10 Jul 2024

A step by step guide to implementing AI stock management

A step by step guide to implementing AI stock management



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


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 (springfair.com).

  • 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



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


  • 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.




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:

  • Integrate EazyStock with POS and ERP systems.
  • Configure reorder points and safety stock levels.
  • Train EazyStock with historical data.


Test and Validate:

  • Compare EazyStock’s demand forecasts with actual sales data for the past month.
  • Validate reorder suggestions for the next ordering cycle.


Train Staff:

  • Conduct training workshops for store managers and inventory staff.
  • Provide detailed user manuals and quick reference guides.


Monitor and Optimize:

  • Monthly performance reviews of EazyStock’s impact on inventory levels.
  • Adjust reorder points and safety stock levels based on performance data.


Scale and Expand:

  • Implement predictive analytics for upcoming seasonal trends.
  • Deploy EazyStock across additional store locations.




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