Going big on Big data: How the Logistics industry is enhancing its supply chain visibility with real-time analytics

By Mahesh AG

The logistics industry is complex with critical sub-areas such as transportation, inventory, warehousing, material handling, packaging and security that need to come together for actionable insight. The ever-changing global economy, fuel price instability, just-in-time requirement of customers, and the necessity of cost-effectiveness add to the complexity of the ecosystem. This, in addition to the huge scale of operations, makes it increasingly difficult for Logistics Service Providers to gain visibility across the supply chain and ensure efficient customer service.

Greater Visibility into Customer Plans

3PLs will benefit immensely from having a greater visibility into their customers’ order management/supply chain planning activities since it provides them a longer lead time window to plan. In most instances, 3PLs are notified at the last moment with little time to plan for efficiencies and contingencies hence forcing a reactive fulfilment operation. 3PL providers can save up to 40% on operational costs by improving decisions such as the optimal selection of inventory placement and transportation modes. The following activities could benefit from advanced operational and strategic information from 3PL customers:

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 Technology as an Enabler

In a recent logistics study by Penn State University and Penske Logistics, close to 96% of the study respondents consisting of shippers and 3rd party logistics providers believed that IT capabilities are a key element of logistics expertise. However, only 60% of the shippers interviewed were actually satisfied with the logistics providers IT capabilities

The need of the hour is provision of a true business process and technology platform that will enable LSPs to further have upstream visibility into demand of their shippers and consignees. The visibility ensures better operational planning resulting in enhanced service and increased efficiency for their customers.

Clearwater International estimates the SCM software market to be worth $13.4 billion by 2017, which represents a strong and growing software segment. The technology solution for 3PLs will require combining several traditional supply chain software functionalities which include:

a) Visibility into the 3PLs’ customers’ relationships with their customers. This increases the chances of 3PL being aware of needs of its customers earlier and enhances their ability to respond to problems before they occur.

b) Linkage of transportation management system capabilities directly with the selected transport providers. This enables selection of appropriate carriers for individual shipments.

c) Visibility into customer demand management systems resulting in the ability to anticipate demand and better serve the customer.

d) Integration compatibility to enable integration of 3PL information technologies with business processes and information systems at customer organizations.

Big Data: The next frontier of Supply Chain Innovation

Distribution, logistics, and production networks can be made more efficient by using powerful data-processing and analysis capabilities. It enables companies to share data with partners across the supply chain that results in development of new services, improved demand forecasting accuracy and discovery of new demand patterns. In addition, they can increase asset uptime and expand throughput, enable preventive maintenance of assets and resource optimization along with conducting near real-time supply planning using dynamic data feeds from production sensors and the Internet of Things.

The pivotal advantage of Big Data is real-time analytics. It complements the end-to-end visibility of the supply chain and enables logistic companies to act rapidly on prospective loss of revenues and profits that could occur at various points in the chain.

A recent big data study by Accenture had 48 percent of the respondents expect to create an organizational ability to react more quickly to changes and 45 percent expect big data analytics to help them gain insights about the future, rather than merely report what has happened in the past

How does Big data affect supply chain visibility?

Forecasting: Forecasting has become difficult in the current era where demand is volatile and product portfolios are increasingly complex. Organizations have had to rely on inflexible systems and inaccurate estimates from the sales force to predict the future.

Today, companies can look at vast quantities of fast-moving data from customers, suppliers, and sensors. Combining that information with contextual factors such as weather forecasts, competitive behaviour, pricing positions, and other external factors, they can determine which factors have a strong correlation with demand which then allows them to adapt accordingly. Advanced analytical techniques can be used to integrate data from a number of systems that speak different languages—for example, enterprise resource planning, pricing, and competitive-intelligence systems—to allow organizations a view of things they couldn’t see in the past.

By implementing fluid demand and supply plans that are updated in real-time, based on true demand signals, material availability and capacity, revenue and profit potential is maximized.

Distribution Network: Distribution networks have evolved over time into dense webs of warehouses, factories, and distribution centers sprawling across huge territories. The tangled interrelationships among internal and external networks can render the traditional network-optimization models impotent.

Big-data-style capabilities can help companies solve much more intricate optimization problems than in the past. With the presence of more variables and more scenarios than ever before, organizations can integrate their analyses with many other interconnected business systems. Analytics on warehouse layout, product inventory and demand can help optimize operations within the warehouse also enabling alerts on depleted inventory or potential roadblocks. As the number of warehouses gets smaller, the remaining warehouses grow bigger and more efficient. By pooling customer demand across a smaller network of bigger warehouses, the company can decrease the variability of demand and can, therefore, hold lower levels of inventory.

Usage of big data and advanced analytics to simplify distribution networks can help logistic companies accrue savings that range from 10 to 20 percent of freight and warehousing costs, in addition to large savings in inventories.

Where to Begin?

In order to have big data to analyze in the first place, companies must invest in the latest technologies, including state-of-the-art sensors and radio-frequency identification tags, which can build transparency and connections into the supply chain. It also becomes important to consider the type of business intelligence tool to implement in order to obtain the visibility that is needed to measure and monitor business across multiple workflows. Companies with an enterprise-wide solution are far more likely to generate a range of important supply chain benefits from their use of big data analytics with shortened order-to-delivery cycle times and improved cost to serve. Companies need to ensure that big data analytics is embedded in supply chain operations to improve decision making across the organization, and hire people with a unique mix of analytics skills and knowledge of the business to produce actionable insights from big data.

About the Author

MaheshMahesh AG is the CoE practice head for the cargo & Logistics practice at IGT. He has more than 2o years of experience in the Airline industry including international Airlines, and has held different roles involving Project Management, Business Analysis and System Design & Development.Prior to joining IGT, Mahesh was in Mercator, the IT division of the Emirates Group where he implemented cargo products like SkyChain/Normad for 12 Airlines globally. He can be reached at mktg@www.igtsolutions.com

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