Last updated on September 20th, 2024 at 12:52 pm
Generally, supply chains generate huge amounts of data. Supply chain analytics include several processes and tools to make sense of all this available data. It uncovers patterns and generates insights.
Supply chain analytics is a crucial component of a thriving supply chain. It is used to manage, improve, and support supply chain operations. Supply chains are important for developing and maintaining the modern economy, and providing quality goods and services to the customers.
Businesses can make more informed decisions and optimise their performance using supply chain analytics. Let us understand what supply chain analytics is, how it is done, and why it is necessary in this guide.
What is a supply chain?
Before we learn about supply chain analytics, we need to understand what is a supply chain and how it is managed. A supply chain can be defined as a network between an organisation and its suppliers to produce and provide products or services to the final consumers. It is the complete lifecycle of a product, from the raw materials to the final sale.
A supply chain includes various steps like procurement of raw materials, manufacturing, distribution, storage, and finally delivery of finished product. It lays out all activities of the production process - the information communicated, natural resources used, human resources needed, etc.
The key steps in a supply chain include:
- Planning the manufacturing process and inventory to make sure that supply and demand are adequately balanced.
- Sourcing or manufacturing the materials required to create the final product.
- Assembling components and building the product.
- Testing the products to find any areas of improvement.
- Storing it in inventory or packaging and shipping the product.
- Transporting the packaged product to the distributor or retailer.
- Distributing the products to consumers.
- Providing efficient customer service to buyers.
We will discuss the steps involved in detail further in this writing.
The efficiency of a supply chain, at both the manufacturing and distribution ends, can either make or break a business. Hence creating a proper supply chain model is very important.
Features of a supply chain
The primary objective of an efficient supply chain is to deliver products or services, along with maintaining quality and quantity within a specified time period. Here are some characteristics of a successful supply chain:
- Balance: A successful supply chain includes several components such as material resources, manpower, etc. All these components operate together accurately, and maintaining the proper balance can help businesses.
- Flexibility and scalability: Supply chains should be able to adjust to varying demands and market dynamics seamlessly. From distribution networks to production processes, adaptability helps in ensuring optimal resource utilisation.
- Real-time information: Supply chains generate huge amounts of data. Access to real-time information is the foundation of a strong supply chain. Using supply chain analytics, businesses can gain insights into the stages of the supply process, and facilitate quick responses and proactive decision-making.
- Cross-functional communication: Seamless collaboration among different areas of the supply chain helps build a robust network. Open communication leads to effective decision-making and a unified approach to challenges.
- Dynamic supplier and distributor relations: A supply chain will only function with suppliers and distributors. Regular communication and strategic collaboration help achieve network flexibility.
What is supply chain management?
Supply chain management (SCM) can be defined as the coordination of a business’s entire production flow, from sourcing materials to delivering finished products. The goal of a successful SCM is to improve the efficiency of all processes involved in turning raw materials into final goods and getting them delivered to the ultimate customer.
Effective supply chain management can help streamline an organisation’s activities to maximise customer value, eliminate waste, and gain a competitive edge in the industry.
Why is supply chain management important?
Effective supply chain management is important for all organisations as it helps minimise the waste produced, production time, and costs. Your company’s profitability is dependent on how your supply chain works. A study showed that companies with advanced supply chain management capabilities are almost 23% more profitable than others.
Successful SCM also helps companies gain a competitive edge. A lack of effective supply chain management can break down the production and distribution process. This can cause a loss of revenue and create internal stress in the company. It could also lead to detrimental customer loss and can negatively impact the company’s reputation.
SCM also helps companies in risk management. Organisations can anticipate and mitigate potential threats. Supply chain management can help improve customer loyalty and satisfaction. Sustainable supply chain management also helps reduce the company’s carbon footprint and impact on the environment.
The five phases of supply chain management
There are five key areas of work in a supply chain - including planning, sourcing, organising, delivering, and managing. The job role of professionals working in this field not only entails traditional purchasing and logistics. They also help find ways to increase company efficiency and keep costs in check.
The supply chain management process includes the following five phases:
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Planning
Supply chain management starts with planning. In this step, supply chain managers predict demand, analyse resources, arrange production, and oversee inventory levels to ensure the quality of the products.
This implies companies need to take into account the raw materials or components needed at each stage of manufacturing, the equipment available, and the employees needed. You need to ensure the transition between steps is seamless and every stakeholder is aware of their responsibilities.
You also must create a strategic SCM model. It will help you determine the metrics and understand whether the supply chain is efficient and effective in meeting company goals.
To learn more about how you can create a strategic supply chain model, explore some of the credible supply chain management courses. This will help you learn from industry experts and gain practical experience.
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Sourcing
Once you have your plan in place, the next step is to source the materials required. This includes identifying suppliers, ordering, receiving, managing inventory, and authorising supplier payments.
