• 00:16
  • Monday ,27 March 2017
العربية

Educated guess vs analysed data: The importance of analytics for strategic CHRO

By-oachim Skura- dailynewsegypt

Opinion

00:03

Monday ,27 March 2017

Educated guess vs analysed data: The importance of analytics for strategic CHRO

The 18th century English writer, Alexander Pope, once said: “a little learning is a dangerous thing.” Much has changed in the 300 years since then, but our propensity to make decisions based on hunches and incomplete information has not.

It is second nature to make ‘educated guesses’ in our day to day lives, whether it is going to see the latest movie by a trusted director without looking at the reviews first, or getting a fresh paint job by the contractor who has been around the longest. Quite often, people just need to make a decision based on a ‘gut feeling’ or a quick comparison of the given options. At worst, a wrong assumption in these scenarios would only lead to watching a disappointing movie or a repaint.
 
The educated guesses we make at work can have much more serious repercussions. In my experience, these generally fall into two brackets:
 
Assumptions based on unfounded correlations; for instance, there is a widespread belief that millennials switch jobs more often than their older colleagues.
Decisions based on short-term rationale; such as the tendency for companies to make HR decisions based only on their current bottom line instead of their long term goals is a prime example.
In the world of work, we cannot afford to rely on superficial or fleeting learning, certainly not at a time where the future is so uncertain for businesses. A concrete understanding of how people’s actions affect the business, their needs, their motivators, and their competencies has never been more important. A more integrated analysis to data is the key to building this solid understanding.
 
Thankfully, a new generation of powerful analytics capabilities allows businesses and HR leaders to feed more informed decision-making while removing the above biases from the equation.
 
Assumptions companies make when managing their people can be quite damaging. For instance, we tend to assume candidates from good schools will better serve the company but how many organisations actually track this in the long term?  I’m currently working with a pharmaceuticals company on a sort of ‘intellectual playground’ where we look at how analytics can make HR more strategic.
 
On the issue of a potential hire’s previous schooling, one of our projects involves tracking long term employee performance to see how strong or weak the link is between factors that affected a hiring decision and their performance over multiple years. The results may yet prove traditional assumptions wrong. Just think of what that would mean for hiring strategies.
 
The point here is not that one analysis will reveal once and for all which schools a company should hire their talent from. Rather, the argument is that analytics can debunk received wisdom, help us address biases we might not recognise, and provide insights we would never get otherwise.
 
Unfortunately, most HR leaders do not take full advantage of HR analytics to make better decisions about employees, largely because they perceive factors like engagement and wellness to be matters of instinct rather than hard numbers. This simply is not true. In fact a more objective approach to people management helps HR take the bias out of decision-making and instead apply sound principles that benefit the entire organisation over time.
 
The challenge with HR analytics is to combine hard data on things like hiring channel tracking, a candidate’s educational background, or a worker’s measurable output with soft data on employee engagement, workers’ perception of HR, and results from performance reviews. This is the only way to gain a complete picture of how all the relevant factors interact to drive employee success, or stand in its way. It would not be a stretch to say integrated data is the lynchpin of intelligent, unbiased HR decision-making.
 
This analytical approach also helps companies test HR programmes more accurately. For example, they can analyse a new intake programme on a more frequent basis to see how effective it is and to quickly make any required changes in light of the patterns revealed in the data. Similarly, the company can pinpoint what combinations of factors drive certain groups of employees to resign or go work for a competitor and work to address those more proactively.
 
It’s essential that the right people can access this data and that they can do so conveniently. HR teams and line managers are ultimately in the best position to bring about change among employees and must therefore be empowered to do so.
 
So, while the analytics process may be complex, the user controls and outputs must be easy and clear enough for the right people to understand and act on them. In the words of the American historian Daniel J. Boorstin: “the greatest enemy of knowledge is not ignorance; it is the illusion of knowledge.”