To survive and thrive in the current ever-changing, hyper-competitive global marketplace, financial managers must go far beyond traditional business concepts. Today they must understand the new dynamics and inter-relationship of forecasting, budgeting, and business performance that will determine their organization’s future success or failure. In this leading edge self-study webinar, you will learn how to:
- Develop effective goals, strategies and plans that lead to successful business objectives
- Leverage the latest technologies and business practices such as data analytics, artificial intelligence, robotics, etc. to support critical business decisions
- Use intelligent forecasting techniques and generative AI to greatly improve the financial planning and budgeting process
To show financial managers how to develop meaningful goals, create strategic plans and set business objectives that lead to a dynamic new budgeting process that generates outstanding results.
SPEAKERS:
David Levi, Senior Vice President, Controller & Principal Accounting Officer, Vonage
Andrés Jalfen, Vice President of Finance, Assistant Controller—Strategy & Budgets, IBM
Brian Mace, Managing Director, Finance Transformation, KPMG
-
Corporate Planning & Budgeting
– Financial Planning and Analysis (FP&A) overview
– Reporting
– Planning
– Analytics
– Business partnerships
– Financial planning process walkthrough
– Techniques to drive agility in the planning process
– Rolling forecasts vs. annual budgets
– Scenario planning
– Embracing analytics in the planning process
– Data analytics
– Business analytics
– Applying analytics
– Budgeting -
IBM's Best Practices for Corporate Financial Planning & Budgeting
– Finance organization
– Business model
– Shareholder expectations
– External value
– Internal value
– Mid-term model and revenue growth
– Portfolio mix driving margin expansion and cash flow growth
– Planning cycles: budget and forecast
– Strategy cycle
– Execution cycle
– Budget
– Forecasting process overview
– Adoption of AI
– Continuing finance transformation journey
– Optimizing workflow
– Applying analytics and leveraging new technologies across finance and operations
– Enterprise performance management
– Utilizing GenAI support -
Intelligent Forecasting Methods & Uses of Generative AI in Corporate Planning
– Market trends for FP&A
– Enterprise data ecosystem
– Automation and adoption
– Concerns regarding AI adoption
– Machine Learning (ML)
– Deep Learning (DL)
– Opportunities for AI and ML in finance
– Intelligent forecasting
– Applying predictive modeling
– Financial planning vs. operational planning
– Industry applications
– Intelligent forecasting case study
– Getting started
– Generative AI for Finance
– Accessibility
– Key concepts
– Finance use cases
– Example for creating summaries and insights of financial forecasts
– Use cases for IR and market intelligence teams
– Analyze investor communications
– Key capabilities and benefits
– Dashboard use
• Identify planning activities within FP&A
• Recognize the purpose of FP&A
• Recognize the primary functions of analytics section of FP&A
• Identify examples of reporting
• Recognize the responsibilities of Corporate FP&A
• Recognize an example of a collaborative deliverable between departments in an organization
• Identify the steps of integrated business planning
• Identify the characteristics of rolling forecasts
• Recognize the number of steps in scenario planning
• Identify the definition of data analytics
• Identify the steps in the data analytics process
• Identify the functions of the corporate finance headquarters at IBM
• Identify the AI and data platform used by IBM
• Identify the forms returns to shareholders can take
• Recognize what high single digit profit growth is driven by
• Identify the processes that are in the execution cycle of IBM’s planning cycle
• Identify ways IBM leverages generative AI
• Recognize the features of an empowered workforce that utilizes an enterprise data ecosystem
• Recognize the percentage of CEOs that have an aggressive investment strategy
• Identify barriers in Generative AI implementation
• Identify the definition of Artificial Intelligence
• Recognize examples of Machine Learning
• Recognize how many main components make up intelligent forecasting
• Identify examples of how predictive modeling is being applied
• Recognize common examples of intelligent forecasting within the industrial manufacturing and financial services industries
• Recognize the definition of Generative AI