HR analytics must look forward, not backwards
Developing HR’s analytics capability to offer predictive insights is an important challenge with which HR teams need to engage, according to a new paper by the Institute for Employment Studies (IES).
In The path towards predictive analytics, author Peter Reilly, Principal Associate at IES, emphasises the distinction between predictive analytics and other management information that does not offer the same forecasting capability. Whilst acknowledging the value of straightforward data reporting, he describes how HR can use predictive analytics to solve important business problems.
The report comments that while quality management information, new ways of reporting (dashboards, visualisation methods and the like), measuring employee engagement, talent statistics, etc. are all important, they are not solving business problems. For example, says Reilly:
“Knowing how to construct an employee engagement measurement scale is a necessary step before connecting to other data items but is not an end in itself. Being able to describe clearly who your top performers are and what the aggregate turnover rate was in the last five years is very useful, but would be much more powerful if you can say what the turnover rate was for your high performers compared with the average and what were the main causes of resignation amongst this elite group. HR analytics comes into play when you predict future turnover based on certain future assumptions and set out the impact it would have on business performance.”
So, what sorts of benefits arise from proper HR (predictive) analytics? The report highlights several questions that the author has seen answered, including:
- What HR practices are associated with encouraging organisational innovation?
- Which locations are likely to combine the best workforce and business conditions?
- What are the costs / benefits of flexible development, internal mobility and such like and what does analysis suggest is the optimum level of people rotation?
- In understanding labour costs, can one take the elements most susceptible to change and model the effect of their reduction on business performance?
- Is there a reliable link between employee engagement and productivity, and which ways can the latter be raised through engagement interventions?
- What people related issues do we need to focus on to improve sales?
- Is there a connection between leadership training (and even socialisation) and safety performance?
- How do you measure organisational culture and what is the relationship between it and organisational performance?
- What are the main people related risks to organisational performance, what impact would they have and how can one mitigate them?
- Can one prove that manager selection impacts subsequent team performance? Which management characteristics have most positive effect?
“Some may be daunted by this list of questions either because they lack the data or the skills to be able to answer them,”
“The standard response to this concern is to steadily build the ability to perform the necessary tasks by improving the comprehensiveness and integrity of your data, by investing in suitable technology to manipulate these data and by hiring / developing staff competent to do the analysis. However, there is an alternative view that this process takes too long and relies too much on the faith of the business to fund the changes without a guaranteed return. Those that take this view say it is better to pick a pressing business issue and get sufficient data to have a stab at addressing the problem and then present interim results back to colleagues with the aim of getting support and resources to finish the job.”
To progress towards predictive analytical work, the report advises, employers need:
- growing understanding of the business challenges relating to people;
- improving knowledge of external environment both in its impact on your own organisation (e.g. legislation or labour market change) and in terms of new research insights;
- turning more to standardised reporting and dashboards, avoiding time-consuming ad hoc reporting;
- pushing the use of self-service tools that allow managers to obtain their own data and run their own reports;
- prioritising the strategic business issues rather than the urgent but less important;
- building capability:
- in the analytics team, increases technical competence but also improve problem specification;
- create cross-functional communities of practice so that one can agree definitions, have access to a wider range of data sets, learn from others and share insights;
- create an ‘intelligent customer’ profile so that HR business partners and their clients know better how to identify issues which are susceptible to analytical intervention.
- developing the use of sophisticated communication tools to lead to better ‘story telling’ in conveying the results of your analytical exercises to a wide audience.
In conclusion, Reilly comments that HR analytics has the potential to add a lot of value to organisational understanding of the link between people and organisational performance.
“It is not an easy task to build the capability to add insight in this way and requires investment in data management, systems and especially staffing. It also requires discipline to ensure that giving attention to these sorts of challenging tasks is not compromised by spending too much time on other worthy activities. Finding a language and process to distinguish between the different types of contribution that management reporting and analytics can make to organisational success is important precisely so as to allow the time and space to tackle the difficult but rewarding predictive challenges reported above.”