From ‘Hire’ To ‘Retire’: Hyderabad-Based Startup Darwinbox Uses Tailor-Made AI And ML Solutions In HR
From the left: Rohit Chennamaneni (Operations Head and Co- Founder), Chaitanya Peddi (Product Head and Co-Founder) and Jayant Paleti ( Sales and Marketing Head and Co-Founder) While there has been an increase in efforts by organisations to streamline human resources processes, it hasn’t always been the case. Jayant Paleti, Rohit Chennamaneni and Chaitanya Peddi, during their consulting careers at McKinsey and Ernst and Young, realised that organisations struggle to furnish critical human capital information during takeovers. In a particular instance, Paleti observed that in a large-scale merger the stakeholders were not aware of key figures like the attrition rate in their own organisation or have the wrong data figures. There can be many challenges on the way, such as the company might have more than one HR system that makes it extremely hard to integrate and draw data, or they still function on an outdated HRMS. To deal with these challenges and make HR processes more streamlined, the trio conceived Darwinbox in 2015 in Hyderabad. The idea was to make HR a strategic aspect of every organisation rather than just a functional fulfilment. Darwinbox And Their AI-Driven HR Solutions As Paleti explained to Analytics India Magazine, Darwinbox is an integrated platform that takes care of all the HR needs of an organisation across the employee lifecycle which includes recruitment, onboarding, time and attendance, payroll, employee engagement, talent management, learning and analytics. “We have gone a step ahead to leverage artificial intelligence to make the experience more engaging for employees. All you have to do is call out to our voice-bot and ask ‘Hey Darwin what is the attrition rate looking like’,” he said. Known for flexibility, ease of use and new age talent management here is how Darwinbox enables HR organisations to accelerate their HR game. Focus on employees: Organisations today understand that every employee has their own capabilities and career path, and the same goals and competencies cannot work the same way for every employee of the organisation. Through Darwinbox an organisation can set relevant goals and measurement metrics for their employees — the goals for the tech team would be extremely different from the sales team and Darwinbox allows for this customisation. Personalised: Unique role-based definitions right from goals to training needs helps organisations personalise the talent critical initiatives. Context based on the user persona helps managers and leaders get all the right data inputs to make talent decisions. It helps to understand an employee’s performance during the probation, identify the right set of candidates for promotion, identify cross-functional skills and assess recruitment effectiveness. Engaging: New age features like continuous and multi-stakeholder feedback make talent management more engaging. This is a major hit with the millennial workforce who like instant feedback rather than wait for an entire year to resolve their issues. Their internal social media platform Vibe and Pulse checks help organisations also engage effectively with the remote workforce. Using AI And ML To Manage The Employee Lifecycle Paleti shares that Darwinbox uses AI and machine learning to draw interesting insights across multiple touch points of an employee lifecycle. Few of the aspects where AI and ML contribute majorly are: CV Ranking: AI helps in identifying the right candidates by not only keywords screening but goes on to solve recruiters’ problems like candidate ranking, rediscovering past candidates and reducing the time on manual tasks. Voice: Leveraging conversational AI and NLP, we have built a voice bot on our platform to help employees perform a series of tasks ranging from applying for a leave to drawing out attrition data. With the introduction of our voice bot Darwin, we have seen a significant increase in adoption and reduction in time of performing tasks. Reasoning and Predicting Attrition: With predictive analytics, organisations can identify who is at flight risk and accordingly plan their attrition rates. They are also able to investigate the key factors leading to attrition and analyse it at an overall organisation level. This is helping them take preventive steps to reduce the attrition rates and assess the efficiency of their recruitment strategy. Promotion Recommendation: With the help of AI, organisations can identify the right resources to move up the ladder. Not only this, they are able to identify cross-functional experience and skill sets to accordingly leverage resources to deliver the best results. Darwinbox also generates vast amounts of data across the employee lifecycle giving holistic data-backed insights into an employee’s career journey. “Our objective has always been to infuse intelligence into the HR function by turning data into business-critical insights. This will help organisations to make better people related decisions like proactively identifying and filling talent gaps, predict employee turnover etc.,” said Paleti. For enabling these functionalities, analytics plays a significant role at Darwinbox. The Technology Stack Chennamaneni shares that they use MEAN stack (Mongo, Express, Angular, Node) for product development and host the product on AWS cloud (Amazon Web Services). “We also use the Kubernetes architecture for best workload scalability. It helps us build multiple layers of security and is easily portable not limiting our choices while choosing an operating system.  