The classical approach to optimizing fleet usage

One in ten fleet managers uses more than 30 digital spreadsheets to do their job. Almost half complain that spreadsheet management takes too much time, distracting them from more important tasks. These numbers expose a major ongoing productivity problem inside modern fleets. Because one cannot maximize fleet utilization effectively and quickly by relying on static data and manual processes.

Even though the years of using Excel to manage fleets should be long gone, one in four SME fleet managers still spends half of their working day updating spreadsheets, as recent research found. In addition, 60% of fleet managers use multiple digital spreadsheets, and 10% carry out their tasks using pen and paper. Of those surveyed, 79% of managers have more than five different spreadsheets to keep track of the cost, maintenance, and mileage data.

The inefficiencies of fleet management spreadsheets lead to lower productivity, but this is not the only drawback. Spreadsheets also impact missed deadlines (63% of fleet managers are guilty of delays) and make the fleet data more susceptible to errors (a major complaint of 37% of fleet managers). So, why do some fleets still choose Excel files over dedicated, modern, and cloud-based fleet management software?

The pros and cons of spreadsheet fleet management

Manual spreadsheet management does offer some advantages. These include:

  1. Low implementation costs (although not always so);
  2. Simple management without extensive technological knowledge;
  3. Employee familiarity with spreadsheets as a tool;
  4. The relative ease of data input and retrieval.

Additionally, in the case of fleets with several cars, keeping track of all vehicles and related data in a spreadsheet, even though time-consuming, may be sufficient. 

However, spreadsheet fleet management becomes a major nuisance for fleets larger than ten vehicles. The hassle, work, and error it produces exceed the outputs it provides. In particular, ‘spreadsheet fleets’ struggle with:

  1. Elaborate spreadsheet set up;
  2. Impossible to include many custom options;
  3. Time-consuming manual tasks;
  4. Limited functionality and reporting capabilities;
  5. Reactive records that don’t provide any optimization insights;
  6. Asynchronous data input that delays decision-making;
  7. Data inaccuracy due to input errors, illegible writing, and incomplete paperwork;
  8. Limited ability to integrate with other systems;
  9. Increased administration time;
  10. Impeded data visibility.

The classical vs. new ways of informing fleet decisions

Fleet managers tend to deal with overwhelming amounts of data every day. They track metrics ranging from fleet asset utilization and fuel economy through the cost of ownership and performance, ending at driver assignments and coaching. Drawing actionable insights from the staggering volume of data determines the success of their fleets. However, obtaining an accurate and up-to-date picture of the fleet out of the constant streams of data generated each second is a formidable task.

To succeed, managers should discard the traditional spreadsheet-based fleet management methods and replace them with more efficient solutions, such as cloud-based, data-driven software that provides insights for fleet optimization based on data that is always accurate, current, and actionable.

So, to illustrate the benefits of the transition from legacy, spreadsheet-based fleet management into the new era of intelligent cloud solutions, let’s review three major areas of fleet optimization and learn how they used to be managed in the past.

Vehicle tracking

Vehicle tracking systems collect data about vehicle locations, typically from a box mounted inside the car. When these solutions first emerged, their chief purpose was to enable locating the vehicle on the map. This way, it was possible, for example, to identify a stolen car’s whereabouts or check if a car had reached its destination.

Today’s vehicle tracking solutions are much more evolved and accurate. Instead of serving one primary goal, they provide data to monitor, route, and dispatch fleets, onboard information, and ensure security. And thanks to a significant upgrade in connectivity in the last decade, cars and drivers can be managed efficiently while en route, not only at rest.

Additionally, geofencing often enhances modern tracking systems to alert managers if a vehicle goes outside a designated area. And advanced fleet telematics, third-party system integrations, and voice or gesture-guided communications are more recent additions to vehicle tracking platforms. Together, they provide fleets with the sophisticated ability to enhance driver safety and driving style, extend car longevity, decrease CO2 emissions, and lower fuel and energy consumption.

