“How can I tell if companies are investing in the post-capex era?”
Data Source Use Case: Online Job Post Data
Hypothesis Category: New Business Initiative
- 4m worldwide (70% of U.S. total job postings)
- Daily collection from 32,000+ companies’ websites (8,000+ public companies)
- Data since 2007, detailed job descriptions since 2014
- Job level, category, region
When developed economies were powered by traditional manufacturing, we could get a good sense of business confidence from the capital expenditure that companies reported. Good investments would start to show up in revenues six or 12 months later, and in aggregate, that reporting also gave us an insight into where we were in the business cycle.
Those signals are much weaker in our new economy of services and technology. That is a world of operational expenditure—wages, salaries, rents and the like—rather than capital expenditure. Hiring engineers and designers is the modern world’s capex, but that information is not reported in quarterly corporate filings.
It is available in the form of job postings, however. We can now collect these from more than 8,000 U.S. public companies, a sample that represents almost three-quarters of all the job advertisements in the U.S.
That information can enable us to see whether or not a company is hiring lots of engineers and designers in its early life and then filling positions in sales and marketing as it matures, giving us an objective insight into management’s confidence in its business model.
Job postings can also tell us about the performance of certain suppliers to the companies that are hiring. For example, when Microsoft’s Azure started to surprise with its success in the cloud computing market, our technology analysts looked for real-time confirmation of the sustainability of this trend in job postings for I.T. positions, which often specify whether the hiring company is looking for someone experienced at working with Oracle, Google, AWS or Azure. That can be an indicator of future cloud-computing investment at the hiring company. Based on what we found, we believed that Azure was likely to sustain its success—but also that it was the preferred solution in the financial sector, versus AWS in the technology sector.
These examples are a good reminder that alternative data do not always come in the form of numbers, and that gathering it and understanding it can suggest new metrics for analyzing individual companies and the wider economy—metrics that often fill gaps in public reporting for the first time.
