Q&A on workforce data: ‘Technology allows companies to search wider, deeper talent pools and recalibrate for change’
The number of contingent workers continues to grow at a rapid pace, and with so many companies now having remote workers and global workforces, managing contingent workforces has become even more complex. Business leaders who don’t have the latest insights from a wide range of workforce data sources cannot properly execute their plans.
“It becomes a strategic advantage for companies that have enough of the right data,” said Dustin Burgess, Senior Vice President at PRO Unlimited’s NorthStar HCM group, the workforce technology provider that helps source, track and analyze the contingent workforce. “If you don’t have enough data to pull from — and the mechanisms in place to ensure the data is timely, accurate and unbiased — you’re not going to be as smart or as competitive when sourcing candidates, regardless of your company’s specific processes.”
Difficulties from the global pandemic have compounded the matter. The challenges — including instant and now-sustained remote workforces, supply chain delays, worker classification problems, new workplace safety protocols, more employment options for those looking for work, and others — have created unexpected and sometimes multi-faceted, interconnected issues.
And on top of everything else, some companies have faced large numbers of layoffs or resignations.
The bottom line is that companies need efficient, effective ways to attract, retain and redeploy talent despite the current climate. The secret weapon to address all of these, alongside traditional contingent workforce management matters, is workforce data.
But not just any data. Companies need to amass large datasets that address their specific needs, then be able to analyze that data strategically, resulting in business intelligence that supports contingent workforce program management and larger business decisions.
To learn more about the impacts of incorporating data and analytics into a contingent workforce program, we spoke more with Burgess, who is the Senior Vice President at PRO Unlimited’s NorthStar HCM group.
Q&A on workforce data with PRO Unlimited
In the non-employee labor space, the current conversation seems to include talk around data in some form or another. How do companies access the data they need, and why are partnerships important?
Dustin Burgess: Data has always been something our clients have been interested in, but it’s definitely more pertinent now. Companies are accessing huge amounts of quantitative and qualitative data, which gives them insight into so many new corners of their contingent labor program management. Because we have access to so much data, it’s imperative that it’s used in ways that truly bring value to organizations. That means having the right partners to institute change.
There are many groups that provide data and analytics consultation, and they’re very good at what they do. However, they don’t understand our data in our space the way our industry experts do. Their recommendations to improve operations and reduce costs can end up increasing things like attrition and time to fill.
We believe making recommendations about how to optimize a contingent workforce should come from folks who understand the downstream impacts to the changes being suggested via the data. It’s really key to work with solutions providers that understand and interpret data across the board, so you can make informed decisions that best suit your organizational objectives.
Most companies use a combination of internal and external data, but all of it has to be managed, cleansed, assessed for value and validity, then interpreted and analyzed. Security must also be considered at every turn. As the world becomes more connected, there is more data that brings greater security concerns and requires expert regulatory navigation. Companies have to be up to date on national and global parameters around data collection, security and privacy, which requires technology and an expert partner that can update operations in real time.
The notion of collecting, analyzing and integrating workforce data into program operations can seem daunting. Where can companies start when they need advice about how to make changes to their existing operations?
There are several paths to enter the conversation and many sources of information. Industry analysts and organizations like Spend Matters or SIA can help companies gain a better understanding of the space and the players within it. Then it’s a matter of having the right conversations with technology and solutions providers, as well as other companies that have adopted similar solution sets.
Companies need to assess the breadth and scope of expertise, global capabilities, technology offerings and partnerships. It’s only through conversations — whether that’s an RFP process, formalized information-gathering interviews or more casual conversations — that well-informed decisions can be made.
We typically start by talking through the challenges your organization has, what types of positions are sourced, what future needs have been identified, what percentage of labor is contingent versus full-time, and what data is already being collected and used for benchmarking. There is no one-size-fits-all blueprint because every organization is set up differently. And company size is not an indicator of existing program success. Sometimes large corporations have little control over their sprawling programs. We go into every situation ready to uncover as much relevant information and data as we can, then establish an individualized way to help our clients meet their business goals.
There is so much workforce data available from internal and external sources. What types of data should companies look for to support their business goals?
Typically, companies turn to their own internal systems for the foundational layer of data. It is often the most trustworthy source and can come from multiple departments such as finance, HR, and procurement. The data provided can include applicant tracking, invoices, pay stubs, vendor payments, 1099s issued, badges and permissions issued and revoked, or anything else that helps establish the status and number of non-employee workers.
External data can come from many sources. We scrape data from public sites like LinkedIn and other job boards. The US Bureau of Labor Statistics provides a service that allows us to pull in other types of public information.
