Identified an exhaustive list of various factors affecting the revenue of the products, such as previous-year business, expected growth, shifts in regional dynamics, the launch of new campaigns, etc.
Forecasted the sales for the year using the identified factors along with factoring in the new campaign planned for the year, which had different conditions.
The forecasted sales were distributed at the region level and based on seasonality to have the expected sales numbers for the year at an associate level for campaign and non-campaign periods.
The varying unit prices for the various products were then applied to these sales units to estimate the revenue forecast for the next fiscal.
This forecast was rolled up at the associate level to estimate the yearly targets for each field team and sales heads.
Established a yearly revenue target 10% higher than the previous year, which was realistic and achievable for the field team.
The monthly distribution of targets helped the field team to constantly monitor and measure their progress and take corrective action wherever needed.
The targets helped the team push additional units for the products through the new campaign released in the year, making the campaign a success and lifting the overall sales.
