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Last updated on 2024年7月22日

You're in charge of fleet safety. How can you use data analytics to prevent accidents before they happen?

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Managing fleet safety is a critical responsibility that requires a proactive approach to prevent accidents. With advancements in technology, data analytics has become a powerful tool in identifying risk factors and implementing preventive measures. By analyzing historical data, patterns can emerge that can help predict and prevent future incidents. This involves collecting data from various sources, such as vehicle telematics, driver behavior, and maintenance records, and then using analytical tools to make informed decisions that enhance safety.

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Francisco Rom?o

Engenheiro Mecanico
Ghamdan Qamhan

Supply Chain Analyst. CSCA. CSCE. CLTE. CHL. CMI. CIQ. Certified. Master of Supply Chain and Logistics Management.

1 Harness Data

The first step in leveraging data analytics for fleet safety is to harness the wealth of data available from your vehicles and drivers. Modern telematics systems provide real-time information on vehicle location, speed, braking patterns, and more. By collecting this data, you can begin to understand the conditions leading up to incidents. Analyze the data to identify common factors in near-misses or accidents, such as harsh braking or rapid acceleration, which could indicate risky driving behavior that needs to be addressed.

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Francisco Rom?o

Engenheiro Mecanico
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Através do tratamento dos dados dos sistemas de telemetria é possível identificar atitudes imprudentes, excesso de velocidade e dire??o perigosa. Além do fator operacional, é possível identificar sintomas de que o equipamento apresenta avarias que podem gerar acidentes e devem ser tratadas, como pneus furados, desnivelamento do veículo, perdas de press?o em sistemas hidráulicos, entre outros.

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Ghamdan Qamhan

Supply Chain Analyst. CSCA. CSCE. CLTE. CHL. CMI. CIQ. Certified. Master of Supply Chain and Logistics Management.
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from my previous experience hiring professional drivers with strong familiarity with the area of operations is a key. I am checking driving patterns and checking vehicle logbooks for variations. Mapping is also important to make fleet drivers aware of road conditions. Data analytics can play a major role in managing fleet.

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2 Analyze Patterns

Once you have collected the data, the next step is to analyze it for patterns that could indicate potential risks. Look for correlations between accidents and specific behaviors or conditions. For example, you might find that accidents are more likely to occur at certain times of day or in particular weather conditions. By identifying these patterns, you can take targeted actions to mitigate these risks, such as scheduling deliveries outside of high-risk hours or providing additional training for driving in adverse weather conditions.

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Jose Cruz

Gerente de Operaciones | Gestión de Flotas y Soluciones óptimas para el Transporte y Distribución | Flota | Materiales Peligrosos | última Milla | CEDIS | Cultura y Desarrollo Organizacional
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Identificación de puntos críticos: Análisis de ubicación: Identificar áreas con alta concentración de accidentes, intersecciones peligrosas o zonas con condiciones climáticas adversas. Análisis de comportamiento del conductor: Detectar patrones de conducción riesgosos, como exceso de velocidad, frenado brusco o uso indebido del teléfono celular al volante. Análisis de vehículos: Monitorear el estado y mantenimiento de los vehículos para detectar posibles fallas mecánicas que puedan ocasionar accidentes.

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3 Predictive Insights

Predictive analytics is a game-changer in fleet safety management. By applying statistical models to your data, you can forecast potential safety issues before they occur. For instance, if a certain route consistently results in hard braking, it might suggest a need for route optimization . Predictive insights allow you to be one step ahead, implementing changes that can prevent accidents rather than just reacting to them after the fact.

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4 Driver Engagement

Engaging drivers in safety initiatives is essential, and data analytics can help personalize this process. By sharing individual driving data with drivers, they can self-assess and improve their driving habits. Recognizing and rewarding safe driving based on analytics also boosts morale and encourages a culture of safety. This personalized feedback loop ensures that drivers are aware of their impact on fleet safety and are motivated to maintain high standards.

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5 Continuous Improvement

Continuous improvement is vital in fleet operations, and data analytics provides the means to monitor the effectiveness of safety measures. By regularly reviewing the data, you can see if changes are having the desired effect on reducing accidents. This iterative process helps refine your safety strategies over time, ensuring they remain effective and adapt to new challenges as your fleet evolves.

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6 Maintenance Proactivity

Proactive maintenance is another area where data analytics can significantly reduce the risk of accidents. By monitoring vehicle diagnostics , you can predict when parts are likely to fail and service them before they cause issues. This not only prevents accidents but also reduces downtime and extends the life of your fleet. A well-maintained vehicle is a safer vehicle, and data analytics is key to achieving this.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Jo?o Andrade

Co fundador na SaltCode | Diretor Comercial & Novos Negócios
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Na década de 90 tive a oportunidade de implementar vários projetos em algumas das principais transportadoras do país e no Brasil fomos os pioneiros com o famoso “Como estou Dirigindo?” Por meio de um canal 0800 conseguimos grandes resultados através das liga??es recebidas, tanto para a preven??o de acidentes como na condu??o de toda a comunica??o quando o pior acontecia … Impressiona os recursos que temos atualmente mas algumas velhas solu??es em minha opini?o ainda s?o indispensáveis e complementares para uma gest?o de alto nível !

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Okafor Mabel

Fleet Manager Oil and Gas
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1 Predictive modeling: By analyzing historical traffic accident data, predictive models can be developed to identify patterns and predict the likelihood of future accidents in specific areas. 2. Identifying high-risk areas: By analyzing data on accident location, time of day, and other factors, high-risk areas can be identified and targeted for interventions such as increased enforcement or infrastructure improvements. 3. Identifying high-risk groups: By analyzing data on factors such as age, gender, and previous driving history, high-risk groups can be identified and targeted for interventions such as education and awareness campaigns. 4.Monitoring traffic flow: By analyzing real-time traffic data.

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You're in charge of fleet safety. How can you use data analytics to prevent accidents before they happen?

1

2

3

4

5

6

7

1 Harness Data

2 Analyze Patterns

3 Predictive Insights

4 Driver Engagement

5 Continuous Improvement

6 Maintenance Proactivity

7 Here’s what else to consider

Fleet Operations

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You're in charge of fleet safety. How can you use data analytics to prevent accidents before they happen?

1

2

3

4

5

6

7

1 Harness Data

2 Analyze Patterns

3 Predictive Insights

4 Driver Engagement

5 Continuous Improvement

6 Maintenance Proactivity

7 Here’s what else to consider

Fleet Operations

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