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Blocked Credit Release

Client:Bacardi
Industry:Liquor
Region:Portugal and India
image background-image
650+
Orders Released
7Mn+
Orders Valued (EUR)

Client portfolio

Our client is one of the largest liquor manufacturing companies in the United States of America, with a perfect blend of rich ancestral heritage and modern innovative flavor, working strenuously at finding the right balance between staying ahead of customers’ expectations and delivering quality experiences.

Overview – Origins

The long-standing customers of a company (that sells goods in the form of products) normally do their financial transactions with a credit account, with a credit limit set for them. The customers place orders in the form of Purchase Orders to the company, the company raises Sale Orders against the POs, then either ship from warehouse or manufacture to demand and then ship to the customers. After which invoices are generated and sent to the customers. They perform the financial payments thereafter.

As this is all a very dynamic process and as payments normally take time, there is a credit account set for each long-standing customer. With each POs getting raised, as long as the transaction amount is within the credit limit of their credit account, the corresponding SOs are created. But whenever a PO is raised and its value goes above the credit limit, there is a stall in the SO creation process. Credit is blocked. To release this blocked credit an approval process with the designated person is necessary. Based on this approval (or rejection), the block is released (or still blocked) and the SO is raised (or not).

This case study details the automation solution that streamlines the approval process and makes credit block release a cakewalk.

Problem statement – The Past

Whenever a PO is raised by a customer that falls over the credit limit, the SO creation is stalled. In order to release the blocked credit, the users run a transaction in SAP. For this, they perform the analysis manually for each of the stalled orders by referring to data from multiple SAP transactions. With the analyzed data, they Release, Reassign or Reject based on the outcome of analysis.

In the case of Portugal, the process is as follows. Based on the value of the credit overflow, the designated person to authorize the Release varies. Therefore, there is an approval process wherein a Credit Specialist collects the supporting data. Then he reassigns the order to the designated person (Approver) in the Approval matrix based on the credit overflow value. This Approver now receives a mail asking for approval/rejection of the order. He then analyzes and decides if the order has to be approved. He then sends his decision to the Credit Specialist, who now runs the transaction to release the blocked credit and post the SO in SAP.

Whereas in the case of India, the approval matrix is based on a regional classification. Based on the region the credit block occurs in, the designated people (Approvers) differ. So, when a Credit Specialist encounters a credit block with a region, he has to reassign the order to the Approver of that region along with the supporting data. With his decision, the credit block is released.

The manual overhead of fetching the supporting data for the approval process, the time-consuming approval process in the form of emails and the necessity for a dedicated person to co-ordinate the above actions made this business process an ideal candidate for intelligent automation using Tulip.

Our Solution – The Present

The automation solution of BeezLabs aimed to completely eliminate the collection of supporting data by a Credit Specialist. The Tulip bots run at pre-configurable intervals of time to fetch the fresh credit blocks. They fetch the supporting data from multiple transaction codes in SAP.

An Approval matrix is predefined as per needs through Rules feature of Tulip. For Portugal, the Rule sets the matrix with Approvers based on value. For India, the Rule sets the matrix with Approvers based on region.

Now, based on the Rule, the Approver is identified and the supporting fetched data for the blocked credit orders are assigned to them via the Tasks feature of Tulip. Task enables the Approvers to view the data and reach a decision on approval. By just a button click, the credit block is released and the SOs are posted.

What makes the approval process even easier, is the mobility offered by Tulip mobile App. This ‘Approve on the Go’ of Tulip comes in very handy in terms of quick actions by Approvers.

Value delivered – The Outcome

Faster response time - Tulip mobile app makes Approve on the Go a reality
Streamlined business process – Regulating the Approval matrix structures the process and hence easy scalability in case of change
Better User Experience - Tulip Tasks simplifies the view of the supporting data and thereby the decision on analysis
Auditing made easier

Potential extended scope – The Future

Credit block release for any sector in any country can be automated with the same approach. With Rules, the schematics of approval matrix can be designed and pre-configured. Depending on the supporting data required for analysis, even other specific data can be fetched by minimal changes in the Tulip bot that retrieves this information.

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