What is Supply Chain Analytics and Why is it Important?
Supply chain analytics allows businesses to examine their operations and view data in real-time. With supply chain management analytics software, companies can improve decision making, take a proactive approach and quickly mitigate issues before they explode into bigger problems.
Armed with in-depth insights into procurement, inventory management, supplier performance, order management, fulfillment, and more, companies can improve their processes and better manage challenges that arise within their businesses with supply chain analytics.
What is Supply Chain Analytics?
Supply chain analytics makes it possible for businesses to collect data, analyze that data, and make informed decisions. Not only does it allow companies to make quicker and better decisions regarding their business processes, but it also enables them to create long-term strategic plans to help their people, processes, and technology.
Think of the supply chain like a set of dominoes; if any problems arise within a business, that challenge will likely impact several other areas and cost the company time and money. Supply chain analytics allows leadership to target these challenges and mitigate the risks – that include poor forecasting, increasing trade regulations, material shortages, rising shipping costs and more – and craft data-based solutions.
History of Supply Chain Analytics
Supply chain analytics began as the idea of scientific management outlined in Frederick Taylor’s 1911 publication of The Principles of Scientific Management. Not only was the framework of a supply chain adopted by key players in the manufacturing dynasty, such as Henry Ford, but business logistics became critical to successful business intelligence throughout the 1900s.
In the early 2000s, companies began embracing ERP systems to analyze supply chain performance. Not only did these systems allow businesses to forecast any kinks in the supply chain, but they helped organizations find ways to improve their expenditures while still meeting customer demand.
Thanks to the widespread adoption of ERP along with solutions like supplier management software, import management software, supply chain planning and other software, companies have continued to improve their supply chain analytics and find more ways to project data trends and make accurate predictions.
One of the most critical additions to the supply chain analytics system was the adoption of cloud capabilities. Cloud-based platforms improved supply chain processes and made it much easier to communicate with external suppliers using real-time data.
Today, supply chain analytics helps companies manage their businesses and improve all processes. According to data gathered from the IDC, as of 2017, the average supply chain had more than 50 times more data than in 2012. We continue to see businesses use supply chain data and develop better ways to gather and track information than ever before.
What is Supply Chain Analytics Software?
Supply chain analysis software allows businesses to incorporate data from numerous sources, including parts of their supply chain and data from third parties.
Supply chain software can also help analysts turn raw data into easy-to-read visualizations. Data visibility is important for supply chain planning, and visualizations are often created and viewed on the same dashboard and provide access to custom reporting options. Yet, supply chain analytics software does more than convert raw data into usable graphs; it offers insights into:
- Inventory forecasting
- Product allocation
- Fulfillment performance
- Logistics costs
- Order accuracy rates
How Does Supply Chain Analytics Work?
Simply put, supply chain analytics describes how businesses make data-driven decisions to identify problems. Analytics help evaluate the internal and external data across the entire supply chain by reviewing customer and supplier information, third-party sources, infrastructure, and various applications to solve problems. These insights help businesses uncover patterns and design proactive solutions to future challenges.
What Kind of Data is Used for Supply Chain Analytics?
What is supply chain analytics without the use of extensive data? Supply chain management analytics utilizes inbound and outbound logistics information. Supply chain analysts absorb as much data as a company can offer and even recommend areas where they should collect more data.
For instance, the data gathered may summarize inventory turnover rate, warehouse receiving and turnaround times, order accuracy rates, transportation and shipment data, fulfillment costs, and more. In addition, supply chain analytics software must utilize data from suppliers, carriers, and 3PLs to gain a comprehensive review of supply chain systems.
What are the Different Types of Supply Chain Analytics?
There are typically five ways that supply chain analytics evaluates data. By utilizing all five types of supply chain analytics, businesses can gain a better insight into their business operations. Learn more about each way below:
Descriptive
Descriptive analytics looks back at what happened in the past. While analytics can make predictions and solve problems in real-time, historical data patterns are equally vital to decision-making.
Supply chain analytics information comes from internal supply chain software and external systems from suppliers, distributors, sales channels, and customers.
With information from each source, supply chain analysts compare data across different periods, identify patterns, and identify potential causes of risk.
For instance, a manager on the manufacturing floor may review a daily analytics report and become frustrated when their distributors arrive late with their deliveries. Once the supply chain team receives this information, they can use supply chain analytics software to investigate the problem and determine possible causes and solutions.
In this example, they might find that the distributor took on a new client and is now servicing them first on their route before delivering to the company in question.
Predictive
Predictive analytics is vital to determining what could happen in the future.
Instead of waiting for problems to arise and for systems to fail, supply chain analytics helps business leaders proactively consider the possible scenarios before they wreak havoc on their business.
These datasets allow analysts to prepare strategies for when problems arise so that the business can be proactive instead of reactive.
For instance, if the Federal Reserve anticipates an economic downturn, companies may order smaller amounts of raw materials from suppliers or proactively cut back the hours of temporary workers.
Prescriptive
Prescriptive analytics combines descriptive and predictive to make informed decisions.
