Indian Transport & Logistics
Logistics

LP Logiscience to add a Grade A warehouse in Delhi NCR

The warehouse is set to offer a single window, end-to-end solution to clients across Northern India

LP Logiscience to add a Grade A warehouse in Delhi NCR
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Varun Gada, Director, of LP Logiscience 

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LP Logiscience, the warehousing and contract logistics arm of the 100-year-old legacy brand, Liladhar Pasoo, recently announced the launch of their new, Grade A complaint, multi-user warehouse in the Delhi NCR region, between Noida and Ghaziabad.

With approximately 7500 pallet positions (1.3 lakh sq.ft.), the warehouse is a part of the company’s ambitious growth plan for the year. LP Logiscience was established a decade ago as the warehousing and transportation business arm of the Liladhar Pasoo group and today handles over 3 million sq. ft of storage space and a reach of 7000+distribution pin codes PAN India.

Since its inception, LP Logiscience has registered an impressive evolution, growing at the rate of 20% - 25% YoY. Now, it is ready for the next phase, with plans to set up state-of-the-art warehouses with aggressive tech adoption and greener operations to qualify for environmental certifications that will help the brand to enhance its global reach.

Speaking about the new launch, Varun Gada, Director, of LP Logiscience said, “This year, we have several new launches and geographical expansions in the pipeline and the Delhi NCR warehouse is the first among them. Against the backdrop of COVID, we have already grown 3X times with our multiclient facilities effectively supported with a strong tech-enabled operation. At the new warehouse, we will be leveraging our learnings and deep domain understanding of our clients, to create and provide A-grade compliant facilities to our clients to cater entire Northern part of India and the NCR region. We also aim to offer the latest and industry-leading compliance and safety features in the warehouse and provide an end-to-end solution with primary and secondary transportation support to clients, that will operate through a single-window solution. Over the next 5 years, we aim to further accelerate digital adoption, expand the geographical reach and build state-of-the-art warehousing facilities, keeping in mind a growth target of CAGR 30%.”

In line with these goals, the new warehouse is set to run on renewable energy sources like solar power for operations and rainwater harvesting, to help clients go green. CNG vehicle deployment for last-mile deliveries is also planned to help keep the transport environmentally conscious.

However, the USP of the warehouse is strategic tech adoption. The warehouse will deploy WMS to give customers a value-driven experience and help maintain the highest inventory accuracy, inventory visibility, and traceability. Apart from all the standard WMS features of expiry, FIFO, and location management, the company has also created its own customized solutions for its operations and a few industry-specific solutions.

Additionally, all their warehouses are cloud-connected, including handheld terminals which are used for all warehouse processes, and have a plethora of tech features, including ERP integration for clients, apps for sales teams showing the available inventory at the warehouse, a shipment tracking apps (TMS control tower), sales revenue monitoring with analytics and monthly division-wise sales target %, LP’s own EHS app for internal use by the operations team, raising safety concerns and suggestions, and a cloud repository of MSDS and COA for their specialty chemical customers. In addition to the above, their time to set up a new warehouse for a new client is just 12 hours in their WMS, which plays a vital role when business continuity is of significance.

With a strong business model supported by an IT backbone, the multiclient warehouse setup offers customization, and flexibility where clients can continue to enjoy superior services while only paying for the storage volume and throughput which has now become the natural extension of LP Logiscience’s business model.

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