How do we know which forecasts to trust for our most critical business decisions? When stakes are high, big data & 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 & complexity.
This webinar is designed for business leaders, data science managers, & decision makers seeking to understand how data-driven approaches can improve forecasting & planning. We will discuss examples of forecasting applications, explore some of the methodologies available, & address effective implementation.
Attendees will leave equipped with the tools to:
Identify types of forecasting applications & issues
Understand the range of techniques available & related challenges
Evaluate potential data-driven approaches for your business
Measure performance in the context of business objectives
Senior Data Scientist, Metis
Javed is an economist & data scientist with experience in banking, finance, forecasting, risk management, consulting, policy, & behavioral economics.