How Predictive Analytics Are Changing Supply Chain Logistics

By Avery T. Phillips

Supply chains make or break a business, as the Target Canada fiasco painfully demonstrated. Distribution challenges were one big reason cited for the catastrophic failure of the expansion effort.

For many businesses, from retail to manufacturing, a breakdown in supply chain or inefficiency in restocking can impact financial stability. Supply chain isn’t exactly a sleek or sexy application of analytics technology, but advancements in recent years can go a long way to protecting vital infrastructure.

How Predictive Analytics Works

Predictive analytics is the result of a number of different advances in how we collect, handle, and analyze data. Specifically, predictive analytics is the answering of several questions related to data:

• What is the most important data to collect?
• What does it tell us about previous performance and problems?
• What improvements can we make based on that data?
• Which patterns does the data reveal?
• Can the data be used to predict patterns in the future?
• Can the data be used to create patterns that are beneficial to the company?

The difference between a whole bunch of data and analytics is knowing what your data is, what you need it for, and how you can apply it to improve the efficiency and profitability of the company. Performing these functions often requires the building of complex systems and algorithms, but the results can be well worth the investment.

Analytics, in the end, is about decision making. It’s about empowering business owners to make decisions based on the best available information, based on facts and analysis.

What Does Predictive Analytics Have To Do With A Supply Chain?

Supply chains are large, complex beasts. They are often comprised of several entirely different companies that produce, quality control, and transport goods. Sometimes they intersect with law enforcement bodies if the chain crosses borders. Predictive analytics can demystify these complex processes and present a business with clear information about the effectiveness of all the links in a supply chain.

Supply chains are inherently vulnerable. Facing regulatory and social pressure about sustainability, concerns about cyber security, and an increasingly difficult retail market, many companies have been slow to catch up with the new circumstances of supply chain management.

Predictive analytics presents solutions to so many of these modern woes. For one thing, they can be used to automate order filling based on the ebb and flow of demand for specific goods. These concerns aren’t just seasonal anymore, supply chains are being taxed by an on-demand economy and high turnaround expectations of consumers. Data can be used to streamline the entire inventory process and solve other supply chain challenges.

Further than that, however, businesses can use data about all of the links in a supply chain to identify weaknesses and potential issues. From technology that analyzes the efficiency of trailer loading, to technology that tracks the location of goods in real time, business owners and the managers of supply chains are being empowered to make decisions about small details that have big consequences. Weak links in the chain can be identified and replaced. Delivery timing can be optimized, and the efficiency of a chain can really be put through its paces once you start collecting and analyzing data in real time.

On-demand isn’t a perk anymore, it’s an expectation of consumers and business clients. Embracing the technology of big data and predictive analytics isn’t a matter of getting ahead, it’s a matter of not falling behind. Take the example of Target Canada to heart, and watch other organizations who don’t pay enough attention to their supply chains.

Avery T. Phillips is a freelance human being with too much to say. She loves nature and examining human interactions with the world. Comment or tweet her @a_taylorian with any questions or suggestions.