Analytical capability-building is the differentiator in a digital economy and an organization-wide analytics enablement can make all the difference
Organizations are deploying workforce analytics to make decisions that are based on hard data and facts, and not driven by instincts
Instincts, experiences and gut feel no longer drive decisions. Today’s decision-making is based on data. And data is present in abundance; however, organizations that can derive sense from the data that is available can achieve competitive edge over others. Analytical capability-building is the differentiator in a digital economy and an organization-wide analytics enablement can make all the difference.
Several organizations today are proactively adopting predictive analytics to make informed decisions across a range of activities such as customer retention, sales forecasting, campaign management, supply chain optimization, and market research. The human resource function is also not far behind. Organizations are deploying workforce analytics and studying their workforce behaviors to discover patterns and make informed HR decisions – decisions which are based on hard data and facts, and not driven by instincts.
The time is indeed ripe for the datafication of the HR function and this development holds the key to transforming HR’s role and impact in driving business decisions with a direct impact on the bottom line.
Predictive analytics can be used in core HR processes such as talent acquisition, attrition, risk management, employee sentiment analysis and capacity planning and enables HR professionals to actively contribute to strategic business development. However, despite businesses waking up to the importance of analytics, it is yet to develop into a strategic HR instrument as companies are still exploring the possibilities of appropriately utilizing the large volumes of data which comprises demographic data, job history, compensation, training, performance history, employee turnover, hire quality, and other critical aspects of HR management. According to Priyadarshi Lahiri, CTO, EdGE Networks “Although a lot of products are coming up in the analytics blanket, the ecosystem is still very disjointed. There are tools like Big Data engines, stream processing frameworks, large-scale charting and BI tools along with visualization tools, but there is hardly anything that brings all these tools together on one platform to make it accessible to the consumer in a simple manner.”
“Data has to be in the right hands to drive analysis out of it” according to Rajiv Jayaraman,CEO & Chief People Officer, Knolskape. And if appropriate algorithms are used and the large chunk of data is mined aptly, it can be used to create statistical models that estimate probabilities and predict future behavior and trends across key HR and business functions. Some of those areas are recruitment, where building analytical-based recommending systems can allow targeting the right jobs to the right people, improving employee attrition rate by carefully analyzing historical data about employee churn behavior and relate this to employee and job characteristics along with an impact of compensation on job motivation or satisfaction.
Accurate profiling of employees through prescriptive analytics facilitates segmentation of the existing employee base that allows for a better understanding of the workforce needs and requirements. Companies can achieve higher employee satisfaction by customizing relevant programs and incentives for various segments that are likely to benefit the most from such initiatives. With this awareness, out-of-the-box solutions can be devised to retain at-risk employees better. Building on this point, Mansee Singhal, Principal – Talent, Mercer India states that “Prescriptive analytics on employees past education, work profile, experiences can help the employer to carefully craft engagement plans. It is an extension to attrition prediction but a more proactive approach to use it for deepening the employee connect with the current organization.”
Predictive and prescriptive analytics models can also help in identifying the reasons for many organizational challenges by analyzing various fields of data from employee demographics, performance, compensation and benefits, market, rewards and recognition, training and behavioral survey scores and suggest appropriate solutions and actions to manage these challenges. Similarly, HR analytics models also help forecast recruitment needs by predicting the demand and supply of talent. This optimizes resource utilization by allowing managers to evaluate their in-house talent supply and training potential in advance, before hiring externally. They can accordingly develop cost-effective plans for recruitment, training, and infrastructure development. Organizations, especially in India, need to work towards building their analytics capability, while restructuring their data sources and redefining the data fields to be recorded. Many still have isolated systems of data management that do not permit a big picture that is required to enable effective analytics. Therefore, many of them face limitations on which data to collect, figuring out the right questions to ask and in getting value from existing data.
Such a scenario is further complicated by a rapidly evolving ecosystem, which makes it difficult for organizations to keep to speed with the volume of data that is now readily available. New technologies are emerging and new sources of data are being discovered continuously. Unstructured data text analytics techniques give HR departments the ability to tap into data sources such as social media feeds, specialized content sharing websites like Medium and Quora, interviews, blogs, customer feedback forms and performance reviews. This unstructured data can be merged with traditional data and used in workforce analytics to add another dimension to human capital management.
Data will not lie, it is telling us everything – provided we know where to look. Given the scenario, it is imperative for leaders to know the business insights they seek and make sure that the recorded data corresponds to that. It is also important to verify the authenticity and accuracy as more and more unstructured and external data becomes integrated into the organizational analytics. It is no longer about owning the most data but rather about how to gain the maximum insights from it and convert it into real business advantage. This necessitates creation of an agile and flexible infrastructure designed to manage data efficiently and move it through the analytics process quickly. Creating a speed advantage does not necessarily require a real-time solution, but it does call for streamlining decisions made within business processes. Every team, including in HR, needs a differentiated view of the data sets to carry out their functions, as not everybody needs the same information and detail. Therefore, Analytics must be made consumable for employees and executives, a resource that they can tap into anytime and anywhere. The entire workforce needs to have access to analytics relevant to their job to make decisions and take actions.