A successful supply chain is heavily dependent on strong supplier relationships. It is also necessary to manage supplier relationships to ensure a reliable supply of raw materials and components.
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Manufacturing
Manufacturing is the heart of SCM. In this step, machinery and manpower are used to transform sourced raw materials or components into something new which is the brand identity.
Quality checks are performed on the finished product to ensure that it meets the company standard. Manufacturers are also often responsible for packaging the products and handling them to delivery service providers. Effective communication between material sourcing, manufacturing, and delivery is crucial to keep production moving.
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Delivery
Delivery involves the transportation and distribution of finished goods. Companies with effective supply chain management will have strong logistic capabilities and delivery channels to ensure safe, inexpensive, and timely delivery of products.
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Returns
A customer might be unhappy with a product and would like to return it or exchange it for an alternative one. It is important to build an effective and convenient return service.
You must manage reverse logistics to ensure that this process is smooth for your customers. You should also provide quality customer service to guide people through the process. It is a key component that helps ensure customer satisfaction.
If you are interested in SCM, here is a guide to pursuing a career in supply chain management. Learn the steps you must take to build a career in the field.
What is supply chain analytics?
It is the process of using advanced data analysis techniques and technologies to gain insight and optimise various aspects of the supply chain. A large amount of data is collected and analysed from different sources such as suppliers, manufacturers, distributors, retailers, and end-users.
Companies use supply chain analytics to make sense of a sea of data, by identifying patterns and providing actionable insights. It helps make improved decisions, supply chain optimisation and enhance overall business performance.
By leveraging analytical methods and tools, companies can gain visibility into supply chain operations, identify bottlenecks in the system, reduce costs of production, enhance efficiency, and reduce risk. Supply chain analytics is used in the SCM process for the following tasks:
- Demanding forecast: Supply chain analytics is used to future demand patterns based on market trends, historical data, and other relevant factors. This is crucial for planning production, optimising inventory levels, and allocation of resources.
- Analysing supplier performance: The supplier performance is evaluated based on various metrics like quality, on-time delivery, and cost. In this way, companies can understand who the reliable and efficient suppliers are. It also enables effective supplier management.
- Inventory optimisation: Inventory data is analysed to determine the availability of materials, proper stocking levels, when reorder is needed, and process timeline. It helps minimise holding costs and stockouts by ensuring that the inventory is neither insufficient nor has excessive supply.
- Logistics and transportation optimisation: The analytical tools are used to analyse transportation data to optimise routes, shipment consolidation, and modes of transportation. It helps improve the time needed for delivery, reduces distribution costs and boosts the efficiency of logistics.
- Risk management: Analytical tools can create contingency plans and mitigate risks from threats such as natural disasters, geo-political issues, or supplier failures.
- Sustainability and environmental impact: Supply chain analytics can also be leveraged to analyse data related to energy emission, consumption, and waste generation. Identifying these can help practise sustainable methods and reduce carbon footprint.
How does supply chain analytics work?
Supply chain analytics uses advanced data collection, management and analytical techniques for supply chain optimisation. Relevant data is gathered from several enterprise systems and external sources.
This data undergoes various steps such as cleansing, statistical modelling, machine learning algorithms and data visualisation tools to gain valuable insights. These insights can be used to enable data-driven decision making.
Supply chain analytics benefits
Analytical tools are significantly beneficial for organisations. Revenue growth, better capital management, and improved margins are just a few of the advantages. Here are some more supply chain analytics benefits:
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Increased planning accuracy
Predicting consumer demand can help supply chain managers plan the supply chain processes efficiently. The analytical tools help organisations ensure the availability of raw materials or components. It also helps businesses cut back on processes that are not beneficial for the company’s growth.
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Anticipate and mitigate risks
Supply chain analytics is used by companies to identify potential risks and come up with a contingency plan for them. Using this information, companies can also anticipate and immediately respond to changing market trends. This allows to make shifts in the supplier base and proactively plan for disruptions.
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Increase customer satisfaction
A company has hundreds of customers, with each having their own preferences. The analytical tools are used to identify customer purchase patterns. It also helps to reduce order fulfilment issues and create a smooth buying and returning process for consumers. This in turn enhances customer satisfaction and drives brand loyalty.
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Supply chain optimisation
Using supply chain analytics you can identify business operations that need a little tweaking. You can determine the processes that are no longer beneficial for your supply chain and reshape them. Making tiny changes at each step to optimise efficiency can help lower the cost of goods sold and achieve high gross margins.
Supply chain analytics challenges
There are several benefits of supply chain analytics, however, there are also many challenges associated with it. Here are some of the common challenges:
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Data Accuracy
Quality data is highly essential for effective supply chain analytics. However, often organisations face challenges related to data consistency, accuracy, completeness, and timeliness. Incomplete or inaccurate data can give insufficient insights and lead to unreliable decision-making. Addressing data compilation issues and ensuring data quality can be complex and time-consuming.
