A large amount of data is not always able to be controlled 100% from the outside, since it is almost impossible to do this without structuring. The Supply Chain Analytics data management system allows you to reap significant benefits from the analysis of inputs of information, which significantly affects the profitability of the enterprise.
Why Supply Chain Analytics is important for business management
Full control and analysis of Supply Chain Analytics give the user or business owner the following benefits and opportunities:
· Identification of errors at each stage of the interaction of all business participants.
· Ability to correct forecasts and business plans to reduce costs and increase profits.
· The ordering of the data set ensures control at any stage.
· The consumer significantly reduces the risks in case of a cyber-attack, since each cluster with information is encoded individually. In the event of an attack by intruders, the entire supply chain does not suffer.
· Supply chain management increases the quality of logistics. and also contributes to better preservation of the goods.
The main advantage of Supply Chain Analytics in business is to improve the quality of customer service at all stages of interaction with him – from preliminary consultations to custom after-sales service.
How to integrate the system into an enterprise risk management strategy?
Analysts at large companies have always paid great attention to the quality of risk management to reduce the likelihood of default and increase profitability.
What makes Supply Chain Analytics different is its specific approach to risk management.
If earlier the data were analyzed independently by experts, by fragments, today such actions take place within strictly sequential supply chains, which, in turn, makes it possible to detect an error in the previous cluster if a failure is detected at the next stage.
ERM – enterprise risk management. The concept has long been included in the traditional business control system. analysts study the market and also identify potential dangers for business.
By comparing variations, the percentage of risks is reduced to the minimum values. This significantly increases the investment attractiveness and contributes to the growth of the price of the company’s shares.
The risk management process using Supply Chain Analytics is an ordered process that follows a certain algorithm. In this environment for collecting, analyzing, and modifying data, four main features can be distinguished:
· Transparency of operations at each stage of supply, the interaction between the customer and the supplier. Provided that all commodity-money relations are registered and under the control of the managing person, the risks are reduced to almost zero.
· Ensuring the protection of transactions – the system gains access to reverse transactions if an increased risk is detected at some stage in the relationship between customers and the supplier.
· Coordination of logistics at every stage. As a rule, well-thought-out coordination of supplies significantly reduces the risk of failures along the entire path of product movement from the manufacturer to the consumer. Coordination of efforts implies centralized management without taking into account the intermediate control of business processes by different persons.
· A full analysis of the data, regardless of their number in the chain of postings, gives the possibility for flexible transform. Even significant defragmentation of the algorithm, provided that accounting is made, will help to get rid of a huge number of risks and prevent the blackout factor.
Thus, risk management is an integral part of any business process, without which an enterprise cannot reach a competitive level, which leads to its gradual bankruptcy.
The Basic Supply Chain Analytics Apps
Many software developers offer special applications to business participants. The action of the programs is based on the analysis of data in the supply chain. To ensure control, the system detects inconsistencies in the actual algorithm and the boundary conditions embedded in the module.
Data is collected, verified, and processed in real-time, both from outside and inside the supply chain, or intermediate points. Most of the specialized business-oriented applications are adapted to common machine languages, which allows them to be integrated practically into any patches and operating system.
Modern applications are based on the ability to seamlessly connect with all participants in business processes using the technology API. Most applications can work in conjunction with inventory management programs, as well as other specialized applications, cloud storage, and databases.
How to reduce risks in the supply chain?
To reduce risks at all stages of the logistics of goods from the manufacturer to the end consumer using modern IT technologies, it is recommended to take into account the following aspects:
· Providing free access to all data.
· Round-the-clock monitoring of all stages of product delivery.
· Timely prevention and constant monitoring of the normal operation of all electronic applications.
· Development of a preliminary plan with the allocation of responsible persons before the start of delivery.
· Increasing the degree of responsibility and expanding the circle of controlling persons while scaling the business.
Of course, not all risks are taken into account by systems and AI, as supply failures can be affected by climatic features of the area, the human factor, and force majeure. At the same time, according to reports from reputable think tanks, when using applications and Supply Chain Analytics technologies, the risks drop to 10% – 15%.
The Future with Supply Chain Analytics Technology
Supply Chain Analytics handles more and more incoming information every year. The IT technology market is growing several times faster than other sectors of the economy. This means the introduction of new applications as well as advanced control systems into virtually every industry.
Analysts predict the development of this supply chain management market more than 5 times by 2025. All the technologies listed above are based on the principle of the development of the Internet of things, which is also rapidly being introduced into all areas of the economy.
Cloud storage and wireless connectivity at every stage of the supply reduce risk many times over. This will lead to a decrease in the number of employees in the future, which will drastically minimize the percentage of defects and the human factor. As a result, all old-fashioned enterprises will gradually fail to cope with the competitive advantage of artificial intelligence.
