results that really offer something new. This is hard to understand. In practice, I’m suggesting you look to the places you don’t have data (such as those who fall out of a system or process rather than the stayers, or those who don’t engage in feedback). A related hint is that we tend to “solution-eer”. This is when we focus on the lack of a solution rather than what the problem itself is. HR have to get better at identifying questions
• Start small but go deep. It is better to identify one or two key target areas to probe the wealth of data than to take a scatter-gun approach and blindly expect to hit the jackpot insight which will take your practices further.
• You probably need tech tools to “do big data”. HR can start with the analytics kit within the HR system (if you’ve one of the best). Whilst we can apply some insightful thinking to our people observations, the possibility of big data means extending beyond our brain’s grasp
• HR have an extra job to attend to the implications of big data use. Firstly, there are the hard facts about security and compliance. Secondly there are questions of culture and sensitivities in the use of personal information
• Understand the sales pitch for people data! It is now proven that people and performance (including tangible measures of talent and engagement) add value to those client-centric KPI’s (see tip no. 2)
• My bonus tip: I recommend getting your head around what an algorithm is. Understand its value but also its limitations. Understand that to a degree you can DIY it with your own thinking (but see tip no. 7) This is simply about knowing what you’re working with. If you’re trusting in rules, which I recommend you do, then pick the designers right!

These tips are a concise, condensed consolidation of where a small and local professional world might be at with big data.
If you’d like more explanation behind my points then do ask for or look out for a meatier read. Or get in touch with practical insights you’ve drawn in your analytical start.

[1] Visit www.sagepeople.com for more information about the Sage People product as well as further content about People Science
[ii] Rob Briner, Professor of Organisational Psychology, Queen Mary University of London, is great to read on this topic
[iii] We like bite-sized at Phase 3 Consulting. For us it means all that manages volume with a modest pragmatism and with expertise, to get results

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