Role of Technology in Supply Chain Management

Technology is playing a key role in supply chain management for digital transformation

Within all supply chains, is a data chain that is vast, complex, and ever-growing. The data collected from these supply chain processes are often not consolidated, if consolidated not analyzed, if analyzed not interpreted well, for the benefit of the Company. Thus, we need highly advanced and updated technology solutions to proactively manage the supply chain data. Artificial Intelligence, Machine Learning, Blockchain, and Digital twins are the leading technologies that supply chains are opting for to bring increased efficiency and transparency to the processes. For some domains, these solutions work well individually, for others, they can be combined to better understand the data, find operational gaps and define steps to take immediate corrective actions.

Where can you see the impact of technology implementation in the supply chain?

In today's era, technology assistance is needed in each and every step and function of the supply chain process. Supply chains generate big data and analytics is needed to streamline this data to information & gain intelligent insights. Let us have a look at the individual stages of the supply chain & understand how technology helps in bringing improved efficiencies.

Starting from the Planning stage. It is undoubtedly the most data-consuming stage of the supply chain process as it needs even the minutest of the details to predict, plan and align the operations. Planning as an operation is interlinked with all major supply chain stages like manufacturing, logistics, inventory, warehousing, packaging, etc. Thus, data needs to be continuously pulled in from all the software that individually manages these processes. For example, Analysis of data from WMS is helpful to plan the inventory and accordingly run the manufacturing. Similarly, data from ERP gives an overview of orders helping the system understand market demand and accordingly work with manufacturing & transportation to give the requisite supply.

Nowadays, technology has revolutionized the production/manufacturing stage to another level. Especially, if we see the chemical or paint industry, the machinery now is capable of interpreting the product composition and properties and automatically defining the right method of production of the product as per the customer requirement. For example, BASF, a German producer of paints recently adapted machine learning technology to interpret customer requirements & give inputs to manufacturing units to prepare the paints in the composition required by the clients. Quality assessment is another area where technology has helped various industries. Agricultural seed processors use a variety of cameras in real-time to get the quality assessments of seeds. This kind of data is collected, compiled, and analyzed to get compliance reports that can further help in strengthening the manufacturing processes.

Then comes the most important stage of supply chain management – Logistics & Transportation management. This stage alone takes up 70-80% of supply chain costs hence, we need to make sure it functions at its 100% efficiency. This stage consumes a lot of data starting from details of the goods, consignor/consignee information, vehicle & vendor details, route to be followed, driver details, driver performance, etc. Thus, this phase needs a lot of coordination internally within the department and with external devices & agencies. Fuel consumption, Speed compliance, On-time deliveries, and Delivery plan are a few of the key analytics that directly helps in performance evaluation & logistics cost savings. We, at Elixia, have completed almost 12Million trips & helped various companies save 5-10% of their logistics costs.

Apart from these stages, analytics also plays a very crucial role in Vendor or 3rd party management. A successful supply chain works in close collaboration with vendor partners who come into the picture at all stages of the supply chain. Data, technology, and ultimately analytics make it possible to consolidate all data and keep a track of their performance, which finally comes in handy at the time of contract renewals. For example, if a company deals with multiple vendors for transportation then it's imperative to have constant tracking of parameters like trips completed, rates provided (in comparison to market rates), their order acceptance rates, and OTIF (on-time, in-full) delivery score, driver performance, etc. A similar case can be taken for companies who outsource packaging, raw material supply, temperature monitoring, etc. Analytics can help them capture the cost structure and define cost-effective models for partner collaborations.

Key technologies backing the required Analytics

Machine learning & Artificial intelligence are the backbones of supply chain analytics. These technologies continuously study the data, develop algorithms and give human-like responses to manage the supply chains. IoT constantly works in the background to collect & provide the raw data that is needed for the AI to work effectively. Digital twin & Control tower then together come into the picture for end-to-end management of supply chains. Control towers closely monitor all the functions of supply chain processes, identify the gap areas & suggest necessary corrective actions. Digital twin, which is nothing but a virtual representation of the original process, shows how the recommended actions can bring overall benefit to the supply chain.

Analytics here works in tandem with all of these technologies to give immediate, practical, and to-the-point solutions to ensure supply chains work smoothly and efficiently. So, in a gist, this is how technology & analytics go hand-in-hand in providing a resilient & cost-effective supply chain management solution.

Author:

Mrudang Vora, Chief Technology Officer, Elixia Tech Solutions