NEWS
Argus CIO Featured in Inbound Logistics Magazine
Written By:
Sarah Frazier
|
February 28, 2024
Argus Logistics Chief Intelligence Officer, Mayur Narasimham, has been featured in the February 2024 edition of Inbound Logistics magazine as a Thought Leader on Logistics I.T.
In the interview-style editorial, Mr. Narasimhan emphasizes the significance of predictive analytics for informed decision-making in businesses, particularly in the context of forecasting freight rates.
Leveraging Predictive Analytics to Gain a Competitive Edge
Predictive analytics helps companies make better decisions. The key is to have good data. For example, enterprises can use data to predict how much demand there will be for their products or services, how much capacity they need, how to manage inventory, and how to avoid risks.
Q. WHAT ARE THE BENEFITS OF PREDICTIVE ANALYTICS?
A. Predictive analytics is a way of using data to make better decisions. It can help us improve our business performance, save money, and satisfy our customers. For example, we can use data to predict how much demand there will be for our products or services, how much capacity we need, how to manage our inventory, and how to avoid risks. We can also use data to offer more value to our customers, such as flexible pricing, tailored solutions, and timely communication.
Q. HOW DO YOU LEVERAGE PREDICTIVE ANALYTICS TO GAIN A COMPETITIVE EDGE IN FREIGHT RATE FORECASTING?
A. The key is to have good data. We need to collect data from different sources, such as routes, weather, fuel prices, the economy, and social media. We need to get data that is up-to-date, detailed, and accurate. Then, we need to use AI platforms and machine learning models that can process this data and find patterns and trends—allowing us to forecast the rates for the next few days as well as see the bigger picture.
Q. WHAT ARE THE LIMITATIONS OF TRADITIONAL FORECASTING METHODS WHEN APPLIED TO FREIGHT RATES?
A. Traditional methods can be unreliable, using simple models or averages that don’t capture freight market complexity and variability. They can’t handle unexpected events, sudden changes in demand, or new regulations. We need agile and data-driven methods that can adapt to the changing conditions and reflect the reality of the freight industry.
Q. HOW DO YOU LEVERAGE HISTORICAL AND REAL-TIME DATA IN PREDICTIVE ANALYTICS?
A. We use historical data to learn from the past, and real-time data to adjust to the present. We use advanced machine learning algorithms to analyze historical data, taking into account factors like seasons, demand cycles, and external influences. This helps us make informed predictions about future freight rates. We also use real-time data to constantly update our predictions. We integrate live information on market movements, fuel costs, world events, and other drivers that affect freight rates.
Q. HOW CAN WE USE FREIGHT RATE FORECASTING TO OPTIMIZE OUR ROUTING AND NETWORK PLANNING?
A. By knowing the future rates, we can plan ahead and make smart choices. We can negotiate contracts with carriers at the best times, and secure capacity at stable costs. We can also ensure timely deliveries for our clients. Moreover, we can use future rate forecasts to guide our strategic network planning. We can locate our facilities in the most cost-effective regions, and choose the most efficient transportation modes.
Q. HOW CAN WE ADDRESS THE CHALLENGE OF DATA PRIVACY AND SECURITY?
A. We need to be transparent and trustworthy. We need to protect our data and our clients’ data, and share only what is necessary and relevant. We can use secure and anonymous data sharing methods, such as aggregated reports and encrypted dashboards. We can also give clients control over what data they want to see and how they want to see it.