How Advanced Data and Analytics Can Optimize Your Supply Chain

Global Supply ChainWhat is supply chain? It is a system of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer. Therefore, the fundamental value of supply chain is controlling the manufacture, storage, transportation, and sales of goods/services to meet customer demand. Advanced data and analytics can play a key role here and here’s why!

What are the supply chain activities for? They are for transforming the raw materials to a finished product and ultimately delivering it to the customer. Traditionally, this involves elements like suppliers, manufacturers, wholesalers, retailers, and finally customers. Managing this chain of elements or the supply chain can be difficult for obvious reasons. However, advanced data and analytics are helping to make things easier.

Today, big data and analytics have widespread application in supply chain management. Big data has been a hot topic in the business world for quite some time now, but you’re probably interested in knowing how big data relates to your supply chain, which includes your transportation.

The Demand of Big Data and How It Could Enhance Your Supply Chain

The Internet of Things (IoT) has created a tsunami of big data that makes it necessary for companies to employ intelligent data management techniques to find the ‘good data’. Considering that almost 90% of the world’s data has been created in the last few years alone, it’s critical that businesses extract meaningful insight from data and analytics. However, this leads us to an important question: what key areas should businesses focus on for best results, and how could this enhance the backbone of their company i.e. the supply chain? We answer that here.

For a very long time now, supply chains have been driven by statistics and quantifiable performance indicators. However, the sort of analytics revolutionizing industry today—the real time analytics of high, rapidly growing and extremely messy unstructured datasets, were largely absent.

From weather to the condition of vehicles and machinery, many factors can impact supply chain management. This prompted supply chain leaders to think long and hard about how this could be harnessed to drive efficiencies. A 2013 whitepaper published in the Journal of Business Logistics called for ‘crucial’ research into the possible applications of Big data within supply chain management. Since then, significant steps have been taken, and now it seems that many of the concepts are being embraced wholeheartedly.

We are already witnessing applications for analysis of unstructured data in inventory management, forecasting, and transportation logistics. For example, digital cameras are routinely used in warehouses to monitor stock levels and the messy, unstructured data provides alerts when restocking is needed.

The above is enhanced by forecasting or analytics—the data captured with the camera can be fed through machine learning algorithms to teach an intelligent stock management system to predict when replenishment of stock will be required. Eventually, warehouses and distribution centers will effectively run themselves with little to no human interaction; at least this is what the theory says.

The Challenges for Supply Chain and How Analytics Can Help

The operations of global manufacturing and logistics teams are becoming complex and challenging as more and more economies become globalized and as companies increase their presence across countries. Inefficient plants, delayed shipments, inconsistent suppliers can stall and delay shipment, which ultimately increases a company’s supply chain costs. While the list is not exhaustive, below are some major challenges supply chain executives face today:

  • Managing demand volatility
  • Visibility of global supply chain and logistic processes
  • Cost fluctuations in supply chain

Executives can overcome many of the supply chain challenges they face today by increasing the use of analytics in supply chain management. A number of organizations are already planning to increase their investments in analytics with a major chunk allocated to supply chain as it holds the greatest potential for innovation and competitive advantage.

Business analytics has improved significantly in the past few years to offer decision support for the critical tactical and strategic supply chain initiatives. As such, insight from these activities are helping the companies to reduce their costs and optimize their supply chain.

So, what are the solutions provided by analytics to the challenges faced by supply chain executives? They are as under:

  • Moving to smarter logistics to improve supply chain visibility
  • Managing volatility through demand and inventory management
  • Reducing cost fluctuations by optimizing sourcing and logistics activities

As these provide the essential data for performance improvement initiatives and provide visibility of supply chain activities, increasing supply chain efficiency should start with enhancing basic metrics and reporting. Through multiple touch points, analytics-driven ‘control-metrics’ can monitor real-time critical events and KPIs. And, when combined with predictive analytics, these metrics can provide valuable savings in areas such as the customer’s freight optimization.

Demand volatility has increased considerably in recent times which has made demand and inventory management a big challenge. In order to perform at market, industries such as retail, consumer goods, automotive require daily or real-time forecast generations. Advanced analytics can be applied to these areas to more accurately anticipate demand and to predict and monitor supply and replenishment policies and plan inventory flow of goods and services.

Supply chain costs account for a significant part of a company’s overall costs and a major challenge for the executives is handling the supply chain costs. Supply chain costs impact key financial metrics like working capital, the costs of goods sold, and cash flow. Therefore, industries which handle large number of inventories must constantly look to improve financial performance. Analytics-driven intelligence can help control costs in key areas of the supply chain such as materials handling, logistics, and sourcing.

From the above, it should be clear that advanced data and analytics can help to optimize your company’s supply chain. For more information on this, get in touch with us today!

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