By Adam Robinson, VP, Product Marketing SONAR
For all freight management segments, navigating a volatile freight market’s complexities stand out as a leading disruption of 2020. This year has taught freight management experts and leaders that nothing is set in stone. Market uncertainty can spin on a dime.
Brokerages, freight forwarders, shippers, carriers, and other logistics service providers (LSPs) need to realize that the only way forward lies in the proper application of data and a robust freight tech stack. After all, applying freight management data can enhance and strengthen decisions regardless of the market conditions and when they change.
And uncertainty began long before the COVID-19 crisis began to unfold.
In this article, we will cover how to use data in volatile markets by covering the following topics:
- Reasons why real-time freight data is paramount to make market decisions
- What Shipping Analytics Tools Should Freight Market Participants Have in Their Freight Stack?
- Top 10 Key Performance Indicators for Shipping Industry
- The Four Types of Transportation Analytics to Know
- What Is Supply Chain Predictive Analytics & Why Should Freight Pros Care
- How Freight Management Analytics Simplify Logistics
Reasons Why Real-Time Freight Data is Paramount to Make Market Decisions
Successful supply chain management depends on the ability to collect data and apply it accordingly. That is an essential capability for all shippers and brokers alike. And major companies have taken notice. As explained by Grainger, “In today’s global economy, technology trends like the Internet of Things (IoT) and Big Data have become an indispensable part of everyday business. Before cloud computing and the era of Big Data, collecting inventory information required more resources and extra manpower. Plus, manual data entry often left inventory management susceptible to human error.” Supply chain professionals need to realize that real-time freight data is crucial to making market decisions and maximizing profitability across all loads for these five reasons.
Real-Time Freight Data Enables Immediate Intervention for Major Disruptions
Supply chain leaders still have difficulty justifying the business case for real-time data within the supply chain. Real-time freight management is not necessarily about booking orders right this second; instead, it focuses on intervening as soon as possible when something goes wrong. Yes, it does allow companies to reduce the time to execute a load. However, its greatest value is in enabling true exception management.
Better Visibility Results in Fewer Customer Complaints and Increased On-Time Deliveries
Improvements within the supply chain, including more on-time deliveries and less risk of damage, will inevitably lead to fewer customer complaints. In other words, customers are more likely to have positive experiences. And that will result in additional improvements in customer retention rates, increase profitability for the individual companies, and overall gains in the value of using that data.
Market Insights Empower Freight Management Segments for RFP Processes
Real-time freight market insights empower freight management segments for improved RFP processes. Regardless of vertical, all companies endure the trials of annual RFPs. Unfortunately, market instability, a characteristic that supersedes nearly every facet of supply chain management, requires renewed RFP processes throughout the year. There are times when the market does maintain stability. However, a stable market does not necessarily appear on the horizon at this time. For that reason, companies need to leverage real-time freight data to understand market trends, use it to guide mini-bids, and even consider investing in their in-house fleets.
Real-Time Data is Less Likely to Result in Revenue Losses Between Quoting and Final Delivery
For freight brokers, the application of real-time data is a no-brainer. Leveraging real-time data allows brokers to get the most accurate view of the market, quote the most realistic rates for shipments, and secure their customers’ confidence. In 2020, supply chains have shown that market dynamics can change within hours. Additionally, securing those positive customer experiences may also involve significant rerouting of shipments, rescheduling final delivery, and sign-on-glass systems to improve safety. Even with some stability returning to the market, customer confidence remains shaken. That’s been the dominant trend in 2020. And success in 2021 will depend on the ability to offer the most competitive freight rates and maximize profit margins simultaneously by using effective supply chain software.
Agile Supply Chain Management Requires Insight Across all Lanes and Conditions
In recent years, agile, flexible and adaptive supply chains have become the new logistics strategies. After all, an adaptive supply chain is capable of surviving disruption. With that in mind, supply chain leaders need insight across all lanes and market conditions to understand what is necessary to achieve the desired result. In other words, the best predictive and prescriptive analytics insights are useless if a company does not look beyond its operation. The market is big. And companies that do not view the external picture are losing revenue growth opportunities.
What Shipping Analytics Tools Should Freight Market Participants Have in Their Freight Stack?
How does your company define success in the supply chain? For shippers, success depends on end-to-end network improvements, according to McKinsey & Company. Shipping analytics tools shine a light on the value of informed freight management. Freight market participants need these top shipping analytics tools in their freight stack.
Shipping Status Tools to Track Freight
Tracking shipment status is a core function of advanced shipping analytics tools. Yes, knowing real-time status is great. But knowing when it will be late or missed is better.
