Data Analytics in Logistics and Supply Chain (LSCM)
In today’s world everything is about data. For any business to succeed, it is imperative that the business should understand the importance of data and Data Analytics. Logistics and Supply chain are now accepted as one of the most important functions of any company for its success. It’s no more just movement and storage of goods.
Data and analytics are transforming many industries and businesses, and logistics is not an exception. The complex and dynamic nature of this sector, as well as the intricate structure of the supply chain, make logistics a perfect use case for data. Valuable insights obtained through data leveraging enable the industry players to optimize routing, to streamline factory functions, and to give transparency to the entire supply chain, for the benefit of both logistics and shipping companies alike.
“Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway”
Geoffrey Moore, Author of Crossing the Chasm & Inside the Tornado
It’s important to realize the importance of big data business analytics in logistics and supply chain management (LSCM). The amount of data involved in Logistics and Supply Chain is significantly increasing. We can use this data for reaping benefits from analysing and overcoming the challenges. Analysing big data can provide us unique insights into things like market trends, customer buying patterns, maintenance cycles, as well as into ways of lowering costs and enabling more targeted business decisions. With the rise of the Internet of Things (IoT) sensors and their adoption, real-time data analytics can play a vital role in the LSCM.
Few of the key aspects of Logistics and Supply Chain are:
Ø Demand forecasting
Ø Sourcing & Procurement
Ø Warehousing & Fulfilment
Ø Route Optimization & Hyperlocal Logistics
Ø Point-Of-Sale
The application of Big Data Analytics can help us in each of the above processes.
Demand forecasting is a key component for any manufacturer. Incorrect forecasting may result in huge losses. With the help of efficient advanced data analytics techniques, the SCM head can better identify prevailing trends. Analytics is key even for after-sales service success.
Procurement is key to any business supply chain. In today’s world with increasing suppliers and vendors, required standards managing it manually is very difficult and can lead to a lot of issues. Data Analytics can help you study and manage various price negotiations, inventory management, purchase orders. Data Analytics helps you identify trends & patterns by applying machine learning in the procurement process. Data analytics helps you sourcing smarter so that you can reduce costs and benefit with huge savings.
Warehousing & Fulfilment today with B2B, B2C, Omnichannel Sales, Festival & Seasonal demands, Back orders, Returns, Reverse logistics has become complex. By applying big data and predictive analytics in warehouse management, models and algorithms help with demand prediction, inventory optimization, material flow efficiency and more which can help you substantially reduce pressures and last time challenges in warehousing and fulfilment.
Route Optimisation in the last mile with growing competition can not only help you increase your efficiency but save a lot of costs, Improve visibility. It’s one of the key processes which needs attention and if hyperlocal is involved you need to surely work on it.
Data Analytics can help you study Point-of-Sale data. The advantage to this is it helps you in retail employee scheduling, shelf space optimization, making sure inventory is always available depending on the analytical forecast and more. It also helps suppliers analyse electronic point-of-sale (EPOS) data to optimize inventory, increase collaboration and drive incremental sales. This analytics needs to work in collaboration with suppliers-retailers to provide better predictive models. Using data from the moment a product is sold allows for the best possible real-time analysis of a product or business performance. Reactive measures can be taken in minutes to hours rather than days.
Data! Data! Data! I can’t make bricks without clay!
Sir Arthur Conan Doyle
For a better Logistics and Supply Chain, strategic focus areas would be Performance management, Productivity improvement, Order processing capabilities, Route optimization, Metrics, KPIs and forecasting, Development of new business models and projects & Digitalization of crucial operations.
Key elements of Data Analytics are
Data Transformation: This essentially means collecting and organising data from various places to one place for study and getting them into a similar format
Data Science: Data science is essentially turning data into knowledge. Data science comprises elements like Algorithms, Predictive Analysis & Predictive Modeling.
Data Visualisation: This is the element where you tell the history and future of the data which helps you for clear actionable points & better business decisions.
API Integration: Here you research and apply the data with the other company for overall business development and positive changes. The integration allows users vital insights important for the business.
Data Security: Data security is a must else it may lead to loss of valuable data or hacking.
You can also get into Graph Analytics which are of 4 types Centrality Analysis, Community Detection, Connectivity Analytics & Path Analysis. Graph Analytics is the analysis among entities such as customers, products , operations and devices. This helps organisations to gain insights that can be used in marketing or analysing social networks. Telecom Operators would typically get into using such analytics.
Transportation and Logistics companies globally face the issues of managing costs and the margins are very thin and dynamic/volatile. They need to surely adapt the usage of Data Analytics which will help them for better decision making, cutting down costs and increasing efficiency/transit times. Logistics firms need to ensure they leverage by using advanced analytics on Performance Management, Fleet Management, Optimization of Logistics & Supply Chain, Cost Management, Business Intelligence, Better Customer Services and Study of outcome of analysis.
In the recent times since the eCommerce boom in India for the last one decade, data analytics has been the key driver for them to survive and succeed in the marketplace. eCommerce business cannot survive without the data analytics and predictive analysis especially for the last mile deliveries, reverse logistics by ensuring collection of data of real time for route optimisation/re-routing etc. Data analytics helps the companies to plan and streamline the operations as well as optimise on resource allocation, fleet management & route optimisation. In fact, many of the Logistics companies such as DHL are working on the next generation technology- “Augmented Reality”.
So, with data visualization, predictive analytics and Big Data, LSCM can turn complexity into a competitive advantage for their business. Most of the companies are in the midst of transforming their supply chains to gain a sustainable competitive advantage. Data-driven decision helps any LSCM to save costs, improve efficiency, manage inventory, better planning & forecasting. Data analytics allows us to better negotiate costs by finding solutions with the suppliers and engaging in long-term contracts for multiple programs.
The goal is to turn data into information, and information into insight.
Carly Fiorina, Former CEO of HP
To give you an idea now most of the large banks, Insurance, Telecom, Retail, eCommerce, Airlines companies have already adopted data analytics.
In India, businesses are at the beginning stages of big data-driven supply chain decision making. More application of Big Data, Analytics & Data Mining will help for even better, faster, smoother & simplify our supply chains. Logistics companies are using data and analytics to operations. Like many other industries, the logistics industry is also going through several changes and adapting to the new digital environment .The leverage of data through innovative technologies that allow companies to have better and new data, and use it in more robust applications, is speeding up the path to a more efficient and sustainable supply chain. So, transformation towards data driven logistics is the only mantra for success and sustainability for LSCM.
