Why is a Data-Driven Approach Important for Finding Talent

Why is a Data-Driven Approach Important for Finding Talent

Why is a Data-Driven Approach Important for Finding Talent

For too long, outdated traditionalism has dictated the way that businesses have assessed their potential workforce.

A reliance on traditional hiring processes, revolving around laborious and inefficient C.V combing, have cost many businesses thousands of pounds in poor decision making. Today’s hiring managers also have new pressures to contend with - they are often hiring for roles that aren’t as clearly defined, requiring skills that are new, and often in the ‘soft’ skills category.

As the workforce becomes more flexible too, the “role” has become less relevant than the need to bring niche skillsets into the business. Hiring is slowing down as the decision-making process becomes tougher – making the skills gap wider and the need for more efficient talent acquisition processes more pertinent than ever before.

Using a data-driven approach to make better hiring decisions

It is very common for people to exaggerate their skillsets and responsibilities on their CVs, and unconscious biases may also have a devastating impact on hiring decisions.  Data-driven staffing platforms can provide a more accurate picture of a candidate’s level of expertise across various skillsets needed for the job. Hiring managers can leverage these tools to gain greater insight into which candidates could successfully perform in a position, removing any candidates who don't meet the criteria.

CVs are useful in illustrating past experiences but are not helpful in identifying any critical soft skill requirements. The demand for soft skills matching is almost exceeding that for hard skills, as businesses today are seeking talent to engage well and become more productive and efficient. Talent Intelligence processing can build high volumes of datasets with increased granularity to continue to refine and enhance connections based specifically on soft skills requirements.

Traditional hiring methods also typically focus on one hire at a time. Machine learning , on the other hand, can refine initial results based on client selections to cultivate and maintain a wider talent pool made up of similar talent profiles for companies to tap into to deliver on any future initiatives, whenever the need arises. Making talent connections faster closes the talent gap and helps businesses to build the agile workforce of the future.

Data is the Future

Organisations are increasingly relying upon data and technology to predict needs within their business and fill current talent gaps quickly and efficiently. At Talmix, we’ve replaced the traditional CV with a multi-layered, inter-connected, and constantly updating, data points profile: The Talent Passport™.

The Talent Passport combines information from multiple sources to create a single and complete view allows for more precise and faster matching of skills to opportunities, categorising information into demographics, micro-experiences, soft skills, feedback, and work style preferences.

A data driven approach guarantees speed, convenience and precision to talent acquisition processes. For an accessible and resourceful way to fill make the right hiring decisions, get in touch with Talmix today.

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