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When chatting with any of your Human Resources friends, particularly those responsible for employee compensation or total rewards, a topic that's likely to come up concerns the ever-increasing salary demands from current and potential employees. How can the company afford these ever-increasing labor costs? When will it end?
The traditional compensation surveys that we've relied on in the past to set pay may not be enough to inform your compensation decisions.
In a frank conversation with Belinda Roberts, Mercer's head of North American Product Development, we discuss what the future of compensation surveys might look like, how to integrate more real-time data, and what Mercer is doing to evolve their current data products.
Join me, Rebecca Adractas (RA), in an insightful conversation with one of the leaders in the evolution of compensation data, Belinda Roberts (BR).
RA: - Belinda, thank you for making time to chat today. This is a very hot topic and your view is so important.
BR: - I'm happy to be here. The future of compensation data is at a pivotal point, and it's exciting to think about what this next evolutionary phase can bring.
RA: - That's an interesting way to think about things. Can you expand on what you mean by the evolution of compensation data?
BR: - Sure. For a number of years, traditional salary survey vendors have collected data in the same way. Over time, technology has advanced the process and methodology of data collection. For instance, we originally collected data on paper, and a human was required to transcribe, aggregate, and report information. Then, we moved to digital copies via Excel kits, which sped up the process and reduced the number of potential errors. Most recently, vendors have used technology to create data platforms, like Mercer Data Connector, where clients can provide their data electronically. Data collected today can be aggregated, sorted, and reported even faster, leading to more timely reporting for clients.
However, there is still some friction in the process. Organizations still require a significant amount of time for efforts like matching jobs to the vendor's taxonomy or putting together the data into the proper form for uploading.
RA: - I actually started my career as an analyst performing those tasks. I would guess that even though it's not frictionless, it's improved significantly.
BR: - Absolutely! Using a platform like Mercer Data Connector has really shortened the time it takes because analysts don't have to do it piecemeal. The platform provides a clear structure for the data, an extensive list of positions for job matching, and a much faster response when something seems out of whack. The real-time feedback and auditing saves valuable time and is a giant advantage over the older paper methods.
Technology has greatly improved the quality and volume of the data that clients are giving us. Because our platform has things like matching algorithms to help you match jobs, we are light-years from where it used to be when it was just the Excel-based exchange.
Currently, we're trying to migrate to the point where all of our surveys are created from data provided through our online Data Connector. Most of our surveys are there, but a few remain outside Data Connector.
Even with the online Data Connector improvement, clients still have to get a file from their HRIS system, format it, and then go through the process of uploading the data to us. A lot of the innovation in surveys has come in the form of improvements to this process, but there is still quite a bit of room for improvement. We're still always making improvements to reduce the client effort involved in supplying data for our traditional annual surveys.
RA: - What are some of the ways to reduce the amount of effort required by participants?
BR: - Well, right now, clients (participants) can't simply push a button to get the necessary information. It often times comes from multiple systems internally, and each client is different. We are asking for information to be structured and tagged in a particular way to fit our platform. Since clients are encouraged to use multiple data sources, they then have to re-match jobs and re-format their data for each vendor. We are looking into ways to connect directly to the main HRIS (Human Resource Information System) and payroll systems, and comp management tools to remove some of these steps.
RA: - Can you tell me a bit about real-time datasets and how they fit into this scenario?
BR: - Great question. A lot of what we are doing around connecting directly to clients' data systems will allow us to produce more real-time data products, with the same high-quality curation clients have come to rely on from Mercer. But, I should mention, another source we see a lot of interest in is crowdsourced data, which is still a relatively new concept in the compensation survey space. Originally, most Human Resource professionals cautioned against the use of these data sources, but as the technology and algorithms have evolved and the ability to vet and validate the data has improved, we professionals have begun to see a place for crowdsourced real-time surveys and the need to keep an open mind. The key questions remain when deciding what data to use:
These "real-time" surveys often don't answer all the traditional questions compensation professionals are looking for. They may help answer the standard base pay questions on certain jobs and how quickly they're moving in a particular direction. But they are often lacking in the total compensation areas of equity, long-term incentives, and policy. So, the information our clients get from a traditional survey is just that much more robust.
That being said, I do think there's a place for real-time surveys especially in a tight labor market. They are an excellent third or fourth source, but I just don't think that they provide enough rigor to base all the pay and policy decisions on yet.
RA: - That makes a lot of sense. We always say there is an art and a science to market pricing. Getting the job matching right against a robust job architecture and having a sense of what the data will tell you given events outside the base salary data. For instance, there has been talk recently about inflation allowances to help employees now without locking the company into long-term commitments.
BR: - I think you're right. Organizations need to compensate employees with base salaries that are within a reasonable band determined by their peer group. Then, it's all the other variables that determine how competitive your job actually is. There's just so much more to compensation data that you need to consider. Sometimes the historical information that we can provide with traditional surveys can provide more useful trend information.
