Building a talent intelligence strategy: Do's and Don'ts

The war for talent has intensified in today's age of the Great Resignation and Quiet Quitting. While organisations strive to attract, engage and retain top talent, the search for the right candidates has become far more competitive. With the rise of emerging technologies, including data analytics, artificial intelligence, and machine learning, talent management challenges could yield the desired business outcomes. 

What is talent intelligence? 

Talent intelligence is a layer of data and analytics capabilities driven by AI. It helps HR and business leaders manage the end-to-end employee lifecycle. There are many focus areas across the employee lifecycle, from managing candidate experience to sourcing, screening, hiring, talent management, performance management, retention, and internal mobility. 

Why talent intelligence? 

Today's workforce is diverse and distributed. To be an employer of choice, organisations must understand their employees' needs, wants, and aspirations and the external talent pool. Hyper-personalization is the key to attracting, engaging and retaining talent with new workplace expectations, including flexibility, agility and a greater awareness of career and business growth. Such an inward-out approach requires companies to benchmark their data against their competitors. And that means a better understanding of the talent pool, skills, jobs and functions.

AI and its ability to augment human workers is one of the most influential forces shaping the future of work, 

Deloitte

Building a talent intelligence strategy: Dos

A progressive talent intelligence strategy can help align people's needs with business needs by providing insights into every employee and candidate touchpoint. Here are some areas companies could focus on:  

• Boost Hiring: Intelligence can help build a focus on skill-based hiring and reduce bad hires by evaluating fit-to-hire based on several factors, including assessment and interview data, strengths and gaps analysis, and potential assessment. It can help assess the employee value proposition and fine-tune the employer brand. 
  
  
• Accelerate employee development: Understand the current and future skill predictions with talent market analysis and match skills and talent to roles to be future-ready. This approach is invaluable in an increasingly hybrid workforce with gig employees. 
  
  
• Assess career growth and talent mobility: With data, one can efficiently conduct role-fit analysis to assess potential readiness for succession planning. Data from performance management systems, coaching conversations, 360 degrees feedback Etc. can be used to formalise growth opportunities. It can ease the time, effort and inputs needed for development and career pathing. 
  
  
• Benchmark compensation and benefits: Employees today are looking at more meaningful benefits, both monetary and non-monetary. Analyse employee data and sentiment analytics centred on demographics, life stage, professional and personal aspirations, gender roles, Etc. to give employees the power of choice. 
  
  
• Align DEI priorities: Identify inequity in HR processes, from payroll to promotion opportunities to policy adherence. Technology-based intelligence can help reduce unconscious biases and level the playing field for DEI candidates and programs.
  
  
• Manage talent risk: By leveraging talent intelligence, HR can identify potential red flags in workforce planning related to critical positions, succession planning, attrition analysis, role-fits, Etc., to enable business continuity. 

Building a talent intelligence strategy: Don'ts 

• Do not rush without the right data capabilities: Organisations may jump into talent intelligence without a strong data foundation. Since advanced analytics is the backbone of talent intelligence, it is essential to start with solid data capabilities that are clean, valid and reliable. 
  
  
• Do not opt for standardisation: The talent intelligence strategy must stem from a strong business case. Every organisation's needs differ, and leaders must refrain from following a universal approach. They must understand and assess the specific impact on one's talent strategy and design a customised talent intelligence platform. 
  
  
• Do not follow a siloed approach: Leaders may tend to limit talent intelligence to certain HR areas, such as talent acquisition. This piecemeal approach is faulty. Talent intelligence must eventually form part of a centralised intelligence function that drives not just talent strategy but the overall business strategy. 
  
  
• Do not forget the human element: With data at your fingertips, there may be a temptation to leave talent decisions to the systems or models. However, HR and business leaders must realise that certain complex talent decisions require a high degree of cognitive thinking and experience-based judgement. Hence, balancing technology and human touch is essential for data-backed yet sustainable talent decisions. 
  
  
• Do not treat it as a one-time intervention: Implementing a talent intelligence strategy is a massive change for all stakeholders. It begins with honing the people and organisation towards building a data culture. Hence, culture curation is a critical success factor in ensuring technological adoption in HR and the wider business teams. 

HR leaders must build a strong business case to generate sustained leadership sponsorship. And this means quantifying the business impact with the right metrics, showcasing ROI, and making talent intelligence an HR prerogative and a core business priority. Hence, the talent intelligence strategy must align with the overall talent and business strategy.