CASE STUDY

PANDA COMPANY Saudi Arabian giant uses CLASS warehouse simulation to meet its business and territory expansion plans

 At a glance CLASS helped: Validate warehouse design Ensure maximum operational efficiency De-risk capital investment Provide accurate scenario outcomes Introduction The Panda Challenge: Optimise allocation of MHE and labour resources Panda is the largest supermarket chain Existing DC operating in with branches Panda wanted to identify the optimal Deliver rapid solutions to distribution in United Arab Emirates and Egypt as approach for current and forecasted challenges well. Today the company has over 25,000 throughput and resource configurations Identify ‘hidden’ potential issues employees serving 110m customers annually at its existing site in Riyadh. The company in over 440 stores. also wanted to assess how the DC could handle increased volume during peak Experiencing rapid store network growth the seasons such as Ramadan given the company needed to build a new Distribution constraints of available warehouse space Centre (DC) in , and improve and Material Handling Equipment (MHE). productivity at its existing 90,000 sq m site A key focus was to identify bottlenecks at Riyadh. and areas for improvement. Saleh Jamal, Senior Project Manager at New DC Panda, said: “Our vision is to continue to be the region’s number one mass market In addition, Panda needed to be confident retailer. Optimising our distribution and supply that the final design of its new site in capabilities is critical to helping us deliver Jeddah would perform as expected. Jamal this objective.” commented: “It was imperative that we could test our blueprint for the DC in a “We chose to use CLASS software because simulated environment before committing of Cirrus’s combined warehouse modelling to any investment. We needed to ensure and distribution network expertise. It is a that predictions of labour requirements, valuable tool to thoroughly test and measure equipment and throughput capacity were warehouse designs and resource allocation accurate and whether there were any before making significant capital investments.” unforeseen issues.” Twitter: @cirruslogistics Linkedin: linkedin.com/company/cirrus-logistics

Project Approach & Results:

Historically Panda had made operational putaway direct to racking; resulting in an decisions based on expert judgement and improvement of more than 50% in the spreadsheets analysis. Moving forward the number of putaway pallets over the same company wanted to use sophisticated and time period. Manpower and MHE resources accurate simulation software to help evaluate were reallocated within the operation projects, initiatives and expansion plans. without any cost implications.

Cirrus consultants provided full training A ‘What-if’ analysis was then conducted to on CLASS to members of Panda’s supply simulate the impact of a 70% increase in chain team at the company’s HQ in volume during Ramadan. A key test finding Jeddah. During the initial training Cirrus was that picking was faster than dispatch helped Panda to create a ‘Base Model’ leading to overflowing outbound areas. representing Riyadh’s current warehouse operations. Actual data was input including In addition, CLASS was utilised to model employee head count, active MHEs, and the planned new DC in Jeddah. Multiple throughput statistics. Panda ran several scenarios were tested before committing operational scenarios to identify the DC’s to specific configurations. Different slotting, ‘stress’ points. picking and staffing strategies were explored so that the finished design and Tests highlighted that inbound was a major implementation would be fit for purpose bottleneck with an overflow of pallets in the from day one. receiving area. High levels of congestion were reducing picking rates while MHEs Jamal added: “One of the most valuable were regularly reaching 100% utilisation benefits of CLASS is that the software leaving no contingency for downtime. supports faster responses and delivers One of the most effective and innovative valuable insight and optimum solutions to simulation outcomes, was to eliminate our distribution and supply challenges. It’s a inbound ‘drop zones’ and introduce powerful and cost-effective simulation tool.”

“We are impressed by the rapid design and modelling capability of CLASS. With a model that has 97% accuracy representing actual complex operations we can be confident about the changes that we are going to make.” SALEH JAMAL Senior Project Manager

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