Reconciliation between buyer and supplier for GST filings

As per the changed government norms, the buyers and suppliers could have  to reconcile the entries before filing the GST Returns.

http://www.business-standard.com/article/economy-policy/infosys-chief-nandan-nilekani-plan-on-gst-invoice-matching-may-be-tweaked-118022300073_1.html


In this regards Turbodata can help the end client in the following ways:

• Consolidated platform for data consolidation, data cleansing and data transformation.
• Capturing data entry errors automatically
• Matching of the GSTR reports with Tally GSTR output

Take a look at the other blogs:

• Why Turbodata GST? 

In case offline GST reconciliation services are required then please contact:

Apoorv Chaturvedi

email: apoorv@mnnbi.com

Phone: +91-8802466356

website: www.mnnbi.com

Turbodata Inventory: optimizing the contribution margin of a large robotics manufacturing firm

Inspired by : Manage It Like You Own It by Mike Hannan

Client problem: The manufacturing end client had a statutory requirement to report the inventory valuation numbers using weighted average valuations. This entailed working through the MRP(Material Requirement Planning) items and finding the closing stock valuations of work in progress items and the final items. Alternatively the margin of the final item needs to be also calculated. The end client looked to optimize the contribution margin of its processes by in depth analysis of the cost of materials leading to cost of sales analysis.

ETL team approach: The ETL team moved from periodic to perpetual inventory valuation after data cleansing, data profiling, data auditing, data consolidation and running the  perpetual inventory valuation based on the historical stock valuations after data transformation.

Steps followed:

·         Automated data capture on the client machine

·         Data cleansing of the end client master data

·         Data auditing by matching with the end client ERP audit reports. The perpetual valuations should match with the periodic valuations.

End client benefits:

·         The closing stock numbers cleared by a top 4 audit firms for statutory reports

·         Visibility into the contribution margin analysis for the end client.

·         Forecasting analysis possible that should help at increasing the inventory turnover ratios and improving the cash flow cycles.

Challenges:

·         Master data management

·         Data cleansing

·         Data profiling and data auditing

Contact: Apoorv Chaturvedi

Email: apoorv@mnnbi.com

Phone: +91-8802466356

Website: www.mnnbi.com

Query reduction implementation example: large hospital chain in Gurgaon

Problem: the nightly process of the hospital chain was taking time because of which the SLA(performance parameter) of the CTO of the firm was not been met. The ETL team was advised the bottleneck sql by the end client manager.

Methodology: the end client had developed the code using cursor logic. The ETL team developed the code using set based logic in order to optimize the usage of RAM. The given process has the following benefits for the end client:

·         Optimum usage of RAM

·         Lower implementation times

·         Error logging and error handling

·         Incremental data loads after the initial data loads.

·         Audit of the transformation process for the end client.

Methodology:

The ETL team adopted the Inmon methodology for resolving the same. The cursor logic was reverse engineered using the set based system. The following were the methodologies adopted by the ETL team.

·         Data normalization: error logging, data audit, incremental data load and optimum usage of RAM.

·         Data transformation: converting the cursor logic to set based logic

·         Data cleansing: obtained from the cursor logic

Final result:

·         The output of the set based system was matching with the cursor logic output.

·         The execution time was reduced by more than 80(eighty) percent.

Suggested next steps for the prospect:

·         Send the bottleneck sql to the ETL team.

Posted by:

Ritu Lakhani

Email: ritu@mnnbi.com

website: www.mnnbi.com

Phone: 0124-4365845.

Excel Consolidation-spreadsheet consolidation

Excel consolidation Problem

Many a times we have seen the following:

·         MS Excel reports been developed and used since developing complex reports is very cumbersome at database level.

o   Large amount of data to be processed to develop these complex reports. Hence the end client does not desire to load the transaction system with these reports.

o   The reports are very complex.

o   The reports require data consolidation from multiple data sources to be developed.

o   The data sanctity of the reports is under question since the data can be tampered within MS Excel

o   Developing the MS Excel reports takes a lot of time.

If the end client is facing these issues then Turbodata should be able to help with the following:

·         Data consolidation services: consolidate data from multiple data sources onto a single location for developing consolidated reports.

·         Data cleansing services: cleanse the data for any bad entries.

·         Data transformation services: provide any business logic that is required for the product.

·         Business Intelligence services at lowest cost: development of complex reports using best in class Business Intelligence  tool at lowest cost(free if possible).

·         User security: each user to see its own data only.

