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Leading Online Pharmacy Chain Reduces Delivery Tat by 18% Using A Unified Delivery Management Solution
技术
- 功能应用 - 车队管理系统 (FMS)
- 分析与建模 - 预测分析
- 功能应用 - 远程监控系统
适用行业
- 医疗保健和医院
- 零售
适用功能
- 物流运输
- 仓库和库存管理
用例
- 车队管理
- 预测性维护
- 实时定位系统 (RTLS)
服务
- 系统集成
- 软件设计与工程服务
挑战
To keep up with evolving end customer demands, our partner wanted to deliver orders using non-conventional and aggressive SLAs, such as executing fulfillment operations in 2 and 6 hours. But owing to the absence of a single robust application to manage on-demand, planned and 3PL-based deliveries and lack of automation capabilities, the online pharmacy store could not generate desired outcomes. Here's a detailed list of the key challenges they faced: Poor visibility of order movement and lack of end customer transparency, lack of capabilities to deliver on aggressive SLAs, surge in cases of deliveries being assigned to non-cost efficient fleet, and manual driver allocation and payment processes.
关于客户
Our customer is a leading online pharmacy store. It's India's third-largest retail pharmacy and wellness products chain in terms of revenue. Operating a large omnichannel and hyperlocal retail network of 24x7 stores, the brand focuses on providing their customers with an assortment of pharmaceutical, nutraceutical, lifestyle and wellness products. Its catalog boasts of over 90,000+ products, including curative and preventive medicines. It operates out of more than 265 stores sprawling across Maharashtra, Goa and Karnataka.
解决方案
Shipsy implemented an automation-powered single platform to manage on-demand deliveries and planned or next-day deliveries. The platform also manages both floating fleet and 3PL-powered fulfillment operations. It enables intelligent selection of delivery partners and ensures seamless driver management and KPI-based payouts. Shipsy's platform empowers the customer to leverage drivers to cater to delivery demands coming from multiple stores. Using serviceability APIs, the platform quickly determines whether a driver is present at a particular location or not. If present, is he immediately available for delivery or not? Based on this, the system sends out an ETA to the end customer. It also prioritizes drivers based on whether they are part of a floating fleet or are dedicated to a store. The latter gets priority to ensure faster and cost-efficient order fulfillment. Shipsy's platform now dynamically changes the ETA based on delivery progress made at each point in the delivery lifecycle. Fresh ETAs are pushed with every status update so that the end customers, instead of seeing a bucket of 2 or 6 hrs, view a tentative time stamp by which they can expect their orders.
运营影响
数量效益
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