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How Big Data is Changing Supply Chains

Today’s blog is written by guest blogger, Lisa C. Dunn a writer for TechnologyAdvice.   She provides some great insights into how big data might be able to be used in supply chains.

Today’s companies face overwhelming reams of endless data flooding in from a broad range of channels.

In spite of this often-daunting aspect of business today, with appropriate use of this data, you can realize a powerful advantage over the competition by boosting efficiencies in your organization’s supply chain.

While it’s been a buzzword for many years now, do you actually understand what big data is, and why it’s so critical for supply chains today?  

In a nutshell, big data is the dynamic, enormous and “disparate volumes of information created by people, tools and machines.” It includes information gathered from internet-enabled devices – think smartphones and tablets – social media, video and voice recordings, and the continued preservation and logging of structured and unstructured data from the company’s internal software like CRM, ERP, and financial software.

In conjunction with the latest analytics technology, big data enables companies to quickly gain useful knowledge from massive volumes of structured and unstructured data from multiple sources.

For supply chain managers, this strategy can help boost visibility and deliver more in-depth insights into the entire supply chain.

Take the Guesswork Out: Real World Examples

There are countless scenarios of companies and supply chain operations applying big data solutions that illustrate the wealth of process improvement opportunities available through the proper use of data. Here are just a few examples:

  • Many companies today utilize the Internet of Things (IoT) and machine learning for predictive asset maintenance to avoid unscheduled downtimes. The IoT can deliver real-time telemetry data via the use of high-tech sensors to reveal production process details. For example, Microsoft partnered with Powel, a water systems provider in Norway, to define an IoT system that detected water wastage. Within a 5 day hackfest, the team was able to build an MVP product that Powel could use to deploy across their entire system.
  • More and more organizations are taking advantage of machine learning algorithms – trained to analyze a company’s data – to more accurately predict pending machine repairs or fails. Losant Technologies is using Google Machine Learning to detect imminent failures through condition monitoring, which gathers millions of sound and vibration data points and analyzes them with machine learning.
  • Big data solutions can help minimize delivery delays by analyzing GPS data, as well as weather and traffic data, to optimize delivery routes better. UPS uses ORION, an internal dynamic route optimization system, and expects to drive 1 million miles less in 2018 due to the big data advancements.
  • Big data is also helping companies manage more responsive supply chains as they can better comprehend customers and market trends, and thus, are able to predict and proactively strategize supply chain-related activities. As an example, a dairy farm was able to use RFID and IoT sensors to detect up and down-stream issues regarding health of cows, quality of fodder, and variant temperature changes, all of which affected the overall quality of milk. The result was a more homogenized product of higher quality.

The Advantages of Analyzing Big Data Run Far and Wide

By leveraging big data, supply chain organizations can improve response to unpredictable demand and reduce related issues. They can also see benefits in the following three areas:

Cost reduction

One of the main drivers of collecting and analyzing big data for companies today remains cost reduction. Real-time information, versus historical data, is critical, and easy access to it within your supply chain can help you establish benchmarks, optimize processes, and in turn, find opportunities to lower costs.

The data you collect can give your company a focal point to help make educated, well informed decisions, which can lead to a more cost-effective supply chain.

Customer satisfaction

Data can enhance customer satisfaction dramatically, as it allows supervisors to pick the most ideal shipping methods, utilize the best carriers, reduce the potential for damage and halt delays – all leading to improved service.

By providing customers with access to data – think real-time tracking – companies and customers alike can quickly see what is in transit, helping with inventory management efforts.


According to an Ethical Corporation report, approximately 30 percent of companies say that traceability and environmental concerns are hot topics right now.

Recalls and traceability are naturally data-intensive. By leveraging big data, you can improve your organization’s traceability performance, as well as reduce countless hours related to accessing, integrating and managing product databases that highlight items that need to be recalled or modified.

Are You Ready to ‘Walk the ‘Walk?’

While some organizations are already aware of how beneficial big data analytics are to today’s competitive business landscape, many companies still find it overwhelming to collect and analyze their mountains of data.

A recent report stated that 64 percent of supply chain execs do consider big data analytics a disruptive and essential innovation, however, only 17 percent said they already had implemented analytics in one or more supply chain functions.

Even if your organization is among the majority of those who have not yet started to utilize big data analytics for supply chain management, it’s crucial to realize that mastering the technology will be a key driver for supply chain executives moving forward.

If you are unsure about how to get started, one approach is to collaborate with a third-party partner that can help gather the data so you can continue to focus on daily operations.

It is important to make sure the partner you choose to help manage your data uses the most up-to-date technology. Also, keep in mind that data integrity is vital. With the never-ending streams of data you can have access to, the key is that it’s accurate and timely. Unfortunately, if the data is inaccurate, it can damage your supply chain. Incorrect data can lead to an array of issues, however, the biggest ones are planning and customer satisfaction.  

Finally, security tends to be an overlooked area when establishing a big data plan. Remember: your data contains sensitive information about vendors, customers, pricing and more. It is essential to ensure that this information is not shared with anyone else without your permission.

The Bottom Line

Big data is increasingly becoming key to having an efficient supply chain and a reduction of costs. In fact, it’s now standard practice to gather and analyze massive amounts of information to help boost revenue.

Experts predict the trend will continue to expand, and the cost-savings alone in efficiently re-structuring supply chains are potentially enough for not only significant additional profit but also for efficient, streamlined operations moving forward. 

Lisa C. Dunn is a writer for TechnologyAdvice and a freelance writer, copywriter and ghostwriter who develops high-quality content for businesses and non-profit organizations. For over 20 years, she has worked with numerous PR and digital marketing agencies, and her work has been featured in well-known publications including Forbes, VentureBeat, Mashable, Huffington Post, Wired, B2C, USA Today, among others.