·         Design of online forms is possible.

·         Data auditing and data profiling services are available.

Contact:

Apoorv chaturvedi

Email: apoorv@mnnbi.com

Website: www.mnnbi.com

Phone: +91-8802466356

Reducing long query times through data compression and sql reduction

Nightly process completion at Afro Incorporation

Irfan, Production Manager, met Sohail(IT Head) in the meeting room.

Irfan: what happened champ? Look worried?

Sohail: It is the nightly report process that begins at 12 am. It is not completing by 9 am. Suneet(IT Manager) is asking for a new server costing Rs. 25 lakhs. Currently my SLA(service level agreement) is not been met.

Irfan: what will happen with the new server?

Sohail: will speed it up. The management is saying that there is no budget left for this year for IT.

Irfan: Now what?

Sohail: am stuck. How is it going for you?

Irfan: very nice. Since the new Japanese(Takashida) came in. He is removing the constraints in production, reducing inventory and increasing throughput. Why do you start the daily process at 12 am. Why not before?

Sohail: because complete data comes by midnight.

Irfan: say a transaction has happened at 11 am in the morning, then  as per the production team, it is in stock for 13 hours since the other data has not come. Am I correct?

Sohail: correct.

Irfan: Takashida would pre process the data immediately and remove the constraint. He would then store the same in a Work in progress area so that the final fitment is quick.

Sohail: basically work for 24 hours instead of 9 hours.

Irfan: correct. Remove the time constraint. But how would you store the work in progress output?

Sohail: I had this consulting team from M&N BI come up to me that it could store the Work in progress output in a separate database by pre processing the business logic

He gave me this link for data consolidation, datatransformation, data cleansing and even Business Intelligence from his website. The company was saying that even advanced analytics and resolving complex inventory issues should be possible by using its products.

What do you suggest?

Irfan: Let us see what Wasim(CEO) says.

An example of what his team has done for another firm is attached herewith:
http://mndatasolutionsindia.blogspot.in/2018/01/query-reductionimplementation-example.html

If you have the same problem as Sohail, contact the following

By:

Name: Apoorv Chaturvedi

Email: apoorv@mnnbi.com

Website: www.mnnbi.com

Phone: +91-8802466356

Inventory optimization through Turbodata

Are you a customer having the following issues:

Having issues with large value of  slow moving inventory
Have issues with cash flow cycles
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

o   Data consolidation

o   Data cleansing: clean the master data before reporting is done

o   Data profiling: find the first instance when the closing stock of an item turned negative at godown or consolidated level.
       Data analytics: have consolidated dashboards along with predictive analytics facilities at economical costs.

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.

Interested in moving towards orderline profitability:

v  Deployment of Turbodata solution(for testing sample data): USD 3000/-(USD Three thousand only)+taxes as applicable. Contact us for a sample demo

v  Buy our standard book based on Turbodata project experiences: USD 5/-(five) dollars

Please contact the following for the above for a demo

Name: Apoorv Chaturvedi

Email: support@turbodatatool.com;support@mndatasolutions.com

Phone:+91-8802466356

Appendix 1

What do the above management philosophies say?

The Goal:

The Goal is inspired by the theory of constraints. This implies that there are 3 parameters that are critical for any firm:

v  Throughput: the rate at which the system generates the sales(our definition of cash sales)

v  Inventory: the input material required to convert the inputs material to final product for generating throughput.

v  Labor: The manpower required for converting inventory to throughput.

The protagonist Jonah in ‘Goal’ also insisted on standard deviations and variations to be part of the process. The variations to be detected on a close to real time basis so that any errors are caught beforehand.

Profit Beyond Measure:

Profit Beyond Measure  is inspired by the Toyota Production system. It emphasizes that the manufacturing company should function like a human body. The functional managers should account for self sustainability(standard cycle times), diversity and interdependence( the manufacturing managers need to look at the whole system like a human body and not just a single component).

The book emphasizes that there should be a reduction in inventory by reducing a changeover times at each of the working station. That is the manufacturing process should start once the customer order has come into the system. The book further looks at ‘Design to order’ by designing multiple configurable modules to offer the end clients multiple types of products.

The system emphasizes catching the errors in production cycle quickly so that there is reduced material wastage.

Sample example of inventory optimization:Inventory optimization of large trading company

FOR FREE MICROSOFT POWERBI DASHBOARDS: please do one of the following:

Email: support@mndatasolutions.com;support@turbodatatool.com