Senior Project Analyst
Executive Summary
The "Senior Project Analyst" role was created to support the CEO of a boutique consulting firm.
Whilst the role would ideally be based in Melbourne, we conducted a search along the East coast of Australia, which led to:
Sizing the Talent Pool
Advising on the distribution of profiles according to skillset
Confirming that the Talent Pool in Victoria was large enough
In this presentation, we'll go through the following:
Sourcing Strategy
Companies mapped: X
RegEx used: 225
Sizing up the Talent market
We casted our net at scale, using 225 keywords to map NSW, VIC and QLD. This returned more than 3914 profiles, which were filtered against the "must-have" criteria, as follows:
Then, we looked at the level of scarcity of each skills, to identify those that would eventually be a bottleneck. Experience in "Change management" may have been too restrictive to our search scope. Our client infomred, it wasn't crucial to the role and could be deemed as a "nice-to-have".
An interesting observation is that, out of what LinkedIn's search engine returned, only 20% of the profiles were relevant!
For a hard-to-fill role, we might have to approach up to 300 prospects to fill the role. Assuming we don't know how candidate-driven the Talent market is, a rule of thumb is to have between 200 to 400 profiles in the initial longlist. In fact, our next step is to conduct a direct approach campaign and we wouldn't want to have to "boil the ocean" by reaching out to more than 400 people!
Here, we realised that the pool of candidates was large enough to allow for filtering on those based in Victoria (330 profiles).
Surfacing Top matches
Now that we've a selection of 330 profiles, ideally, we want to review the most relevant ones first. This is done through a combination of "must-have" and "nice-to-have" criteria, as follows:
By slicing our selection into four tiers, we get to surface the profiles that best match each set of "nice-to-have" criteria. From there, our software sorts by relevance, according to a score card system.
With a 50% accuracy, it didn't take long before getting a curated Longlist!
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