Many compensation professionals understand that the segments of jobs or employees influence how you need to focus on slightly different data sets. Interestingly, we have seen how traditional data sets and nontraditional data sets tend to skew in different directions. For instance, traditional data tends to skew toward the bigger cities and the bigger organizations, while crowdsource data tends to skew toward more junior roles, younger people, and often more rural representation. That information can be really useful if you're looking at certain jobs in your organization. Categorizing the use case for different data sets is important within clients' organizations, as well.
RA: - What do you think about the democratization of salary information that is available to anyone with an internet connection? Is this a positive trend?
BR: - Again, we were cautious when salary data was first crowdsourced and reported without any oversight. As some of these real-time data sources have become more robust with validating and cleaning the data (removing outliers), they have become better sources. The trouble with these sites and data sets is that they do not teach the nuances of compensation to the user. Again, base salary is one large but singular way of comparing compensation. The number alone does not tell you about incentives and whether they are tied to individual or company performance. Simplistic pay data may not capture the employer investments in employee benefits.
Additionally, the difficulty is not just a technical difficulty of collecting more data more regularly. As vendors, we have to follow certain rules. Take safe harbor rules, for example, where data has to be aged 90 days. These rules and guidelines ensure that vendors are not helping clients collude with each other, setting pay decisions that will sway the market.
That being said, we are seeing a large shift in thinking away from secretive compensation and a movement toward pay transparency. I think it's the transparency of the philosophy around how organizations pay that employees care about. It seems like a lot of employees right now don't believe that their comp teams really know what they're doing. And I think that's because organizations just haven't been transparent.
RA: - So how would you suggest compensation departments become more transparent? Mercer recently released 3 New Rewards Strategies on TAAP. One of them focuses on how companies are creating reward business partners to upskill managers and strategically partner with HR and the business. Can you elaborate a bit on what you are seeing companies put in place?
BR: - Yes! Managers are the ones at the frontline with employees. They are the ones having these conversations in formal reviews and casual meetings. Mercer has done some polling, and the managers are often just as confused about how to handle these conversations as the employee. They don't know any more about how compensation is determined than the employee does. And that's a real problem.
When we keep managers in the dark, we're setting these people up for failure while asking them to have these sensitive conversations with employees. And, you know, that's just not fair. And I think if you want your managers to be effective, and you want to keep your employees engaged, you've got to give the managers the tools to be able to have that conversation. I think employees just want a little information to indicate that someone is making active decisions and looking out for them. So when you approach your manager, and your manager can't answer simple questions because they are also unsure, it creates doubt in the mind of an employee about their future and job satisfaction.
RA: - There have been a lot of changes to how we collect and use compensation data. What are some of the trends you see sticking, and where do you think this area is headed?
BR: - Great question. Over the next three to five years, I think we will see the addition of more nontraditional data sets used to assess the competitiveness of roles and employees. As I said, traditional data sets are not going away, and traditional vendors are going to continue to refine how they collect data to make it easier for everyone involved. But, we will see new nontraditional data sets enter the market, and the use of new types of data points like supply and demand of particular skill sets. But, there's room for everyone because people cost is very important to organizations.
I think we need to continue working with our clients to create new products, help them understand how to utilize the data better, and help them communicate compensation with their managers and employees.
Change is going to move quickly. Just the changes in technology will demand it, anyway. And there are always younger generations of Human Resources professionals who aren't tied to a particular way. Consider how much technology has changed our work capabilities and now has changed our expectations. We are transitioning to the next generation of compensation data in the coming years.
RA: - There is much talk about employee personalization and the personalization of rewards. Traditionally, salary survey data was de-coupled from the personal stories and individual motivations of the employees. Now it seems more common to champion the individuality of our workforces and strive for more equitable win-win scenarios in the employee contract. Do you see compensation shifting?
BR: - I think we'll see increases in organizations giving different categories of employees or personas choices about how they want to be compensated. We talk about knowing what our employee's needs are and wanting to make the most impact with the compensation data we have. If you have an employee who is just starting out in their career and carrying a huge student loan debt with them, they may elect to take a larger portion of compensation in bonuses to pay down debt, or they may prefer a higher salary so that they can pay down the debt in a steady fashion. Each employee has their own story and their own motivation for working. Having survey data that can help facilitate the conversations can help drive us closer to a mutually successful scenario.
Companies are using artificial intelligence, machine learning, and predictive modeling to establish compensation guidelines and reward strategies. The future of rewards is more agile and personalized than ever before.
RA: - Thank you for your time and insights! This has been an enlightening conversation and I'm sure our readers will appreciate your expertise on this subject.
For more information on the future of compensation data for your organization, contact us at email@example.com or 855-286-5302 today!