Use cases

Operational improvement with Namuda process mining

Organizations are constantly seeking ways to streamline their operations, cut costs, and enhance productivity. However, in the complex web of interconnected processes that define modern businesses, uncovering inefficiencies and optimization opportunities can feel like searching for a needle in a haystack. This is where process mining steps in as a game-changer.

USE Cases

At its core, process mining is the practice of analyzing event data generated during the execution of processes to gain insights into how these processes actually operate. By tapping into this rich vein of operational data, organizations can reveal hidden patterns, identify bottlenecks, and pinpoint areas for improvement with unprecedented precision.

Order to cash

The order to cash (O2C) process, refers to the set of business activities involved in fulfilling customer orders, generating revenue, and collecting payment. It encompasses everything from the initial placement of an order by a customer to the receipt of payment for goods or services rendered. Consequently, the Order-to-Cash process is a key business process in many enterprise information systems.
Process mining offers substantial benefits for order to cash processes by providing deep insights into every stage of the process, from order placement to cash collection. By analyzing event logs and transactional data, process mining can uncover inefficiencies, bottlenecks, and deviations
Additionally, process mining facilitates continuous monitoring and improvement by identifying patterns and trends over time, allowing businesses to adapt quickly to changing market demands and customer preferences. Ultimately, leveraging process mining in O2C processes can lead to improved customer satisfaction, increased profitability, and sustainable competitive advantage.

Purchase to pay

The purchase to pay (P2P) process, also known as procure to pay, refers to the sequence of steps that an organization follows to procure goods or services from external suppliers and then pay for them. It encompasses all activities involved in purchasing, receiving, and paying for goods or services, as well as managing supplier relationships.
Process mining can significantly enhance purchase to pay (P2P) processes by providing valuableinsights into every stage of procurement, from requisition to payment. By analyzingtransactional data and event logs, process mining uncovers inefficiencies, identifies bottlenecks, and detects deviations from optimal workflows. These insights empower organizations to streamline their P2P processes, reducing cycle times, minimizing errors, and enhancing overall efficiency.
Moreover, leveraging process mining in P2P processes can lead to cost savings, improved supplier relationships, and greater compliance with procurement policies and regulations.

Supply Chain

The supply chain processes encompass the entire lifecycle of a product or service, from the sourcing of raw materials to the final delivery to the customer. Process mining holds significant potential for enhancing supply chain processes by providing valuable insights into the various stages of the supply chain. These insights enable organizations to optimize inventory management, streamline procurement processes, and enhance logistics operations.
Additionally, process mining facilitates proactive decision-making by identifying patterns and trends, allowing supply chain managers to anticipate issues and implement corrective actions swiftly. Ultimately, leveraging process mining in supply chain processes can lead to improved efficiency, reduced costs, and enhanced customer satisfaction.

Production

Process mining can significantly enhance production processes by providing valuable insights into every stage of manufacturing operations. By analyzing transactional data and event logs from production systems like Scada, MES, Maintenance systems and IoT, process mining can identify inefficiencies, bottlenecks, and deviations from optimal workflows. These insights empower organizations to streamline production processes, reduce cycle times, minimize down time,and optimize resource utilization.
Additionally, process mining facilitates continuous monitoring and improvement by identifying patterns and trends over time, enabling proactive decision-making and swift corrective actions to improve overall efficiency and productivity in manufacturing operations.

Finance

Accounts Payable
The accounts payable (AP) process is a fundamental aspect of financial management in organizations. It involves the management of outgoing payments and the liabilities a company has for goods and services received but not yet paid for. Efficient management of the accounts payable process is essential for maintaining good supplier relationships, managing cash flow effectively, and ensuring compliance with payment obligations.
With process mining, organization scan get a deeper understanding of their AP processes, identify areas for improvement, and implement targeted interventions to streamline operations, enhance efficiency, and drive cost savings.
Account reveivable
The accounts receivable (AR) process is a fundamental aspect of financial management in organizations. It involves managing incoming payments and the amounts owed to a company by its customers for goods or services provided on credit. Efficient management of the accounts receivable process is essential for organizations to optimize cash flow, minimize bad debts, and maintain healthy customer relationships.
Process mining helps organizations to gain a deeper understanding of their AR processes, identify areas for improvement, streamline operations, enhance efficiency, and optimize cash flow management.

Introducing Namuda Process Discovery Canvas™

Glamox

A tool designed to provide transparency in business processes through systematic exploration and data-driven analysis. It enables us to identify blockers and bottlenecks in our value chain and eases our work in optimizing our business processes

Tuan Viet Vo
Head of core business operations, Glamox Group
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