Kuebix Predictive Analytics TMS

What is Predictive Analytics and How is it Used in Supply Chain Operations?

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You may be familiar with the term predictive analytics – but have you ever stopped to ask yourself what it really means for your supply chain? Analytics help companies streamline process efficiencies and make sure important trends aren’t overlooked. Regardless of the industry your company is operating in, predictive analytics can help your company interpret their current performance to help them better understand and predict their future. 

Breaking it Down – Defining Predictive Analytics

Predictive analytics is formally defined as “the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.” It extends beyond analysis of current operations and provides the best possible projection of what a company’s performance will look like in the future. Businesses who utilize predictive analytics can uncover patterns and relationships in their structured and unstructured data. 

Predictive analytics is especially useful because it automates the process of forecasting. Companies who utilize predictive analytics can then place their focus on critical daily tasks instead of going through a manual forecasting process. The biggest challenge associated with predictive analytics is that it requires a substantial amount of historical data. If the software doesn’t have enough data, it will have a hard time finding and visually displaying patterns and trends.

The MHI Industry report revealed that the number of supply chain professionals using predictive analytics has grown 76% from 2017 to 2019. Earlier implementations of predictive analytics focused on inventory management to help reduce cycle times and improve customer service. Over the past couple of years, the concept of predictive analytics has evolved and can now be applied across industries including healthcare and transportation planning.

Companies utilizing the Internet of Things (IoT) are already taking steps towards collecting the data needed for predictive analytics. Whether they realize it or not, the data they’re collecting can fuel their efforts towards projecting and improving the future of their supply chains. For example, a company utilizing predictive analytics in their supply chain can view historical data about on time delivery (OTD) to make better decisions about who they book with in the future. 

Harnessing the Power of Predictive Analytics in Supply Chains

If you’re like many shippers, this type of advanced technology might seem outside of your grasp. With the help of a transportation management system with built-in predictive analytics functionality, however, any shipper can leverage this futuristic tech. TMSs can provide predictive analytics to give you the immediate intelligence you need to make better logistics decisions every day. 

Whether it’s holding your carriers accountable through carrier scorecards, managing your yards and docks more efficiently, or simply ensuring that you are paying the lowest rates for the best service, predictive analytics gives you the information you need to make decisions that will be real game-changers for your business.

 

Big Data

Why is Big Data Such a Big Deal?

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If the amount of data flowing into, out of, and within the four walls of your company is out of control, you’re not alone. Organizations of all sizes are experiencing the impact of the Information Age, and even government agencies admit that they’re feeling overwhelmed by data fatigue right now.

The National Security Administration isn’t even immune to this problem. In NSA is so overwhelmed with data, it’s no longer effective, says whistleblower, William Binney, a former NSA official who spent more than three decades at the agency, said the U.S. government’s mass surveillance programs have become so engorged with data that they are no longer effective, losing vital intelligence in the fray.

Credit that fact that the world’s data volumes have grown in astronomical leaps over the last few years with creating this level of data fatigue. And as the variety and velocity of data has grown, the usefulness of traditional data warehousing strategies has decreased exponentially.

It Keeps Going and Going and Going…

By 2025, research firm IDC believes the total amount of digital data created by the world will reach 180 zettabytes, up from 4.4 zettabytes in 2013. The astounding growth comes from both the number of devices generating data as well as the number of sensors in each device… approximately 11 billion devices connect to the Internet now. The figure is expected to nearly triple to 30 billion by 2020 and then nearly triple again to 80 billion five years later.

What many companies don’t realize is that with effective management of big data, the ability to leverage information and use it to make better transportation and logistics decisions is readily available.

In fact, after accumulating terabytes of data over the years, most companies already have the foundational information right within their own four walls. The challenge lies in extracting this data, determining which of it is (and isn’t) useful, and then turning that information into actionable insights.

What This Means in Logistics

The impact data is having and will continue to have in the logistics industry can’t be overlooked. Companies are realizing the importance of integrating all modes of carriers and all related data into central data repositories for full visibility of everything from rates and tracking information, to complex reporting and score carding. And carrier data is just the first step. The goal is to pool data and allow collaboration among every key stakeholder in a supply chain both external (carriers, suppliers, customers, 3rd party systems) and internal (buyers, accounts payable, logistics, warehouse, procurement, executive team). When this is achieved, a whole new world of supply chain efficiency becomes possible.

To learn specific ways to initiate better data management in your organization, download our white paper “Effectively Managing Big Data in Your Supply Chain.”