Big Data in Logistics and Supply Chain

“Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains.” - Forbes

Many industry trends, like the colossal rise in e-commerce sales with its impossibly fast delivery promises, are spelling greater complexity for the supply chain, creating an urgent drive for innovation. With the world moving at a fast pace towards Industry 4.0, a data-driven revolution is sweeping the Supply Chain.

As products flows through each stage of the supply chain, a host of data (information) is produced. As Supply Chain evolved to a global reach, the volume of data collected from its numerous processes and the velocity at which it is being generated has increased at an extraordinary pace. The manner in which an organization collects, stores and analyses these enormous data sets can give them a powerful advantage over the competition.

Smart companies are employing robust technologies to improve the performance, output, monitoring and control of their operational processes, resulting in a boost in productivity, lowered maintenance and asset management costs, and reduced health and safety risks. But they can only achieve this through gathering and meaningfully analysing their Big Data.

What is Big Data?

A buzzword for many years now, Big Data has been defined as extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions. It includes information gathered from internet-enabled devices, social media, video and voice recordings, as well as structured and unstructured data from a company’s internal software like CRM, ERP, and WMS.

Why is it important to Supply Chain?

As previously mentioned, supply chains generate tonnes of data and the way companies gather, store and analyse this Big Data is becoming increasingly imperative to staying competitive. Unfortunately, many warehouses still run on fully or partially manual operations. This means a lot of valuable resource, time and effort is wasted on entering the same data multiple times across different spreadsheets or systems, significantly increasing the risk of data inaccuracy and errors. Furthermore, Big Data is not meaningful on its own.

Therefore, companies need to adopt a robust system for harvesting, analysing and patching information together as to provide useful insight for forecasting and decision making.

WMS and WCS

With the hefty investments behind warehouse automation, it’s critical to put the right systems in place to maintain your automated equipment, as well as to collect information from them.

A WMS offers capabilities to control inventory and the business logic that drives people and processes within the Distribution Centre. Additionally, a warehouse control system (WCS) can bridge the gap between the WMS and MHE software. It operates and manages the material handling equipment as well as providing the conduit to programmable logic controller (PLC) scanning for machine inputs. It connects all material handling equipment and software in order to support all aspects of the production cycle including receiving, processing, storage, picking and shipping.

At each decision point, the WCS determines the most efficient flow and conveys commands to the equipment controllers to achieve the desired result. Moreover, real-time data from all connected systems allows for any issues to be quickly flagged and traffic rerouted around the problem, giving users an immediate prompt to fix the problem.

IIoT

According to Wikipedia, Industrial Internet of Things (IIoT) refers to interconnected sensors, instruments, and other devices networked together with computers' industrial applications. This connectivity allows for data collection, exchange, and analysis, facilitating improvements in productivity and efficiency. The IIoT is an evolution of a distributed control system (DCS) that allows for a higher degree of automation by using cloud computing to refine and optimize the process controls.

“IoT is set to revolutionize the supply chain with both operational efficiencies and revenue opportunities made possible with just this type of transparency. In today’s market, supply chain isn’t just a way to keep track of your product. It’s a way to gain an edge on your competitors and even build your own brand.” - Forbes

IoT devices can offer great benefits for all aspects of supply chain management. Forbes’ contributor Daniel Newman wrote a broad and helpful summary of supply chain areas IoT can help with:

  • Asset Tracking – RFID and GPS sensors can track products “from floor to store”

  • Vendor Relations – data obtained through asset tracking also allows companies to adjust order schedules, as well as identify suppliers or vendors that may be costing them money

  • Forecasting and Inventory – IoT sensors can provide far more accurate inventories than humans. Moreover, their data can be used to identify trends to make better educated inventory forecasting

  • Carrier integration – connect directly with your transportation partners to drive efficiencies

  • Scheduled Maintenance – IoT can also use smart sensors on warehouse equipment to manage planned and predictive maintenance and prevent down-time

Machine learning

Machine learning algorithms and the models they’re based on find anomalies, patterns and predictive insights in large data sets. Machine learning and AI-based techniques are the foundation of a broad spectrum of next-generation logistics and supply chain technologies now under development. (Forbes)

Gartner predicts that by 2020, 95% of Supply Chain Planning (SCP) vendors will be relying on supervised and unsupervised machine learning in their solutions.”

Machine learning, through data collection and analysis, can further improve distribution centres and warehouses by:

  • Creating better logistics schedules;

  • Forecasting ideal inventory quantities to meet clients’ demands, reducing overstock and allowing companies to better prepare for busy periods like Christmas, Black Friday and Cyber Monday;

  • Generating better analysis of risk factors that affect product pricing, allowing managers to secure higher profit levels;

  • Higher shipping accuracy and speed (by calculating the best routes incorporating traffic information);

  • Ability to report on consumer trends, allowing managers to better match their product offerings with their customers’ needs

Machine learning will exponentially improve report generation and fill many previously blank gaps for managers, allowing better allocation of resources and resulting in higher profitability.

Big Data Analytics

“Big Data Analytics involves the use of advanced analytics techniques to extract valuable knowledge from vast amounts of data, facilitating data-driven decision-making.” – Mohamed et Al, Big Data Analytics in Supply Chain: A Literature Review

In modern corporations, several business departments outside the warehouses and distribution centres - such as marketing and sales – have become reliant on Big Data analysis to gain better customer insights. These insights can offer a significant value in areas such as product development, market demand predictions, supplying decisions, distribution optimization and customer relationship management.

Conclusion

Big data is helping companies operate more responsive supply chains as they better understand customers and market trends. It’s allowing managers to predict and strategize in a much broader and more accurate manner.

By leveraging big data, organizations are transparently tracking production, employee and equipment performance. Furthermore, they’re dramatically enhancing customer satisfaction, by streamlining picking, packing and shipping as well as offering more access and real-time visibility into their order status.

According to Gartner, CIOs have realized that sustainable digital transformation and task automation go hand in hand. The number of enterprises implementing artificial intelligence (AI) grew 270% in the past four years and tripled in the past year. Because of this growth in digital supply chain implementations, companies are investing in training programs for employees with backgrounds in statistics and data management.

Is your company leveraging the power of Big Data? Talk to us about digitizing your supply chain today!

Image credits: Gerd Altmann from Pixabay