Best Practices for Big Data?
The Big Data fad has really caught on as a hot topic in Human Resources analytics, largely due to HR being one of the last corporate functions to really embrace the idea that loads of data can inform strategic decisions. Providers and users of talent assessment and performance management are now jumping at the opportunity to showcase how “big data” can solve big business challenges.
There are some alarming statistics out there about the Big Data Movement; IBM recently noted that 2.5 quintillion bytes of data are being produced daily - meaning 90% of the world’s data have been created in the last couple of years. Granted, not all are connected to the HR footprint, but we know that a bi-product of Big Data focus is companies spend more time and resources collecting data than analyzing and using them to solve real world problems in real time – and HR is no different. The jury may still be out on a comprehensive list of best Big Data best practices, but having used copious amounts of quality data to help clients solve business challenges (and experienced my share of mistakes along the way) I find it important to at least recognize the following factors in making sense of any volumes of data.
Use your head. You’re far better off starting with an idea than somehow finding a needle in a haystack. What Big Data experts fail to note is the resources required to crunch and process all your data is staggering. So start with an end in mind – what are the critical questions needing to be asked and answered in order to deliver real value to the stakeholders. Start with the stakeholders and create a map –understand what they want/need now, in one year and in two years, then determine what we need to do to capture, measure, analyze and report back on exactly that.
Do not assume cleanliness. Data are almost always touched by human hands. Even among top-tier providers of applicant tracking systems (ATS) and your own internal IT departments and HRIS functions, the big challenges with Big Data are that what you need is rarely going to be easily accessible and in one system. This means time, mistakes and rework, so having a plan that outlines the desired outcomes will allow those who are supporting data extraction, merging and delivery to do their best for you.
More is rarely better. Volume of data does not equal quality of data. So think like performance management processes – it is impractical to sit with your direct report and tell them to work on improving 67 things as part of their annual development process. It is more likely you are discussing 3-5 topics to work on for the next year. Eliminate the noise in the data that interferes with a clear line of sight among 3-5 critical variables to inform solid strategic decisions.
Be prepared to answer “what do we do?” The words ‘So what, now what?’ are getting thrown down more in meetings today than ever before. While great that Big Data can inform diagnosis, it is also critical to deliver recommendations on how to move the needle or close whatever gap is uncovered. In my experience, 95% of executives don’t care about your data – they want prescriptive recommendations about what to do regarding the data. Actionable data are better.
Do not “drink the Kool-Aid.” As you continue to amass data that supports your map for success, don’t be afraid to explore how clean, complete and useful your data are with respect to informing strategy. Course correction is a necessity (particularly as the corporate priorities shift) and it is also far easier to expand on smaller “chunks” of Big Data than it is to figure out what is wrong with your current approach because your Big Data are too big.
In closing, Big Data has tremendous potential, but it is unrecognized to date; few are sure where to even start. Trying to make sense of all of it at one time is next to impossible. Starting with manageable, bite-sized pieces will help you avoid analysis paralysis, keep you focused and deliver a much clearer message.
James H. Killian, Ph.D. is Vice President | Research & Advisory Services with Chally Group Worldwide, headquartered in Dayton, OH. Chally Group focuses on helping companies drive profitable growth by supporting their execution of data-driven winning strategies in sales and leadership development.