11 Jul 2024

A step by step guide to implementing AI stock management

AI guide to implementing

AI stock management tools in a small business can significantly enhance inventory control, reduce costs, and improve efficiency. This is a simple guide to help you start using AI in retail and small business. Learn about other ways AI can be used by retailers here: Harnessing AI: A Guide for Independent Retailers - Autumn Fair 2024

Step 1: Identify Needs and Set Clear Objectives

Identify Problems:

Frequent stockouts of popular items.
Excess inventory of slow-moving items.
Inaccurate demand forecasting.

Set Objectives:

Reduce stockouts by 20% within six months.
Decrease excess inventory by 15% within six months.
Improve accuracy of demand forecasting.

Step 2: Choose an AI Stock Management Tool

Identify Key Features:

Demand Forecasting: Predict future sales based on historical data.
Automated Reordering: Automatically generate purchase orders when stock reaches predefined levels.
Real-Time Tracking: Monitor inventory levels in real time.
Supplier Management: Optimize order quantities and manage lead times.

Evaluate Potential Tools:

See our brief comparison of two leading tools below, for a more detailed analysis of the top five tools read this article: Comparison of AI stock management tools for Small Business.

Inventory Planner is ideal for businesses requiring advanced forecasting and willing to invest in a comprehensive tool. It is particularly beneficial for those heavily reliant on e-commerce platforms.
EazyStock is suited for businesses looking for in-depth inventory optimisation and willing to invest time in training to fully utilise its capabilities. It is a robust tool that grows with your business.

Step 3: Prepare Your Data

Gather Data:

Sales Data: Collect sales data for the past 12-24 months, including transaction dates, quantities sold, and prices.
Inventory Data: Compile data on current stock levels, SKU details, product categories, and locations.
Supplier Data: Gather information on supplier lead times, order quantities, and delivery schedules.

Clean and Organize Data:

Remove Duplicates: Ensure there are no duplicate entries in your datasets.
Correct Inaccuracies: Fix any errors in product codes, descriptions, and quantities.
Standardize Formats: Ensure consistency in data formats (e.g., date formats, SKU codes).

Format Data for AI Tool:

CSV Files: Many AI tools require data in CSV format. Convert your datasets accordingly.
Field Mapping: Map your data fields to match the AI tool’s required input format (e.g., date, SKU, quantity, price).

Create a Data Backup:

Before making any changes, back up your original data to prevent loss.

Test Data Import:

Import a small subset of your data into the AI tool to ensure it’s formatted correctly and imports without issues.
Verify the accuracy of imported data in the AI tool.

Step 4: Implement the AI Tool

Integration:

Connect the AI tool to your POS and ERP systems.
Ensure data synchronization between systems.

Configuration:

Set up parameters (reorder points, safety stock levels).
Define rules for automated reordering.

Training the AI:

Load historical data into the AI system.
Allow the AI to analyze data and learn patterns.

Step 5: Test and Validate the AI Tool

Test Predictions:

Compare AI’s demand forecasts with actual sales data.
Validate reorder suggestions against your inventory needs.

Assess Performance:

Check if the AI tool is improving stock levels.
Evaluate user feedback from staff.

Step 6: Train Staff

Training Sessions:

Conduct hands-on training workshops.
Provide step-by-step guides and video tutorials.

Ongoing Support:

Establish a support system for staff queries.
Offer refresher training sessions periodically.

Step 7: Monitor and Optimize

Regular Reviews:

Monthly reviews of AI tool performance against set objectives.
Analyze stockout and overstock rates.

Make Adjustments:

Fine-tune parameters based on performance data.
Update the AI tool with new sales and inventory data.

Step 8: Scale and Expand

Additional Features:

Explore adding predictive analytics for new product launches.
Implement AI for supplier management and procurement.

Multiple Locations:

If applicable, deploy the AI tool across all store locations.
Ensure consistent data and integration across locations.

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Example: Implementing EazyStock in a Small Gift Shop

Let’s go through an example of implementing EazyStock for stock management in a small gift shop:

Identify Needs and Set Objectives:

Reduce stockouts of popular seasonal items by 20%.
Decrease excess inventory of slow-moving gifts by 15%.

Choose EazyStock:

Features: Automated replenishment, demand forecasting, real-time tracking.
Integration: Compatible with the shop’s POS and ERP systems.
Cost: Fits within the budget with a clear ROI.

Prepare Data:

Sales Data: Gather 18 months of sales data, including dates, quantities, and prices.
Inventory Data: Compile current stock levels, SKUs, and product categories.
Supplier Data: Collect lead times, order quantities, and delivery schedules.
Clean and Standardize Data: Remove duplicates, correct inaccuracies, and ensure consistent formats.
Format Data for EazyStock: Convert data to CSV and map fields according to EazyStock’s requirements.

Implement EazyStock: