In the current business environment, which is full of volatility, uncertainty, complexity and ambiguity, any organization faces two most important challenges. These are development of new products which can fulfil customer expectations and second is developing a suitable supply chain for this product. In the present context, supply chain is not limited to ensure the supply of the product to the customer, rather companies want to take competitive advantage from their supply chains. Many e-commerce companies are investing huge resources in improving their supply chain capabilities so that they can take strategic advantage from the supply chain.
"With the help of cognitive technologies, supply chains can understand, reason, learn and interact like a human but at enormous capacity and speed"
In developing a sound supply chain, which can provide you advantage, many Indian organizations have done tremendously well including Maruti, Amul, Indian Post, Patanjali etc. But in most of the cases in India, supply chain is not owned by a single actor. Fragmented ownership of supply chain is a big impediment in making sound decisions for supply chain. Original Equipment manufacturer (OEM) can control immediate predecessor and successor but supply chains are sufficiently long and many a times OEM does not know the end partners of the supply chain. Fortunately, development of Information Technology is helping in integrating various actors of supply chain.
Supply chain analytics will only be helpful when decisions are taken for entire supply chain. If we optimize individual stations in the supply chain, then the whole philosophy of supply chain will be lost. With the help of supply chain analytics, organizations can improve operational efficiency and effectiveness by enabling data- driven decision making at all three levels, i.e. strategic, operational and tactical.
Supply chain analytics is not limited to analysis of huge amount of data which is generated from different sensors and digital platforms. It is much beyond the analysis. Therefore, a good supply chain analyst should understand the context as well as tools for analysis. Earlier only structured data was available, which was easy to analyse, like data available from point of sales. Now huge amount of unstructured data is generated. Supply chain analytics is ability to use this very large unstructured data for meaningful decision making. The most critical part of decision making is speed of developing information and taking actions on it. For example, if traffic on a toll road is increasing, system should increase the rate of toll, so that who want to use that road for taking the benefit of faster travel can actually achieve it, however at a higher price and those travellers who are cost sensitive will take a longer route to avoid high rates of toll. In a day, these fluctuations in toll price may take place many a time, based on traffic condition. This ability of the system is possible when we are feeding CCTV data to computer systems to calculate traffic density at any point of time, and based on this information toll prices are automatically decided.
Learning supply chain analytics is becoming important for supply chain managers. But it is important for them to make a proper balance between the basic aspects of supply chain management and then understand how decision making can be improved with the help of data analytics. Generally, supply chain managers need to make decisions for locating new facilities, their size, role in the supply chain. They also take decision regarding inventory level in the supply chain. Inventory level is directly related with service level and cost of meeting this service level. Third important decision is related to transportation activities, which include size of vehicle, route planning etc. Decisions with respect to facilities, inventory, transportation depends on supply chain strategy and business strategy of the organization. Supply Chain Analytics will help in improving the decisions so that a better fit can be achieved between business strategy and supply chain strategy.
The field of supply chain analytics borrows knowledge from the field of supply chain management and data analytics. At times, focus is only on data analytics and basic area of decision making takes a back seat. This will not serve the purpose. Learning supply chain analytics is like walking on a tight rope. A perfect balance is needed between supply chain concepts such as efficient supply chain and responsive supply chain, optimization for various supply chain decisions and using data for real time decision making.
Now adays, we hear about cognitive technologies such as artificial intelligence, machine learning and deep learning. Supply chain analytics is the foundation for applying cognitive technologies to the supply chain decision making. With the help of cognitive technologies, supply chains can understand, reason, learn and interact like a human but at enormous capacity and speed. It is becoming almost mandatory for the new era, where Industry 4.0 type of concepts will change the way we work. Industry 4.0 will support communication between various devices. CCTV can communicate with laptop. Mobile phone can communicate with washing machine and air conditioner and so on.
This advanced form of supply chain analytics is ushering in a new era of supply chain optimization. It will reduce human intervention and will automatically sift through large amounts of unstructured data to help an organization to improve forecasting, identify inefficiencies, respond better to customer needs, drive innovation and pursue breakthrough ideas.
Supply Chain analytics is providing large number of career opportunities to young managers. Some industry sources have projected that supply chain analytics global market will touch $4.8 billion mark by year 2025. This means, the scope is not limited to India but to other developed nations also.