Driving Business Impact with Better Quality Talent Data: 3 Factors to Consider
Better quality talent data and a consistent talent pipeline can drive business results in many ways
According to several surveys and studies conducted in recent months, it is evident that two of the main challenges that surround the role of HR in tech involve better talent attraction and talent retention processes. Given the current state of the global workforce as a result of the Covid-19 pandemic where furloughs or massive job losses are still unfolding, there is more pressure on talent management and talent acquisition teams to help businesses optimize existing resources while reducing internal issues related to talent management. And this process starts by having access to better talent data.
In the absence of a strong talent data management and talent analysis system and the right tech and infrastructure, organizations will not have the capabilities they need to work towards a successful future.
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Factors to Consider When it Comes to Talent Data Management
When diving into the fundamentals of a strong talent management and talent retention process, there are many factors that HR teams need to focus on, the most important ones are the quality of their talent data and the ability to effectively use and access this data from anywhere, anytime.
Talent Data Quality
The job market is constantly evolving and with today’s rapid tech evolution, the skills required for different roles are also changing. Having the right and most recently updated talent and candidate data for particular roles built into a central system will help recruiting teams access the best-fit talent faster. Using automation to clean, de-dup talent data and using data enrichment engines to score more candidates based on a company’s distinct hiring specifics will enable teams to reach more candidates with most having the right qualities needed for the role.
Unified Vision of Talent Data
When it comes to managing talent data, the aim should be to maintain updated, clean, unified data so that recruiting teams find it easier to search and filter candidates and implement the right automated workflows to start fruitful candidate conversations.
Having the database built out is not enough, talent teams need to know how to use this data to their benefit. They need to be armed with the right recruitment data and analysis technology and skills to assess the data. Implementing talent data platforms as part of a typical HR Tech Stack can help unify data and key information across departments and solutions thereby streamlining processes and efforts.
Power the Talent Pipeline with AI-driven Technologies
Most recruiters are used to working with job titles and company names, the right AI powered tools can run through large databases of job titles and company names and relate information to specific hiring needs far more quickly. AI powered tools can use the talent data to accelerate candidate screening, job matching, and even workplanning planning initiatives; all of these activities will be more seamless and powerful when done with the right AI-powered HR Tech and when integrated with the other key business functions. Machine learning algorithms can also learn semantic searches to help find talent information from sources the company or hiring team is not used to look at otherwise. In time, ML algorithms can learn from datasets that recruiting teams have put together, or from repeated action-feedback loops within the system, the algorithm learns, then gives a suggestion to the recruiter.
The Future of Work is one where HR will have to play a more critical role in maintaining standards amidst different challenges. To future-proof an organization, the right resources are a starting point and this is where there has be to a renewed focus on optimizing hiring needs and processes down to the zero. HR teams will have to start relying more on their talent data and new predictive behavioral tools more to help structure and shape future teams effectively.
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