For the past few years, buzzwords about (big or small) data and making sense of all that information have been thrown around quite often by industry research analysts and vendors alike.
First things first — what is big data? Where does it come from?
According to the Gartner IT Glossary big data includes high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.
The fourth V, veracity can be considered the most important. How accurate is that data in predicting business value? Do the results of a big data analysis actually make sense? Data must be able to be verified based on both accuracy and context.1
More specifically in the context of HR professionals, department managers, chief learning officers, and training managers, the vast pool of information consists of personnel data, learning or training data, job profiles, competencies, performance appraisals, and more. Your organization already has some or all of these pieces of data, and even a lot more. One of the challenges is that these pieces of information are most likely stored or recorded in silos.
Last year a group of executives at one of our big company clients decided to take a hard look at efficiency and outcome issues around learning.
Having to deal with a variety of use cases, end-user groups and training providers, not to mention the complications of operating in more than 50 countries and 18 languages, the executives saw their immediate task as getting on top of the data.
To this end, they put the following into effect:
All courses, seminars and training events now end with a mandatory, standardized evaluation comprised of five questions, the first being the by-now-classic Net Promoter Score (“NPS” or the number of raving fans minus the number of complainers divided by the total number of responses multiplied by 100, this process yielding a number somewhere between minus and plus 100 – big positive numbers are good). The NPS question is followed by simple, sensible questions on each training program’s relevance by job role and topic, quality and effect.
Individual employee progress is now measured the same way and on the same scale for all training.
Costs are standardized on a per-employee basis and resolved to a base currency.
I just read an article on Forbes magazine online about IBM CEO Ginni Rometty predicting three ways that technology will change the way we do business. The Forbes article was based on Ms Rometty’s speech at the Corporate Conference of the nonprofit Council on Foreign Relations. There is a video recording of this session here.
I couldn’t agree more with all the three ways that Ms Rometty analyses, and I believe all three of these ways profoundly affect the business we are in: human capital management. Here’s how:
Analytics – data analytics are coming to HR and the ability to harness talent-related data affects every talent-related function from hiring, to training, to engagement, to career development, to succession planning, to retention, to compensation, to dismissal. Moreover, talent analytics provides the link between talent management processes, business metrics, and value creation.
Social – it may sound like a cliché, but the new fabric of the enterprise is social and it is strategic. Social technologies are enabling employee collaboration, knowledge and expertise sharing, people search and team formation, informal learning, continuous coaching and mentoring, and peer recognition models in a way that transcends formal organizational structures and redefines strict HR transactional processes.
Personalization – we see personalization into the talent management as targeted recruitment, personalized learning and development plans, on-demand performance support, workplace technology consumerization, and individualized career paths. This is the point when talent management is transformed from an HR-driven process to a business-driven one.
These three ways are not predictions into the future, but instead they are changing our business today. Thoughts?
Big Data is all the rage right now. Industry analysts and pundits of every stripe are singing the praises of analytics the way snake oil salesmen once hawked miracle potions to help us all live longer, healthier, more fulfilling lives.
Would that data analytics were as simple as buying a bottle of potion.