Helping SaaS Vendors build high-performing GTM and Delivery Teams across APAC

Changing market dynamics are propelling APAC startups to take a different approach, to ensure their recruitment initiatives rapidly scale and quickly generate better hiring results. With the increasing demand for technical talent within the APAC region, recruiting teams are in an arms race to adopt new technology and create new ways of attracting top talent. One solution being explored is Machine Learning (ML). The value of the ML market in the APAC region alone is expected to reach $13 billion AUD by 2023, expanding at a compound annual growth rate of 51.3% through then. ML is giving computers the ability to learn without direct programming. This is primarily managed through various pattern recognition processes. In the recruiting world, this can mean telling a computer to find the ideal candidates for a vacant position. This can be done by identifying patterns a recruiter might overlook due to various reasons. One of the biggest challenges for recruiters and HR departments currently is connecting with massive networks without committing a consequential amount of time and resources. One example is having thousands of connections on LinkedIn, but not being sure how to leverage these connections. This is where ML can be most beneficial for your startup. Recruiters and HR departments can start to recognize pure data points, such as a candidate’s contact information, profile, and work history, and be able to match these data points with employment opportunities. ML doesn’t automatically choose the best candidate, instead, it reduces the field of search, allowing recruiters to focus on analysing the intangibles. From this, a better hire is made, leading to a greater ROI and high LTV from each candidate. Going further, ML is able to take a broader view of trends in specific industries and titles. For example, ML can identify a candidate that has been at their current employer for X amount of time with their current title. ML recognizes a pattern of employees leaving said title after X amount of time. Therefore, it gives recruiters insight that the candidate will likely be looking for a new employment opportunity soon. This can save recruiters and HR departments a large amount of time, effort, and other resources. If your startup can see the early promise of ML as a source of growth and better hiring results, let me know. I’d love to share my insights with you and discuss how ML can benefit your startup.

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