How do we know which forecasts to trust for our most critical business decisions? When stakes are high, big data and machine learning techniques can drive significant value across a wide variety of applications. However, finding the right approach is difficult. A tempting solution may perform well in one context but poorly in others, rely on unavailable information, or incur impractical costs. Whether it’s demand forecasting, supply chain management, or any other application, getting it right requires balancing the need for performance with the constraints of implementation and complexity.
This webinar is designed for business leaders, data science managers, and decision makers seeking to understand how data-driven approaches can improve forecasting and planning. We will discuss examples of forecasting applications, explore some of the methodologies available, and address effective implementation.
Attendees will leave equipped with the tools to:
- Identify types of forecasting applications and issues
- Understand the range of techniques available and related challenges
- Evaluate potential data-driven approaches for your business
- Measure performance in the context of business objectives