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TERMS LIKE “TALENT SCIENCE” AND “PREDICTIVE ANALYTICS” ARE BECOMING PART OF THE ESSENTIAL HR LEXICON. WE STAND AT A UNIQUE POINT WHERE WE CAN ANALYSE THE PAST AND USE IT TO FORM PREDICTIONS OF THE FUTURE. BUT ADOPTION IS SLOW AND EFFECTIVE IMPLEMENTATION SOME WAY OFF FOR MOST.
ARTICLE BY JILL STRANGE, VICE PRESIDENT, HCM SCIENCE APPLICATIONS – INFOR “A deep understanding of your stakeholders, your employees,
your company, and its pain points will help to ensure your strategy and its outputs are aligned with your mission”
Talent science is generally defined as the practice of using mathematic principles, algorithms, and data to more objectively manage the identification, hiring, and long- term retention of the workforce. Predictive analytics goes a bit deeper by using those same objective principles to see into the future based on events in the past. These predictions may include inventory management or scheduling optimisation, or they may be more talent-centric, like recommendations on job candidates who will stay employed longer or excel in one job role versus another, and which training needs should be addressed to move an individual up the ladder of success. But much more than buzzwords, many are touting talent science and predictive talent analytics as the key to the new retention model for the 21st century. Large HCM juggernauts are claiming the ability to predict the likelihood of an employee leaving the company by leveraging post-hire data collected through HR systems. Others use pre-hire data combined with existing incumbents and performance measures to predict who has the right stuff to raise the bar. But the most successful applications focus on combining data from both before and after the point of hire and apply those data to job candidates and employees in a continuous loop. With enough people in the organisation, predictive models can be developed and refined over time with the addition of more data, then reapplied to the incumbent workforce to determine the likelihood of both high performance and turnover. There’s a great deal of information in
the world on how to implement an analytics- 46 | thehrdirector | DECEMBER 2019
based approach to HR, but you can’t find what truly matters to your business through an internet search. A deep understanding of the stakeholders, employees and the company, and its pain points will help to ensure your strategy and its outputs are aligned with the mission. Data can help you to validate conclusions, but your internal research will help to focus on what is important to the success of strategy. Understanding the organisation’s current technology landscape is essential to determine the predictive analytics process. Legacy systems can store data in various and disconnected ways, introducing potential error into the processes. Grasping where data resides and how to obtain the information relevant to your needs can be a daunting task if the organisation’s previous strategy involved multiple systems designed to serve specific needs as opposed to a suite of products designed to work together from the start. When applying predictive analytics and talent science to your organisation, having good measurement and understanding what you are measuring is key. You must understand what you want to predict, how you want to measure it, and what impact this is going to have. Determine what data is required to predict your desired outcome. If long-term employee retention is the goal, understand that different variables may be required over a strategy focusing on short-term employee performance. Additionally, ensure objectivity in your data, even data driven efforts can fail if you don’t know why your results are happening. From initiation through maturation, be sure that you work with people who know what they are doing and take the time to
understand your business. Data scientists can help to shed light on key factors predicting company success but need to have a deeper understanding of the data involved to draw accurate conclusions. A partnership between analytics experts and the business, as well as any potential external vendors can help to ensure you have a full view of the data, the analytics process, and the implications for your organisation. Predictive analytics should not be deployed in a vacuum, nor is it a process that happens once. To truly ensure success of your strategy, it must be evaluated from a qualitative and quantitative perspective. Are your analytical models predicting employee retention and/or performance? If field-level interventions like pre-employment assessment are applied as part of the process, do users see the value? Driving the adoption of data-driven technologies in HR may be a daunting task, but is also a worthwhile one. By balancing an understanding of the data available with the needs of the business, HR can start to drive results for the business through tying human behaviour to organisational success.
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FOR FURTHER INFO
infor.com
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