Commission is one of the most widely used tools to motivate salespeople, but also one of the most flawed. In practice, studies and industry experience show that up to eight out of ten companies make mistakes in their commission calculations. This means lost time, declining confidence and ultimately lower performance.
Why is this happening? And why is it so hard to do right?
One of the biggest reasons is the use of manual processes, typically in Excel. Although Excel is a powerful tool, it is not built to handle dynamic incentive models. When data has to be entered manually, when formulas become more complex, and when several versions circulate between managers and the finance department, the risk of errors increases significantly. A single typo can lead to incorrect payouts, and even small discrepancies can create big conflicts.
Another problem is lack of transparency. When sellers can't see how their commission is calculated in real time, they often start keeping their own spreadsheets. It leads to duplication and distrust of management. Many sales managers find that they spend days reconciling numbers and explaining payouts rather than focusing on driving growth.
Errors in commission are not just an administrative problem, but a psychological one. A seller who experiences errors in his payout loses motivation. Incentive models are supposed to act as a driving force, but if the system is not perceived fairly, the effect can quickly turn to frustration.
The solution is automation and clear structure. When commissions are calculated automatically based on CRM data, the risk of errors and delays is eliminated. Employees can track their earnings in real time, and management can rest assured that the numbers are accurate. It frees up time, increases trust and creates the transparency that is essential in modern sales organizations.
In the end, proper commission isn't just about paying the right amount. It's about creating a system that is experienced equitable, motivating and scalable. The fact that eight out of ten companies still make mistakes shows how difficult it is to do manuallyand how great the potential is in thinking new.