Big data, not something one would expect a company’s HR team likely to devote much time to, is, in fact, a valuable resource more and more being utilized by people managers. Representing enormous amounts of collected information of just about everything from user behaviors to productivity patterns to health statistics, when used in conjunction with analytics, HR management systems have been able to find insights into engagement, productivity, management styles, and employee well-being. Collecting and analyzing employee data is assisting organizations to implement quantifiable strategies to ensure their staff perform optimally for greater business success.
Although a number of technologies exist to augment the training and development of staff, big data analytics helps employers better understand areas for improvement and identify staff most likely to fill such gaps. Through analysis of current output, areas of highest interest, and styles of learning and retention, it’s possible to better place candidates in training schemes more suitable to them, thereby ensuring greater success for the individual, and, of course, the business. Another factor essential for such positioning is employee engagement, a component identified to be valuable in retention of information and ultimate performance.
Understanding why different people engage better in particular areas and with certain skills is no mean feat, but big data analytics is providing the tools to do it. HR is able to identify trends through the analysis of big data and create strategies to support employees in the attainment of their, and the business’s, goals. And with cloud-based software systems further enhancing the collection and processing of employee data, business leaders have all of the information they could need to process current behaviors and production, and consider better ways to manage and guide their staff for greater output.
For workforce analytics to have a truly impactful effect on business success it’s important first for a set of HR goals to be established. Key performance indicators such as employee happiness, retention rates, individual progressions within the organization, and personal productivity levels could form part of the initial goals, and in collaboration with all business units will later help measure the extent of successful execution.
Technological solutions can then be implemented for the collection and analysis of data, including online tools such as surveys often used to gauge employee immersion and enthusiasm. More advanced platforms provide the means for deliberate employee interaction, i.e. through mobile applications, as well as devices which reflexively measure various employee indicators such as happiness, productivity, interest, and retention. With cloud and IoT accompaniments, these systems gather information through a range of activities and allow HR teams to access and analyze collected data regardless of employee location.
Actively involving employees in human resource analytics can be of even greater benefit, with staff actively engaged in the examination of their data and the insights it reveals; such involvement also provides the advantage of ensuring the right data is collected, and through an appropriate timeframe. It’s also likely to make implementation of future strategies run far more smoothly if staff have been involved in the project from the get-go and feel a sense of connection to the results, recognizing the value of new tactics being suggested. With the necessary measurements made clear, testing results against initial key performance indicators, it’s necessary to understand where implementations are in fact advancing objectives, and providing staff with an awareness of these triumphs promises even greater buy-in for future projects.
Strategies will need to be continuously assessed and amended based on data gathered and the revision of objectives. Moreover, as data collection and analysis progresses, we’ll have new tools and schemes to employ. For the HR team wishing to make valuable contributions to the business, big data analytics could become a standard providing more sophisticated practices that point endeavors in the right direction.
By Jennifer Klostermann