We are one among the very few product companies who have been able to successfully leverage this technology,” he adds. Clients And Use Cases The startup is currently catering to the mid and large enterprises such as Dr Reddy’s Laboratories, Arvind group, IIFL, Paytm, Emcure, Nivea, Myntra, Bisleri, Aurobindo, GVK Bio, and others. While explaining a use case of how Darwinbox caters to these clients Paleti cites an example of Delhivery, India’s largest fulfilment and logistics company present over 1,200 cities with over 20,000+ employees. They have digitised their entire HR functions from Hire to Retire using the Darwinbox platform. They have been able to achieve increased process adherence and have freed up at least 30 percent of the HR bandwidth from working on transactional processes. The team now focuses on contributing to the overall strategy and organisation decision-making process. Along with the senior leaders leveraging AI-powered analytics to make data-backed decisions, over 7,000 employees of Delhivery leverage the first of its kind AI-powered voice bot “Darwin” to perform tasks on the platform in a conversational and engaging way. The conversational interface reduces the time taken by an employee to perform a task like applying for a leave by 50 percent. Competitive Edge “The strength of any AI algorithm depends on the data correctness, completeness and the number of variables available to predict or select the desired result. Unlike many standalone AI based HR solutions, in our case, as an end-to-end HR platform, we hold information about an employee across their employee lifecycle which helps our AI-based analytical framework evaluate factors beyond the obvious,” he says. For example, to evaluate the CV fitment for a role, Darwinbox analytics engine considers factors beyond the past hiring success rate of similar profiles but extends to even include the attrition rate, performance ratings, engagement index and exit feedbacks of similar profiles before identifying a match, thus making the prediction much more robust. Their core HR is designed in a way to capture a maximum number of influencing factors across an employee lifecycle. Added to this the platform’s intuitiveness drives completeness of employee data. Most organisations before onboarding Darwinbox had only about 30 percent of employee profile information completed. With Darwinbox, employee profile completion increases on an average to 90 percent which helps our analytics framework identify more and deeper insights. Growth Story And The Way Ahead Peddi proudly shares that since their inception in 2016, they have been able to onboard over 100 clients and engage with more than 3,00,000 employees. Their revenue has doubled since the previous year and they are now being recognised as one of the fastest growing HRMS solutions across the country. They currently boast an employee strength of over 130 employees who are striving to help Darwinbox reach new heights, amongst which the 70 are a part of our engineering team, that consists of AI and analytics professionals with strong problem-solving skills. “We invest in our talent by sending them to various training and development seminars and providing with the right platforms to build on their skill sets. This has really worked for us as some of our best programmers today have grown into AI and analytics roles,” shared Peddi. While they are growing at a significant rate, the Darwinbox team is looking forward to product development and market expansion in the coming years. “As a part of product development, additionally to the existing seven modules, we are looking at building three new modules—Rewards and Recognition, Travel, Learning and Development. In terms of market expansion, we are looking to grow exponentially in India and will also begin our expansion into the South-East Asia market,” he said on a concluding note.
While there has been an increase in efforts by organisations to streamline human resources processes, it hasn’t always been the case. Jayant Paleti, Rohit Chennamaneni and Chaitanya Peddi, during their consulting careers at McKinsey and Ernst and Young, realised that organisations struggle to furnish critical human capital information during takeovers. In a particular instance, Paleti […]
Darwinbox was founded in 2015. The idea was to make HR a strategic aspect of every organisation rather than just a functional fulfilment.
["HR Analytics"]
["machine learning", "artificial intelligence", "AWS", "AI", "HR Analytics", "ML", "RAG", "NLP", "analytics", "predictive analytics", "kubernetes"]
["AI", "artificial intelligence", "machine learning", "ML", "NLP", "analytics", "RAG", "predictive analytics", "AWS", "kubernetes"]
Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.