The market
Few markets move as fast as Sri Lanka’s vehicle market. After a five-year pause, vehicle imports reopened in February 2025, and demand that had built up for years arrived all at once. Within months, the Central Bank set loan-to-value caps on vehicle loans and leasing, then tightened them. Fuel prices are revised every month under a cost-reflective formula. Landed prices move with import duties and the rupee. And interest in electric and hybrid models keeps growing.
For a distributor, every one of these forces changes what buyers can afford and when they decide to buy.
Planning leaned on past sales and experience. When demand rose or fell, the team could rarely say which force caused it, or how much. Was it the new leasing limit, the latest fuel revision, a rival’s launch, or the exchange rate? Pulling the numbers together by hand took days every cycle, and the answer still came down to judgement.
With imports to order months ahead, a wrong read is expensive: too much stock of the wrong models, or too little of the right ones.
Every day, Forevate reads the signals that shape this market and joins them with the distributor’s own sales history:
- Social conversation about brands, models and the cost of owning a vehicle
- Customer sentiment in reviews and comments
- Fuel prices, including each monthly revision
- Leasing and loan-to-value rules from the Central Bank and lenders
- Import policy, duties and the exchange rate
- Interest in electric and hybrid vehicles
- Rival launches and leasing offers
Forevate looks back over past sales and works out which signals moved demand, and by how much. A dip after a tighter loan-to-value rule, for example, can be separated from the effect of a fuel price rise in the same month, with an estimate of each one’s share.
Those same signals are then tracked every day. When the Central Bank, the fuel formula or a rival moves again, the team sees the likely effect on demand before it reaches the showroom.
Planning conversations now start from evidence. Instead of debating why last quarter moved, the team sees which signals drove it and by how much, and uses the same signals to estimate the months ahead. Import orders, pricing and launch timing are argued from the same picture.
- 3X faster future demand prediction. Estimates that took days of spreadsheet work are ready from a daily feed, built on the signals already being tracked.
- 70% less manual analysis. The team spends its time deciding, not collecting data.
- 25% more accurate demand estimates, built on the signals that actually moved past sales.
Forevate shows the likely effects; the distributor’s team decides.
