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8 Applications of Business Intelligence and Big Data in Supply Chain Management

8 Application Of Business Intelligence And Big Data In Supply Chain Management 01

Supply chain management has become more complex and interconnected in today’s rapidly evolving business landscape. Enterprises are leveraging cutting-edge technologies such as Big Data and Business Intelligence (BI) to gain a competitive edge, optimise processes, and enhance decision-making throughout the supply chain.

In this article, we’ll delve into real-world applications of Big Data and BI that are reshaping the world of supply chain management.

What is supply chain management?

Supply chain management (SCM) refers to the strategic coordination and integration of various processes, activities, and stakeholders involved in producing, distributing, and delivering goods and services.

The main objective of supply chain management is to ensure the efficient flow of materials, information, and resources from suppliers, distributors, retailers, and ultimately to end consumers. Through supply chain management, companies can optimise processes to achieve cost savings, reduce lead times, enhance product quality, improve customer satisfaction, and maintain a competitive edge in the market.

Here are the critical components of supply chain management:

  • Planning involves forecasting demand, setting production schedules, and determining optimal inventory levels to meet customer needs while minimising costs.
  • Sourcing entails selecting suppliers, negotiating contracts, and managing relationships to ensure a reliable supply of raw materials and components.
  • Manufacturing/Production involves transforming raw materials into finished products through various production processes while maintaining quality and efficiency.
  • Logistics/Distribution encompasses the transportation, warehousing, and distribution of products to different locations, including retailers and consumers.
  • Inventory Management aims to balance supply and demand, minimise carrying costs, and prevent stockouts or overstocking.
  • Information Management covers effective communication and sharing across the supply chain to facilitate coordination and decision-making.
  • Demand Management includes understanding and predicting customer demand to ensure products are available when and where needed.
  • Collaboration and Coordination involve cooperation and coordination among stakeholders, including manufacturers, distributors, suppliers, and retailers.
  • Risk Management is mitigating potential risks that could disrupt the supply chain, such as economic issues, disasters, geopolitical events, or supplier issues.
  • Sustainability and Ethical Considerations usually involve integrating environmentally sustainable practices and ethical considerations into supply chain processes.

8 Application of Business Intelligence and Big Data in Supply Change Management

Effective supply chain management requires careful planning, continuous monitoring, and the use of business data to make informed decisions and adaptations as needed. Likewise, the relationship between supply chain management and data is symbiotic and transformative. Data is crucial in optimising and revolutionising supply chain management practices, enabling organisations to make informed decisions, enhance efficiency, and adapt to changing market dynamics.

Likewise, here are some ways you can use big data in supply chain management:

Big Data In Supply Chain Management

1. Demand Forecasting and Inventory Management

Effective demand forecasting and inventory management are vital for the success of any business. It allows companies to anticipate future demand patterns and plan production, procurement, and resource allocation.

However, accurate demand forecasting relies on historical sales data, market trends, and external factors. This is where big data in the supply chain can help. Big Data and BI tools enable organisations to analyse historical sales data, market trends, and external factors to predict demand with higher accuracy. This empowers companies to optimise inventory levels, minimise stockouts, and reduce excess inventory, ultimately leading to cost savings and improved customer satisfaction.

2. Supplier Relationship Management

Supplier Relationship Management (SRM) plays an essential role in the sustainability of any business. It strategically manages supplier relationships to maximise value, minimise risks, and foster collaboration.  Big data can help organisations to assess supplier performance based on on-time delivery, quality, and responsiveness metrics. Leveraging Big Data in Supply Chain Management can help businesses analyse supplier performance metrics, track delivery times, and assess product quality.

This facilitates data-driven decisions when selecting and managing suppliers, leading to better partnerships and a more resilient supply chain.

3. Route Optimisation and Logistics

For several compelling reasons, route optimisation and logistics play a vital role in efficient and effective supply chain management. Efficient route planning leads to shorter travel times, faster deliveries, and reduced lead times. This directly translates to cost savings for businesses by reducing operational expenses associated with logistics. Likewise, it enhances customer satisfaction, as timely deliveries are essential for meeting customer expectations and maintaining competitiveness.

