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Pioneering Investment Strategies Leveraged by Machine Learning

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 To evolve their enterprise, the sports giant decided to replace their outdated planning software with SAP Analytics Cloud for planning.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.

Founded in 2001, our client is part of one of Italy's largest and most influential banks. The client, thanks to its significant assets under management, is one of the major asset management companies in Europe. As of Q2 2022, the company manages a substantial portfolio worth 392 billion euros.

The Challenge

Our client’s first goal was to provide its customers with innovative and high-performing investment strategies. To achieve this, the company needed to leverage the expertise of its management teams and use cutting-edge technologies capable of harnessing larger datasets in terms of volume, speed, and variability while keeping them lean. Therefore, the primary focus was optimizing investment strategies to improve investors' returns.
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The Approach

Together with Avvale, the client developed machine-learning models running on the Azure platform, merging its specialized asset management competencies with Avvale's technology and data scientist expertise.
This choice made this company a pioneer among asset management companies in Italy, being the first to use machine learning algorithms to predict stock index price trends thanks to a predictive modeling process. These algorithms analyze historical data, market trends, and various indicators to identify patterns and relationships that can help predict future stock price movements. By conducting a comprehensive, comparative analysis of the results generated by traditional statistical models and machine learning algorithms, it was possible to assess the real-time accuracy of the latter. This assessment revealed an improvement in the accuracy of stock price index forecasts, demonstrating the effectiveness of the machine learning algorithms.

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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

For the past three years, this client has trusted Avvale because of the observed tangible benefits.  By implementing advanced machine learning models, they have gained valuable insights into stock market trends, resulting in accurate predictions for both short and long-term scenarios. Specifically designed methodologies and dashboards ensure a clear understanding and interpretation of the generated information. Drilled-down dashboard visualizations enable detailed analysis, supported by system emails and summary visualizations. Thanks to the ability to assess models' performance in response to daily market changes, the client can now benefit from personalized, real-time forecasts and aggregate results to develop customized portfolio strategies. As a result, investment strategies have improved significantly, along with the opportunity to make better-informed investment decisions that contribute to a more responsible financial ecosystem.

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