Analytics-Driven Processes to Reduce Excess Inventory
Shippers also need a way to look beyond the enterprise’s four walls to understand waste. Wasted warehouse space leads to higher overhead. Yet analytics-driven processes can reduce excess inventory. For example, just-in-time fulfillment models, drop-shipping, and cross-docking avoid wasted space. And they keep inventory levels lean.
Collaborative Analytics Resources to Inform Conversations
Collaborative analytics help the supply chain work together. But modern supply chains are super-complex. Collaboration means parties must share data in real-time. And collaborative analytics provide the information needed to inform everyday conversations. That extends to guiding freight bids too.
For example, market conditions show shippers’ rate trajectories. Shippers can then better understand and work with freight parties to avoid delays.
Increased Insight into Warehouse Management Capabilities
Transportation only provides a partial picture of an industry. Viewing transportation networks with multi-angled metrics goes a long way to reducing costs. One of these metrics is the Logistics Managers Index (LMI), which SONAR provides users. For instance, shippers see the warehouse use rates via the LMI. Multi-angled views like distribution center wait times help to avoid surprises.
Improved planning through wait time analysis benefits all parties.
Things go wrong in supply chains. That much is always going to be true. Seeing the delays in one part of the network is key to stopping the disruption. That helps shippers avoid excess detention fees by better planning their dock schedules.
Demand Forecasting Insight from Ocean and Intermodal
Using shipping analytics tools, shippers see across modes. Ocean freight impacts on trucking is another use case. Ocean freight that arrives in a port means opportunities for trucking companies. However, it also may lead to the need to move equipment and assets.
For instance, a shipper may look to move in-house fleets to port cities. Analytics help shippers preempt changes in the market despite the mode. Higher port activity leads to tighter trucking capacity in portside O/D pairs.
Compliance Management Resources
Even if a shipper follows all the right steps, compliance can remain an issue. Shippers need to maintain compliance with truckers, carriers and other trading partners. That includes compliance with the inbound freight routing guide and outbound activities. For sensitive shipments, it takes on a new value. Compliance could include routing sensitive shipments faster to a given facility. Thus, companies can move higher-priority freight faster.
An inbound routing guide may need extra sign-offs for delivery after-hours. The most relevant example of this need for added complexity is the pharmaceutical industry.
Finance Analytics Capabilities
Delivering a load does not equate to a complete transaction—only freight payment does. But trucking rate invoice errors are more common than many realize. The problem only grows worse in larger supply chains. The urgency over fast payment amounts to excess freight spend. But again, shipping analytics tools can check everything. They sort through prior quotes, invoices and shipment data to check invoice accuracy.
Insight in Lead Times
Shipping analytics tools also provide insight into the lead time. For instance, increased lead time in high-demand markets will lead to higher rates. When rates rise in a more valuable aspect of the market, drivers will follow. Then, the cycle becomes self-propagating and stimulates higher rates on spot loads. Knowing volume volatility and market dynamics adds value. Shippers then become more proactive.
For instance, shippers might encourage customers to order earlier.
Analytics for Consumer-Facing Systems
Analytics also add value post-final mile delivery. Analytics can inform shippers of increased return rates, problems during delivery and more. These analytics help shippers avoid typical eCommerce problems. Leading by example, supply chain managers can make more proactive decisions. For shippers, consumer-facing analytics guide customer service. That is the foundation of success in supply chains.
Top 10 Key Performance Indicators for Shipping Industry
“Key performance indicators can make or break supply chain operations, and it seems as though there are more to choose from every day,” says Morgan Forde of Supply Chain Dive. That is the crux of digital tech in supply chain intelligence. Leaders get so involved in leveraging data that they overlook the meaningful aspect. Data for the sake of data lacks value. Tracking the top key performance indicators for shipping industry success, or supply chain KPIs, means boiling them down the essence of these 10.
Wait Times
Successful supply chain management begins with prioritization. Freight broker and shipper profitability requires strategic prioritization of arrivals/departures. And that begins with understanding average wait times for given locations. Viewing any WAIT metric within FreightWaves SONAR can provide a market view of average wait times at facilities in a given city. And by looking at the markets with the highest rates, indicated by share of the treemap and color intensity, it’s possible to prioritize truck schedules better.
Percent of New Truck Orders by Class
Another excellent way to gauge activity within the industry surrounds the volume of new truck orders by class. Of the key performance indicators for shipping industry success, this metric is relatively simple. A rolling volume of new truck orders reveals how overall capacity within the market is trending. As the transportation data regarding order volumes increase, it indicates network expansion throughout the industry.
