A Guide to Understanding Analytics in a Supply Chain

By Indeed Editorial Team

Published January 3, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

The supply chain is a vital component of business success because it can influence a company's capacity to deliver a pleasant customer experience and account for a large portion of costs. This chain is a web of suppliers, businesses, and consumers covering elements from resource procurement to end-user delivery. Understanding how to apply supply chain analytics can help you make company operations faster and more cost-effective. In this article, we discuss how supply chain analytics work, explain what a supply chain is, explore the types of analytics, highlight its importance, and answer some frequently asked questions about a supply chain.

How do analytics in a supply chain work?

Using analytics in a supply chain can help bring together information from various applications and third-party sources to optimize decision-making across the positional, strategic, and functional mechanisms that constitute supply chain management. By enhancing real-time insight into supply chain activities and their effect on consumers, supply chain analytics can help coordinate supply chain planning and implementation. Improved visibility can also increase supply chain network flexibility by enabling decision-makers to make more informed trade-offs between expenses and customer satisfaction.

The process of developing supply chain analytics often begins with data scientists who have a thorough understanding of a specific aspect of the business, such as working capital, stock, and service standards. These professionals look for connections between various data streams to develop a predictive model that maximizes the supply chain's output.

Read more: Analytical Skills Defined and Explained

What is a supply chain?

A supply chain is a channel between a firm and its suppliers to create and market a specific item to the final customer. This channel includes various operations, individuals, entities, data, and resources. Additionally, the supply chain depicts the stages involved in getting the good or service from its origin point to the consumer. Firms may establish supply chains to minimize costs and stay competitive in the business environment. Supply chain management is critical because a well-managed supply network can result in fewer expenses and a faster production process.

What are the steps in a supply chain?

The following are the critical steps in a supply chain:

  • organizing the inventory and production operations to guarantee a suitable balance between supply and demand

  • producing or acquiring the resources required to develop the final product

  • assembling components and assessing the completed product

  • packaging the item for delivery or retaining in inventory until a future date

  • transporting and conveying the final product to the distribution company, retail outlet, or customer

  • providing consumer service assistance for product returns

What are the types of supply chain analytics?

There are four primary types of supply chain analytics that firms can consider when developing more efficient operations that can save time and finances. Below is a short description of each type:

Descriptive analytics

Descriptive analytics evaluates previous events and can identify patterns using historical statistics. This data may emerge from organizational supply chain technologies or external frameworks offering input across distributors, carriers, multiple sales intermediaries, and consumers. Descriptive analytics can reveal patterns and infer potential reasons for shifts by considering similar forms of data from multiple time intervals.

A manufacturer may examine a descriptive analytics report on a regular basis to determine whether the company's shipments to distributors are on time or behind schedule. If delays often occur at a particular location, the manufacturer can then investigate the matter more and discover, for instance, that a blizzard usually affects the area where that network of distributors operates during that time of the year, slowing down its shipments.

Read more: Understanding How to Complete a Risk Analysis

Predictive analytics

As the term suggests, predictive analytics can enable businesses to anticipate what may occur and the commercial implications of various events, including potential chain interruptions and other business implications. By compelling managers to examine these potential outcomes in advance, they can develop strategies to use if these events occur. For example, managers may have the opportunity to prepare for an anticipated rise or decline in demand using predictive analytics and can react appropriately.

For instance, a manufacturer may assess recent financial forecasts and predict sales can decline by 15 to 18% over the coming three months. They may prepare for this outcome by placing smaller orders with raw material suppliers and reducing part-time employee hours for the coming month to save money.

Prescriptive analytics

This type of analytics incorporates predictive and descriptive analytics to suggest actions that a company can perform immediately to accomplish its goals. These analytics can assist businesses in addressing issues such as large-scale supply chain interruptions by assessing their own statistics alongside those of other business associates. As this type of analytics is more complex, it requires more sophisticated technology, such as business intelligence software, to efficiently analyze and simplify massive data sets.

For instance, prescriptive analytics may assess suppliers considering metrics such as constant delay in supplies, lowered production capacity, and declining economic circumstances. Using these statistics, this type of analytics can inform the manufacturer when there's a possibility that a supplier may halt operations within the following months. In response, the manufacturer may request a meeting with the supplier's management to determine whether they're experiencing financial complications and how the manufacturer might be able to help. If both parties can't reach a clear compromise, the manufacturing company might assess other supplying options to maintain their schedule.

Cognitive analytics

Cognitive analytics aims to emulate human reasoning and behaviour, which can help businesses resolve demanding, complicated issues. When interpreting data, these analytics might account for contextual factors. It performs this function through the use of artificial intelligence (AI), specifically deep learning and machine learning, which can enable it to become more intelligent over time. By using this technology, companies can significantly minimize the amount of effort needed by employees to develop these insights and assessments while also allowing other teams apart from the data science team to extract and interpret results.

With AI-enabled applications, the manufacturer may be able to optimize most of the work that accompanies supply chain planning. The technology can analyze all available information, along with internal and external influences, and provide very reliable, informative suggestions for the quantity of each product that the company can create in the following months to satisfy demand. This function may eliminate the additional expenses that may result from producing more stock than necessary or missed sales because of the inability to fulfill demand.

Read more: What Is Quantitative Analysis?

Why is supply chain analytics important?

Supply chain analytics can assist a business in making better informed, timely, and efficient decisions. The following are some of the benefits:

  • Cost savings and increased margins: You can obtain detailed data to enable seamless synchronized management and real-time insight into multiple data sources that contribute to operational effectiveness and valuable discoveries.

  • Increased awareness of risks: By identifying patterns and trends throughout the supply chain, supply chain analytics may help detect current risks and forecast potential risks.

  • Enhanced planning precision: Supply chain analytics can aid a corporation in forecasting future demand by studying client data. It may enable a business to determine which items may no longer require maximum production as they become less lucrative or anticipate future client demands.

  • Constructing a lean supply chain: Supply chain analytics can enable businesses to monitor warehouse activity, partner reactions, and consumer demands to make more educated decisions.

Frequently asked questions about supply chains

Below are some answers to some frequently asked questions about the supply chain concept to help your understanding:

What is the difference between supply chain management and business logistics management?

Professionals may frequently use the terms supply chain management and business logistics management, or logistics synonymously. Logistics is a component of the supply chain. Logistics refers mainly to the aspect of the supply chain that relates to the organization and regulation of the transportation and storage of products and services from their original location to their end destination. Logistics management starts with raw materials and finishes with the shipment of the final product. Effective logistics management can guarantee that deliveries occur on time and in excellent condition at all stages throughout the supply chain.

Read more: Guide to Standard Deviation in Finance and How to Calculate

What is the relationship between supply chain and deflation?

Over time, supply chains have evolved and become more efficient, which has helped to check inflation. For example, as efficiency in supply and delivery from point A to point B increases, transportation costs typically decrease, which can lower the final price of the product. While experts may usually view deflation unfavourably, supply chain efficiencies are among the few instances where deflation can be beneficial.

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