Sales compensation is vital to sales success and company growth. For decades, companies have gathered different tools to manage compensation. As companies have expanded, they often find difficulty scaling their manual processes to drive further growth.
Previously, sales performance management (SPM) has typically been categorized as solely focused on incentive compensation management (ICM) and sales compensation planning. It is quickly transforming due to a variety of software tools aimed at helping improve day-to-day execution of the sales process.
In the past, organizations had fewer products to sell and small numbers of sales reps to manage and compensate. As companies scaled with growth, legacy and home-grown ICM systems drove the need for automation tools to help reduce errors commonly associated with manual ICM processes. However, these systems were solely focused on compensation management and not necessarily on enabling sales planning or driving sales attainment.
The Challenges of SPM and ICM without Automation
In recent years, there has been enormous growth in the size and complexity of company product lines and sales channels. Unfortunately, home-grown and legacy compensation management systems are struggling to keep a business operating at digital speed. They also fail to address the complexities of companies’ sales organization, including overseeing sales territories, designing the right compensation plans, motivating the sales teams, and using data an analytics to spot misaligned quota targets.
In addition, current systems are unable to keep pace with demands, including huge data volumes and shifts in priorities. Without the right data, leaders and executives struggle to make good decisions. For organizations to become more efficient and agile at aligning policies and programs with results, there's a growing use of sales compensation to drive financial and sales performance.
Why AI/ML and Automation are Necessary for Growth
Building the right model to deliver flexibility and agility is critical. It’s important to understand company goals and design a pay and performance structure to reduce inconsistencies and friction points between finance and sales. Ultimately, your sales compensation plan should drive sales behaviors that help achieve company objectives and drive growth.
When thinking about SPM, it’s important to look at the overall strategy from planning to compensation, to attainment across the entire sales team. This allows leaders to evaluate methods to best optimize overall strategy. The real success is managing sales performance is enabling the sales team to spend the majority of their time selling.
With visibility into sales performance, leaders can make decisions dependent on market conditions to accelerate attainment of sales goals, and reps can see their earned commissions in real time.
Gathering Big Data with The Right Tools
With the growth in SaaS-based systems, data has emerged as a critical tool for designing, managing and updating compensation and reward strategies to reflect current business conditions. While current home-grown and legacy compensation management systems have access to lots of data, there is a lack of structure and meaning to gather timely and relevant insights to boost overall sales performance.
Artificial Intelligence / Machine Learning (AI/ML) capabilities help reveal insights and opportunities for optimizing sales performances. While AI/ML solutions have been linked to primarily customer service and sales situations, there are enormous opportunities for organizations to use data to analyze their sales performance with AI/ML algorithms to optimize territory planning, design the right incentive plans, and accelerate attainment and overall sales performance.
Discover additional benefits of AI/ML capabilities for your company in our two-part webinar series. In the series, we’ll discuss how organizations can use data-driven intelligence to address key enterprise challenges and how intelligent SPM solutions can overcome the challenges to produce the following business outcomes.