ULTRON: Managing Warehouse Space and Item Obsolescence MING401

ULTRON: Managing Warehouse Space and Item Obsolescence

Author: Debjit Roy, Mayank Pratap, Premm H. Raj

Pub. Date: 2020

Product: Sage Business Cases

DOI: https://doi.org/10.4135/9781529704471

Disciplines: Business & Management, Operations Management, Logistics, Operations Strategy

Access Date: June 1, 2023

Publishing Company: Indian Institute of Management, Ahmedabad

City: London

Online ISBN: 9781529704471

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Abstract

The case focuses on the ULTRONs logistics problems in its warehouse in 2016. The warehouse con- tained a growing portfolio of products that were older than 180 days. The main reason for the dated inventory was the absence of a warehouse management system, which resulted in a failure to imple- ment First-in First-out (FIFO) sequence of the products in the warehouse. Given the substantial invest- ment costs associated with installing a new warehouse management system, warehouse manager Ahuja must evaluate other alternatives for implementing FIFO at his manually operated warehouse.

Case

It was October 2016. Despite it being the peak festival season in India when sales were highest for ULTRON (the leading white goods manufacturer in India), Niraj Kumar, the logistics head of ULTRON, and Ravindra Ahuja, the warehouse manager for the logistics division of ULTRON (in Gujarat, India) were not at ease. With an inventory of products older than 180 days and a growing product portfolio, managing a warehouse man- ually without any warehouse management software had critical issues such as, not being able to maintain First-in First-out (FIFO) for inventory and low picking efficiency (Since white goods are subject to risk of ob- solescence, FIFO method is used for inventory valuation). The fairly large unit size of each stock keeping unit (SKU) made it nontrivial to manage the warehouse without warehouse management software. Ahuja was evaluating various options possible to achieve FIFO at no additional software expenses.

ULTRON

ULTRON was a large Indian conglomerate operating in various business verticals, one of which was con- sumer electronics division comprising of air-conditioners, washing machines, refrigerators, LCD/LED televi- sions, microwave ovens and small home appliances. The company operated 16 manufacturing facilities and 62 warehouse facilities across India. Apart from its own consumer electronics division, the company also acted as a distributor for several international consumer electronics brands in India. ULTRONs revenue in 201314 was about USD 4.92 billion and the profit was about USD 11.2 million.

Warehouse Overview

In Gujarat in India, the company had four warehouses, the largest of which was located in Gandhinagar, hav- ing capacity of one lakh square feet (9,290 square metres). This warehouse was originally a manufacturing facility which was later relocated. The layout of the warehouse is provided in Exhibit 1. All warehouses lo- cated across the country were similarly operated. Thus, we will be using the Gandhinagar warehouse as an example to illustrate the processes within a warehouse.

All warehouses operated by ULTRON were multi-brand facilities, which housed products from more than one brand within the same location. Apart from brands owned by ULTRON, multi-branded products from partner companies were also warehoused and distributed from the same facility.

Overall, there were more than 500 SKUs grouped under 12 different product categories from six brands. A sample SKU product list indicating the average statistics per month in the warehouse and corresponding SKU dimensions are shown in Exhibit 2a and 2b. The product composition in the warehouse is shown in Exhibit 3.

Each warehouse was divided into several areas to store the products of different brands. The area allocated for a brand was further divided into smaller areas for different product categories. Products within a category were stacked one over each other based on stacking norms belonging to the product. These norms were in- dicated on the packaging material for each product.

The dimensions of the warehouse are illustrated in Exhibit 1. The vertical usable space was 24 feet, of which only 1012 feet were currently used due to the limitation of stacking norms. Vertical expansion in the current setup was not an option. The floor utilization of the warehouse peaked at 90100% during the festival season from September to November.

The warehouse operated for one shift every day, starting at 9:30 am and ending at 6:30 pm. The order re- quests from retailers for each day were processed by the supervisors from morning 9:30 am based on order invoice ID and location of dispatch. Dispatch of goods usually started at 12 pm noon every day. Vehicles owned by the warehouse facility were used for transportation to retailers. The list of dispatch vehicles avail- able at the warehouse is given in Exhibit 4. An internal audit was performed every month to track the products within the warehouse.

The warehouse consisted of a mix of skilled and unskilled labour for its daily operations. The employee details of this warehouse facility are given in Exhibit 5. The employees were trained to perform all operations with- in the warehouse such as loading, unloading, put-away and picking. This cross functional training increased labour productivity.

Warehouse Processes

Docking Bays

There were four docking bays in the warehouse as seen in Exhibit 1. Based on availability, each docking sta- tion was used for either inbound or outbound operations. Apart from these, there was a spare docking bay located at the rear of the warehouse which was rarely used. For consolidation of order items, there was sig- nificant amount of space located near the docking stations for loading and unloading products.

Inbound

Products manufactured in ULTRONs factory would arrive at the warehouse during any time of the day. Every inbound product would be scanned into the SAP based inventory management system using the serial (SR) number. No physical inspection was done after entry into the warehouse, before updating into the inventory management system. Based on initial security checks for relevant purchase order and product quantity, the supervisors would provide permission to unload the products and assign labour for the same.