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Lack of standardisation
Standardisation of data is crucial for carrying out meaningful analysis across different data sources. However, in many cases, there is no proper standardisation since data is collected in various formats - different measurement units, categorisation, and naming conventions. Effective analysis is hampered by this inconsistency.
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Data volume
In a supply chain, a vast amount of data is generated from multiple sources, including suppliers, warehouses, production lines, delivery services, and end-users. Dealing with large amounts of data and managing its complexity could be overwhelming. Organisations need to leverage analytical and technical tools to extract meaningful insights.
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Technological infrastructure
Implementing supply chain analytics requires strong technological infrastructures including, analytical tools, data storage, and computing capabilities. Organisations must learn about and invest in the right technology to handle processing, advanced data visualisation, and integrating requirements. Technology upgrades and maintenance is a good investment that helps the organisation work at its full potential.
Key features of effective supply chain analytics
Effective use of supply chain analytics helps protect and improve the reputation of the company and ensures long-term sustainability. There are five key ‘Cs’ of effective supply chain analytics. These features have been listed below:
- Connected: Supply chain analytics allows organisations to access unstructured data from social media and structured data from IoT (Internet of Things). Also, several other traditional data datasets can be accessed using traditional ERP and B2B integration tools.
- Collaboration: Cloud-based commerce networks are used to enable multi-enterprise collaboration and engagement. This in turn helps in improving collaboration with suppliers.
- Cyber awareness: Achieving cyber security is an enterprise-wide concern. Organisations leverage supply chain analytics to strengthen systems against cyber hacks and intrusions.
- Cognitive ability: Modern supply chains are integrating artificial intelligence (AI) to rapidly assess data and make decisions. AI is being used to make the supply chains automated and self-learning.
- Comprehensive: A modern supply chain can scale its analytical abilities with increasing data. This ensures that the insights are fast and comprehensive.
Types of supply chain analytics
Supply chain analytics includes different kinds of analysis techniques and methods that can be applied to different aspects of a supply chain. Here are some common types of supply chain analytics:
- Descriptive analytics: This type of analysis uses data to identify trends and relations, like supply chain performance or warehouse inventory levels. Historical data is analysed to understand past performance and what is happening in the supply chain.
- Diagnostic analytics: Diagnostic analytics is used to diagnose a supply chain problem like why a shipment has been delayed or why a product is not up to the company’s standard. It is also used to understand why a trend or relationship exists.
- Predictive analytics: In this type of analytics, real-time and historical data is used to forecast the outcomes in a supply chain. Predictive analytics uses statistical modelling, machine learning algorithms, and data mining. It helps predict demand, optimise inventory levels, identify any potential disruptions and overall supply chain planning.
- Prescriptive analytics: This type of analytics analyses the data, prescribes a course of action and provides decision support. Optimisation techniques and simulation models are used to understand various scenarios and suggest an optimal path. Prescriptive analytics helps to make data-driven decisions related to inventory management, production planning, optimisation of transportation, and risk mitigation.
- Cognitive analytics: This type of analytics is used to replicate the human brain’s capability to think and reason. Organisations use it to answer the difficult, complicated questions that arise from large data sets. Cognitive analytics leverages deep learning to understand patterns.
Wrapping Up
Supply chain analytics is used by organisations to make data-driven decisions, improve operational efficiency and boost customer satisfaction. It also plays a key role in gaining a competitive edge in today’s dynamic and complex business environment.
Using analytical tools companies can make necessary changes to the supply chain process which helps boost revenue and better customer experience.
Supply chain analytics requires a blend of technical and domain experts who can leverage the tools and methods to identify areas of improvement. Organisations are always on the lookout for skilled professionals who understand the intricacies of supply chain analytics.
If you want to build a career in supply chain management, check out the Advanced Certificate in Supply Chain and Analytics course offered by Imarticus in collaboration with IIT Roorkee. This six-month course has been curated to help you gain expertise in data-driven decision-making.
Frequently Asked Questions
What are some of the information sources for supply chain analytics?
Data for supply chain analytics is obtained from numerous sources. One such source is the feedback offered by consumers regarding the product or service offered. Historical data is also used to understand the purchase patterns and predetermine the success rate of a particular product.
What do supply chain managers do?
Supply chain managers are responsible for a smooth transition between the various stages of SCM. Their main role is supply chain optimisation to boost portability. They plan the business process, optimise transportation routes, select suppliers, track shipments, and keep records of payments.
How is supply chain analytics used to improve manufacturing in SCM?
Manufacturing is one of the crucial steps of SCM. Supply chain analytics can be used to decrease production time and cost. It can also be used to determine the suitable allocation of resources and improve product quality.
Can AI be used in supply chain analytics?
Artificial Intelligence (AI) can be used in supply chain analytics to automate processes such as data collection, analysis, and interpretation. This allows organisations to gain rapid insights and identify inefficiencies.