We also pay for data from a variety of vetted sources to give our clients more complete information in a number of areas. We have found that local market data is invaluable because it lets us assess geography-based candidate supply and demand, local competition and rates. That’s critical when you design employer-brand strategies, especially if you’re going to have a robust remote workforce. When companies expand into new countries, for example, that data is absolutely necessary when making hiring decisions.
We gather a portion of that data from our network of trusted partners. Our network of more than 10,000 staffing firms located all over the world provides local market intelligence that informs us about trends, regulatory changes and in-demand skills.
Overall, we pull data from about 40,000 sources, which means there has to be a strong process for data validation. Whatever solution a company chooses to manage their data has to be technology-driven because the sheer amount of data is too great to undergo manual review. That technology should include controls so the data can be synthesized into existing systems and provide protection from risk.
The amount of data available today seems endless, which also makes it feel somewhat overwhelming. Why is it important to have so many disparate sources of data?
Companies benefit from using the widest range of data available that addresses their current and future needs. It is important for organizations to look at individual components to see how they integrate into the larger decision-making process to ensure they are considering all of the components that could impact their business goals.
Right now, diversity, equity and inclusion (DE&I) is the emerging data topic across the board, regardless of industry. Historically, most organizations tracked supplier diversity, but that conversation has shifted materially to candidates and workers. This change has created a gray area around what can be tracked, what can be asked for and what should be self-reported. Most organizations rely on self-reporting and some level of inferred diversity metrics that are verified; they are also starting to track progress. No matter what type of DE&I data our clients are looking for, they want the information — it’s critical in achieving their goals.
Direct sourcing data is also more important now since workers have more choices and are looking at employer brands to make their decisions. This area has seen a shift away from the traditional employer-of-record services to technology-enabled solutions that use AI and machine learning to facilitate candidate matching.
The technology allows companies to search wider, deeper talent pools and recalibrate for change when there are shifts in job descriptions, candidate responses or any number of other changes to company need and candidate availability. A solutions provider should be monitoring things like the success of brand campaigns, changes around market rates and employee satisfaction.
Worker experience, which relates to employer brand, should be a component of every company’s data so they can really understand what’s working and what’s not. We facilitate NPS surveys and other information-gathering tools to elicit data around questions like overall satisfaction, what types of benefits workers want, how they found the role and their interest in remaining after an assignment has ended.
Redeployment is an interesting use case for us because to be successful, it requires incredibly strong data. Companies can save money, reduce time-to-fill, lessen onboarding time and ensure better culture fits if they can rehire workers who are already familiar and happy with their non-employee experiences. Having robust data can tell a manager exactly who is nearing the end of a contract, who is appropriate for upcoming openings, what a worker’s performance has been and current bill rates. Using this data can effectively support planning so there are fewer lags in hiring and less downtime.
Perhaps the hottest topic we’ve seen in the past few months has been pay parity, but we look at it as a broader question. While we absolutely look at pay equity to ensure every worker is paid the same rate for the same work, we also look at job parity, a component of the conversation that’s sometimes overlooked. At PRO Unlimited, that means we leverage AI and machine learning to make sure contingent job descriptions are equal across the board, which includes contract workers and full-time employees.
Our technology ascertains whether there is a match with regard to skills, role responsibilities, education requirements and any other factors across the entire job taxonomy. By taking job parity into consideration, companies can properly address both parity and equity concerns, which reduces risk.
Once an organization makes the decision to incorporate data into their existing operations, what should they look for regarding integrations and interoperability?
It’s vital that companies have the ability to tap into and effectively use the data within their internal systems. When talking about data around talent, that can come from a multitude of departments and sources. Much attention is being paid now to specific technologies, but that choice needs to be made with a clear understanding of the types of data that need to be captured. And one point that can’t be overlooked is where that data will add value within the organization and within each different process flow. There is a correct spot to insert data where it will impact decision-making, and it has to be inserted early enough in the process to appropriately inform those decisions. And that is a critical component because it’s one thing to have access to data, but if it isn’t available until after decisions have been made, it can’t provide value.
When looking for solutions providers, what should companies expect with regard to evaluating their current situations? Are there common technology components that play a role in successful programs?
For companies to successfully adopt and utilize technology solutions around data, their providers should have some evaluation mechanism to determine where their existing systems and processes are in relation to where they would like to be. We look at the maturity of the existing contingent workforce management program and ask questions like what technologies are in place, who manages the program, and what goals will a new program have. There is no one best way to establish and maintain a data-based program, but there are definitely commonalities to those that are successful.
This Brand Studio post was written with PRO Unlimited.