The world of work has changed massively in the last year, and with it, a rush of startups have emerged with new technology and approaches to improve how it is shaped, and specifically how human resources departments do their jobs.
In the latest chapter, Visier, a Canadian startup that has built a big-data engine to ingest and analyze information from disparate human resources and related applications to develop more accurate profiles of people and departments — useful when considering remuneration, promotions, and wider hiring budgets — has raised $125 million (USD), a Series E that the company confirms now values it at $1 billion.
The funding comes on the heels of the company seeing massive growth in particular in the last year, with companies scrambling more than ever before, in a new world of more hybrid and remote work, to get a better grip on how and what teams and individuals are doing. Visier said it now processes employee records for 8,000 customers, large and high-profile enterprises like Adobe, BASF, Bridgestone, Electronic Arts, McKesson, Merck KGaA, and Uber that collectively represent some 12 million individual users across 75 countries.
New backer Goldman Sachs Asset Management was the sole investor in this round. Previous investors in Visier include Sorenson Capital, Foundation Capital, Summit Partners, and Adams Street Partners. Visier — pronounced “busier,” which co-founder and chairman John Schwarz joked you are not supposed to be when using its product — has now raised just under $220 million.
As Schwarz described it to me, the challenge that Visier is addressing is that while everyone uses HR management tools like Workday, Success Factors, any number of payroll applications, and more — on average 20 applications per department, he said — to chart a lot of basics of how an employee works day to day or month to month, a lot of that data remains in silos and so it’s hard to get a “360” view based on all of it, and that’s before considering how to take that information and benchmark it against other information outside the business.
The solution that Visier provides is a big-data engine that it has built that can connect to any and all of those apps, ingest the data contained in it, match it up to provide visualizations of the current state of things, and increasingly also predictive insights. Today, this is done typically for HR departments, but this has applicability to managers, finance departments, and really the employees themselves.
“In the future, we want to help everyone understand the policy today, which impacts the outcome tomorrow,” he said in an interview.
The move to build big-data analytics targeting particular areas of an organization has been an interesting trend that has played out in other departments, too, such as sales, finance, risk analysis, and other areas. The idea here is not unlike what data scientists have been working on for years with wider analytics questions: tapping troves of data from disparate sources to order it better, match it up with each other, to provide insight into wider trends and activities within an organization.
As data science becomes more democratized — and thanks to advances in no-code and low-code tooling, turned into tools that even non-technical people can implement and use — we will likely see many more use cases where this idea gets applied. After all, data is the new oil, but unlike actual oil, we seem to be supplied with an endless amount of it these days.
And yes, we’ve seen a real rush of HR tools come to the market in recent years — and see a lot of funding in the current climate as their businesses see customer interest rise — they include HR platforms like Hibob, HR aimed at particular verticals like Personio or Factorial, or for distributed workforces like Oyster or Remote, or those that are building supercharged org-charts like ChartHop.
But Visier believes that there are no big-data players looking to be not primary-source repositories of information but big data integrators from other platforms. Schwarz notes that in most cases, the “competition” will be custom-made implementations built by systems integrators using Tableau or something similar but not the same as what it provides in terms of real-time analytics.
“It’s all about using data from other sources,” he said, pointing out that it’s telling that Workday tried to build something like what Visier provides, but that more than half of Visier’s customers also use Workday (meaning whatever is there is not quite doing the trick).
“Access to information about employees and the health of an organization has never been more critical,” said Holger Staude, a managing director within Goldman Sachs Asset Management. “We’re excited to partner with Visier at this pivotal moment and support the company’s continued growth.”
News Source: TechCrunch