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Big data is a big deal for the HR function

Future of Work|Talent

By Tracey Malcolm , Shekar Nalle Pilli Venkateswara and Wen Wan | March 20, 2019

In Hong Kong, big data is helping the HR function improve the talent management process – hiring decisions, planning and promotion, also meeting training and development needs.

Big data, described by some as the “new oil” fuelling the digital economy, as well as expanding the frontiers of productivity and innovation, is also helping the HR function improve the talent management process.

As big data continues to climb to the top of the corporate agenda, information and insights from analysing big data can now help with everything from hiring decisions to planning and promotion and also meeting training and development needs.

As our world becomes increasingly digital-dependent, for organisations in Hong Kong and globally, today, the HR function is in a prime position to make a quantum leap forward in terms of impact through utilising big data to connect talent to work to improve business outcomes. This is something that HR professionals have always excelled at – creating a competitive advantage through people. Using big data to achieve defined outcomes means replacing presumptions with validation, and intuition with decisions based on predictable outcomes. Consequently, big data is an important component in helping the HR function to align itself closer to an organisation’s business strategies by providing important talent insights and creating end-to-end talent experiences that forge new and stronger links between talent management practices, employee productivity and key business objectives. While HR-related big data is growing at an unprecedented rate and organisations understand the need to harness data and extract value from it, many HR practitioners are asking themselves — how can it be done effectively?

Begin with the end in mind

With the race under way to gain a competitive advantage by understanding all elements of the workforce, these days managing HR-related data has become increasingly critical to any organisation. Every business, irrespective of industry sector, generates what may qualify as big data on a daily basis. For organisations moving towards data-driven solutions, in order to achieve successful outcomes, it is crucial to take the first steps with clear objectives in mind. This includes deciding which questions can be answered from the available data on hand. Also, will the data allow for clear decision-making in a data-driven system? For example, to help employees perform better, organisations need to know exactly what they want to improve. What are their current skills? What skills can they develop? What can be done to motivate them to learn new skills? If these questions are not answered in a clear and strategic context any big data plans may well stumble. As a starting point therefore, a focus on a couple of key areas where there is a strong chance to deliver real business impact is more likely to deliver results than trying to implement predictive analytics across every HR domain.

Correlating big data in the new world of work

There are many shades of grey that arise when navigating the world of big data. It requires the ability to search for, extract, and analyse relevant information from diverse data sets. When it comes to consolidating big data, in spite of having access to a wealth of statistics and information, many HR departments struggle with managing the data they have on hand. The problem often lies in the data being kept in an impracticable form. Frequently, data such as recruitment, on-boarding, benefits and performance ratings are kept in different systems and formats which, without the applicable systems and know-how, can be difficult to retrieve and analyse. In addition, changing workplace demographics and working styles attach new layers of complexity when analysing and assimilating big data to provide useful insights. Prime examples include new types of jobs, new skill requirements and career trajectories being reshaped by technology. Add to this an expanding multigenerational workforce matrix and the rise of "gig" or contingent contractors and it quickly becomes apparent that the changing workplace demographics significantly increase both the range of data sources and the variety and volume of data that needs to be analysed.

Building a data-driven HR function

There are four key elements to building a strong capability for leveraging HR-related big data: crafting the right strategy; defining key roles and staffing; focusing on processes and governance; and choosing the right technology and analytical methods. From an HR perspective, big data is a goldmine, which can cover all areas of talent management. Nevertheless, big data’s ability to transform an organisation’s workforce for the better is not just about collecting impressive amounts of data or slicing and dicing data in lots of different ways. Analysing data alone does not generate value. To increase the chance of successfully attaining objectives, the HR function needs to harness data and understand how this impacts decisions around aligning talent strategy with the business strategy.

Data analytics has been on HR leaders’ minds for quite some time and organisations are at different maturity levels when it comes to making use of data analytics. For the HR function at an early stage of adoption, and looking for guidance, there are often opportunities to learn from other areas of the organisation where the use of big data has reached a more mature level. For instance, the customer services department is often a first port of call for big data. Similar to the way big data is used to address customer experiences, the HR function can utilise big data to predict and develop talent processes and solutions that are individualised. For example, accessing a benefits marketplace for individual choice and enrolment and leveraging digital employee interfaces to predict talent needs and create data-driven employee insights.

At the same time as data is becoming more abundant than ever, there is a growing demand for professionals with the skills to collect, validate and manage data. To get the right analytical insights, specific roles and capabilities are needed. Balancing analytical, IT and management capabilities is critical, because identifying and applying data-driven talent analytics effectively requires multiple disciplines working toward a single goal. As the growing complexity of big data analytics continues to push organisations to seek professionals with specific skills — such as data science, artificial intelligence, business intelligence and data infrastructure capabilities — the good news is that many organisations in Hong Kong are likely to already have professionals working in big data roles, for example within the IT function, although they are unlikely to focused wholly on HR related data. Meanwhile, to varying degrees of sophistication, many HR professionals leverage analytics as part of their general HR role focusing on “talent analytics” and “people analytics”. Leveraging the skills of HR practitioners in these existing roles to become part of an HR “big data” team can be beneficial in two ways — firstly, members of the new team will already be familiar with the organisation’s data, structure systems and culture, and secondly, it can represent new career opportunities for HR practitioners looking for a new challenge.

Big data technologies for HR purposes

From analytics to algorithms, technology tools have swiftly become an influential force in contemporary HR talent management. The exponential increase in data means that new tools and technologies are needed to answer important questions regarding recruitment, workforce productivity, the impact of training programmes and how to identify potential leaders. They can help the HR function by doing a lot of the heavy lifting by analysing what does work and what does not. With no one-size-fits-all solution and a vast array of systems to choose from, like any technology investment, HR data analytic platforms should support current data analytic requirements as well as possess scalable capacity to support future objectives. For instance, depending on needs and preferences, consideration needs to be made between “SAS” and “Python” programming languages and a choice made between “Tableau”, “Power BI” and “Qlikview” visualisation platforms.

Successful big data management requires good governance

In addition to designing strategies for developing a data-driven HR function, the creation of a data governance policy is equally important. Sound data quality, processes, systems, controls and governance are central in managing the risks attached to managing talent management data. Constructing a data governance policy originates with implementing a best-practice compliance standards framework and a roadmap with a focus on the protection of sensitive data through policies and standards. The HR function also needs to sharpen its ability to manage ever-stricter data privacy regulations and growing cyber-security risks they face as stewards of some of the organisation’s most sensitive information.

Although big data will not solve every HR challenge, with access to large amounts of information and the availability of technology tools to churn through large volumes of data, HR practitioners can feel increasingly confident in their ability to answer talent management questions more positively. The challenge, however, is not to become over confident with what the data is saying, but instead to use data to augment intuition and experience.

The article was written for the 2019 March/April edition of Human Resources, the official journal of the Hong Kong Institute of Human Resource Management (HKIHRM).

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