Make Your Supply Chain More Agile With Supply Chain Data Analytics

• By Sunny Kumar
• 25-11-2022
• Data Science

In the present market, the demands and situations are extremely dynamic. This calls for agility in companies that can rapidly change as per the change in requirements. Supply chain agility is the ability of a company to adjust its strategy to meet such demands. For a company to be agile in the supply chain, there must be excellent inventory management and agility in delivering produced goods.

For the Supply chain’s data analytics, there must be quick and efficient stratification, and the quality of the goods must be kept up under all circumstances.

Need For Data Analytics in Supply Chain

As mentioned earlier, the present-day market is more unpredictable than ever before. Manufacturers see unprecedented circumstances that require agile stratification for continuous production. Here are examples of a few situations which prove the need for supply chain agility:

• Supply chain agility can continue the company's industrial production even in case of scarcity of raw materials from a particular supplier. An agile supply chain can quickly look for other alternatives or other sources of raw materials rather than let the yield fall by depending on only one source
• The demand for certain goods may keep increasing or decreasing suddenly. Similarly, the kind of labor that you have may also vary from one time to another. A flexible and agile supply chain ensures as per requirement and quality checked products throughout the year.
• Supply data chain analytics also helps managers to understand the market and the demand curve better, and they can make better strategies by foreseeing the requirements and trends.

Introducing Supply Chain Analytics

The supply chain is one of the most critical units of a company because it is directly related to customer satisfaction, and it is that part of the company that takes most of its funding and investment. Supply chain analytics involves the analysis of the information which companies can collect from their supply chain. A number of software applications are connected to each of the steps in a supply chain that record the database of all that is happening in that particular phase. This includes the supply chain execution systems for procurement, inventory management, order management, warehouse management, and shaping and delivering goods.

How Can Supply Chain Data Analytics Lead To More Agility in the Supply Chain?

• Upon analysis data extracted from these systems can be interpreted, and bottlenecks can be identified to make the supply chain even more efficient!
• Supply chain data analytics help organizations are more agile and make better, quicker, and more efficient decisions about their production and business processes. It gives real-time insight into the company.
• The supply chain data analytics reports and dashboards are instrumental in helping companies identify and understand their potential risks and strong areas. This ultimately leads to improved optimization of their inventory management and more satisfied customers.
• Supply chain data analytics can help companies improve future planning and set more realistic and achievable goals under their maximum potential. Even the risks that the companies take after considering these analytics are more calculated than blind.
• The ultimate aim of data analytics in the supply chain system is to prepare the company for any unforeseen risk, market change, or situation that may need re-stratification of the company processes.

Different Applications Of Supply Chain Data Analytics

There are many supply chain data analytics applications in a supply chain that can make the supply chain extremely agile and efficient. Here are the most striking examples of supply chain applications in data analytics.

Supplier Relationship Management

Most companies involved in the production have numerous different suppliers for even a particular raw material. The ideal supplier is that who caters to all the needs of your company, is reliable, and gets the company the maximum profits. But even the suppliers' behavior is not constant, and it may keep changing as the market changes. Supply chain data analytics helps determine which supplier will presently be the best fit by keeping track of the supplier's activities.

Development of Product

The constant system of feedback that the supply chain data analytics offers to the company helps in quick and efficient development of the product. If for any reason, the production rate does not meet the demand of the people, the supply chain data analytics can help figure out the place hiccup in the supply chain and rectify it so that the development of the product is maintained.

Predictive Analysis

Even though we consider the market to be very volatile and quickly changing, experts can use supply chain data analytics to predict the upcoming trends in the market. This helps the company prepare beforehand and develop a strategy that meets the demand of the people. The data also comprises customer behavior, because of which the company gets an in-depth view of the needs and demands of the customer, and they can use this information to attract and cater to more customers.

Conclusion

Data analytics supply chain helps expose those problems of production that may be hindering the company's growth or draining economic power. Simple solutions can be introduced, new strategies can be framed, and new processes can be developed if a problem is detected through supply chain data analytics.