Finance teams are under pressure to forecast faster and more accurately in changing business conditions.

Join us for an exclusive session to explore the latest forecasting innovations coming to IBM Planning Analytics, including new forecasting models, machine learning capabilities, and advanced statistical forecasting techniques designed to improve planning accuracy and reduce manual effort.

🗓 Monday, 30 June 2026
⏰ 10:00 – 11:00 AM AEST
💻 Free Online Webinar – LinkedIn • Facebook • YouTube

What's in it for you?

In this session, you’ll learn:

• How forecasting in IBM Planning Analytics is evolving

• New extended forecasting libraries and models

• Weekly, daily, and multivariate forecasting capabilities

• How machine learning models like Auto-ARIMA, BATS, Holt

• Winters, and XGBoost can improve forecasting accuracy

• Best practices for handling seasonality, trends, holidays, and external variables

• How to compare forecasting models and improve forecast confidence

You’ll also see a live demonstration of the new forecasting experience in IBM Planning Analytics, including forecast summaries, confidence ranges, scenario analysis, and outlier management.

Who should attend:

• IBM Planning Analytics (TM1) users
• FP&A and business analysts
• Anyone curious about how AI can level up enterprise planning

What's in it for you?

More ways to forecast

TM1 used to have one way of predicting the future. It now has several, each designed for different situations — businesses with seasonal swings, complex cost drivers, or multiple factors influencing the same number. You pick your data, the system works out the best approach, and gives you a forecast you can actually explain to a board.

Forecast by the week or day, not just the month

Until now, TM1 forecasting worked in months. That's fine for an annual budget but useless if your business moves faster than that. You can now forecast by week or by day — so if you're in retail, logistics, or any business where conditions change quickly, your planning tool finally keeps up.

Why you should be there

This session will help finance teams better understand which forecasting models are best suited for different business scenarios and how machine learning can improve planning accuracy. Attendees will gain practical insights into reducing manual forecasting effort, improving forecast confidence, and applying advanced forecasting capabilities within IBM Planning Analytics through real examples and live demonstrations.