By analyzing historical patterns and looking into the future to determine potential challenges, prescriptive analytics allows businesses to make decisions, craft goals, and solve problems for the future.
For instance, prescriptive analytics may determine that a mine that gathers raw materials will increase its cost for shipping in the upcoming year due to economic conditions and increased transportation costs.
With this information, business leaders can determine if they should try to find a new supplier of raw materials or find a different way to transport that same material.
Cognitive
With artificial intelligence (AI) technology, cognitive analytics attempts to replicate human thinking and behavior. Using machine learning and deep learning, AI can help businesses reduce the labor required by staff, produce more accurate reports and analyses, and help employees further understand the data.
AI helps manufacturers and business leaders automate the tedious tasks required by staff. Data obtained through AI is highly accurate and can reduce expenses, remove human error in data entry, and provide detailed projections of how much product is required to be successful in the next quarter.
Diagnostic
Diagnostic analytics focuses on previous events and works to answer why something did or did not work. Instead of working in the dark and randomly making changes, diagnostic analytics in the supply chain can help companies determine the best course of action for mistakes, errors, and delays.
For example, supply chain analytics that focus on diagnostic data may work to understand why shipping delays occurred, why there was a procurement disruption, and what reduced carrier capacity. Analysts can make better suggestions to prevent and deal with these problems in the future by reviewing the challenges.
Why are Supply Chain Analytics Important?
Supply chain analytics play a vital role in enhancing company processes and enabling data-driven decisions. Understanding potential risks and planning to counter supply chain challenges provides lasting value to organizations, helping them navigate the global marketplace.
The use of specialized analysis software enhances the planning capabilities of companies by balancing inventory and projecting sales trends, leading to reduced costs and improving risk mitigation and planning.
Real-time insights and comprehensive data access help companies trim expenses while identifying potential problems. With this data, businesses can create actionable strategies to reduce the likelihood of risk or solve problems when they arise, promoting overall stability within the supply chain.
Accuracy in planning, facilitated by supply chain analytics, is essential for predicting future demand and planning for materials. This corrects common issues of having too little or too much inventory, reduces errors, and increases profits. For these reasons, supply chain analytics within business strategies is indispensable to success and ultimately enhancing customer satisfaction.
The Five Cs of Supply Chain Analytics
Since supply chain analytics has taken a prominent role within leading businesses, researchers and organizations have identified the top 5 features to look for in supply chain analytics. The research group IDC uses the “five Cs” of the supply chain to summarize the leading features to look for in analytics:
Connected
Supply chain analytics must help connect sources and analyze various Avenues of Technology. A key component of Supply Chain management analytics is the ability to access data from multiple sources and ensure their data is connected. After unifying their data, businesses can access unstructured and structured data through ERP and B2B integration technology.
Collaborative
Collaborative supply chain analytics promotes cooperation between suppliers, partners, carriers, and other parties. Improving collaboration with various suppliers and even customers makes it easier to enhance processes and products. One of the best ways to do this is to utilize Cloud Solutions so everyone can seamlessly exchange ideas and information.
Cyber “aware”
Cyber security is vital to remain secure from cyber intrusions. For that reason, businesses must have robust cybersecurity resources and should consider employing outside experts to help protect their supply chain data.
Cognitively Enabled
The integration of AI technology helps to improve the supply chain system. Not only does supply chain analytics improve with the use of technology, but it can help companies better understand problems, gather accurate data, and recognize solutions.
Comprehensive
Daily reports or one-off insights can only provide so much information. For that reason, software for the supply chain must have extensive and comprehensive data. Supply chain analytical capabilities must include real-time data so that Business Leaders can make decisions and offer insights based on up-to-date information.
What are the Benefits of Supply Chain Analytics?
There are many long-lasting benefits of having a powerful supply chain analytics system. Supply chain analytics allow business leaders to make decisions with real-time data and uncover insights and patterns that introduce new opportunities to improve processes.
From improved visibility to avoiding stockouts, the benefits of supply chain analytics are significant. Some common benefits of implementing supply chain analysis software include:
- Reduction in late shipments
- Enhanced resource allocation
- Deeper understanding of customer preferences
- Improved order management
- Increased accuracy in planning
- Enhanced risk management
- Greater customer satisfaction
Supply Chain Analytics is an Imperative for Your Business
Supply chain analytics have become a crucial tool for manufacturers and business leaders. As we have seen, this technology empowers organizations to make data-driven decisions, forecast potential challenges, and optimize various aspects of their operations.
QAD is among the providers that offer advanced solutions to address complex global supply chain issues. Our digital tools help in real-time decision-making and contribute to long-term strategic planning, connecting people, processes, and technology.
We cannot overstate the role of supply chain analytics in shaping efficient and resilient business strategies. From historical trends to predictive insights, companies across industries are leveraging these analytical tools to drive growth, reduce costs, and navigate the ever-changing landscape of the global marketplace.
To learn how to manage supply chain analytics more efficiently and effectively, Contact QAD for more information.
