Artificial Intelligence is here and rapidly becoming part of everyday life. Almost three-quarters (72%) of HR professionals use AI tools at least once per week, and that figure will only grow in the coming years.

Hiring can be a challenge at the best of times. It’s hard to find great people to join your team, especially if you’re looking for people with in-demand skills.

How did your recruitment efforts work out last year? Did you find the right talent to help you meet your strategic goals? Or did you spend last year feeling lost in a frustrating maze of resumes and interviews?

A strong hiring process can help you identify the best candidates for any role. But even the best recruiters can't predict with 100% accuracy how a new hire will perform in your team. Sometimes, a very promising candidate might turn out to be disappointing. Other times, the person with the patchy resume might evolve to become your star player.

A formal salary structure helps businesses make informed, equitable compensation decisions while saving time and money. By benchmarking market data, defining clear job levels, and establishing consistent pay guidelines, organizations can improve retention, support career progression, and reduce costly compensation errors. I'm certain that, in your business, you have probably given a fair amount of thought to what percentage of salary increase to give employees. You've probably also had conversations with managers on how much to offer a candidate they want to hire, or what a new salary should be for someone who moved to a new role internally. These are all common compensation conversations that happen throughout the year in business. Due to these universally recurring pay questions, many business leaders that I work with find that putting in the time and effort to develop a formal salary structure provides a major payoff in the long run. A salary structure can help inform all compensation-related decisions that occur in a business in a market-based, internally equitable, intuitive, and efficient, timely manner. Sounds pretty good, right? Let's dive even deeper. The Business Benefits of Having a Formalized Salary Structure One of the biggest benefits to having a salary structure in your business is that it puts all of your compensation benchmarking into a tool that in effect, summarizes your market data and the scope of work at each job level of the organization. Why does this matter? Well, when you are frequently having conversations about what salary to offer a prospective candidate, what compensation looks like for your current employees who bring you printouts of what they found on salary.com, or even pricing strategies for RFPs, this tool becomes incredibly helpful in saving your precious time and energy. In addition, once you create a base salary structure, you can then apply that structure to whatever geographic areas your organization does business in to properly account for the cost of labor. With remote work now the norm and the increasing popularity of employees moving across the nation, this tool gives you quick access to the data you need to make informed decisions. Having a business tool with this flexibility can save your organization tens or even hundreds of thousands of dollars (depending on the size of the organization). Ok, that's a big statement and range, I know. Here's how a salary structure can save you money: Reduction in errors regarding how employees are paid. In otherwise, you've done the homework to know you are paying your team fairly and competitively, but not overly compensating well beyond the market. Reduction in opportunity costs through increased efficiencies now that salary administration guidelines are in place. In addition, having a salary structure with defined levels can help your organization create a foundation for career pathing. Career paths are another important retention tool to have in place so that your employees understand their growth potential and understand how they can advance their careers within your organization. It's widely known that some of the top reasons why employees leave an organization is because 1) they feel they aren't compensated fairly or 2) they don't see future growth opportunities. Ok, so hopefully I've done a good job describing why salary structures can make a difference in your business. Now, I'll go into more detail on how to design a salary structure. What is Needed to Develop a Salary Structure? As a consultant, when I start a new compensation project such as developing a salary structure like this, I always first ask my client, "what is your philosophy towards paying your staff?" I'm essentially trying to understand if there is a compensation or total rewards philosophy for how the business approaches pay decisions in general. Every organization is going to have a different philosophy based on its unique position and circumstances. When I understand the philosophy of if you try to pay at the high end, average, or a little lower with generous benefits, then it can help inform how the salary structure is approached. The other important piece of information that is critical to developing and implementing a salary structure is having clarity of job roles within your organization. This will help us understand the full scope of the job role and level. It's important to have solid documentation regarding what each