Compensation Data Then and Now: A 20-Year Perspective


I’ve been very fortunate to serve for nearly 20 years helping top 100 Fortune companies transform their sales operations. And in that time, I’ve seen several evolutions take place throughout the industry – everything from changing buying habits to tighter budgets to technological advancements. But one of the major changes that has revolutionized the way sales processes are done drills down to a sales industry staple – compensation.

When I first entered this business nearly two decades ago, the way compensation was configured, and even the purpose it served, was vastly different than how it’s used today. Primarily, compensation was seen as a payment structure to incentivize sales reps for meeting and/or exceeding the company’s sales goals. In other words, the more customers, revenue and leads a sales rep delivered, the more money he or she would make in compensation for that work.

Don’t get me wrong. Compensation is certainly still used to incentivize the salesforce. However, truly successful sales organizations have learned to utilize new data management technologies to tap into compensation’s true potential to drive process outcomes.

It’s no secret that sales creates a lot of data – a sometimes overwhelming amount of data – that when properly analyzed can uncover profitable insights for organizations. The challenge for companies has always been, “how do you collect that data to make it valuable and actionable?”.

Sales leaders have learned that the answer to mining that data is not through customer relationship management (CRM) systems (the age-old standard), but via compensation systems. It only makes sense that data that is linked to money would be the most accurate because it is the most scrutinized and the most regulated.

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Organizations can tap into compensation-related data to drive better results in terms of productivity, profits, customer satisfaction and other company-wide goals. For example, sales reps can gain instant visibility into their performance by analyzing the wealth of information that data can afford them, such as if they are meeting with enough customers each week, what customer pain-points they might need to troubleshoot, which territories need more attention, etc. Armed with this type of information, reps will know exactly how many more calls and meetings they need to schedule each day in order to meet their company’s all-important quarterly metrics.

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The first step in turning all that rich data into actionable insights is to harness it – but this can be a burdensome process for non-technical reps who don’t have the same analytical experience as trained data scientists. This is why today’s sales teams are using automated and efficient data management processes, such as no-code extract, transform and load (ETL) tools. These tools enable sales to quickly validate and pre-process data by giving reps the power to make changes or additions to the data management process themselves without needing to involve expert developers or the IT team.

No-code application capabilities give sales reps all the information they need to sell more successfully by tracking their progress with real-time visibility into their daily activities – e.g., they have more direction on which customers to visit and how often, and in turn, they can inform management about individual customer needs. Additionally, sales reps are more successful in hitting their goals because the data consolidation process is automated, freeing up resources to focus on what matters most – selling.

The industry will undoubtedly continue to evolve as more technology and sales strategies tied to those technologies emerge. The one thing that will remain constant is compensation, and the data tied to that compensation. Organizations that learn to harness the wealth of information compensation data can afford them are the ones that will be profitable for years to come.



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