Introduction :

This module will provide system generated MBQ , Purchase budget wise purchase planning or complete Open to buy analysis.

OTB Analysis :

Open-to-Buy (OTB) is a crucial retail planning tool that helps merchants manage their inventory effectively and avoid overstock or understock situations. To create a comprehensive OTB provision, a system should consider multiple inputs and parameters:

1. User-Provided Purchase Budget:

   • The user, often a merchandiser or buyer, provides a budget that represents the total amount available for purchasing merchandise during a specific period, such as a season or a fiscal year.

2. System-Generated MBQ Min and Max Levels:

   • The system calculates the Minimum Base Quantity (MBQ) and Maximum Base Quantity (MBQ) for each product based on historical sales data, demand forecasting, and other relevant factors.

   • MBQ represents the minimum quantity of a product that should be kept in stock to meet customer demand.

   • MBQ Max represents the maximum quantity that should be kept in stock to avoid overstocking.

3. Purchase Orders (PO):

   • The system tracks existing Purchase Orders (PO) that are in the pipeline but not yet received.

4. Pending Orders:

   • Pending orders are customer orders that have been placed but not yet fulfilled.

5. Stock in Hand:

   • The system checks the current stock levels for each product in inventory.

   • This is essential to determine if there are overstock or understock situations that need to be addressed.

With these inputs, the system can guide the complete OTB provision by following these steps:

a. Budget Allocation:

• The system starts by deducting the value of pending orders and existing Purchase Orders from the user-provided purchase budget. This provides a more accurate available budget.

b. Inventory Assessment:

• The system assesses the stock in hand for each product and compares it to the calculated MBQ and MBQ Max levels.

• If stock levels are below the MBQ, the system suggests reordering to reach the MBQ.

• If stock levels are approaching or exceeding the MBQ Max, the system advises against additional purchases.

c. Budget Allocation for Replenishment:

• Based on the inventory assessment, the system allocates a portion of the available budget for replenishing products below the MBQ.

d. Budget Allocation for New Purchases:

• The remaining budget can be allocated to new purchases of products based on factors like seasonality, trends, and supplier terms.

Open

Purchase Analysis : 

Considering all the purchase related parameters along the purchase budget this module provides clarity over purchase planning along with complete Pending PO report.

Open

Comparative analysis :

• Budget Vs Actual

• Purchase Vs Sale

Go to--> Merchandise --> Purchase Analysis

Vendor Analysis :

This module designed for retail management can provide detailed vendor-related analysis, including vendor-wise Net Sales, Sell-Through Percentage, and, importantly, Vendor-wise Returns. Here's a breakdown of how such an analysis can be conducted:

1. Vendor-wise Net Sales:

   • The system collects transaction data and categorizes sales by vendors.

   • It calculates the total sales revenue generated from products associated with each vendor during a specific period, such as a month, quarter, or year.

   • Vendor-wise Net Sales provide insights into which vendors are contributing the most to your overall revenue.

2. Sell-Through Percentage:

   • Sell-Through Percentage is a key performance indicator (KPI) that measures the effectiveness of selling products from a specific vendor.

   • The system calculates the Sell-Through Percentage by dividing the total units sold for a vendor by the total units received or available for sale during the same period.

   • A high Sell-Through Percentage indicates that products from a particular vendor are popular and are selling quickly.

3. Vendor-wise Returns:

   • The system tracks product returns and associates them with the respective vendors.

   • It calculates the total value of returned products for each vendor during the specified time frame.

   • Vendor-wise Returns analysis helps in identifying vendors whose products have a higher return rate, which could indicate issues with product quality, fit, or other factors.

4. Vendor Performance Metrics:

   • In addition to Net Sales, Sell-Through Percentage, and Returns, the system can provide various vendor performance metrics, including:

     • Gross Margin by Vendor: Calculating the profit margin for each vendor's products.

     • Inventory Turnover: Measuring how quickly products from each vendor are sold.

     • Days Sales Outstanding (DSO): Evaluating the time it takes to receive payment from customers for products sold by each vendor.

5. Data Visualization and Reporting:

   • The system presents this vendor-related analysis in the form of intuitive charts, graphs, and reports.

   • Users can access dashboards that display vendor performance metrics, allowing for quick and informed decision-making.

6. Trend Analysis:

   • Over time, the system can help identify trends in vendor performance. For example, it can show whether a vendor's performance is improving or declining, helping retailers make strategic decisions about their vendor relationships.

7. Vendor Management:

   • Armed with this detailed vendor-related analysis, retailers can negotiate better terms with vendors, make informed decisions about which vendors to collaborate with or expand relationships with, and take proactive steps to address any issues related to returns or sell-through percentages.

In summary, a system that provides vendor-related analysis plays a crucial role in retail management by offering insights into vendor performance, helping retailers optimize their product assortments, improve profitability, and enhance relationships with suppliers. It empowers retailers to make data-driven decisions for better inventory management and vendor selection.

Go to--> Merchandise --> Vendor Analysis