Fleet management companies (FMCs) have a wealth of data in their hands. Every step in the vehicle lifecycle is a data point. That data, when harnessed properly, becomes invaluable to FMCs as they evaluate fleet operations and enhance their services to a customer base that is looking for accuracy, ease of use and differentiated products.
Gathering, organizing, and analyzing real-time fleet data empowers FMCs to predict fleet vehicle lifecycle trends, boosting efficiency and service at every stage. Analyzing data properly is critical to predicting fleet lifecycle trends and taking the right steps (at the right time) to optimize your operations.
Real-Time Data Analytics for Fleet Lifecycle Management
Traditional data analysis is frequently hand-coded into shared spreadsheets, or, in some cases, not at all. Many FMCs have operated for decades without a sufficient system for consolidated data collection and analysis, which has made predicting lifecycle trends an impossible task.
Today, data is front and center in leading FMCs. Increasing customer wants, needs, and even demands require FMCs to understand the vehicle status at every step of the vehicle lifecycle so they can provide the level of service clients have come to expect.
End-to-end data orchestration allows FMCs and the customer to gain a high-level view of the fleet vehicle lifecycle across the fleet and for each vehicle. From upfitting delays to driver behavior to condition reports for vehicle remarketing, and everything in between, FMCs can access real-time data on vehicle status enabling them to make data-based predictions for future needs and provide transparent visibility to customers for vehicle status queries.
The benefits of data-driven analysis in predicting fleet vehicle lifecycle trends go on and on. Here are just a few:
- Optimize fleet costs by extending or shortening vehicle life based on accurate predictions
- Reduce vehicle downtime and repair costs through preventative maintenance
- Improve safety and compliance through predictive insights
- Enhance overall fleet performance by optimizing vehicle usage and replacement timing
- Delight customers with a modern fleet experience by proactively meeting their needs
The Glaring Problem of Data Analysis within Fleet Lifecycle Management
Fleet management and leasing companies have tons and tons of data for each fleet, asset, and client. However, organizing that data for effective analysis and problem-solving remains a challenge. Most FMCs still operate with disjointed information systems and data that lags behind the real-world application – keeping data siloed and ineffective. They manage and maintain a high volume of data for clients and their fleets, but that data is typically stored within multiple systems. This disjointed approach makes accurate, effective data analysis difficult, cumbersome, and, in some cases, impossible.
Predictive Analysis for FMCs
Collecting, processing, and analyzing various data points within the fleet lifecycle is essential to predict fleet lifecycle trends. Getting this process right is crucial for FMCs competing in this space. Data analytics empower FMCs to enhance their business, service, and customer experience today and tomorrow. Here’s a quick step-by-step on how FMCs can implement data analytics to predict fleet lifecycle trends:
Data Collection
Thorough data collection is the precursor to predictive analysis. Optimized fleet management businesses gather data from various sources, including
- Telematics: GPS, speed, fuel consumption, engine hours, idling times, and routes
- Maintenance Records: service schedules, repair history, and parts replacement
- Operational Data: Usage frequency and driver behavior
Real-time Data Processing
Once gathered, data must be processed so managers and their teams can organize, read, and analyze it, including in
- Data Cleaning: Eliminate irrelevant or duplicate data
- Normalization: Standardize data from different sources for consistency
- Integration: Combine data from various sources like GPS systems, maintenance logs, and financial reports into a single location
Descriptive Analytics
The data you collect can then be analyzed to identify key patterns in your fleet lifecycles, including
- The average lifespan of different types of vehicles in the fleet
- Typical maintenance intervals and repair patterns
- Cost of ownership and maintenance over time
Predictive Analytics
This is where your data comes together for trend prediction. Automation and AI technologies allow FMCs to understand historical trends, like those above, and model future trends with collected data. Data patterns and automated insights predict lifecycle trends, allowing you to
- Estimate the expected remaining lifespan of each vehicle based on usage, maintenance, and operational factors
- Forecast maintenance needs, fuel usage, or the likelihood of breakdowns based on historical performance
- Categorize vehicles into different stages of their lifecycle (e.g., early, mid, or end of life)
Fleet Lifecycle Optimization
Based on the predictive models, fleet managers can make informed decisions about
- Vehicle Replacement: Anticipate when a vehicle will become inefficient or costly and create a replacement plan.
- Maintenance Scheduling: Use predictive analytics to shift from reactive to proactive maintenance, minimizing downtime and repair costs.
- Cost Management: Optimize fuel consumption and operational costs by predicting when vehicles are nearing the end of their lifecycle.
Predictive analysis drives fleet management and leasing success. When FMCs can accurately anticipate the next step, they provide better service and products and reduce operating costs, all of which serve and delight the customer. With the right tools, data analysis is simple and straightforward. The Ridecell platform empowers FMCs to execute data analysis more effectively than any other product on the market. Our solution enables them to accurately predict fleet vehicle lifecycle trends to optimize operations and delight customers at every touchpoint.
Predicting Fleet Lifecycle Trends with End-to-End Orchestration
While data is, of course, the cornerstone of predictive analytics, it is only useful if it’s accessible and visible. Real-time data visibility across the organization is essential for FMCs to operate effectively now, tomorrow, and ten years from now.
FMCs need a single source of truth to see activity, usage, and performance for every vehicle across every fleet. Ridecell provides the only solution built for FMCs that uncovers blind spots, surfaces operational insights, and recommends actions that allow you to not only predict fleet vehicle lifecycle trends but also capitalize on them.
You don’t have to worry about manual data collection and analysis when you implement the Ridecell Platform in your fleet management and leasing company. Your lifecycle data is automated within the system, giving you and your clients a holistic view of the fleet lifecycle. End-to-end orchestration allows you to
- Track supplier performance – Compare historical performance across vendors to prioritize the highest performers.
- Visualize the impacts of various activities – Focus on activities that provide the greatest cost savings.
- Uncover underutilized assets – Complete vehicle usage visibility helps you rebalance assets for increased profitability.
- Consolidate information for customers – Provide customers with a complete view of their vehicle status from delivery to in-use operations.
- Maximize lifetime value – Optimize delivery times, utilization, and remarketing value to ensure vehicles generate the most revenue automatically.
Every aspect of the Ridecell platform is designed to improve your fleet management operations. From evaluating historical data to predictive analysis for future fleet lifecycle trends, our tools empower you with end-to-end visualization that ushers in the digital transformation of your fleet management and leasing business.
Connect with our team to learn how the Ridecell platform can help you optimize fleet management, position you for future success, and increase your sales starting now.