Tender Rejections
Any successful list of key performance indicators for shipping industry improvements must include tender rejection indices. Key metrics, such as SONAR’s OTRI and ITRI, help enterprises identify weaknesses or problems where covering a load may occur. Since rising levels of rejections indicate increased demand, users should view multiple rejection indices at once. That is especially true when viewing various locations. Fortunately, leveraging a resource, such as SONAR’s Lane Scorecard, to see various metrics for multiple sites can hasten the process.
Carrier Compliance
Freight management parties must also track carrier compliance. That includes adhering to the routing guides, fulfilling contractual obligations, and any such deviations.
On-Time Pickup and Delivery
Tracking on-time pickup and delivery is an additional opportunity to leverage key performance indicators for shipping industry success. Enterprise leaders should also take both holistic and granular views of these metrics. For instance, track on-time pickup and delivery across your whole network and within top O/D pairs.
Inventory Velocity
Inventory velocity provides insight into how quickly freight turns over within your company. Faster speed amounts to faster truckload quotes and increased business profitability. At the same time, decreasing rates may indicate limited resources or trouble maintaining current operating status.
Annual Freight Spend Deviation
Freight managers understand typical expectations for annual freight spend. While some deviation is always inevitable, it is still imperative to track. Obviously, major disruptions will typically coincide with drastic deviations from the typical freight spend. However, recognizing such deviations as they begin to occur can help managers preempt significant market changes. That contributes to proactive transportation optimization.
Percentage of Returned Shipments
Shippers should also track the percentage of returned shipments. That is especially crucial in e-commerce ordering. And they must track typical causes for returns. Knowing why customers return a product is the only way to help prevent future returns.
Cash-to-Cash Time Cycles
The cash-to-cash time cycle refers to the monetary transactions that occur for a given order. It is the complete cycle time average from the moment a customer pays for an item through the point of payment to the carrier or any other third parties. Tracking the time cycle gives managers a way to gauge overall business health. As the time cycle decreases, it indicates faster fulfillment, invoice processing, and freight settlement. The insights gained through this aspect of the top key performance indicators for shipping industry success will help companies identify possible candidacy for shipper-of-choice status. The same applies to carrier-of-choice status for brokers.
Freight Bill Accuracy
Freight invoices typically contain marginal errors. But inaccuracies add up to major losses over time. Enterprises need to track all invoices’ accuracy and validity with advanced freight tech, such as auditing software.
The Four Types of Transportation Analytics to Know
Within the ever-changing shipping and freight management market, there is an underlying need to know and understand shipping data trends running throughout the industry. Transportation analytics is rapidly evolving into the next age of discipline for the supply chain. From peaks and valleys in sales to highs and lows in income channels, transportation analytics can help managers, 3PLs and partners stay on the same page, focused and unified.
Four types of transportation data analytics are usually implemented in stages throughout the freight supply chain network. Companies must note that no one type of analytical process will be better than the other when used alone. They are interrelated and interconnected, each one offering different insights and data. With data being necessary for every freight logistics and shipping chain, transportation analytics are becoming common among transportation and freight forwarding providers.
Descriptive Analytics for Transportation Logistics
Descriptive transportation analytics focus on describing or summarizing the existing data collected throughout the various channels. It can be defined by using existing business intelligence tools to get a clearer picture of going on or what has happened with shipments, payments, delays, damage reports, customer feedback, and more. It can be combined with any other aspect of data related to transportation logistics. These analytics literally describe the history of what happened within the freight network, such as the ins and outs of carrier sourcing from the past.
Diagnostic Analytics and Data Interpretations
Understanding what happened is a great starting point, but it begs the question, “why?” Diagnostic analytics seeks to answer that question. With a strong focus on past performance, this analytical process commonly gets used to determine the causes leading to the supply chain’s current state. The result of transportation analytics often helps to interpret data into something easier to share and apply throughout the freight network. Accessing and sharing diagnostic data with team members and third parties make it easier to respond to, correct and prevent future issues. This form of analytics is where the meaningful gains of process improvement begin.
Predictive Analytics that Impacts Shipping Chains
Feeding on diagnostic data, predictive transportation analytics emphasizes predicting the possible outcomes, a core benefit of their use in volatile freight markets. That is an immeasurable benefit for an industry rife with both risk and volatility. The traditional theory that transportation management marches to a bi-annual beat is on the way out the door. And teams need a better way to how what happened becomes what is on track to happen. Transportation predictive analytics prepare managers and frontline workers with insight into the future. By using statistical models and implementing automation and digital techniques, freight managers can control the end-to-end shipping chain. Such data access allows for more control and adaptability in the long run.
