Talent Management: Use of Technology and Analytics

Talent Management: Use of Technology and Analytics
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Introduction

Technology and Analytics play a vital role in talent management, acquiring manpower, maximising every stage of the hiring process. In this era of transformative cognitive technologies like AI and machine learning, the complexities of talent acquisition and talent management have accelerated into high gear, driven by longer life spans, cultural and ethnic diversity and a highly-competitive global recruitment landscape. Without the proper utilisation of technology and analytics, talent management can become an operation bottleneck that will suppress the growth of operation. The technology source used by companies are social media, job portals, out bound hiring, social networking, e-mails, messages, tele-calling etc. are commonly used for targeting the prospective employee. In today’s fast-paced business world, it’s become obvious that people, practices, and systems must become nimbler too. Within this landscape, forward-thinking companies are using technologies and data segmentation to analyse smaller and smaller segments of their workforce as they develop strategic human capital plans, target job candidates and tailor employee benefits to match individual values, personality and behavior.

Technology driven Talent Management

Technology also allows for more in-depth analysis and reporting which provides managers more and better information to make the best decisions for getting the best out of the employees under their supervision. Using analysis tools and metrics, top performing employees can be groomed for leadership roles instead of the company having to depend on outside candidates. In a global market that continues to generate increased competition for the best talent, a company that fails to develop from within risks the loss of continued growth and market dominance by failing to retain their best assets as well as attracting top new talent.

Managing talent effectively places considerable demands on any organization. The sheer scope of the task means that a successful strategy becomes much likelier when technology is utilized. For each talent management function, most companies have traditionally used various standalone applications. Storing these applications and the data generated on each user’s personal computer or network servers at the firm is normal practice in these circumstances.

The talent management is critical to the firm’s well‐being and an integrated solution can positively impact on performance, employee loyalty and business strength. The advent of cloud computing has provided companies with a feasible alternative. Many of the headaches associated with the conventional approach can be eliminated using a solution that offers:

Cost effectiveness: There is no requirement for a company to regularly invest in hardware, software and in‐house IT support services. Corporate servers are removed from the equation as applications and data are hosted by the provider’s own network.

Flexibility: The dynamic nature of the technology provides real‐time access, upgrades when required and the capacity to swiftly adapt the application’s configuration and processes as user needs evolve.

Integration: It becomes simpler to merge the various talent management processes currently handled in different parts of the firm. Better integration with other HR functions is likewise attainable.

Wider application of training and development programs: The problems associated with conventional technology systems invariably meant that talent management activities were confined to high performers. Because cloud computing allows all employees appropriate levels of access to the system, scope exists for an organization to maximize the potential of its entire workforce.

How Data and Predictive Analytics play a crucial role?

From talent acquisition to performance management, HR departments are trusted with some of the most vital functions in an organization. When it comes to HR decision making, organizations want to make sure that there is no guesswork involved and are increasingly turning to predictive analytics to make data-backed decisions about the future. When it comes to setting key organizational priorities, items like big-name client wins, product launches, and high-profile partnerships must be secondary to the happiness of your people. Engaged, high-performing talent is a prerequisite to achieving any other business aim. The problem are the HR leaders and managers typically rely on guesswork to assess employee happiness. Lacking data-driven insights, such surface-level prognoses are often inaccurate, resulting in high attrition rates and higher turnover costs. The good news is that AI tools and predictive analytics are available to help HR leaders and managers identify the peaks and pitfalls of performance on individual, team, and corporate-wide scales, and reward employees accordingly.

AI and predictive analytics give business leaders the ability to benchmark compensation, identify flight-risk employees, and determine compensation boosts by deriving data that they would previously have had to ascertain through gut instinct. To understand its employees and how to keep them highly engaged, companies need data about what makes employees stay, what makes them successful and what can be done to build business strengths like leadership, innovation and customer service into the workforce. This will come from strong people analytics. People analytics looks at highly relevant data about people to solve specific business problems such as sales productivity, customer satisfaction and employee experience. The goal of predictive analytics is to provide structure, consistency, greater insight, and improved accuracy to the talent-management strategy.

To make the most of an integrated talent management solution, these following components should be considered: –

  • A cloud-based SaaS solution, which enables scalability, flexibility and cost efficiencies.
  • Mobile device optimization and mobile apps that facilitate real-time talent management across borders and in remote locations.
  • Integrated social media applications to harness the power of the world’s social networking sites for finding and attracting new talent.
  • Integrated HR analytics and Big Data applications for predictive workforce planning.
  • A solution that is reflective of regional needs to ensure localized compliance, adequate flexibility and cultural adaptation.
  • A simple and engaging platform that supports speed and reliability with cultural characteristics built into the user experience.
  • A support model that provides both high- and low-touch assistance through direct and partner channels, as well as regional support that caters to local languages and time zones.

Conclusion

Human resources are in the midst of a transformation. Consumerization of the workplace, changing workforce dynamics, and an increasingly competitive talent landscape have raised employee expectations from their workplace to new heights. The result is that talent management is being redefined with the use of technology and analytics in new and innovative ways, to meet the dynamic business shifts. Once an organization understands the enabling and empowering role of emerging technologies, it can develop tactical solutions for HR function and long-term strategic plan on organizational design. The trend toward automating hiring has companies developing software to take bias and discrimination out of the processes, as well as reduce costs and speed the time to hire.

The long-term talent strategy and plan inform what training and development that an organization needs. Along with this virtual cycle that is both top-down and bottom-up, emerging technologies play critical roles shaping business models, employee behavioral and aspirations, as well as technology enabled programs and tools that an organization can should adopt to ensure that it is prepared for adapting its talent management to the rapidly-changing market and becomes more competitive every day.

 

AUTHOR

Sanidhya Somani,

Btech II,ECED.

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