Inventory Optimization

Stock Forecasting

Stock Movement (In/Out)

Warehouse Management


AKRA TECH prepared the project well under the time specified. He immediately understood the purpose of the project and provided relevant solutions in our discussions. The final product required no modifications and met the criteria for the project perfectly. We are very likely to return to AKRA TECH for future work.
Sabaa.org, USA

Inventory Forecasting with Tableau

We have built an inventory forecasting tool with the help of python and Tableau to create a dashboard view in the application which displays the forecasting information. This helps in the analysis and forecast of the future requirement of products for any store. Our forecasting tool provides an analytical approach to take business decisions.

Our in-house inventory forecasting tool has been built using Python and tableau. The inventory forecasting tool can be customized completely as per the client’s requirement.

Data visualization allows us to create custom dashboards to track all key product/store metrics and that provide ongoing alerts when metrics fall below a certain threshold.


  • No. of products
  • No. of Product Rented
  • New products/Period
  • Delisted products/Period
  • Rental Orders/Period (month)
  • Days rented/Period (month)
  • Rentals by each period of time (1, 2…7…30 days)
  • Avg days/rental
  • Rental Revenue/Period
  • Avg Revenue/Rental Order
  • Days rented/Period
  • Avg Products/Rental Order
  • Product Rating


  • Total Users
  • Total Owners
  • Total Revenue/Client/Period
  • Avg Revenue/User/Period
  • New Users and Owners/Period


  • Gross revenues
  • Gross and net profit
  • Customer acquisition cost (CAC)
  • Customer lifetime value (LTV)
  • The average revenue per user (ARPU)
  • Supply Expense/Revenue
  • Revenue/sq ft


  • No. of PU's & Deliveries/period
  • No. of PU's & Deliveries/FTE/period
  • Avg. PU's and Deliveries/period
  • PU's vs Deliveries
  • Average time to PU or Deliver products
  • No. of PU's and Deliveries by each employee/period
  • No. and % of on-time PU's & Deliveries
  • Field Revenue/FTE