How we informed the location strategy of a global engineering business
Stratigens data enabled a 5000+ headcount tech engineering business to compare locations for software engineers. Our data informed the firm's real estate strategy, ensuring they were in the right places to tap into rare skills
The client problem
Having grown through acquisition, this business had a number of different office locations globally with software teams dispersed around many of the locations. There was a plan to grow the team considerably and the CHRO wanted to understand where in the US they should do this.
The client had two of their existing locations in mind and needed to understand the talent market for software engineers in each so they could inform a real estate decision.
Using Stratigens™, the client was able to search across both locations, looking for software engineering talent that was within a commutable distance of each office to see key data on the talent market including supply and demand plus other factors that contribute to a location decision.
Stratigens surfaces data on skills availability, competition for skills and which organisations you’d be competing against for the same skills. Plus, other location related data such as cost of living, transport, infrastructure and the ease of doing business in a place. This information is combined to make a recommendation on the best location.
Our client could see how many software engineers there were in each location, the proportion of the market that was dispersed across industries and the live demand for software engineers in each region. Additionally, they could see what current salaries were being advertised by others in order to attract this talent.
Stratigens data showed that from the firm’s current list of offices, competition for software engineering talent was significantly lower in Charlotte compared to other locations. This information informed the company’s strategy, saving them recruitment costs and ensuring they were in the right place to attract the talent they needed. More importantly, they were able to see how small the market was and to feed this data into their strategic thinking to determine how to maximise both markets.