Live blog notes from Matthew Hanwell’s presentation to the HR Tech Europe spring conference, London. Hanwell works in HR technology at NorthgateArinso.
Big data is 1.8 Zettabytes created a year says IDC. Big is relative term and you are already sitting on a lot of useful HR data.
Volume, velocity and variety are the new features of data. Can you keep up with this data and this variety and how do we interpret it? But just understanding headcount has proven to be a challenge for HR and finance.
We are in an open cast mine when it comes to data. We need to refine, process and interpret it and decide what is relevant for your business. The tools are there to do this on a a massive scale. Processing is beyond the Excel spreadsheet. It is more like an MRI scan – multi-dimensional vs the old style X-ray, which is the old way of looking at HR data.
Social network analysis is key – networks, tie strengths, key players, cohesion – does this analysis show performance and can it determine performance. Compare this analysis with the organisational structure – understanding the network analysis is critical for predicting performance. The
Unstructured data on the web is the growth area of big data. For example, the conversations, comments etc on the web.
You could understand what your people are saying using sentiment tools, such as Twitrratr, especially after corporate announcements and product launches.
Could you answer this question: How would you visually reflect your org to a decision maker?
HR is very good at aggregating data but it is one of the most dangerous things that has happened in HR. Gave an example of 5.2% global attrition rate at one company. The data interpreation was that nothing too bad was happening. The company saw no need to act but the data hid 40% of attrition in one area of the business and hardly any, 0.02% attrition, in another part of the business. It is like having one hand in oven and hand in the freezer but the body feels fines. ‘Search out the hotspots,’ said Hanwell.
Predicitive analytics will be hugely important for HR. How can we predict development needs, attrition rates etc so we can proactively intervene before we have a problem.
Can we find Gold from the data? Looked at Goldcorp case study. Goldcorp challenge – gave geological data away and ran a competition to find where the gold was. 52 companies participated and an Australian 3-d mapping company won. GoldCorp found $10bn gold from the data. Hanwell aaded: ‘Maybe you should publish your employee data.’
He summarised: data driven decisions are better decisions but knowing is not enough if it does not lead to action. And added that the biggest barrier to HR doing this is the attitude of HR people towards data (and skills and competencies) – the business is interested in this data so HR needs to get good at it.
