What is Supply Chain Analytics?

What is Supply Chain Analytics?

Supply chain analytics is the application of data analysis techniques to the information generated within a supply chain. The objective of supply chain analytics is to improve the efficiency, effectiveness, and performance of the entire supply chain network.

Generally, a supply chain comprises suppliers, manufactures, Wholesalers, retailers and customers. Intense competition and compulsion to reduce costs have impelled organisations to maintain an effective supply chain network. Therefore, organisations came up with various tools and techniques for effectively managing a supply chain.

Globalisation gave a major push to supply chain management. Organisations that operate in a highly competitive global environment need to have a highly effective supply chain management system in place. For example, Apple faces huge demand for their products as soon as the products are announced in the market. Most Apple products are manufactured in China; therefore, Apple needs to have a highly efficient supply chain to ship items from China to different countries in the world.

It can be concluded from the above discussion that the supply chain is a dynamic process in which various parties, such as suppliers and distributors, are involved in delivering products and services to fulfil customer requirements. Thus, in the absence of a supply chain, there would be disruptions in the flow of products and information.

It can be said that a supply chain plays an important role in an organisation. Thus, it is of utmost importance for an organisation to manage activities involved in a supply chain. The activities in a supply chain converts the raw material into a final product which further can be delivered to the customer.

Almost every economy is getting globalised today, and the companies are competing to increase their presence in the global market. The operations performed by global manufacturing and logistic teams are getting more intrinsic and challenging.

Delay in shipments, ineffective planning and inconsistent supplies can lead to an increase in the supply chain cost of the company. Some issues faced by supply chain organisations are as follows:

• Visibility of global supply chain and various processes in logistics
• Management of demand volatility
• Fluctuations of cost in a supply chain

To overcome such challenges in the supply chain, supply chain analytics is used by most organisations or supply chain executives. Organisations are planning to increase their investment in analytics to perform better in the market in comparison to their competitors.

With improvement in supply chain analytics in the past few years, it helps in making decisions for critical tactical and strategic supply chain activities.

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Solutions Provided by Supply Chain Analytics to Supply Chain Organisations

Various solutions are provided by the supply chain analytics to supply chain organisations are as follows:

Use of smarter logistics

The use of smarter logistics helps supply chain organisations in providing more visibility in the global market. With the growth of businesses, opportunities are developed worldwide to lure customers by satisfying their needs related to the product irrespective of the geographical location. As customers are present Worldwide, a complex Web of the supply chain has been created that must be monitored closely to remain competitive in business.

The use of advanced analytics-driven ‘control metrics’ allows the monitoring of real-time critical events and key performance indicators (KPIs) with the help of various touch points. The integration of these metrics with predictive analytics provides a high amount of savings in areas, such as freight optimisation. Organisations that are making investments in supply chain visibility can take decisions to increase supply chain responsiveness, optimise cost and minimise customer impact.

Managing customer demand through inventory management

Due to globalisation and variations in products to fulfil the requirements of globally available customers, demand volatility has enhanced to a significant level. Industries in various sectors, such as retail, consumer goods, automotive need daily or real-time prediction to perform better in the market.

Advanced supply chain analytics can be implemented in these sectors or related industries more precisely to forecast demand and describe and monitor policies related to supply and replenishment. It is also used for planning the inventory flow of goods and services.

Reducing cost by optimising sourcing and logistic activities

The cost involved in the supply chain is a major portion of the company’s overall cost. The supply chain costs significantly impact various financial metrics, such as the cost of goods sold, working capital and cash flow. There is a constant requirement to improve organisations’ financial performance which can manage huge amounts of inventories. The main areas where costs can be handled by using analytics-driven intelligence include materials, logistics and sourcing.

Analytical tools help in providing better visibility to the actual total component cost of products. It is necessary to decide between the buying and selling of products. With the availability of complete information at their fingertips, organisations can decline material purchases through improved practices in the supply chain and better price negotiation.

The fluctuation in patterns of demand of customers and an increased base of suppliers and logistics partners make organisations redesign their logistics network planning. With the growth of the business, suppliers also increase; the companies can use these suppliers against each other by applying analytics to get the lowest price from them. Supply chain managers can use sophisticated analytics programs which can provide them with real-time supplier performance management data to improve their strategies.

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Types of Supply Chain Analytics

Following are various types of supply chain analytics:

Descriptive Analytics

This provides visibility and a channel of actual information throughout the supply chain, whether internal or external systems and data.

Predictive analytics

This assists an organisation with understanding the vital outcome or future scenario and its implication on business. For example, predictive analytics would help you project and neutralise distractions and risks

Prescriptive analytics

This assist organisations with solving problems and partner for maximum business value. This helps businesses to associate with logistic partners in reducing time and energy towards mitigating disruptions.

Cognitive analytics

It helps organisations respond to difficult questions in simple terms in which a person or team might respond to a question. It helps organisations in thinking through a difficult and complex situation like, “How could we optimise or develop X?”

Applying cognitive technologies:

Supply chain analytics also established the application of cognitive technologies like artificial intelligence or AI in the process of the supply chain. These understand, rationalise, educate and interact like human being at an enormous capacity and pace.