Every morning, millions of delivery partners across India and beyond log in to their apps, hoping for a good earnings day. Yet, the number they see at the end of their shift is rarely a product of chance. It is the result of algorithms — silent systems balancing dozens of variables in real time. Understanding these dynamics is not just about technology; it’s about fairness, motivation, and sustainability in the on-demand economy.
The Truth About Delivery Algorithms
Delivery platforms depend on algorithms designed to keep the marketplace balanced. If partners lose motivation, the entire system collapses. Each pricing model attempts to reconcile three competing goals: cost efficiency for the platform, fair compensation for partners, and affordable prices for customers. The dilemma is structural. Platforms cannot raise payouts indefinitely; higher delivery costs discourage orders, which in turn reduce work for partners. Yet, if pay feels unfair, partners stop logging in, triggering delays and refunds. Sustainability lies in constant calibration.
How Pay Is Calculated
Take a typical `52 order. The payout usually combines a base fare (often `15-25) with a distance component. When demand exceeds supply, surge multipliers can significantly raise earnings — sometimes up to twice the usual amount during peak hours. Partners carrying multiple orders earn smaller increments for each additional delivery, reflecting reduced travel and waiting time. Behind the scenes, dozens of inputs — traffic, weather, restaurant readiness, location density, and even recent performance — shape the final amount. The number on the app represents the outcome of complex micro-decisions. Weekly bonuses are similarly calculated with precision. Too easy, and the company overspends; too hard, and partners lose interest.
How Commerce Changed the Game
The rise of 10-minute delivery services has redefined the model. Instead of logging in at will, partners now book fixed slots, and earnings depend on how many orders arrive within that time. This improves efficiency for companies but limits flexibility for partners — if demand drops during a booked shift, they cannot easily switch elsewhere.
The trade-off is sharper than ever — greater efficiency for platforms, less autonomy for workers. Different delivery segments optimise for different factors. Food delivery rewards peak-hour activity and high acceptance rates. Quick commerce prizes speed and volume within micro zones. E-commerce logistics offer steadier, block-based pay with lower volatility.
What Shapes Earnings in Practice
Earnings depend on more than what appears on-screen. Peak hours can yield multiple times the midday rate, and ending near busy restaurants improves the odds of quickly getting another order. Vehicle mileage also directly impacts take-home pay — a bike running 80 km per litre leaves far more profit than one at 40. Ratings, too, can influence priority in order assignment, though most platforms factor in proximity, availability, and performance. Despite these calibrations, luck still plays a role — a slow restaurant, a sudden traffic jam, or bad weather can all tilt outcomes.
Fairness and Transparency
For many partners, the deeper frustration lies not in pay levels but in opacity. Sudden shifts in rate cards or unexplained changes in incentives erode trust. Algorithms might be mathematically fair, but fairness is also emotional. A partner waiting 20 minutes at a restaurant feels unseen when that time goes unpaid. Compensating waiting time acknowledges hidden labour. Fuel indexing would ensure distance pay keeps pace with fluctuating petrol prices. Extra incentives during traffic—hours would reflect the added burden. These reforms aren’t radical — they simply reinforce the message that fairness matters as much as efficiency.
The Way Forward
Understanding AI-driven pricing isn’t about gaming the system; it’s about informed participation. Partners benefit when they understand what drives fluctuations and can plan accordingly. Platforms benefit when partners trust the logic behind the numbers. Transparency is the key. Companies could share summaries of payout logic, explain major policy changes and provide periodic insights into how edge cases are handled. Even if every order cannot be broken down due to complexity, regular communication builds confidence that the system is not working against workers. Ultimately, these algorithms succeed only when they balance the interests of all three stakeholders — customers, companies, and delivery partners. Fair, transparent pricing is the bridge between them. The more partners trust the system, the more likely they are to stay engaged, deliver well, and keep the engine of the on-demand economy running smoothly for everyone.
The Writer is a tech expert & researching on fairness in pricing
