Supply Chain Management

A Full Guide What is Supply Chain Analytics

Supply Chain Analytics

Because it directly impacts a company’s ability to offer a positive customer experience and also accounts for many of its expenses that can impact overall profitability, the supply chain is an essential piece of the puzzle for success. The supply chain is the network of suppliers, businesses, and end-users. It covers everything, from raw material sourcing to delivery to end consumers. businesses can use supply chain analytics to analyze supply chain data.

Many businesses recognize the importance of their supply chain and have increased their supply chain management (SCM). They are looking for ways to speed up, make it cheaper, and make the long journey from a raw material supplier to end-user easier. This is particularly important as supply chains are becoming more complicated over time. Companies work with increasing numbers of international partners and are under greater pressure to deliver their products quickly.

Many people, organizations, and activities are involved in supply chains, creating a lot of information. Supply chain analytics can help you make sense of this overwhelming data and turn it into easily digestible dashboards, reports, and visualizations that will influence key decisions and improve results. In a competitive landscape, it is crucial to have easy access to these analytics.

What Is Supply Chain Analytics?

The analysis of data from supply chain applications is supply chain analytics. This includes information drawn from many applications that are tied to supply chain management systems, such as order management, fulfillment, and procurement. A supply network works as a series of dominoes. Each step affects the next, and any problems at any stage can impact customer satisfaction.

Each of the software pieces mentioned may have its own reporting capabilities, which can shed light on a specific step in the supply chains, such as the predicted lead time for suppliers, safety stock levels at warehouses, or the number of orders fulfilled per hour. However, supply chain analytics can be most effective when all the systems are connected, often via an Enterprise Resource Planning system.

To present and describe data from the global supply chain, you can use either an ERP or another program. Businesses can use supply chain analysis to identify suppliers and/or processes that could be avoided, reduce inventories and schedule events and programs, and improve forecasts.

It gives employees a complete view of the logistics network, allowing them to understand both the upstream and downstream effects of any disruption. The system allows them to quickly respond in a manner that minimizes the problem as much as possible. Some systems can even send alerts in real-time to warn of potential problems before they become a bigger problem.

Also read: Top 10 Manufacturing Analytics Use Cases in Supply Chain

What Is the Role of Supply Chain Analytics?

Companies can use supply chain analytics to analyze, evaluate and act on the data generated from their supply chains. This allows companies to not only make quick adjustments but also long-term strategic decisions that will help them gain a competitive advantage. It is nearly impossible to manage supply chains that span the globe and include hundreds of entities. It is at best inefficient.

Supply chain analytics can be used to plan for demand (using historical data and other variables to predict what customers will buy); to plan sales and operations (manufacturing or purchasing the goods that an organization needs to meet forecasted demand); to manage inventory (tracking sell-through and which SKUs it must replenish); These activities can all be used to increase efficiency and reduce costs.

By planning more accurately, you can avoid excessive spending on procurement and stockouts. This will also help to reduce excess inventory (which could lead to obsolete inventory). Your business can keep costs low while still providing a great customer experience, which will make you stand out from your competitors.

Today’s most successful companies continue to use supply chain analytics as a key part of their daily operations. These numbers are being more closely monitored by organizations than ever before. They also use various analytics techniques to optimize every link within the network.

Why Is Supply Chain Analytics So Important?

Supply chain analytics can help companies in all industries make faster, more informed decisions about how they run their businesses. It delivers lasting and real value to companies who use it.

These dashboards and reports help companies understand and identify their potential risks and improve their planning. They also optimize their inventory management to better meet customers’ high expectations. Analytics software might detect if a particular transportation provider is consistently late in delivering shipments over the past month. This software can detect the pattern and indicate the possibility of further delays. The solution can also quantify the effect of such delays, including the potential delivery times and the cost of return/chargebacks.

Analytics can help you plan better by providing more accurate forecasts that allow you to put in place all the operational pieces necessary to meet your expected volume. A retailer may notice a steady increase in sales and anticipates the holiday season. It might place more purchase orders with suppliers or hire more contractors to ensure it is ready for the surge in orders. The retailer can search for alternative suppliers if there isn’t enough capacity to handle these large orders.

Businesses often have either too much inventory or too little. This is not ideal. Excess inventory exceeds the cost of required inventory while running out of items means lost sales. Analytics can help you balance your inventory to avoid stockouts and keep costs low. Based on the average lead time for each supplier, the system may trigger an alert for SKUs running low. The operations team can use sales trends to help them decide which items need more warehouse space, and which ones should be phased out or kept low-quality.

