I spent yesterday at the jobs2web conference, a recent acquisition of Successfactors, which is a recent acquisition of SAP. They are a recruiting marketing software firm – they make it their job to make recruiting on the web as easy as possible.
I had a chance to visit with John Greene (Client Services Director) and Phil Schrader (Analytics Manager) about their analytics functionality. They’ve done a nice job of making all sorts of recruiting activities track-able, enabling advanced reporting of the candidate traffic. For example, in what they call their “cost of doing nothing” stacked bar chart, they depict the total volume of candidates as well as the proportion of candidates coming in through various channels, which, because of their work on tracking, accounts for the near-whole picture of candidate behavior and movement. This chart, as well as other reporting functionality, makes evaluating the wisdom of specific recruiting investments quite easy for those in the recruiting function. It fulfills the promise of analytics – enabling better decisions, in this case, in regards to an organization’s recruiting strategy.
It is, however, not quite ‘analytics’ – well, on second thought, I suppose it depends on your definition of analytics. I define it as using statistics embedded somewhere in the program. However, like every provider I know of in the talent management software space, the solution is that of aggregate reporting rather than predictive statistics or forecasting. Many organizations are not yet to the predictive stage in their analytics practice maturity (there still sit in what we call stage 2 – see Josh’s Big Data report http://insights.bersin.com/research/?docid=15430 for more), so this advanced reporting functionality is needed – without a doubt. But the holy grail of predictive analytics is still unrealized.
But give jobs2web a year or two, maybe less. They are perfecting a system of ‘normalizing’ job types across organizations, which will allow them to say with authority the best recruiting grounds for certain types of jobs. This type of analysis uses regression (most likely) and will be useful in predicting the best way to spend recruiting dollars by job type. In other words, rather than adjusting the current recruiting strategy to just-in-time data from their system, they will be able to advise their clients on how to invest smarter from the get-go.
Take the application of normalizing jobs one step further. By tapping social media data or collecting additional data from not-yet-applied candidates, jobs2web could supply those in the trenches of workforce planning a talent supply report, letting them know not only how to recruit certain types of employees better, but where to recruit them as well. Want to open a manufacturing site in China? Where is the managerial talent located within that mammoth country? How about in 10 years when the workforce is even younger than it is today? If they follow a natural R&D course with this capability, jobs2web may be well-positioned to do workforce supply analyses in a just-in-time way that could rival the work done by our economist brethren. Couple this analysis of supply with increasingly advanced predictive statistics applied to the demand side of the equation (extrapolation of workforce segment growth and shrinkage based on the business strategy, employee performance, and turnover) jobs2web might enable organizations to play a whole new ball game. Revel in the power of analytics!