Learning and Development
Data-Driven HR training: Leveraging analytics for performance enhancement
Worldwide, the corporate sector is focused on reskilling and upskilling its workforce to meet the challenges posed by a volatile technological and economic landscape. Corporate training expenditure in the US alone amounted to US$101.8 billion in 2023. Training programs are a considerable expense, and tracking return on investment is difficult. At the same time, it is essential to create a learning organisation that innovates, is adaptable to constantly changing environments, and nurtures employee growth. All organisations are looking to maximise the impact and benefits of their employee training. Data-driven, AI-enabled learning analytics involves collecting, measuring, tracking, and analysing learning and development-related data to derive insights that help achieve all-around optimisation.
Utilising data to drive learning and development (L&D) starts with choosing appropriate and relevant training content. Analytics on integrated employee performance, organisational performance, customer feedback, and other data can provide insights into skill and performance gaps. These insights help organisations figure out the training that employees need to be better at their jobs. For example, performance data might reveal multiple new employees constantly flouting a particular safety protocol. The related learning data analysis will throw up the shortcomings in the corresponding training sessions. In an environment of constant change, analytic tools can anticipate future talent needs for an organisation. These solutions can break down jobs into their component tasks, allowing organisations to leverage cutting-edge technology to reimagine and reinvent work processes. Organisations can be future-ready by ensuring that their workforce has been provided with the technological and social skills to make the most of challenges and opportunities. Insights from data can also be utilised to identify obsolete or inconsequential training. Pruning off irrelevant training saves cost, effort, and time.
Data-driven training provides employees with a learning approach customised to their abilities, needs, and learning styles. The data provides information regarding the learner, which enables the preparation of content, learning paths, and resources to create an optimal and comprehensive learning experience. The learner’s interaction with the system provides data that helps ensure that the training journey is aligned with the goals set by the learner. The pace of learning can be tailored based on individual profile data detailing cognitive strengths and weaknesses and learning goals. Adaptive learning constantly measures proficiency and, accordingly, sets the difficulty level. The personalised experience improves the individual’s engagement and motivation to learn. Intelligent analytics helps learners realise their potential by recognising boredom or the need for extra help and recommending appropriate corrective measures like raising the difficulty level or providing additional support.
As the skills available within an organisation drive business agility and growth, L&D is moving beyond training delivery to directly impacting business outcomes. Accordingly, it is imperative that L&D assesses and gauges the effectiveness of training based on alignment with business outcomes rather than focusing only on KPIs related to content consumption. Learning analytics helps organisations by deriving insight into whether the skills developed have created talent that can deliver business objectives. L&D analytics keeps track of strategic skill development, predicts changes in required skills, and rates course effectiveness on the enablement of new skills and the reach of training within different functional groups of the organisation. Analytics solutions monitor indicators such as the most popular modes of learner engagement, cost of intervention, choice to build or buy, least accessed content, and ready-to-retire content. These indicators highlight the efficacy of the L&D system. Training performance analytics connects learning and business metrics to calculate the value of learning to organisational growth.
AI-powered training analytics provides descriptive, diagnostic, prescriptive, and predictive insights into an organisation’s L&D program. This holistic outlook enables focused learning initiatives and alignment of training with business objectives, making L&D an equal partner in the organisation and not just a support function. Intelligent training analytics has transformed L&D but faces data privacy challenges. Organisations must adhere to privacy regulations and laws. Updated security standards, data encryption and anonymisation, and well-defined and authorised ownership and access protocols are essential requirements.
The rapid rate of technological change has caused skills to become obsolete at an equally swift rate. Consequently, life-long and continuous learning has become an inevitable element of professional roles. People-centric organisations that adopt learning analytics ensure that employees are up to speed and improve employee engagement and satisfaction. Businesses that implement L&D analytics encourage and foster a corporate culture of learning by providing a personalised, adaptive, and self-learning environment that optimises training.
How can Infosys BPM help?
Learning and Development are vital to organisational growth in this age of constant technological upheaval. The Infosys HR BPM Learning and Development Outsourcing Services team provides solutions that encompass all aspects of the Learning function and drive business improvement. Our Training Process Outsourcing Services cover strategy, content, delivery, administration, and analytics.
