The global transportation analytics market is experiencing significant growth and is expected to reach $37.4 billion by 2028, with a compound annual growth rate (CAGR) of 18.7% during the forecast period. The increasing demand for real-time data and analytics to optimize operational efficiency, reduce transportation costs, and improve customer service drives the adoption of transportation analytics solutions. These solutions help monitor and analyze transportation data to assist with better-informed decisions. As data becomes the default in the transportation industry, more freight forwarders ask, is it enough? What must support their data for it to be used to its full potential?
In a Challenging Transportation Industry, Freight Forwarders Turn to Data
Freight forwarders are trying to manage a number of challenges that have surfaced in the industry in the past few years. These are not just problems that are presently unfolding, but it’s also an overarching need to be more proactive to manage future challenges. Global supply chains have seen the potential for problems to arise caused by delays and shortages. Freight forwarders have encountered capacity constraints and changes in transportation costs. There is increased competition and rising customer expectations as the industry undergoes a digital transformation, and freight forwarders must compete for talent. On top of all this, there are added pressures to reduce carbon footprints and adopt sustainable practices.
Freight forwarders are recognizing that they must be more agile and proactive and that access to data is instrumental in addressing their biggest challenges. Real-time transportation data can help mitigate supply chain disruptions, lead to operational efficiency, and help reduce costs, ultimately allowing them to optimize their operations and improve their competitiveness in the market.
Yet Freight Forwarders Ask, is Data Enough?
Exploring the prospect of expanding their scope of data, freight forwarders’ next question should be, “so what?” In other words, what does this do for me? How does this benefit the business? The purpose of data is to drive action. How do freight forwarders turn raw data into informed action?
Dealing with raw data, freight forwarders often face high overhead costs of in-house data management, difficulty obtaining actionable insights from past operations, and the challenge of gauging the performance of supply chain partners. The large amount of data freight forwarders collect on their operations can be overwhelming and difficult to analyze, making it challenging to make informed decisions that optimize the supply chain network and improve operational efficiency. Without clear key performance indicators (KPIs) and other data, like on-time in-full (OTIF) delivery rates, it can be challenging to assess the performance of supply chain partners and identify areas for improvement.
With Challenges and Unknowns, Freight Forwarders Demand Actionable Analytics
Freight forwarders are questioning the usefulness of data that lacks context and analysis. Simply having data does not lead to better decision-making or operational efficiency. It's essential to have the right data, collected and analyzed in a meaningful way, to derive insights. Freight forwarders must consider the quality and relevance of data they invest in and how they use it to create value.
Actionable analytics provide companies with detailed, measurable information that can guide them to achieve their business goals. There are three main types of business analytics: descriptive, predictive, and prescriptive.
Descriptive analytics helps businesses understand historical data and identify trends, patterns, and anomalies. This is useful for discovering areas where improvements can be made and for gaining insights into business operations.
Predictive analytics is used for forecasting future events based on historical data, identifying potential risks and opportunities, and making data-driven decisions that mitigate risks or capitalize on opportunities.
Prescriptive analytics is for getting recommendations based on insights gained from descriptive and predictive analytics. This allows businesses to make informed decisions with a range of options based on the outcomes of different scenarios.
How Container Analytics Help Freight Forwarders Navigate Decisions
Data analysis allows freight forwarders to make data-driven decisions to enhance efficiency, reduce costs, and improve customer satisfaction. Here are three specific ways that data and analytics into the movement of their shipping containers help freight forwarders.
Improving responsiveness
Shipping container analytics can provide real-time data on the location and status of containers, allowing freight forwarders to quickly respond to any issues that arise. If a container is delayed in transit, freight forwarders may proactively communicate with customers and take corrective action, minimizing the impact of any delays or disruptions.
Identifying opportunities for continuous improvements
By analyzing data on the movement of their shipping containers, freight forwarders identify patterns and trends in their operations, where they can optimize their processes and reduce costs.
Maximizing ROI
In optimizing their operations, freight forwarders increase their ROI. They gain insight into maximizing the advantages of saving time and resources to provide excellent customer service.
Find Actionable Container Analytics Through VIZION API
While data is an essential component of informed decision-making, it is not enough on its own. Freight forwarders must invest in data analytics capabilities to extract value from their container data and make better business decisions.
VIZION API provides this level of analytics for real-time container visibility, so freight forwarders always know where their containers are in the process and how they can use this data to improve their operations. To learn more about VIZION, reach out to us today to book a demo.
