A well-functioning and smooth supply chain are crucial for the success of any service/product-based business. A simple supply chain has four basic elements, and all these elements should work in coherence with each other to ensure the seamless completion of a supply chain. Overall, it is a complicated process that requires regular monitoring to adjust it according to the supply and demand trends in the market. Data analytics is employed to design and improve excellent supply chains and manage them efficiently over time.
Big data that provides valuable insights regarding each step of the supply chain is known as supply chain analytics. The popularity of e-commerce is forcing businesses to streamline their supply chains to ensure timely and affordable deliveries to their customers.
Data analytic software is employed to collect data from any part of the supply chain. A competent data analyst or manager analyzes that information to design a supply chain strategy based on data-driven results. Candidates with the knowledge of business administration and data analytics can be ideal for such a job because they are aware of both the business and data-related complications of a supply chain and can optimally use data to better the company. Various colleges across the US offer an MBA in data analytics. Therefore, pursuing an online MBA in data analytics will make you eligible to work as a supply chain manager. You can use this knowledge to help businesses improve their supply chain strategies.
Improve Supply Chain Strategy with Data Analytics
In this article, we are going to discuss some ways to improve supply chain strategy with data analytics.
1. Predict Future Demand
Demand forecasting is crucial for building an unwavering supply chain and improving the supply chain strategy of a business. Advanced data analysis techniques like predictive forecasting, data mining, and predictive analysis can help companies predict future demand and make intelligent decisions accordingly.
Data analysis techniques allow you to collect and analyze the history of orders and inventory of your business. Data analysis can help predict future orders so that you won’t end up over or understocking, costing your business a large amount of money.
2. Improve Operational Efficiency and Productivity
Inefficient logistics or operations can reduce productivity and affect the supply chain. Therefore, supply managers can use a data analysis method called sales and operations planning (S&OP) to improve the operational efficiency of a supply chain.
Similarly, business intelligence (BI) also provides access to data about past consignments, stock levels, inventory turnover, and sales ratios. Analyzing that data using different BI tools can help businesses optimize the overall operations by accelerating the process, improving productivity, and amplifying profits. According to Forbes, using advanced supply chain analytics to increase productivity can also help reduce total costs by 56%.
3. Improve Product Tracking in the Supply Chain Process
Product tracking is crucial for reliable supply chain operations. Products can be tagged with a radio frequency identification (RFID) tag or printed with barcodes for traceability. A barcode scanner or a radio frequency identification device can easily provide valuable information (expiry date of food products or price) regarding a product.
Data analytics helps companies track their products from the production process to the market shelves. Tracking products allows for an easy distribution process and communication regarding products during different supply chain stages. Easy access to valuable information about the product can also help distributors make timely deliveries without damaging the product or compromising its quality.
4. Reduce Flaws in your Supply Chain Strategy
Data analytics tools help you view recurring data patterns in your supply chain, which can be beneficial to pinpoint potential problems. Consistent data analysis can help you stay on top of your supply chain process. Data analysis can provide you with details regarding the amount of raw material available and the amount needed for a specific order so that you can timely contact the supplier or change the supplier to meet the demand.
Data analytics tools can notice even minute changes in production time, allowing you to be prepared and plan for product delivery accordingly. Moreover, data analytics reduce the risk of loss to the business by reducing the flaws and improving the supply chain strategy.
5. Understand Consumer Behavior
Consumers demand high-quality services and products, and their buying behavior can vary. In the past, consumer behavior rarely affected the supply chain, but now consumers have significant influence over the supply chain. According to a research paper published in the International Journal of Physical Distribution and Logistics Management in 2015, environmentally conscious consumers prefer not to purchase from businesses that employ questionable environmental practices in their supply chains.
Moreover, data analysis can help observe the buying pattern and predict consumer behavior. For example, an increase in demand for a specific product can be analyzed through data analysis, and businesses can adjust their supply chains accordingly to meet the increasing demand. It allows companies to retain customers and increase their revenue.
6. Optimize Capacity Planning
Predictive data analysis techniques are employed to monitor the market trends and evaluate the production capacity of your supply chain. It provides a comparative data report that allows you to balance the supply chain by adjusting the availability of raw materials required to engineer enough products that meet the market demand.
Data analysis provides several valuable insights regarding supply chain operations, raw material inventory, and warehouse stock. All these factors can be adjusted according to demand and provide an excellent basis for capacity planning, helping optimize the supply chain.
The Bottom Line
The supply chain is a crucial part of any business. An efficient supply chain streamlines the whole process of product formation from production to retail store shelf. Designing and managing a well-functioning supply chain requires skilled managers and data analytics. Various data analysis techniques can be used to design, implement, and improve a good supply chain strategy.
Supply chain data analytics can help predict future demand, improve product tracking, and improve productivity and operation efficiency in all parts of a supply chain. Moreover, an efficient supply chain also reduces flaws in a supply chain strategy. Understanding consumer behavior can also be easier through big data analysis. Overall, data analytics is needed for a seamless supply chain. Hopefully, this article will help you understand the ways to improve supply chain strategy with data analytics.