job does relative to the other jobs within a job family across the organization, regardless of job function. Quality job descriptions are a prerequisite to informed decisions on pay, and they will be used when we're slotting jobs into the salary structure. Another prerequisite to making informed decisions on pay involves market pricing your jobs. Compensation benchmarking is an HR best practice that should be conducted regardless of whether you are implementing a salary structure. What Are We Aiming For? In order to accurately slot jobs into a salary structure, we will need to define the levels of the compensation structure to tie in the talent market and ensure it is also in line with your organization’s structure, and vocabulary of how the work is described. We want to have an end product where we are able to review a new job that's been created at your organization, and quickly and accurately slot it into the correct level of your salary structure. Can I Just Copy a Structure That Already Exists? In short, no. There are numerous types of salary structures that exist in the market, and there are an accompanying multitude of ways to approach this sort of project. Ultimately, the approach that makes the most sense for your business takes into account: the specific types of work that your company needs and expects to have the industry(s) that your organization is situated in whether there are multiple labor markets/geographies in which your business either has worked, expects/hopes to have work, or talent in whether there are any unique characteristics that may impact your business in a way that’s different than the general market (i.e., a government contractor who employs people with clearances, they are at a premium on the market). Some organizations will bake in premiums into their structure levels, and some will include those premiums on top of the compensation associated with the levels. When this occurs, there are typically multiple structures in place to account for the fact that it’s unlikely that the premiums apply to all employees. How to Design a Salary Structure for Your Business It’s difficult to provide specific guidance towards creating a structure without knowing what an organization already has in place, and what the objectives and goals are for the business. With that said, there is some general guidance that should be applicable regardless of the route that you decide to take. When building a salary structure based on the approach that best fits your organization’s level of expertise and needs, I recommend that you consider two primary factors including 1) the range spread of your salary and 2) geographic differentials. As you have probably pieced together from this article, making sure that your organization has a solid foundation in place before you build a salary structure is critical to your salary structure being successful. If you already have in-house expertise that has experience in creating a salary structure, you should be leveraging their knowledge throughout the lifecycle of the entire project. If you do not have the in-house expertise to create a salary structure, it is recommended that you reach out to an external resource and begin engaging with them as early as the planning phase of the project. A lot of the steps listed above are common sense, but just because they’re common sense doesn’t mean that they’re always executed effectively. If you take the time to slow down, consider all of the relevant factors that would influence your salary structure, and intentionally approach this project for your organization, you will be on a path towards saving your company a ton of money in the future! FAQ What is a salary structure and why does my business need one? A salary structure is a framework that organizes jobs into levels with defined pay ranges based on market data and internal equity. It helps businesses make consistent compensation decisions, reduces errors in employee pay, increases efficiency in salary administration, and supports career pathing by showing employees clear advancement opportunities. How do you create an effective salary structure? Creating an effective salary structure requires understanding your compensation philosophy, maintaining clear job descriptions that define roles and responsibilities, conducting compensation benchmarking against market data, and considering factors like geographic differentials and range spreads. Organizations should also decide whether to use traditional structures with multiple narrow bands or broadband structures with fewer, wider ranges. What is the difference between salary grades and salary ranges? Salary grades are the levels or tiers within a salary structure that group similar jobs together based on their value to the organization. Salary ranges are the minimum and maximum pay amounts established for each grade. Together, they create a structured approach where jobs of similar scope and complexity are grouped into grades, each with its own pay range. How often should salary structures be updated? Most organizations review their salary structures annually to ensure they remain competitive with market rates. However, in volatile markets or highly competitive industries, more frequent reviews may be necessary. Organizations should also conduct deeper structural reviews every two years and adjust ranges when significant market shifts occur or when recruiting data reveals persistent challenges filling certain positions. Additional Resources SHRM, Creating Competitive and Equitable Pay Levels Harvard Business Review, Why Your Organization Should Use Salary Benchmarking SHRM, Keeping Pay Structures Current in a Volatile Market

