Blue-Chip Recruit

How a Fast-Growing Tech Firm Met its Aggressive Growth Goals by Applying Artificial Intelligence to its Real Estate and Workforce Expansion Plans

1. Summary

Okta is the world’s leading identity company and provides cloud software to help companies manage and secure user authentication into applications. It also helps developers build identity controls into applications, websites, web services, and devices. Headquartered in San Francisco, the company has grown rapidly and achieved $835m in revenues in fiscal 2021.

2. Case Study


An extremely tech-intensive and ambitious company, Okta needed to support the rapid growth of its real estate business by recruiting highly-skilled people at a sharply accelerated pace. Recruiting emerged as a strategic consideration, with Okta executives weighing the ability to attract and retain top talent when deciding on locations for new offices, both in the US and internationally.

Like many companies, Okta had contracted with a service to provide information about talent availability. However the team at Okta had a vision for a better-informed decision-making process that could include criteria like housing cost trends, and move toward incorporating a diverse array of factors affecting geographical flows and their impacts on talent availability.


Okta’s initial solution was to use early-to-market services from real estate companies that were trying to enhance their insight into the property market’s effects on talent flows, leveraging data from the Bureau of Labor Statistics. Problems with these services soon became apparent, including:

  • Lengthy contractual obligations
  • Limited flexibility to build more data sources into the modeling and to enable greater insight around factors relating to individual candidate roles
  • Infrequent updates on trend factors—a particular problem for a company growing as rapidly as Okta
  • Lack of insight into factors affecting work/life balance, which directly impacts retention and overall HR costs.

The team sought viable alternatives from consultancies and other real estate specialists and found none. That prompted the team to launch a pilot project to develop the capability in-house. That effort, however, was quickly abandoned due to the time and cost required to research and source data and to create data models and visualizations. Okta also faced a resource challenge, as it needed to research and understand disparate flows of data and analyze specific insights in the context of workplace trends.

After scrubbing the pilot program, Okta reached out to, a start-up working towards an AI-driven workforce solution. Okta quickly established a relationship that allowed it to help influence the direction of development of the solution. This enabled Otka to engage in blue-sky thinking about requirements that could affect the life-quality of potential recruits. For example, data sourced and analyzed by included:

  • Cost of living changes due to spikes and bubbles in housing costs, within high-growth tech-specialist areas
  • Infrastructure limitations that impact an area’s growth
  • Transit authority data on cities’ transport services and travel times
  • Rental cost and availability trends.

The Vertis ML system uses data captured from a wide range of sources, including public sources such as government databases and web crawlers from sites such as Zillow. In addition Vertis considers several x-factors, such as GitHub downloads and developers’ skills/login locations. The company’s custom-built data ingestion software captures raw data from these sources, consolidates and merges it, and then feeds it into a machine-learning model.

Vertis’ technology in essence acts like a recommendation engine. The AI model gets trained using the pre-gathered data to calculate a score for each location. The model can be made granular enough to consider each zip code separately. The outcome of the recommendation engine is an overall score that informs the rank of each targeted location. The model is dynamically trained to continually provide real-time customizable results.

Vertis continues to advance the AI model it developed with Okta, while adding data sources such as economic growth, workforce diversity, and job-market indicators such as trends in vacancies.


Understanding the high costs associated with an in-house build, the team was gratified to learn that the annual cost of the Vertis software license was similar to the cost of a single consultancy engagement. Okta had already paid for several such sessions during the early months of its effort. By switching to the Vertis solution, the company significantly reduced spending that would have gone to paying for consultant engagement to develop the solution in-house.

More importantly, the Vertis solution has armed Okta with vastly improved insight, enabling the company to accelerate its program of rapid recruitment to meet the scale of business opportunity. Erin McNamara, Okta’s Head of Real Estate and Workplace Strategy, says the Vertis solution has allowed the company to push forward its aggressive real estate and workforce expansion plans.

Lessons Learned

Pre-pandemic, almost every organization was already thinking about digital transformation and the need to confront issues already in the sights of most tech companies. The rapid transition to remote work in almost every industry undoubtedly accelerated this transformation. Among the learnings Okta took from its engagement:

Focus on the right things: Skills are a major factor in enabling this change, and Okta’s quest to recruit smarter puts it in the vanguard of companies that increasingly view recruitment and retention as critical to future growth. The ability to leverage real-time data in the effort has been a game changer.

Work with the right partners: Without the insight provided via Vertis, recruitment inefficiencies could have slowed Okta’s ambitious growth plans, especially given the added complexity from the pandemic. People’s lifestyle, work, and transport preferences are in flux, and successful recruitment and retention depends on understanding these factors as they evolve.

Engage the right stakeholders: Okta credits its successful rollout in part to a broad effort to engage multiple departments and disciplines across the company, communicating the need for the new recruitment strategy and opening a dialog on how it can best be executed. For example, factors influencing decisions on sales teams’ locations require different considerations than those for tech teams. Okta has also adapted its relationships with recruitment partners, which need to be able to action the insights from Vertis.

Attract the right people: Okta’s Dynamic Work framework enables the company to recruit and hire high-caliber talent from around the globe, a strategy that has proved beneficial during the pandemic and provides opportunity to achieve greater diversity. Leveraging Vertis ( provides Okta with quantified insight into geo-locations, educational institutions, candidate pool search dimensions, and recruitment metrics such as time in pipeline, time to offer, and offer acceptance rate. Together, these help Okta understand where key talent is available.

3. About GigaOm

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4. Copyright

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