Forecasting for future hiring

Forecasting for future hiring


Fulfiling tech roles for a financial services customer

Our financial services customer reached out to us in 2019 needing help to fulfil their tech group’s open positions, including 175 Java and data engineering roles.

The challenge

Creating an expedited solution

With the customer’s stretch goal to complete hiring by the end of 2020’s first quarter, we needed to move quickly to fulfil the open positions.

How we helped

Starting with a candidate pool of 200+

Within the first seven days of being notified of the need, we identified, tech screened and code tested 200+ candidates.

From this pool, we coordinated and completed 90 interviews with hiring managers and made our first 53 engineering job offers, at a 59% interview-to-offer ratio.


Ahead of schedule

By the end of January 2020, we successfully filled all 175 engineering roles, two full months ahead of schedule.

The customer let us know this was the fastest hiring of engineering candidates they had ever experienced, by a wide margin.

Continuing success

For the program to remain successful, the team needed to be able to prepare for what’s ahead.

Our Pontoon Analytics team developed a forecasting model with time series analysis using an autoregressive integrated moving average.

Using past data with current hiring trends from the program, they created a model that predicted future needs.

This model allowed for 94% forecasting accuracy, enabling proper coverage and readiness.

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