Data-driven HR teams can leverage artificial intelligence to enhance strategic decision-making through five key applications: combining multiple data sources into unified reports, performing sentiment analysis on employee feedback, identifying retention risks through pattern recognition, analyzing skills gaps for workforce planning, and designing tailored benefits packages based on employee demographics and preferences. In recent years, Human Resources leaders have played an increasingly strategic role within their companies. CHROs are to be found in most C-Suites, and their insight helps to shape long-term strategy. This change is happening mostly because HR teams can provide invaluable insight into the current state of play. This insight is supported by the rich people data gathered on HRIS platforms, plus related systems like ERPs (Enterprise Resource Planning). As a result, companies that use people metrics enjoy consistently higher profits than other businesses. Now that Artificial Intelligence (AI) is on the rise, HR professionals have a chance to become even more impactful. In this blog, we’ll examine some strategies for using AI in the HR function. But first, let’s look at how HR data influences decisions. Data-driven decisions in the HR department Human Resources is one of the most data-rich departments in any business. HR teams have access to vital information, such as: Labor costs: Including salaries, benefit expenditure, and other associated costs Operational capabilities: Available skills within the current team (as well as any skills gaps) Resource allocation: Performance and scheduling data, which helps avoid over- and under-staffing Culture and DEI metrics: Measurements of the organization’s progress against inclusivity goals Engagement and retention metrics: The organization’s ability to get the most from staff and retain the most valuable people This information is hugely important at a leadership level, as it allows them to game out strategic decisions. For example, a business might want to expand into a new product line. Does the current team have the operational capabilities to support that product line? What are the costs of hiring more people to support this project? HR data provides answers to all of those questions. Data-driven decision-making also helps the HR team perform their responsibilities. Data insights can tell if your hiring strategy is working, if employees are engaging with professional development, and if your team structure is evenly balanced. The biggest challenge for HR teams is analyzing and acting on all of this data. In fact, many HR leaders now find themselves overwhelmed by the sheer volume of data—only 12% of companies conduct regular reviews of contingent workforce data. And that’s where AI can help. How Artificial Intelligence can help HR AI is still an emerging technology with dozens of new tools appearing each week. On top of that, you might find AI capabilities appearing in your existing software. The ideas below are based on the capabilities found in some of these AI tools, as well as general AI platforms like ChatGPT. It’s worth shopping around to find an AI tool that allows you to do what you need. If you need help, speak to an HRIS consultant for advice. (A word of caution: Do not input sensitive information such as employee records to an AI tool unless you have verified that the tool is secure. Speak to the software vendor or consult a HR IT expert.) 1. Combine multiple sources of HR data One of the strengths of AI is that it can work with data from lots of different sources, even if it’s in a different format. For example, say your HR team wants to perform a detailed analysis of employee engagement data. This data might include a range of different sources, such as: Productivity data exported from your HRIS Resource allocation data from your ERP An Excel spreadsheet that records sick leave and other unexplained absences. Written notes from an employee satisfaction focus group One of AI’s strongest features is its ability to combine different sources. With the right AI tool, you could potentially upload a number of different sources, then ask the AI to combine them into a single report. 2. Perform sentiment analysis Engagement analysis is one of HR’s most important responsibilities. Engagement data can reveal a lot about your current state. For example, poor engagement could mean that you have issues with organizational culture, Total Rewards, or employee wellbeing. AI can help collate engagement data into a single report, but it can also go one step further. “Sentiment analysis” looks at the language that employees use, categorizing phrases according to sentiment: Positive sentiment words: Empowered, encouraged, valued, appreciated. Negative sentiment words: Unclear, frustrating, difficult, disappointing AI is also capable of analyzing context, so it can tell the difference between “My boss makes me feel empowered” and “I wish my boss made me feel more empowered”. This allows for fast, accurate analysis of large quantities of data. With AI