Route planning and optimization

A fleet planner or manager works with hundreds of variables and constraints each day to develop the most efficient routes. But even though route optimization plays a strategic role in fleet management, manual route planning is still commonplace.

If we also consider the changing customer expectations, shorter delivery windows, and rising operational costs, traditional route planning strategies fail to deliver. For example, documenting and developing routes in spreadsheets impede real-time tracking of the delivery fleet. Additionally, the lack of immediate visibility into each fragment of the fleet negatively impacts the accuracy of ETAs for deliveries and increases the risks of fleets running empty miles.

Fortunately, modern, software-based route optimizers resolve the challenges created by spreadsheet-based operations. These powerful logistics tools apply Artificial Intelligence technology to determine the shortest and most efficient routes. They are essential, among others, for vehicle allocation, historical data interpretation, cost-wise route optimization, or minimizing empty miles.

Integrated with AI-driven telematics solutions, modern route planners improve productivity and increase compliance with the service-level agreement (SLA). They also enable fleet managers to handle on-demand orders and reroute on the go to cater to delivery changes initiated by a customer. Considering the steady expansion of delivery fleets and strengthening competition, the ability to dynamically respond to market trends and challenges can be a winning strategy for many first and last-mile delivery companies.

Driver scheduling

As in the case of route planning, much of the driver scheduling still occurs in pen and paper and static digital spreadsheets. However, data-driven fleet management solutions are the only way forward if you seek optimization of this process.

First, they can help free the manager’s workload by automating some tasks involved in the planning process. But their crucial benefit is predictive capabilities. They enable managers to create more customized schedules that take into account the unique driving patterns on top of other parameters. By matching driver’s capabilities with information about the route, weather, traffic conditions, and other data, data prediction engines help planners improve fleet utilization and solve empty repositioning issues.

Beyond the spreadsheet-based fleet management

We can agree that antiquated spreadsheet-based fleet operations have become irrelevant for modern fleets. Thus, forward-thinking fleet managers increasingly switch to data-driven fleet management software, which optimizes fleet operations swiftly in various areas:

  1. For instance, sophisticated mobility analytics can analyze driver behavior in detail, taking into account traditional telematics data and augmenting it with various information from third-party apps, systems, and devices. Based on these analyses, fleet managers can fine-tune their driver coaching to adjust to each person, which ultimately reduces the number of accidents and prevents vehicle downtimes.
  2. Another useful insight that AI-based analytics brings that no spreadsheet can deliver is eco-efficiency profiling. By analyzing individual driving patterns, modern fleet optimization systems can suggest improvements that lead to lower fuel consumption and car wear, all of which protect fleet revenue and reduce emissions.
  3. Thirdly, proactive vehicle maintenance delivers insights that help optimize costs by predicting the optimal timing for car maintenance.
  4. Finally, AI-driven fleet composition analytics insights can help managers determine whether they should upgrade their fleets with electric and hybrid cars and what fleet makeup would help them optimize profits.

The missing piece of the fleet analytics puzzle

Fleet optimization technology is progressing rapidly, offering new features and opportunities to fleet managers and planners to improve their results. At the very minimum level, digital fleet management solutions in the cloud can automate basic functions and set managers free of manually updating spreadsheets. But this is not all they have got to offer.

By advancing from static, retroactive fleet management into data-driven fleet analytics solutions, fleet managers get a wider context of each trip, enhanced with insights about driver behavior, road conditions, weather changes, potential road hazards, etc. This knowledge collected and analyzed by intelligent algorithms lay the foundations for more sustainable, predictable, and manageable fleets.

Key Takeaway: Spreadsheets played their part in improving fleets in the past, but they no longer belong in the future. Instead, they must clear the path for modern, data-driven fleet analytics, which uses innovative perspectives, such as augmented driver behavior analysis, to empower fleet managers with data and give them a competitive edge with optimized fleet operations.

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