Put-Away

Once the goods were unloaded, the supervisors would assign labourers to put-away the products in their re- spective locations within the warehouse. Manually operated hydraulic fork lifting pallet trolleys were used to move the goods to their destinations. 14 such trolleys were available within the warehouse facility. A sample image of this trolley is shown in Exhibit 6.

Picking

A pick-list containing the invoice ID, date of invoice and model number would be generated by the supervisors and handed over to the pickers. As there was no warehouse management system in place, the picking was not done using a serial number. Supervisors knew the exact location of each model inside the warehouse and would direct the pickers to these locations.

Dual Cycles

To reduce the transit time between successive picks or put-aways, the warehouse followed dual cycles. Unlike traditional single cycle put-away or picking operations which were done sequentially causing significant dead- heading time, dual cycles performed both put-away and picking in one cycle. That is, an employee performing put-away of inbound goods was also provided with a pick-list for picking, using which the employee could pick an item on his way back to the consolidation area near the docking bays. This is illustrated in Exhibit 7. On an average it took around five minutes for an employee to start from the consolidation area for put-away or picking and return to the consolidation area. The number of products which could be transferred in a single cycle varied across categories and is listed in Exhibit 8. In many cases, a pallet was not used for transporting the goods in a trolley due to the bulky nature of these goods. This could have led to damages to the protective packaging while in transit within the warehouse.

Returns

Returns constituted about 12% of the entire shipments from the warehouse. This could have been due to a variety of reasons such as product malfunction or product obsolescence. In such cases, the service depart- ment within the warehouse checked for potential defects and corrected them in house and sold the products as seconds at discounted rates

Problems Faced

The problems faced by the warehouse manager are listed below:

1. Being a large appliance warehouse, movement of goods within the warehouse was slow. The aver- age per unit SKU value was very high, thus any damage to the goods while moving them could prove to be expensive.


2. FIFO maintenance Due to the lack of a warehouse management system, it was not possible to track the manufacturing aging of the products in the warehouse. Additionally, moisture within the ware- house could damage the packaging of the goods if they were left unattended for a long Repack- aging of the goods would cost the warehouse an additional USD 7.5 per box.


3. In the current setup, the location of a product could vary with time and usage. Products were stored based on availability of space within the warehouse. This could lead to low picking efficiency due to the lack of a warehouse management system to track the exact location of any product within the warehouse. The large variety of SKUs and small quantities also added to the low picking efficiency.

Options Available

To maintain FIFO and improve the picking efficiency, Ahuja was considering the following options.

1. Mezzanine floor : Building a mezzanine floor would provide him sufficient space to demark the new goods from the old ones. This space would also enable them to have a double-deep storage with aisles on both the sides, which would provide the labourers, access to every product stacked at a particular location The setting up and the removal of the mezzanine floor was easy and less time consuming. The capital investment required for setting up a mezzanine floor was USD 2040 per square metre.

2. Colour coding : A colour coding scheme could be used to identify the new and the old inventories in the The colours could be used to identify the inventories based on the month of arrival of the consignment. This could help in maintaining the FIFO as it would be easier to identify the older inventories in the stack. At the same time, it could also create complexity as there were more than 500 SKUs across six brands. The cost of 100 colour coded stickers was about USD 1


3. Pallet flow rack system : A Pallet Flow Rack system as shown in the Exhibit 9 is an efficient solution to handle the FIFO problem in a warehouse. In this system the racks have an inclined structure to enable the flow of the pallet under gravity. The loading can be done from the back of the racks and the unloading is done from the front side. Once a pallet is unloaded from the front the next pallet in the rack comes to the unloading position. The number of boxes which can be stored per product us- ing one standard EURO pallet of 1200 mm by 800 mm dimension is shown in Exhibit 2b. The capital investment required for setting up a pallet flow rack system was USD 80100 per square metre, for one level of pallet rack space.


4. Dedicated fast pick area : Another option was to have a dedicated fast pick area for the critical prod- uct categories where the frequency of picking and put away were high. The older inventories could be stacked in the dedicated fast pick area, whereas the new inventories could be stacked at the back of the warehouse and be shifted to the fast pick area as and when During the peak season, the shifting of inventories from the storage to the fast pick area could be a problem as the labour utilization during the season is high. No capital investment was required for this option.

The options stated above could be used to maintain the FIFO in the warehouse but to improve the picking efficiency it was very important that the labourers be able to identify which part of the warehouse they had to go to to retrieve the inventory and how they could reach the location in the shortest possible time. A racking system with a layout which could identify exactly where the product is located in the warehouse would be useful. To reduce the time taken to access the various parts of the warehouse, an efficient aisle configuration such as cross-aisle or angled aisle could be used to optimize the pick path. This kind of a configuration re- quired software support which could prove to be very costly.

Conclusion

The speed of current operations in the warehouse was fairly high due to the absence of additional processes associated with a warehouse management system. Wondering if these were the only possible options to achieve FIFO at no additional software investment costs, Ahuja was thinking about the course of action to be taken before meeting his supervisors the next morning.

https://doi.org/10.4135/9781529704471