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Product Manager - hyperlocal SaaS | Locus logistics, an IKEA company
Overview
Overview
Product
Control center or control dashboard for businesses to manage their on-demand and scheduled deliveries based on the proprietary algorithm. Formerly TrackIQ and LOTR rider app (Locus on the road), these products are now rebranded as 'control tower' and driver companion app respectively. These work interdependently to give a dispatch or logistics manager real-time insight into deliveries, rider effectiveness and most importantly, meet customer SLAs.
Contribution / Responsibilities:
Scope of work is on-demand delivery management for B2B clients, including algorithm and dashboard customization for B2B users. This is anything a customer orders and expects within company’s promised time (30min to within the day). In addition to client requests, all PMs including myself were responsible for building products based on market interest and business relevance.
As the product and client customizations are proprietary, this page would instead be a showcase on an initiative and an attempt at customizing and pushing the algorithm to support quick commerce.
buy now, literally
buy now, literally
Quick commerce with aggressive delivery SLAs were becoming common differentiators and marketing strategies of various hyperlocal organizations in e-grocery, food delivery, medicine delivery, among many. Despite unfavourable unit economics, many big and small players were entering this arena, however reluctantly. An overwhelming number of existing clients wanted to see if they can improve their delivery times with the magic of our algorithm.
The almost super-hero algorithm already optimizes delivery time, time on road (shortest route), emissions and custom priorities like premium or express delivery as set by dashboard users. What it was lacking is the support for dark-store based model where instead of a main warehouse, there are many mini-warehouses or assignment centers. And a client would have to recalculate the promised delivery time because it can change from city to city and dark store to dark store.
the PLAN
the PLAN
How would you convince different stakeholders?
How would you convince:
business that this was a worthwhile project?
engineering to modify a working codebase?
clients to be willing to pilot?
What is the plan?
The business brief
The business brief
the math problem
the math problem
Based on location of dark store / restaurant & number of delivery personnel, the SLA that can be promised to customer is reverse calculated mathematically. Serviceable area is also defined using this data + historical traffic data
Dark store or restaurant is created as anchor point in the algorithm. All trips start and end there.
Rider data like location, delay, idle time, time on road, waiting time, phone battery level, etc are recorded in real time as parameters to assign rider for the next order
Customizations are done to the solution as per client and industry. For eg: for food delivery, food preparation time is also considered. For a different client, fairness or equal distribution of work is also considered and so on
Solution is released for a pilot and continuously fine-tuned based on product metrics like least carbon emission, rider assignment, SLA, time on road, etc
The Outcomes
The Outcomes
After initial resistance, two clients agreed to test out the modified algorithm in two locations each. We were hoping to see reduced delivery times before the clients outright promise an improved delivery time, and of course, no major issues.
As a direct result, we were able to see improved delivery times for a Canadian client from 90 minutes to 45 minutes. The modification also optimized rider assignment for a food delivery client by factoring in the food preparation time, which improved the rider assignment from 47% to 92%.
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