All of these numbers and metrics help businesses meet customer needs. Any hiccup in the supply chain could negatively impact customer experience and possibly cause them to shop elsewhere. Companies can also track analytics that directly impacts the customer experience, such as order accuracy rate and on-time delivery rate, in order to identify and correct any concerns.

Types of Supply Chain Analytics

Companies should be aware of four main types of supply chain analytics to improve their operations and save time and money.

Descriptive Analytics

Descriptive analytics examines the past. They are able to identify patterns in historical data. This information can be derived from both internal supply chain execution software and external systems that provide visibility to customers, suppliers, distributors, etc. Analytics can be used to compare data from different periods and identify patterns.

A manufacturer might review its descriptive analytics dashboard daily and find half of its distributors’ deliveries are late. The company’s leaders can investigate the problem further and discover that the snowstorm that hit the area where the distributors are located has caused delays in its deliveries.

Predictive Analytics

Predictive analytics, just like the name implies, helps companies to predict what could occur and the business impact of various scenarios including possible supply chain disruptions. Leaders can become proactive and not reactive by forcing them to think through these scenarios. Leaders have the time to plan for a spike or fall in demand and can then react accordingly.

If the same manufacturer is looking at it, it might review the Federal Reserve’s latest economic projections and predict that sales will drop by 10-20% over the next quarter. It orders fewer raw materials from suppliers and reduces the hours of part-time employees for the following month.

Prescriptive Analytics

Prescriptive analytics combines the results from both descriptive and predictive analytics to recommend what actions a business should take to achieve its goals. This type of analytics can help companies address problems and prevent major supply chain disruptions. It may be possible by evaluating their own data and the information of other partners. Prescriptive analytics require more sophisticated software that can quickly process and interpret large amounts of data.

Prescriptive analytics can tell a manufacturer that it has a major supplier in Southeast Asia and may be at risk of going out of business next year. This outcome is likely due to a history of declining economic conditions, late orders, and reduced capacity. The manufacturer can request that the supplier’s executives meet with them to determine if they are in financial trouble and what it might do to help. If the matter is not resolved, the company can begin to look for other suppliers to replace it.

Also read: What is Distribution Management and Planning?

Cognitive Analytics

Cognitive analytics attempts to mimic human thinking and behavior. They can be used to help companies answer complex, difficult questions. These analytics can understand the context and interpret results. Cognitive analytics uses artificial intelligence (AI), particularly machine learning and deep learning to achieve this. This allows cognitive analytics to grow over time. This allows staff to reduce the time required to create these reports and analyses. It also empowers other employees to extract results and to understand them.

The manufacturer’s AI-enabled software may allow it to automate a lot of the work involved in demand planning. It could use all data available, including external and internal factors, to generate highly precise, detailed recommendations for how many products it should produce in the next quarter to meet the demand. This helps to reduce the extra costs associated with producing more inventory than is necessary and also prevents lost sales due to failures in meeting demand.

Benefits of Supply Chain Analytics

We’ve seen that accurate supply chain analytics can have long-lasting and profound benefits. They can provide valuable insight and patterns that help to improve supply chain operations at all levels. They can identify opportunities for process improvement and alert operations leaders to potential problems they may have missed. Analytics can be a valuable tool for identifying supply chain risks and anticipating future ones.

Real-time analytics can also help firms and companies improve their profitability, avoid stockouts and reduce shipment delays. It also allows them to adapt to changing customer preferences. This data helps companies optimize their use of resources and leads to cost savings. Without this data, many decisions are made based on guesswork or historical data.

Supply chain analytics is a key step towards achieving data-driven organizations. Simply put, supply chain analytics can help company leaders make better decisions when they have access to detailed information about their supply chains and reports.

Challenges of Supply Chain Analytics

The greatest challenge in supply chain analytics is the high barrier to entry. For those who currently lack the systems to gather these insights, purchasing the technology can be significant – though worthwhile – investment. It is not possible to rely on email, spreadsheets, and point solutions to collect and review critical data. Supply chain management systems are essential for businesses to track goods from their raw materials through to delivery. An analytics solution is required to turn the data into useful reports or visualizations in order to fully take advantage of it.

A business must also have robust processes in place to collect all necessary data. It is important that all information from the supply chain be stored in a central database. This requires reliable integrations. An organization can only understand its current supply chain status and outlook if all data flows smoothly.