Prescriptive Analytics for Preventative Planning
The final type of transportation analytics commonly used in freight logistics goes by the name of prescriptive analytics. Data collected with earlier methods gets used to recommend one or more courses of action on a point being analyzed. Using such an approach helps managers develop several responses to a single issue arising by predicting the outcomes of a certain choice. These are the active form of analytics, showing what a company needs to do differently to achieve an optimum result. The data then highlights and prescribes the best option.
What is Supply Chain Predictive Analytics and Why Should Freight Pros Care
Some of the most cost-effective software and methods supply chain professionals and freight brokers can adopt are supply chain predictive analytics programs. While still relatively new to the supply chain, analytics implementations have skyrocketed in popularity since its birth a little over 10 years ago. According to Supply Chain Dive, “The number of supply chain professionals who say they’re currently using predictive analytics at their company has grown 76 percent from 2017 to 2019, according to a Supply Chain Dive analysis of the annual MHI Industry Report.” Supply chain predictive analytics is reimagining the supply chain’s future and saving leaders in the industry a lot of money along the way.
What is Supply Chain Predictive Analytics
Companies become apprehensive when it comes to newer technology and stepping into new software. It helps to understand the concept of supply chain predictive analytics. As reported by Supply Chain Dive, “Predictive analytics is the process of taking the data gathered from everyday operations and converting it ‘into valuable nuggets of insight.’” Essentially, these “valuable nuggets of insight” create a window into everyday operations. Knowing exactly what’s going on and when it’s going on is the most valuable tool in a supply chain operations arsenal. Supply chain predictive analytics informs users of different issues that likely will occur, where they occur, and when they occur. This allows supply chain professionals to understand errors, and ultimately their application will prevent future errors from happening.
When issues are resolved before they occur, supply chains save money. Some issues include missed shipments, shipment delays, and when dealing with international shipping, withheld shipments. The information supply chain predictive analytics offers creates peace of mind for supply chain professionals and assists in eliminating ongoing supply chain or transportation issues that can become costly over time.
The Value of Supply Chain Predictive Analytics
Part of successfully implementing supply chain predictive analytics is knowing how to wield these tools properly. And that involves understanding them and knowing how they work. These platforms may become confusing at times, but all team members throughout the supply chain must become fluent in the software available. The information available realizes its true potential through the ability to accurately interpret the information provided. Some of the challenges with the supply chain will and already do accurately predict freight’s future. Supply chain predictive analytics plays an essential role in freight forecasting. Think about it. Forecasting has become especially crucial and challenging, given the state of the COVID-19 pandemic this year. And leveraging predictive analytics helps companies see the writing on the wall and intervene to repaint it when necessary. Ultimately, using supply chain predictive analytics is essential to driving down excessive spending and supply chain professionals’ costs.
Best Practices for Using Predictive Analytics
Logistics companies depend almost entirely on their efficiency and accuracy. Utilizing predictive analytics is the perfect way to draw near to error-free goals. There are many ways that supply chain professionals can adapt and use predictive analytics to their advantage, such as:
- Connect your systems via EDI and API. Doing so creates a more effective flow between software and allows for a more user-friendly experience.
- Leverage IoT-enabled sensors to collect more data. Data collection is imperative to provide an invaluable working relationship between predictive analytics and logistics companies.
- Use autonomous processes to comb through and apply data. Using automatic features, analytics and automated data management eliminate human error and oversight, leading to fewer costly mistakes.
- Automate high-priority items’ notifications to avoid mistakes. This gives users less room for error, especially if it is made known to them.
- Train all team members on how to apply those insights. The ability to properly use automated systems is only as useful as its user-friendliness. Ensure everyone is aware of procedures to provide seamless use and transitions.
- Pay attention to software updates. Technology is ever-changing, so it is vital to make sure software is up to date to keep the most accurate readings.
- Plan, replan and plan again. One rule in the supply chain is absolute; managers must plan according to what data indicates has, is, or may happen. This is key to eliminating any mistakes. Technology is also not accurate 100 percent of the time, so double-check to make sure nothing slips through the cracks.
How Freight Management Analytics Simplify Logistics
Relying solely on manual shipping data analysis continues to yield poor results. The adage of trying too many workers and not enough leaders grows more apparent. And even the freight management analytics of five years ago do not necessarily respond well to today’s shifting and changing market. The old ways of recording, processing and responding to analytical data need a streamlined approach. New ways must be adopted. And that all begins with deploying advanced freight management analytical resources and tools that actively work to lower all risks, ranging from detention through final mile management.