Big Data analytics in supply chain management allows companies to optimise transportation routes, considering traffic patterns, weather conditions, and delivery schedules. Similarly, it will enable supply chain managers to identify inefficiencies, streamline processes, and implement continuous improvement initiatives. This results in reduced fuel consumption, lower transportation costs, and faster delivery times.

4. Risk Management and Resilience

Risk management and resilience are crucial to any organisation’s success and longevity. In today’s rapidly evolving business landscape, where uncertainties and disruptions are becoming increasingly common, companies must prioritise these areas to safeguard their operations, reputation, and bottom line.

Using BI and big data in supply chain management can help gather data, including geopolitical events, weather patterns, and economic indicators that can contribute to risk assessment and mitigation strategies. As such, supply chain managers can assess potential risks and develop contingency plans. This enhances the supply chain’s resilience and ensures continuity even in challenging circumstances.

5. Quality Control and Compliance

With increasing globalisation and complex supply chains, it becomes even more critical to maintain high standards throughout the entire process. Likewise, ensuring quality control and compliance in supply chain management is crucial for any business. It plays an important role in maintaining product quality and meeting customer expectations.

However, quality control can only be established and maintained with sufficient data. This is where BI and big data come. Business Intelligence tools and big data analytics can monitor and analyse product quality data at different supply chain stages. This helps identify defects, ensure compliance with industry standards, and maintain product integrity.

Through this, businesses can ensure that their products and services meet the required specifications. This not only helps in enhancing customer satisfaction but also helps in building a solid brand reputation.

6. Real-time Tracking and Traceability

Real-time tracking and traceability have become essential in modern supply chain management. In today’s fast-paced and interconnected world, businesses face increasing pressure to ensure efficiency and accountability throughout their supply chains. But real-time tracking capability enables companies to have complete visibility into their products’ location, condition, and status.

Big Data in Supply Chain Management provides real-time visibility and transparency into every part of the supply chain. This transparency allows stakeholders to monitor operations, identify bottlenecks, and track the movement of goods. Any issues or delays during transportation or handling can be identified immediately. This ultimately can lead to smoother operations and improved customer satisfaction.

7. Collaborative Decision-Making

Supply chains involve multiple stakeholders with diverse expertise, including suppliers, manufacturers, distributors, and retailers. As such, collaborative decision-making is essential. It encourages different parties to collaborate and bring unique viewpoints to the table. This facilitates faster problem-solving as stakeholders pool their insights and brainstorm solutions, expediting decision-making.

However, often, collaborative decision-making can take more work to apply. Due to diverse beliefs and interests, stakeholders often clash. This is why data sharing and integration are needed among supply chain partners.

Through big data analytics in supply chain management, businesses can create a centralised hub for stakeholders across the supply chain to access and share data-driven insights. Thus, when data flows seamlessly between different entities, stakeholders can make synchronised decisions, align goals, and respond rapidly to changing circumstances. This fosters collaboration and facilitates coordinated decision-making.

8. Sustainability

Sustainability holds significant importance in supply chain management for many compelling reasons. It primarily helps companies decrease costs by reducing waste, improving energy efficiency, and optimising resource utilisation. Likewise, encouraging sustainable practices can help with reputation and brand value as more customers prefer environmentally responsible companies and products.

However, some can be bothersome. Supply chains are often extensive and involve multiple stakeholders, making coordinating sustainable practices across various stages and partners challenging.

This is where integrating big data in supply chain management is essential. It can identify inefficiencies and areas of waste within the supply chain, enabling companies to implement sustainable practices, reduce environmental impact, and promote circular economy principles.

Maximise Your Big Data in Supply Chain Management!

In summary, big data is the lifeblood of effective supply chain management. It empowers organisations to optimise processes, makes data-driven decisions, enhance collaboration, and adapt to dynamic market conditions. As technology and data analytics evolve, the relationship between supply chain management and big data will only deepen, ushering in new opportunities for innovation and growth.

If you’re seeking to harness the full potential of data in your supply chain management, look no further than SOMA Technology Group. SOMA Technology Group offers tailored solutions that align with your specific needs. Contact us now!

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