tools, you can perform sentiment analysis on a large body of engagement data, such as survey results, exit interview notes, or feedback forms. You can also ask the AI to analyze historical data, showing how engagement trends over time. 3. Identify retention risks AI is also great at identifying complex patterns within your HR data. This makes it an excellent tool for forecasting and pattern-based predictions. One common HR data pattern is the retention risk. An employee might be a retention risk if they meet any of the following criteria: Unusual number of sick days or leave requests Declining logged-in hours Negative feedback from managers, customers or colleagues Salary is below market average or less than their peers A HR professional might not spot any of these red flags by themselves, but an AI can be trained to look out for telltale patterns. When an employee is deemed to be a retention risk, the AI can suggest appropriate next steps to prevent turnover. 4. Analyze skills gaps Every team has certain available skillsets, and certain skills gaps. For example, you might have a Java developer but not a C++ developer, or Spanish speakers but no Mandarin speakers. Data-driven HR teams can gather skills information and create a picture of the current team. An AI tool can go one step further by: Collating public information about required skills for specific roles Creating a skills matrix for a specific project type Identifying gaps between available skills and skills needed Again, AI’s biggest advantage is size and speed. With the right AI tool, you can analyze enormous quantities of data and create detailed job profiles for every position. This gives you a clear, up-to-date picture of the skills your team requires. With this information, you can fine-tune your recruitment strategy and your professional development program to meet strategic requirements. 5. Design effective benefits offerings Creating a compelling benefits package is key to attracting and retaining top talent. However, with so many options available, it can be challenging for HR teams to determine which benefits will be most valuable to their employees. AI can help by analyzing employee data, such as demographic information and survey feedback, to identify employee preference trends. For example, if a significant portion of the workforce consists of young parents, AI may suggest offering more robust parental leave policies or childcare benefits. By leveraging AI insights, HR teams can design benefits packages tailored to their workforce's specific needs and preferences, ultimately leading to higher employee satisfaction and retention. The future of AI in HR As AI technology continues to advance, its potential applications in HR will only expand. From automating routine tasks to providing predictive insights, AI has the power to transform the way HR teams operate. However, it's important to remember that AI is not a replacement for human judgment and expertise. Rather, it is a tool that can help HR professionals make more informed, data-driven decisions and focus on strategic initiatives that drive business success. By embracing AI and leveraging its capabilities, HR teams can position themselves as key strategic partners within their organizations, driving innovation and contributing to overall business success. Need help with HRIS or other HR technology? Speak to a Helios HR consultant today! FAQ How Can AI Help HR Teams Analyze Employee Data More Effectively? AI excels at combining data from multiple sources—HRIS platforms, ERP systems, spreadsheets, and qualitative feedback—into unified reports. This capability allows HR teams to analyze complex datasets quickly, identifying patterns and trends that would be time-consuming or impossible to detect manually, leading to more informed strategic decisions about workforce planning and talent management. What Is Sentiment Analysis and How Does It Benefit HR? Sentiment analysis uses AI to categorize language in employee feedback as positive, negative, or neutral while understanding context. This enables HR teams to rapidly analyze large volumes of engagement data from surveys, exit interviews, and feedback forms, tracking sentiment trends over time to identify culture issues, engagement problems, or areas requiring immediate attention. Can AI Predict Which Employees Are at Risk of Leaving? AI identifies retention risks by analyzing patterns such as increased sick days, declining logged hours, negative feedback, and below-market compensation. By detecting these warning signals early, AI enables HR teams to proactively intervene with at-risk employees through targeted retention strategies, potentially preventing costly turnover before it occurs. What Role Does AI Play in Identifying Skills Gaps? AI analyzes job requirements, current employee skills data, and industry standards to create comprehensive skills matrices for specific projects or roles. This analysis reveals gaps between available capabilities and needed competencies, enabling HR teams to develop targeted recruitment strategies and professional development programs aligned with strategic business objectives and future workforce needs. Additional Resources SHRM, What HR Professionals Must Know About AI-Powered Analytics Harvard Business Review, Is HR the Most Analytics-Driven Function? SHRM, The Role of AI in HR Continues to Expand