Avvale | Case Study | Leveraging AI for Road Safety Improvement

While they expertly deliver innovation and quality to their customers, Callaway Golf’s previous planning and reporting tool wasn’t making the cut. To evolve their enterprise, the sports giant decided to replace their outdated planning software with SAP Analytics Cloud for planning.

Together with Avvale, Callaway Golf successfully implemented SAP Analytics Cloud across their global enterprise in just 6 months. Now, Callaway Golf has a single, consolidated planning solution that has enabled streamlined expense and asset plans so they can focus on what they do best– revolutionizing the sporting world with cutting edge equipment.

The Challenge

In the first decade of the 2000s, the company implemented road safety improvements by enhancing technical and regulatory standards, utilizing Automotive technology and the Tutor system, and introducing robust and consolidated internal procedures. However, in the last 10 years, a plateau has been reached. To take the next step toward "Vision Zero" - eliminating road fatalities - the company needed to transition from reactive safety measures to proactive, predictive strategies.

Despite having access to massive volumes of data, including 750 million rows spanning more than a decade, covering over 5,000 km of highways and 130,000 recorded accidents, the challenge was transforming this raw information into precise, actionable insights. The complexity of analyzing accident probabilities - while accounting for human behavior, infrastructure conditions, and unpredictable traffic dynamics - posed a significant barrier to progress. The company required a strategic partner capable of bridging this gap and unlocking the potential of its data.

The Approach

Aiming to provide the company with a fully data-driven model, we leveraged AI and Machine Learning on AWS cloud infrastructure to create a solution that guides the transition from a reactive to a proactive approach in road safety.

Our team integrated academic research, historical accident data, and real-time traffic patterns into a hybrid analytical model. Using advanced metrics such as Crash Modification Factors, we identified key risk contributors, while scenario analysis tools optimized the planning of preventive safety interventions. To ensure a seamless transition, we deployed two Minimum Viable Products (MVPs), testing and refining the model before full-scale implementation. This ensured scalability and maximized the accuracy of predictive insights.

By combining statistical formulations with AI-powered models, Avvale provided a solution that allows the client to precisely assess accident probabilities for every highway segment, enabling a level of foresight previously unattainable. Our agile methodology ensured that the model would continuously evolve, adapting to new data and reinforcing the client’s long-term commitment to smart infrastructure and sustainable mobility.

The Challenge

Before integrating SAP Analytics Cloud, Callaway Golf's planning landscape centered around SAP's legacy planning solution, Business Planning and Simulation (BPS). While BPS met Callaway Golf's planning needs for many years, the enterprise began to experience limitations with their old solution:

Disconnected plans across the board: As Callaway Golf expanded and acquired new brands, planning processes greatly differed across the enterprise with some business units using Excel spreadsheets and others using legacy solutions for planning.
Outdated planning functionalities: The existing legacy planning solution lacked many modern functionalities. Among them, salary calculations and asset depreciation automation needed improvement. As a result, it became difficult to create detailed and accurate forecasts across the globe.
Significant IT support: The legacy solution required continuous management from IT to maintain runtime. IT had to carve out a full day every week to manually maintain the solution.
No single source of truth: Various departments and brands used different data sources, which led to data silos across the organization, making it difficult to gain a clear picture of the enterprise's planned expenses.
Rigid user interface: Legacy forecasting system was difficult to navigate and lacked working functions and calculations across the board, such as planning on depreciation and existing assets, adding vendors or members on the fly, and breaking down their cost center expense planning forecasts.

The Approach

With Avvale experts on their side, Callaway Golf laid out the following goals for their new planning landscape with SAP Analytics Cloud:

Crowdsource and consolidate plans across the enterprise to gain a global overview of their planned expenses and expand the input capabilities to each responsible owner.
Leverage elevated planning functionalities to create faster and more accurate forecast cost center expense and asset reports. The ability to customize calculations enhances and automates the reporting metrics.
Harness the power of self-service analytics to alleviate IT from the burden of simple maintenance and data entry requests, so they can focus on high-ROI tasks.
Maximize user-driven admin capabilities to control the management of calculations and forms.
Create new KPls driven by the business needs.

When SEM-BPS was the center of Callaway Golf's planning landscape, flexibility was a huge factor that was missing. SAP Analytics Cloud contains powerful scenario planning capabilities that help organizations quickly uncover actionable insights to make data-driven decisions. For Callaway Golf, SAP Analytics Cloud's modern planning functionalities provided users with the ability to:

Add members on the fly
Plan on existing as well as planned assets and automatically calculate the depreciation of values
Test "what-if" scenarios for deeper analysis by creating private versions of plans
Customize the solution based on their current business process
Perform driver-based calculations
Empower users to execute end-to-end planning scenarios, without the help of IT

The Impact

Today, our client has a cutting-edge application active on the entire motorway network. This innovative solution efficiently processes vast amounts of data to deliver actionable insights on the phenomenon of accidents, promoting a proactive approach to road safety and a circular approach to infrastructure management.

The model proves superior in identifying relationships between road conditions and observed accident rates compared to neural net models and time series analysis models, achieving an accuracy rate of 99.6% in predicting the annual number of accidents.

Through the integration of Machine Learning algorithms, customers can now analyze extensive datasets with ease, receiving timely and pertinent information tailored to their specific needs from the entire managed motorway network. The tailor-made solution addresses the escalating demand for comprehensive variable monitoring, facilitating informed decision-making and improving operation and maintenance service.

Vehicle Accident Rate Forecasting: Leveraging AI for Road Safety Improvement

The Challenge

The Approach

The Challenge

The Approach

The Impact