The skilled labor required to create and interpret certain analytics is another challenge. Although software makes analytics more accessible for supply chain workers, many of whom don’t have any data science background, it is still important to consider whether your organization has the right people to help you. It may not be necessary to train your employees on how to use the analytics solution. This is a major concern for larger companies who want to take advantage of the latest technology to gain deeper and more detailed insights into their supply chain.

Features of Supply Chain Analytics

Leaders may be asking what to look for when looking for supply chain solutions as supply chain analytics becomes more prominent in many organizations. The “five Cs” are five key features that IDC, a research group, has identified as important in supply chain analytics.


Supply chain data analytics efforts start with data. It’s crucial that the solution has access to all relevant sources of information. These connections extend beyond the ERP system and other business systems to include any technology that your business uses to collect data, such as IoT devices.


Supply Chain Partners are crucial to your success. Businesses should never lose sight of this. Businesses should work with suppliers and customers, where possible, to improve products or processes. These parties can now exchange ideas and information in a much more efficient way with cloud solutions.


As businesses add more software to their networks, cyberattacks are becoming more common. This is something companies need to recognize and rely on their internal cybersecurity resources as well as outside experts for assistance in equipping any systems that are connected to their analytics with the required protections.

Cognitively enabled

Cognitive analytics, Cognitive analysis, which, as we have noted, uses AI to draw their conclusions, will undoubtedly play a greater role in supply chain and logistics analytics over the coming years. Cognitively enabled analytics allow companies to quickly assess the impact of disruptions and prioritize their response. This solution is more efficient over time and opens the door to further automation.


Reports and insights that are only a few pages long can only take you so far. An organization must have comprehensive and detailed observations in order to reap the benefits of analytics software. The solution must not only provide extensive functionality but also the ability to scale as it processes increasing amounts of data.

Also read: 9 Best Tools Help in Supply Chain Management

Supply Chain Analytics tools

Analytics is becoming more crucial as the pace of business increases and supply chains around the globe become more complicated and longer. To gain better insights and reduce risk, a growing number of companies are turning to supply chain analytics tools.

This software converts a lot of logistical data collected from your operations into dashboards that managers and executives can easily access. Based on this information, executives and managers can make adjustments or recommendations.

This software is designed to help managers keep optimal inventory levels, meet all customer orders on time and in full, as well as procure and/or fulfill orders. It can also improve profitability by allowing them to make recommendations, adjust, or even change their mind. It automates many of the manual tasks required to achieve these goals, allowing managers to concentrate on more value-added tasks.

Advanced analytics software supports cognitive and prescriptive analytics. It also provides in-depth reporting capabilities. This will be particularly valuable for larger companies, which spend millions of dollars annually on supply chain-related expenses.

Future of Supply Chain Analytics

In recent years, the supply chain has been a center of innovation as many companies realize that this area is ripe for cost savings and improved customer service. Analytics will play a crucial role in achieving many organizations’ goals of greater supply chain transparency and visibility. The global supply chain analytics market is expected to exceed $10 billion by 2025.

Prescriptive and cognitive analytics is still not possible for smaller businesses due to their high cost and time commitments. However, this is changing rapidly and will soon become more accessible. To give small businesses the same benefits as enterprises, leading suppliers of supply chain software in the emerging and mid-market sectors are already incorporating AI.

As companies digitize and adopt IoT devices in factories and warehouses, supply chain analytics will draw from a larger data set over the coming years. Technology providers will use a variety of technologies that fall under the AI umbrella to transform this ever-growing data set into useful insights. This is the only way companies can actually reap the benefits of the huge amount of information that comes from their supply chain.

Choosing the Right Supply Chain Management

Without a supply-chain management platform, any supply chain analytics project will fail. This software manages your supply chains from beginning to end, including procurement, warehousing, storage, picking, fulfillment, shipment/delivery and reverse logistics. The supply chain management software manages every piece of the network and provides the necessary data to enable supply chain analytics. Some SCM solutions include built-in analytics.

There are many supply chain management software options. Not all solutions offer the same functionality and features. Businesses should be careful when choosing a solution that will meet their future and current needs. When choosing a platform to help them create more efficient and stable supply chains, companies should consider data reliability, ease of use, and ROI. Companies can begin to reap the many benefits of supply chain analytics once they have chosen software that is right for them.

Written by
Aiden Nathan

Aiden Nathan is vice growth manager of The Tech Trend. He is passionate about the applying cutting edge technology to operate the built environment more sustainably.

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