Prismberry’s Solution for Seamless Order Processing in Warehouse Management

about Case study

Utilizing a decade-old system, especially in warehouse management, can lead to delays and inefficient operations. From three different steps for picking, segregation, and packaging to a lack of effective picklists, sales-returns segregation, and order prioritization obstructed the workflow

However, Prismberry acted as a strategic partner to help the company streamline the processes, digitizing the picking, and optimizing the logistics. Let’s understand how Prismberry’s solutions revolutionized the old system, making it more efficient and easy to process.

4.6
4.6/5
$20 Million

Annual Savings Delivered

100+

Solutions Delivered

50+

Satisfied Customers

60%

Increase in Energy Efficiency

Challenges

Many operational challenges impede efficiency and customer satisfaction. Let’s look at the following major issues due to the outdated Warehouse Management System (WMS).

System Load Failure

As the load increased, the system failed, which affected the smooth functioning.

Manpower and Time Overhead

The workflow was burdened with high manpower consumption and time overheads that affected overall productivity.

Inefficient Shelf Visits

Pickers were forced to revisit the same shelf several times for one pick list, which resulted in a waste of time and energy.

Configuration Limitations

The lack of a picklist configuration made it impossible for trolleys to handle OTC and Medicinal products at the same time.

Shipment Acceptance Dilemma

The system’s binary approach to approving or rejecting the whole shipment affected the operations in terms of financial losses and customer relationships

Order Processing Inconsistency

The absence of order prioritization led to processing orders only according to the date when they were placed, which caused operational inconsistencies.

Paper Cost and Wastage

Manual processes resulted in additional paper costs, wastage, and pickers’ time.

Order Misclassification

Customers placed a combined order containing OTC and Medicine, but processing considered them as separate orders, and this confusion persisted till the end.

The challenge

Confidentіal Inc. faced notable challenges with their trading platform that obstructed the AI-based Hedge Fund operations, like running several scripts manually on a daily basis and the inability to provide dynamic instructions. Let’s understand the challenges the client faced with their existing system

Unscalable On-Premise Infrastructure

The platform was hosted on AWS and on-premise infrastructure. The on-premise systems lacked scalability and resilience. Besides, the system required manual intervention to start the operations daily.

Static Instructions

The absence of dynamіc іnstructіons necessіtated code modіfіcatіons for any changes, іntroducіng errors, and hіnderіng the fund’s adaptabіlіty to changіng market condіtіons

Time-Intensive Machine Learning Algorithms

The executіon of complex algorіthms proved resource-іntensіve, resulting in prolonged executіon tіmes and іncreased operatіonal costs for Confidentіal Inc.’s Hedge Fund.

Manual Trading Operations

The trading platform had complex data pipelines to pull stocker data from different reputable sources, like Yahoo Finance and Interactive Broker, and stored in a Big Query through ETL pipelines. Frequent manual scrіpt executіons on a daily basis resulted in operatіonal іneffіcіencіes, 2-3 hours to set up a system for trading operations, and required human intervention, affecting the overall relіabіlіty of tradіng operatіons

Prismberry Solution

Here’s how Prismberry tackled each challenge with innovative strategies

01. Merged Picking and Segregation Processes

Introduced tray along with trolley carts that integrated picking and segregation.

03. Segregation and Packing Consolidation

Streamlined the process further by merging segregation and packing screens.

05. Shelf-Based Picking Optimization

The Sort by ShelfNo. feature was introduced, which allowed the pickers to collect all goods from one shelf in an economical manner.

07. Configurable Picklists

Applied picklist configuration so that trolleys could carry out OTC and Medicinal products at the same time

02. Return Segregation Implementation

Implemented return segregation, with packaging details and quantities captured in returns processing for better efficiency

04. Order Prioritization with Cutoff Date

Introduced CutoffDate for orders feature, where picking was done by placement date to ensure consistent processing

06. Digitalized Picking with HHD

HHD digitized picking, replacing manual processes, leading to greater accuracy

08. OTC and Medicine Order Merging

Merged OTC and Medicine orders under a parent order that simplified the post-picking process of streamlined order management.

01. Merged Picking and Segregation Processes

Introduced tray along with trolley carts that integrated picking and segregation.

02. Return Segregation Implementation

Implemented return segregation, with packaging details and quantities captured in returns processing for better efficiency

03. Segregation and Packing Consolidation

Streamlined the process further by merging segregation and packing screens.

04. Order Prioritization with Cutoff Date

Introduced CutoffDate for orders feature, where picking was done by placement date to ensure consistent processing

05. Shelf-Based Picking Optimization

The Sort by ShelfNo. feature was introduced, which allowed the pickers to collect all goods from one shelf in an economical manner.

06. Digitalized Picking with HHD

HHD digitized picking, replacing manual processes, leading to greater accuracy

07. Configurable Picklists

Applied picklist configuration so that trolleys could carry out OTC and Medicinal products at the same time

08. OTC and Medicine Order Merging

Merged OTC and Medicine orders under a parent order that simplified the post-picking process of streamlined order management.

Results

The effectiveness of the solutions offered by Prismberry improved warehouse management, which can be regarded as a drastic change in terms of efficiency and cost savings.

Enhanced Order Handling

The system can smoothly process 35,000-50,00 orders a day to reach and cater to around 1.5 crore orders in the year 2023

1.5cr

orders in the year 2023

Increased Processing Capacity

The system can process over 1 lakh orders per day, a significant improvement in processing capacity

1lakh

orders per day

Streamlined Workflow

Operational steps were reduced from 3 to 2, reducing the workforce requirement by two-thirds and total processing time by three-fifths

2/3rd

manpower reduced

Efficient Picker Utilization

Significant saving of pickers’ time with improved picking operations

Savings

of picker’s time

Versatile Trolley Use

Trolleys can now process orders of any type, resulting in high flexibility and maximized resource utilization

High Flexibility

and maximized resource utilization

Return Handling Optimization

The precise documentation of the quantities to level returns allowed to retrieve around 50-60 lakhs INR every month.

50-60lakhs

cost optimization

Operational Speed Improvement

The solution led to a 1.2% gain in speed and reduced the breaches from 0.8% to 0.1%.

1.2%

enhanced the operational speed

Optimized Capacity Usage

The earlier capacity, which was 1.25x, was reduced to an effective 1.1x

1.1x

reduced capacity

Cost-Efficient Paper Handling

The cost optimization of paper was ensured by up to 60%, resulting in saved picker time and savings of Rs. 1 per invoice.

60%

cost optimization

Significant Monthly Savings

The economic benefits of around Rs.25 lakhs of monthly savings were ensured, and a 30% reduction in additional shipments compared to the previous scenario.

25lakhs

monthly savings

The technology that we use to support Paysafe

jQuery, JavaScript, HTML CSS, and AJAX-enabled dynamic user ID
JSON and XML forms
PHP and CodeIgniter
Microsoft SQL Server

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