The Applied

sift

: our not-so-secret

sauce to

data-driven

hiring

We share it freely because we want to improve hiring, regardless of whether your organisation uses Applied.

Let’s be clear: leave your CV at the door

The information contained on CVs isn’t a very good predictor of whether someone will be good on the job.

Instead, Applied’s first stage (the sift) uses work sample questions to help you identify the best candidates with data-led outcomes.

The perfect sift in 5 steps

Some of these steps can be implemented by yourself, but we do it best 😉

STEP 1

Anonymise

Basic personal information such as name, age, race and gender can trigger a reviewer’s unconscious bias. As you don’t need this information to assess whether a candidate is great for the job, we remove it up front.

STEP 2

Chunk

Chunking means breaking the application into pieces and grouping answers to the same question together. This prevents confirmation bias

As humans, we often look for information that confirms our existing beliefs, this is known as confirmation bias.

Believing a candidate has made a great point because they've studied at a top university? Confirmation bias.

and allows reviewers to assess answers faster.

STEP 3

Randomise

Each member of the hiring team will see candidate answers in a different order to ensure the ordering effects

Order effects happen when we make several judgements one after the other. When hiring, we usually make kinder judgements early on and get progressively harsher as we continue, meaning somebody at the bottom of a CV pile has to be extra special to stand out.

don’t impact a candidate’s overall score.

STEP 4

Review

The hiring manager can decide which team members contribute to assessing the candidates. Each reviewer sees one answer at a time and rates it against a marking guide to give it between 1 and 5 stars.

STEP 5

Collate

Reviewers’ scores are automatically reconstituted and combined into a leaderboard that shows the best candidates.

Explore Applied's features

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Keen to see the sift in action? See this and much more by scheduling a demo with the team.

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