The continuous evolution of analytics has led to a new generation of people analytics. As companies prepare for a new world of work, they must continuously develop an in-depth understanding of what lies ahead, from new business priorities to talent opportunities. This calls for leveraging analytics, and hence the need to build analytics infrastructure aligned to the business needs.
Future of work- A revolution unfurled
There are three key trends that are informing the future of business:
- Data is ever-dominant: From limited HR records, today, people-related data encompasses a number of data points and they cut across talent processes, engagement, and experience platforms. This data is applications-oriented, multi-source and unstructured, and must be handled with diligence.
- Innovation is multi-pronged: In a bid to enhance employee experience, HR is moving from transactions to journeys. Cognitive learning due to man-machine interactions is enabling this shift. Employees today expect data-visibility rather than relying on their managers. The future of innovation will be driven by story-telling and visualization capability through data-adoption.
- The hybrid world of work: With a complete or part remote-working model, the role of analytics has expanded – and it must lead to wellness, engagement while enhancing productivity.
Organizations must look at analytics with a new lens to thrive in the new normal.
The four levers to ensure a seamless data-experience are:
- Data governance: The lack of data quality and availability can lead to a significant amount of time spent on non-value added tasks. To ensure a connected, intelligent business, companies should explore a common data-model from a transaction point of view. Data must be integrated from multiple sources across processes. Upholding data quality including accuracy, completeness and timeliness of data is critical. Applying emerging technologies can help organizations become future-ready and outpace change by providing a data-backed, ‘real’ employee experience.
- Infrastructure: The analytics infrastructure must be accurate, error-free, autonomous, and responsive to support a hybrid environment. Organizations must focus on the latency and data processing power in the system design.
- People capability: Capability for data-readiness is two-fold i.e. skills and mindset. The skillset involves understanding statistics/ data combined with the capability to ‘infer’ trends. And the mindset shift is about asking questions i.e. from ‘What’ to ‘Why-How-What If’. The journey of analytics is filled with questions and organizations must build capability around asking causal questions, predictive questions, prescriptive questions and visualization questions to create a story around the data. This will foster leadership buy-in for analytics.
- Culture: Cultivating a mindset of trusting one’s own data is possible by driving adoption and personalization of data. Analytics interactions must be conversational (voice and digital assistants), adaptive (constantly learning from you) and visual (creating delightful experiences), and available on multiple devices.
Whether it is about governance, tools, mindset, personality, security, or any of the multiple levers, one must leverage the power of one-analytics platform to truly drive data-orientation.
How can HR Roles and capabilities drive this data-transformation?
HR must don multiple hats to be able to build a business-driven, one-analytics platform. This is possible by playing the following HR roles:
- The evangelist: HR must ensure adoption, outcome and value for the business. Ask the core questions, such as ‘What problem am I trying to solve?’ by focusing on the efficiency and effectiveness, to use data to solve a business problem.
- The inquisitive thinker: Thinking out-of-the-box and asking the right questions means that HR leaders must continuously ask questions themselves. HR must move beyond run-of-the-mill solutions to bring about a real and sustained data-change.
- The disruptor: Often, the driving questions have to be disruptive in nature, to complement today’s disruptive technologies and business environment. Hence HR professionals must have the skills and the mindset to question the status-quo.
- The analyst: At its core, the capability to build inferences and multiple perspectives is essential to data-success.
- Data Sourcing – through personal datasets, enterprise applications, external datasets etc.
- Extract and preparation of data – through BI tools, data prep tools, and custom tools etc.
- Analyze data using spreadsheets, point solutions, desktop analytics, custom apps etc.
- Review data outcomes with all stakeholders i.e. C-level executive analysts, Finance, HR, Marketing, Sales, Ops, IT etc.
- Act: Finalize business and talent decisions based on data outcomes – HR leaders must instil a research-mindset, while upholding data privacy and information security.
These new HR capabilities are essential to build a data-driven, holistic decision-making process. HR leaders can choose to build this in two ways: 1) A step-by-step phased intervention by trying to analyze by asking the right questions. Or 2) HR and business leaders can identify critical business and identify specific drivers that need review. Either ways, it starts with being self-aware and gauging readiness for data-success.
Analytics is raising hitherto unknown questions; it is making leaders think about aspects which they had no inclination or insights into earlier. ‘How has the composition of my workforce changed over time?’, ‘Are we hiring and maintaining a diverse workforce?’, ‘Is compensation impacting retention?’ and many more. This practitioner’s view is helping HR as a function to become much more strategic, rightfully influencing the business success. HR must always seek to understand how data could impact business if they could answer these questions? This is possible by putting in place a collaborative enterprise analytics platform that can enable the CHRO and the HR organization, with decision-making insights through a holistic view of data. Such a platform must be simple-to-use and it must have sophisticated capability to help achieve the objective of looking at the overall employee lifecycle. This is the key to moving from transactions to interactions, and hopefully towards the experience stage.