Freight Management Analytics Reduce Confusion Over What Happened
Problems will arise despite the best planning and preparation, but freight management analytics can help reduce their frequency and severity while making the entire process more streamlined. According to Business Wire, “Supply chain analytics holds the key to mitigate a number of businesses complexities. It has the potential to enhance the end-to-end performance of the supply chain in terms of financial, operational, as well as managerial aspects.” It all begins with understanding what happened. Identifying past issues is the job of descriptive algorithms within analytics, showing what happened. By using descriptive and diagnostic analytics, freight management parties begin to see not only what happened, but why. In this critical moment, the idea of freight foresight and prediction takes hold within shipping tools.
They Indicate a New Focus on Insights Related to Carrier Performance
An inability to look beyond the four walls of an enterprise remains a constant threat to today’s freight management parties. Outdated analysis and management methods are becoming increasingly more difficult amid lockdowns, supply shortages, and increased consumer demands. And the current predictions for the industry have only made these shortcomings more obvious. Freight management analytics have also advanced significantly, affording insight into carrier performance. That leads enterprises to a more streamlined and efficient process from end to end.
Analytics Help Companies Make Data-Driven Decisions to Find the Most Lucrative Loads
It’s important to recognize a core problem among logisticians today. Analytics available now are not those of the early 2000s. They have advanced and brought faster and easier-to-understand supply chain KPIs. Remember that freight management analytics simply interpret raw data to help draw conclusions about performance, costs, profits and chain management. Mainly, freight analytics used in the shipping and freight management industry to improve load and order acceptance and freight loads. In the past few years, the focus has been on the use of data analytics in the supply chain to continuously look for the most lucrative opportunities. In turn, freight management parties realize a stronger ROI and increased profit margins.
Freight Management Analytics Lower Barriers to Efficiency by Streamlining Performance Measurement and Management
A benefit freight management and logistics teams can enjoy by embracing freight management analytics is a more streamlined approach that allows for better communication and improved visibility. According to Industry Week, “All businesses with a supply chain devote a fair amount of time to making sure it adds value, but these new advanced analytic tools and disciplines make it possible to dig deeper into supply chain data in search of savings and efficiencies.” And by digging into that data faster, the typical barriers to analytics in shipper and digital brokerage uses fall by the wayside.
Analytics Power AI, Which Enables Autonomous Logistics
Leveraging freight management analytics will always have benefits in freight and logistics. It has the potential to handle all types of data regardless of mode, possible effects of disruptions like weather and more. With accurate data and automation, enterprises can stay ahead of the curve. And that’s a remarkable advantage in the profit margin-thin world of logistics. Also, artificial intelligence (AI) services and a digital approach reduce inefficiencies by using new tools, e.g., chatbots, to create better experiences and engage with clients. That boosts overall communication and allows for better decision-making in real-time, becoming actionable broker sales tips too.
Regardless of where you look, the supply chain is continuously evolving to reflect more data-driven processes and apply near real-time insights. Data is crucial to making the best decisions and allowing freight management segments to maximize profitability per load.
With that in mind, the freight market will always remain volatile. And as the pandemic wears on and administrative changes begin, having access to an advanced freight rate engine that can consider market volatility and provide the needed insights into day-to-day operations will become essential to success.
For that reason, all freight management segments need to realize that not using data to guide day-to-day decisions is leaving money on the table. They must understand that through the power of big data analytics, enabled by SONAR, it is possible to understand market volatility and play to it. And lastly, they should follow the previously mentioned steps to identify the best way to maximize profitability, renew bidding strategies, and get the best rates or service levels possible. It is that simple.
Build a More Proactive Freight Management Strategy with Data-Driven Decision Making Through SONAR
Regardless of intention, freight data must be actionable. It must offer a way to act on information and add value. After all, anyone can look at market trends. But the differentiators in the market apply that data to guide freight management partnerships, frontline worker performance, and validate internal data findings. And that’s the value of SONAR. Request a SONAR demo to learn more about how the right freight data engine can add value to your supply chain.
BIO: Adam Robinson is a data-driven storytelling marketer who has fallen in love with the quest to make supply chains as high functioning, collaborative, waste-free, and productive as possible in an altruistic endeavor to maximize human capital. Adam works at the intersection of sales, marketing, and product, giving him a unique opportunity to build a community around a platform at FreightWaves that meets his passion & personal mission of hyper-efficiency.
