The supply chain is a network between the producer and the consumer. It involves activities which convert the raw materials into products that can be used by the customers. Companies who keep customer satisfaction as their priority will give importance to supply chain management. Supply chain management implies that the speed by which a product gets delivered to the customer needs to be increased. No compromise should be made on the quality of the product as well. Efficient supply chain management helps to reduce the cost of doing business for a company.
Big data is a collection of large masses of data. These data are collected from different sources and can be analyzed to obtain relevant information. By proper utilization of big data, several benefits can be achieved by the companies in the area of supply chain management. The sad part is that two factors limit the full impact of big data, according to Mckinsey & Company. Firstly many supply chain managers do not have any proper knowledge regarding big data. Secondly, many companies lack a structured process to explore the possibilities of Big data analysis. These factors have a very severe effect on the business of a company. Many supply chain managers do not have the vision to see things that can be achieved if Advanced analytics with AI is implemented in the supply chain. Business can run more efficiently, tackle risks and improve their overall performance by doing so.
Businesses should choose quality over quantity if they are made to choose between any of them. Quality data can do a lot more good to you than quantity. Data collected should be relevant to your business. Understanding the type of data that needs to be analyzed is an important thing. After obtaining a precise idea, data should be tracked, captured and analyzed. Only decision-makers with the best and most informed understanding of their data can set the standard for their business’s success, according to Forbes. Artificial intelligence can have a significant impact on the supply chain. Subsets of Artificial intelligence, machine learning and deep learning have an endless potential in supply chain management.
There are numerous benefits of big data analysis in the supply chain, and they are:
- Big data analysis help the supply chain managers to select the right method in the supply chain cycle. They can choose a proper delivery method so that timely delivery is made possible, and thereby, customer satisfaction and experience can be improved.
- Cost reduction- Data collected can be used to establish benchmarks, optimize the process and take well-planned judgments. Having access to quality data within the supply chain can help in reducing the cost to the maximum extent as well as help in making timely decisions.
- By analyzing historical data, risk mapping, and scenario planning, effective risk management can be made possible.
- Transportation efficiency can be maximized– By making use of data, we can keep track of the movement of goods. Proper actions can be undertaken to solve any issues occurring during the transit.
- Data analysis can even help the companies understand the changing needs of customers – timely delivery can be made possible by analyzing data. It will help to improve customer satisfaction. Customer feedback will be available on various websites or social media platforms. It can be collected using data scraping or web scraping and can then be analyzed to improve customer experience further. Customer demands and needs tend to change always. It is wise to keep track of the customer behaviour to provide them with products which will make them happy.
Big data and machine learning if used correctly, can optimize the supply chain management in the following ways:
- Identifying issues – Machines that need some repair or having some failure can be identified by making use of the machine learning algorithms. Using machine learning algorithms to analyze various sounds from machines can help identify the faults in machines. It would help save a lot of time and money. Losant Technologies is making use of IoT and machine learning for industrial predictive maintenance.
- Avoid unplanned downtime – As mentioned before, by using machine learning algorithms, unplanned downtime can be reduced. By using algorithms to track the process continuously can help prevent unplanned downtime, thereby, increasing the efficiency of supply chain management.
- Make predictive analysis possible – Predictive analysis can be made possible by data analysis. Big data helps the business to predict how the economy fluctuate over time. Similarly, big data can help generate weekly forecast the sales volume for upcoming week. According to Deloitte, “Supply ChainTalent of the Future Findings from the Third Annual Supply Chain Survey” also supports this point.
- Optimization of delivery routes – Geo analytics is a way by which many issues that exist in the industry can be solved. GPS data analyzation can help reduce the wait time and can improve the driving up accuracy. “Making Big Data Work: Supply Chain Management“,a report by the Boston consulting group, provided an insight into how big data is being put to use in the supply chain also back this.
- Big Data Analytics in Supply Chain: Hype or Here to Stay, a report by Accenture, states that by incorporating big data analytics into supply chain processes will help to obtain a shortened order-to-delivery cycle. The report also gives an idea about faster and more effective reaction time to supply chain issues is possible by embedding Big data. The following graphic from the same report clearly shows the difference between the performance when big data analysis is embedded in day-to-day operations with ad-hoc basis.
Data analysis can help a business to improve brand reputation, marketing methods, the volume of sales, product quality, and so on. Data analysis combined with AI has the potential to transform the supply chain management completely. With big data having such capabilities, many companies still haven’t started making use of big data analytics. Data can be gathered from any source. But this data as a whole is of no use to the business if you are not analyzing it. After analyzing, necessary plans should be made to implement it as well. With a well-thought-out process, supply chain professional can make the most out of artificial intelligence and Big data. The facilities or technologies to analyze these data are available, and it’s high time companies should start making use of these technologies. Demand for big data will keep on increasing, and there is no way to stop the growth of Data analytics industry.
Sandra Moraes is the Content Management Specialist at Datahut. Professionally she is a Data Scientist and researched Data Analytics. She authored on Data Science and Customer relationship.