Few topics hold the prestige of logisticians like Big Data. The applications of Big Data in business are numerous. In freight management, Big Data yields opportunities for improvement. The right strategy can propel the smallest of competitors through better, data-based decision making in international transport to the front of industrial battle lines.
The reason behind the application of data is immense. Fifteen of the U.S. economy’s 17 sectors, reports McKinsey and Company, generate and store more than 235 terabytes of data, which is more than the sum of information contained in the Library of Congress. Every customer interaction, movement in the supply chain, and activity becomes an invaluable data asset that freight forwarders can use to refine transport cost-effectiveness and improve their customers’ supply chains.
The ways we collect data has evolved too. Smartphones, connected sensors, robotics, smart transport management systems (TMS), the Internet of Things (IoT), and artificial intelligence feed on data, as well as generate even more data for use to reduce costs.
In supply chain management, Big Data uses range from better international freight forwarding and passage through Customs to end-to-end visibility. Even low-volume shippers that have not considered the implications of Big Data are likely already using it in some form, so demand for a viable Big Data solution has grown exponentially.
Before taking the plunge into the Big Data Revolution, let’s go back to understanding why it’s essential, how Big Data’s used in business, its benefits, and what you need to take full advantage of it.
Why Is Big Data Important?
The reasons for the importance of Big Data can be boiled down to two words—competitive advantage. Big Data and its symbiote, analytics, are transforming supply chain management. Previously unstructured information has risen to power, and real-time analytics can provide a one-stop visualization of the entire supply chain, reports Bernard Marr of Forbes.
Given the sheer volume and scope of today’s supply chains, it’s easy to see why Big Data has become a priority. However, Big Data can be confusing.
Experts disagree on the definition of Big Data. It might be described as the amount of data collected across both internal and external sources. It might include the analysis of this data through analytics. It could be the end-results listed on a manager’s dashboard regarding transport costs, or it could be the projections for how external factors, like the weather, will influence arrival time.
Instead of trying to pin down Big Data organization into a specific definition, taking a broad view is more effective. In other words, a definition that meets all understandings and interpretation of Big Data, such as:
“Big Data is the crossroads where data collection, analysis, action and review intersect.”
Applied to freight forwarding, the definition of Big Data becomes more specific:
“Big Data is the resource that shippers use to understand transport costs at the crossroads of data collection, analysis, action, and review.”
Mostly, Big Data’s value exists within all transport activities, as well as extending beyond customer-shipper interactions and including products throughout their full life cycle.
How Is Big Data Used in Business and How Does Big Data Help Business?
Big Data in business is a significant opportunity. Big Data tools to unlock savings through multi-modal transport in freight forwarding, reduce risk, streamline Customs’ Clearance, and get freight to consumers faster.
Applied Big Data and analytics to cargo insurance claims increase efficiency and handling when things go wrong. This reduces expenses, making cargo insurance more affordable for freight forwarders. In turn, savings translate into savings for your company. Paired with complexities in cargo insurance across international boundaries, understanding the intricacies between cargo insurance standards and processes is key to reducing expenses and mitigating risk.
Accurate comprehension of why Big Data in Business is a „Big Deal“ must also consider the impact on customer service. In the age of e-commerce, Walmart has deployed Big Data to improve pharmacies’ efficiency, streamline store checkout, manage supply chain processes, optimize product assortment, and create a seamless experience from online to brick-and-mortar sales. Walmart and Amazon’s global reach means moving product faster across international borders, so freight forwarders have a personal stake in enhancing their operations.
Top companies around the globe are making great strides in the various Big Data Uses. These include Amazon, Google, Apple, Microsoft, Uber, Target, PetSmart, Sam’s Club, Chili’s, the Cheesecake Factory, FedEx, UPS, USPS, DHL, and more. The list is limitless, and the most prominent companies have undoubtedly unlocked the savings possible through Big Data and analytics-based freight forwarding. Virtually any company engaged in e-commerce is likely using Big Data, even if just reviewing visitor logs on an e-commerce site.
As explained by DeZyre, companies using Big Data have a common thread: the ability to collect and manage data in a continuous cycle of improvement. Big Data analytics in freight forwarding target and retarget ways to achieve the lowest freight rates, identify possible bottlenecks, and optimize transport management to streamline operations.
Having access to data is great, but knowing what to do with it is another story. In fact, 62.5 percent of Fortune 1000 firms have Big Data initiatives in progress, and statistically, investment into Big Data has grown by more than 500 percent between 2014 and 2017. Demand for a better Big Data-based initiative is growing.
According to Big Data Informatica, a provider of Big Data solutions for business, the technology alone cannot make the improvements necessary to stay competitive in today’s market. Amazon and Walmart have made that much clear. As a result, it takes a combination of people, processes, and technology. For FreightHub users, this combination takes center-stage with a user-friendly, intuitive dashboard. Remember the crossroads? People, processes, and technology comprise the hubs and are the cornerstone of how big data helps business move forward all aiding in making the appropriate and most cost effective path forward.
