Are you a customer having the following issues:

v  Having issues with large value of slow moving  inventory

v  Have issues with cash flow cycles

v  Do not have clarity regarding product profitability

Our product Turbodata can help your firm with resolving the above issues. The product is inspired by philosophy of The Goal by Eliyahu Goldratt and Profit Beyond Measure by Thomas Johnson and Ander Brohms(please see the appendix 1 for a summary of the philosophies)

 Both the philosophies imply that the end client should use the order line profitability instead of using the periodic calculations. Only then would the end client get complete visibility into its operations and profitability by customer, region etc.

 What is required for determining the orderline profitability?

For determining the same the end client needs to have valuations of inventory using perpetual method instead of the periodic method.

As a case to the point, consider the following:

In the attached scenario of an item, the valuation using weighted average/FIFO has been done on periodic basis. Hence the end client looses the orderline profitability details by using the same.

However in the snapshot below using Turbodata, the weighted average calculations are done on a daily basis(as in the attached snapshot)

This enables the end client to calculate orderline profitability.

 Issues with calculating the orderline profitability:

v  In some of the software,  negative stock is allowed.  Because of the same orderline profitability calculations might be impacted. The sample below gives the first instance of negative stock for an item.

Sample attached below:

v The physical stock entries valued at 0(zero) value can create discrepancies in the stock valuations.

v Data consolidation from multiple systems could be required for calculating the same.

v  Data transformation in terms of business logic of the end client needs to be done so that the required calculations come into force.

 By using Turbodata, the end clients shall be able to achieve the following:

v  Go towards orderline profitability by getting an estimate of cost of goods sold based on perpetual FIFO and weighted average calculations.

v  Achieve the following activities

• Data consolidation
• Data cleansing: clean the master data before reporting is done
• Data profiling: find the first instance when the closing stock of an item turned negative at godown or consolidated level.

v  Better management of inventories: by finding the profitability of the sale of items at the orderline level for a given set of customers.

v  Prepare the data for predictive analytics and forecasting through data compression and sql reduction. The predictive analytics and forecasting is required to capture the variations from the standard values for sales. A significant variation is to be captured early so that the end client could take the corrective actions quickly.

Please contact the following if any queries:

Name: Apoorv Chaturvedi

Email: apoorv@mnnbi.com

Phone: +91-8802466356/0124-4365845

Website: www.mnnbi.com

Blog link: http://mndatasolutionsindia.blogspot.in/