The Move Toward Automated Compensation Applications

Limited Data Sources

Top performing employees cite competitive pay as one of their priorities when selecting a place to work. How do organizations reliably determine salary ranges and then keep them updated throughout the years so they can attract and retain top performing employees? Historically, some HR professionals have acquired a salary survey or two in order to cobble together the salary ranges they need. Others have hired a consultant to perform that service for them.

With advances in technology, organizations are quickly learning to rely on automated compensation applications. These applications easily solve the three main problems with the traditional process: limited data sources; lack of time and/or expertise; and in-actionable data.

Reliable data is the foundation of competitive and defensible pay practices. The typical small to medium enterprise uses only one or two salary surveys in order to determine salary ranges. Unfortunately, one or two salary surveys can’t provide statistically significant data. Ideally, an organization would use a minimum of five surveys, but this quickly becomes cost- and time-prohibitive. The resulting paradox can be difficult for one individual organization to resolve.

Fortunately, automated compensation applications can solve that problem because they take advantage of economies of scale. A good automated compensation application provider can purchase and aggregate data from multiple, reliable, salary surveys. Also, keep in mind that even the best surveys have unavoidable biases built into their processes. For that reason, be sure your automated compensation application uses a variety of surveys, rather than relying on just one source.

Lack of Time and/or Expertise

Time is a scarce resource everywhere. Most small to medium sized organizations don’t have an HR team that has the time to focus just on compensation. Participating in salary surveys (to offset survey costs) and calculating ranges based on the results can easily take one to two months of time. Managing that exercise annually can distract from other important initiatives. Automated compensation applications free up time associated with both the initial and the ongoing analysis because salary updates are applied annually. Yet, time isn’t the only bottleneck.

Compensation expertise is often limited on teams that are really strong in many other areas. Common errors such as looking at job titles instead of job duties can cause major miscalculations and internal inequity. For example, some organizations seem to make everyone a Vice President of one area or another. But if you look at their job functions, their day-to-day work is more aligned with entry- or mid-level positions. Not everyone has both the experience to know that titles can be misleading and the knowledge of how to adjust ranges appropriately. In this example, if the organization doesn’t have the compensation expertise to look beyond job titles, they will be vastly overpaying their employees.

Automated compensation applications dramatically reduce the time required to create and update unbiased ranges in part because of automation and in part because of experts within the application’s organization. The important thing is that your time is freed up and you know the job is being performed following compensation best practices.

In-Actionable Data

After you’ve created or updated your salary ranges, what can you do beyond hiring people at the right price? With traditional methods you can’t do much. The data provided is largely in-actionable for other important purposes. The move toward automated compensation applications is changing that.

Analytics is becoming increasingly important within human resources. Using traditional data to look for trends, trouble spots, and inequity is very difficult - especially for an HR professional not trained in analytics. Analytics give you a visual way to understand your organization’s compensation trends.

Another component of in-actionable data has to do with strategic decision making. An organization may have a lot of data but may not know what it all means or how to use it. In fairness, “in-actionable” data is a bit of a misnomer because data that is not actionable to one person may be actionable to an expert who knows how to interpret it. Some of the top automated compensation applications will give you access to consultants who can help you take the data, analyze it, and use it to transform your team and drive business results.

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