Nicolas Boucher – Financial Analysis for FP&A
All the Financial Analysis Methods and Application in Real Life that they don’t teach you at school!
How would I describe this course in one sentence:
This is the course I would create for myself if I was going to teach the younger me how to analyse a P&L and give insights to my management and business partners.
Why you need to take this course:
- You are sick of your role in accounting and want to move to FP&A
- You are a new FP&A analyst but you don’t have access to appropriate coaching to improve your performance
- You are stuck in a routine and you feel you have hit a roadblock
- You don’t find appropriate resource online that can help you with improving your work
- You want to increase your salary
Who the course is for:
- Any finance professional with the motivation to improve his/her soft and technical skills
- Finance professionals wanting to transition in a role with more analysis, forecasting and business partnering activities
- Students wanting to learn real world professional skills directly applicable to your next position in Finance
How you can benefit from my experience:
I am Nicolas Boucher, a Finance Thought Leader with more than 1,5 million followers across social media.
I have 14 years of experience working as a financial auditor for a Big 4 firm and having different finance leadership roles in a multi-national company.
During my career, I have trained, coached and managed more than 5000 people on AI for Finance, auditing, controlling, accounting, Excel and Powerpoint.
What You’ll Learn In Financial Analysis for FP&A
- Analyse sales and margin variances, including product mix (PVM Method)
- Understand cost variances
- How to calculate project variances
- Identify insights from raw data
- Link financial figures with operational data
- Learn how to make back-of-the-envelope calculations
- Headcount related KPI and analysis
- Understand how you can use variance, profitability and sensibility analysis to bring insights to your company
- Horizontal and vertical analysis
- Sensitivity analysis
- Overhead analysis