Making your marketing operations more agile and accountable is no different. Technology alone can’t do it – it takes a well-orchestrated combination of people, process, and technology, as noted in a previous post. By using Big Data, FreightHub can ensure all data provided is accurate and understandable, a key concern for communicating with stakeholders.
What Are the Benefits of Big Data in Business?
We could go on all day about the benefits of Big Data in business, not to mention the benefits of Big Data in logistics. Warehouse logistics, yard management, the capacity crunch, and the talent gap are only a few of the primary areas Big Data could transform through its benefits. Rather than going down that rabbit hole, we need to look at the top applications of Big Data in the supply chain, as explained by Cleverism, which include:
- Real-time delivery tracking. Consumer expectations are at historic levels; they do not care about the limitations of a company or international boundaries. They want their products delivered as soon as possible. Real-time delivery tracking, regardless of whether it’s in-transit by sea, land, or air, can be used to strengthen visibility into the shipping process. A host of technologies, including AIDC, RFID, Bluetooth, and the IoT, can be used to document every step when freight becomes the responsibility of the freight forwarder. This provides peace of mind to companies and the ability to notify customers when delays occur.
- Optimized freight rate classification and freight forwarding. Big Data allows companies to develop the complex models necessary to find and use best practices to reduce international shipping costs. For example, FreightHub uses Big Data analytics to keep costs in check, enabling lower cost freight forwarding and better service. , analytics streamline freight forwarding to manage spend and ensure positive outcomes for consumers.
- Customized production and service. In today’s age, customers expect a personalized experience. Since it is impractical to carry stock in high quantities for every possible product and specification, such as color and size variations, Big Data use to determine a realistic demand forecast can enhance the accuracy of inventory. Accuracy with data gives shippers an opportunity to better project their use of outsourced services, like freight forwarding.
The underlying benefits of Big Data include efficient systems and processes. One part of the discussion that has not yet been analyzed, pardon the pun, is the effect of Big Data on equipment. Big Data enables better forecasting by carriers so that rates can be appropriately assessed and without added fees. Improved forecasting has the overall effect of reducing freight spend.
Pre-Deployment Data Analytics Steps to Master for Use in Business
The scope of Big Data use cases and benefits mean applying Big Data in the supply chain will require more time and effort than meets the eye. Implementing business intelligence for freight forwarding is not a last-minute process.
For instance, some companies using Big Data have taken the time to review their assets, identify their limitations, and consider available Big Data solutions or working with a Big Data organization, such as Big Data Informatica and Advantage Data.
The best-laid plans for continuous improvement through Big Data depend on the company’s ability to absorb the shock it may bring. Believe it or not; Big Data in business can result in additional risk for those that have “relied on proprietary data as a competitive asset,” explains McKinsey & Company.
Businesses must evaluate how using Big Data could improve or change the fundamental processes in managing freight, such as gaining real-time visibility into freight forwarding costs.
Change management is essential to making sense of Big Data organization and implementation, especially when learning how to use new systems So, it’s critical your organization has, according to Edwin Lopez of Supply Chain Dive, a “well-thought-out” process for implementation. This process includes:
- Bridge the divide between privacy and convenience.
- Establish a data-driven culture as a core principle in business strategy.
- Use “Sentiment Analysis” techniques to connect with customer feedback.
- Define specific and broad goals of use of Big Data, which includes identifying business requirements before gathering data. In freight forwarding, some common goals are correctly classifying freight, identifying delays, automate notification systems, and gain real-time visibility to transport status.
- Recognize the limitations of Big Data, such as cleaning data to reach meaningful insights. Merely capturing data is not enough, and the wrong data will result in low-level insights. Even worse, inaccurate or misinterpreted data can have severe consequences for a company’s Big Data goals.
- Create a change management team to handle the implementation and transition to the use of Big Data in business.
- Get your heads in the cloud, which is a key to the scalability of Big Data, as well as opens the door to software-as-a-service (SaaS) platforms that streamline supply chain management; FreightHub’s services include cloud-based dashboards to make visibility and applications of Big Data clear to users.
- Implement a means of capturing data, and use agile management methodologies in implementation.
- Embed Business Intelligence systems, a form of Big Data, into a workflow or conventional systems.
- Test It; any plan for new technology and systems should be thoroughly tested to ensure its success.
What’s It All Mean?
If your organization has already taken the ten steps to pre-deployment data analytics and reached its maximum goals with existing systems, you are ready to put the power of Big Data to work in your organization. The opportunities for Big Data are clear in freight forwarding and beyond. Stop wasting time, and start utilizing Big Data-based solutions for transport management and building your case for Big Data uses in business now.