HR has been a laggard when compared to other functions in opening up to the possibilities of analytics. Through an interview with Dr. Arun Krishnan, Founder & CEO, nFactorial Analytical Sciences, we explore details on how data-driven insights obtained from HR analytics across three main areas: Hiring, Engagement and Retention can help HR leaders make judicious, critical and informed decisions.
By slurping relevant data into the crowd from existing HRIS systems (or even from simple Excel Sheets), n!Core provides a de-facto integration of existing systems without too much of an overhead.
A growing Indian economy with an increasingly diverse and mobile employee base poses significant challenges for organizations as they look to hire and retain the right talent. We believe that the need to become more efficient in talent acquisition and engagement are going to be key drivers for business and for the industry in general. These in turn will help us as we look to scale-up.
Companies on an average, have between 6-10 systems that store employee specific data including payroll, performance and leave management systems. Our philosophy has been to make our solutions agnostic to any underlying data and information systems that organizations might have.
Rather, we are working on lightweight solutions that sit on top of the existing data systems and pull together data required to build predictive models into a data store in the cloud. This ensures that organizations don’t need to change their legacy systems but can still benefit from using advanced analytical tools.
Our core product is called n!Core (pronounced encore). We are building six key modules currently with the modules being in various stages of development. The six modules are:
n!List will provide automated resume and job description (JD) parsing, resume-JD matching, candidate “stickability” prediction and candidate “personality matching”. While many companies can accomplish resume/JD parsing and matching, our unique differentiator is in the industry-specific stickability models that can provide probability estimates for a candidate’s tenure.
Another key differentiator is in our personality-matching algorithm that makes use of IBM’s Watson Analytics suite of tools. As one of IBM’s Global Entrepreneurship Program members, our access to the entire suite of Watson Analytics tools enables us to provide products with cutting-edge algorithms.
While we recognize the trend towards mobile recruitment, especially since nearly 45% of job seekers use a mobile device for their job searches, our products are focused more on internal use by HR departments and the executive teams.
Most of their work still gets done on laptops and desktops with a few using tablets. Our strategy is to start with responsive sites that would render well even on tablets and other mobile devices. Eventually, we do plan on having native applications for mobile devices.
n!Pulse, as the name suggests is a pulse survey that provides a “happiness index” on a near-real time basis. Employees will get a popup at a random time during the day with different mood indicators. A simple click on their mood at that time the popup comes up will be recorded. Anonymity is provided by averaging the mood at a functional/divisional rather than at an individual level.
Analytics on the data collected can provide organizations with critical information on the differences in “mood” between different functions/divisions or across days or the time of day. Correlations can also be observed between specific periods of high stress and specific projects or policies.
Sentiment analysis is provided through the tool n!Quire wherein employee feedback is collected. Natural Language Processing (NLP) is used on the unstructured text and advanced sentiment analysis procedures are used to obtain an overall trend about the sentiment associated with various topics. While accuracies for predictions can typically not be guaranteed, we will keep updating models such that accuracies increase over time.
n!Tice uses historical data about employees including their pay, performance, personal characteristics, employment history and other associated metrics to build a model. This model is then used to provide an indication of the probability of an employee to churn at any given point in time, given the employee’s history in the company.
Since, the probability of survival of any employee in a company decreases with time, an indication of the probability can be of immense value to HR leaders and the management at large. They can be proactive rather than being reactive in terms of the actions they take for either retaining high-value employees or in planning for the eventual parting of employees they deem as providing less value.
The HR Industry overall, is waking up to the fact that they are trailing other functions when it comes to the judicious use of data to make critical decisions. As companies like Google demonstrate, using analytics to inform talent acquisition, engagement and retention can really help in building both a strong culture and an efficient organization.
I foresee a greater foray by organizations into HR analytics. HR functions will definitely start to hire people who have expertise not just in organizational behaviour but also with a more analytic bent of mind. Older systems such as year-end organizational surveys will give way to continuous engagement and feedback mechanisms leading to HR organizations gradually transforming itself from a reactive to a proactive force.
We are initially looking at companies with over 1000 employees at a minimum, within India. Our goal is to become India’s premier HR analytics company. At the same time we are exploring channels with multiple partners to take our products to US and Europe. Some of our modules such as n!Pulse and n!Quire lend themselves well to being served as SaaS products and we intend to make use of digital channels for these.
In the near term, we are looking at completing all the modules that we have planned for and that are under development. In addition, we are looking at developing modules for workforce planning that would use models to help simulate multiple scenarios based on business goals and deliverables.
The Indian market is slowly but surely waking up to the possibilities that analytics can provide for the HR function. While attrition and retention have been the key areas that have traditionally got lot of attention, I see a lot more companies investing in solutions to track and enhance employee engagement.