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People Analytics

Fact based decisions through powerful People Analytics

People analytics can enhance the power of a dashboard in various ways

You might shy away from “People Analytics” (PA) thinking that it is a completely new field in HR that requires different inputs and different skills (which you believe you don’t have at hand) and is therefore “a big project we can’t handle right now on top of everything else”. In many organisations the situation is rather the one of somebody buying a new car with modern safety features (e.g. lane-keep-assist or adaptive headlights) – and not switching them on. So we encourage you to view People Analytics as great new opportunities to complement your existing HR work – just “switch them on step by step”:

Most HR functions use some sort of metrics – ideally a dashboard. People analytics can enhance the power of a dashboard in various ways:

Reactive analytics:

While “reactive” versus “proactive” typically has a negative connotation, there is really nothing wrong with truly understanding the past and present before taking decision about the future. So reacting to a Key Performance Indicator (KPI) being off target by looking at the related data (via descriptive analysis) is a good start. After all, it is important to make sure all stakeholders understand what the data tell before engaging in decision making about measures. Drilling into data related to the KPI and identifying patterns creates a sound platform for joint action. Visualization usually does a much better job in explaining a pattern than long text full of jargon – most of us intuitively understand pictures much better than text. We often run this kind of little project with clients – whether they use an “ailing” KPI as a starting point or – if they don’t have KPIs yet – use the first project session to come up with hypothesis about pain points in their organization. Then we jointly “switch on” the analytics capability of our client – identifying and analyzing data that could be related to the topic with the goal to get to an actionable insight.

Have you for example ever ventured into understanding what drives the fact that in some areas of the business most open positions are filled within short time and at low cost with high performing candidates who stay – while in others, especially Millennials take long to be hired via expensive campaigns and leave again after a short time. What would you answer if your CEO asked you how to explain this in a few sentences?

Proactive analytics:

In the past, too many analytics project have produced little more reaction from top management than a polite “That’s interesting” – but lacking the second, much more important part “now what do you suggest we do to address it”. People analytics are only worth the investment and help HR in their role as value adding partner if they include recommendation for action and a business case including expected cost and return. In particular we have seen cases where – based on patterns behind success stories related to concrete P&L impact (e.g. high performing teams, successful leaders) – we helped HR teams identify action that could trigger “more of this” – and therefor shape action items proposed to management or simply processes and structures in general accordingly.

Have you for example ever checked what is behind the fact that some departments constantly “produce” high performing teams while others don’t? What would you answer if your CEO asks you what to do to triple the number of high performing teams?

Predictive analytics:

Who hasn’t heard this one (attributed to Niels Bohr): “Prediction is really hard, especially about the future”. The tricky part of predicting what will most probably happen in the future is that we only have the past as an input (e.g. “In 2016, employees with a technical college degree and a tenure between 2 and 4 years who worked on more than 4 parallel projects had 82% probability of leaving” – ok but does that mean that John will quit?). Nobody has full data about the past and future situations will be impacted by factors not previously known – that is why it is absolutely essential to build business and functional acumen into models that predict that future. While some software vendors claim that their solutions have predictive models “built in” we have seen that truly valuable and actionable predictive insights need HR to go beyond automatic crunching of historic data. Best results – i.e. avoiding costly problems or boosting people driven innovation and efficiency – are usually achieved by combining internal understanding of culture, strategy and data with temporary expertise regarding the analytic process (including its limitations).

Have you ever celebrated with your team because your fact based insights into consequences of poor change management helped you design learning and feedback structures that increased return customer business by double digits?

F-Top Institute supports clients in all three types of analytics in order to get powerful results in a fast and efficient way: Structuring pain points or success stories, identifying the data sets needed for analysis, cleaning the data, processing the data, validating the results, interpreting the results, recommending solutions and actions via bringing in the best practice from the financially most successful organisations.