Case Study 1:

ABC Telecom is a leading telecommunications company facing challenges with customer retention. With increasing competition in the industry, retaining customers has become critical for sustaining profitability and growth. ABC Telecom implements predictive modelling techniques to address this issue, forecast customer churn, and proactively intervene to prevent attrition.

Demonstrate the role of predictive modelling techniques to forecast customer churn and proactively intervene to prevent attrition.

Case Study 2 :

ABC Manufacturing is a global company specializing in the production of industrial machinery. With a complex supply chain involving numerous suppliers, distributors, and partners, ABC faced challenges in managing the flow of information and transactions efficiently. To streamline its business processes and enhance collaboration with partners, ABC decided to implement Electronic Data Interchange (EDI).

Learning Objectives

1. Manual Processes: ABC relied heavily on manual data entry and paper-based communication for exchanging business documents such as purchase orders, invoices, and shipment notices. This led to errors, delays, and inefficiencies in the supply chain.

2. Data Accuracy: Manual data entry increased the risk of errors, resulting in discrepancies in order fulfillment, invoicing, and inventory management.

3. Lack of Integration: The lack of integration between ABC's systems and those of its partners hindered real-time visibility into supply chain activities and made it challenging to synchronize processes.

4. Compliance Requirements: ABC needed to comply with industry standards and regulations governing the exchange of electronic documents, such as ANSI X12 and EDIFACT, to conduct business with its partners.