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DRIVING IMPROVEMENT: DATA ANALYTICS, PROCESS IMPROVEMENT AND INCENTIVEBASED PAYMENTSPresented by: Samuel Lin, MA, PMP, CHQ Director, Strategic Operations Chris Ray, MS Administrative Manager, Performance
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How to fill out driving improvement data analytics

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How to fill out driving improvement data analytics

01
Gather all the necessary data on driving behavior, such as speed, acceleration, braking, and lane changes.
02
Clean and organize the data to remove any inconsistencies or inaccuracies.
03
Determine the key performance indicators (KPIs) that will be used to measure driving improvement, such as average speed, fuel efficiency, and safety rating.
04
Analyze the data using statistical methods and data analytics tools to identify patterns, trends, and areas for improvement.
05
Generate reports and visualizations to communicate the findings and insights from the data analysis.
06
Use the insights to develop targeted driving improvement programs, interventions, or training initiatives.
07
Monitor and track the progress of driving improvement initiatives over time using the analytics data.
08
Continuously iterate and refine the data analytics process to drive ongoing driving improvement efforts.

Who needs driving improvement data analytics?

01
Driving improvement data analytics can be beneficial to various stakeholders, including:
02
- Fleet managers or logistics companies that want to optimize the efficiency and safety of their drivers to reduce costs and mitigate risks.
03
- Insurance companies that want to determine the driving behavior of their policyholders to calculate accurate premiums and identify high-risk drivers.
04
- Government agencies or transportation authorities that aim to improve road safety by identifying problematic areas, enforcing regulations, and implementing targeted interventions.
05
- Driver training schools or instructors who want to assess their students' driving performance and provide personalized feedback and coaching.
06
- Individual drivers who are interested in monitoring and improving their own driving habits for personal safety, fuel efficiency, or eco-friendliness.
07
- Automotive manufacturers or research institutions that need driving behavior data for research and development purposes, such as improving vehicle design or autonomous driving algorithms.
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Driving improvement data analytics is the process of using data to analyze and improve driving behaviors and habits.
All drivers and organizations that are looking to improve their driving practices are required to file driving improvement data analytics.
To fill out driving improvement data analytics, drivers and organizations can use technology such as telematics devices or software to collect and analyze driving data.
The purpose of driving improvement data analytics is to identify areas for improvement in driving behaviors, reduce risks on the road, and enhance overall safety.
Information that must be reported on driving improvement data analytics includes driving speeds, braking patterns, acceleration rates, and adherence to traffic laws.
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