What is the optimal way to allocate resources for financial modeling?

The purpose and scope of any model needs to engage business stakeholders and drive decision making. If it’s too accounting and finance centric and doesn’t consider real business scenarios and drivers it will be a waste of time and scope will be off track. One of many key focuses is cash flow and optimal deployment of resources (people and investment) in order to maximise bottom line margins and EBITDA. What’s valuable is determined through DCF analysis and other key valuation techniques. Ultimately the focus is on the output and start with the end in mind. With a well built model what decisions could be made better that are currently gut feel! Focus on solving this challenge and the scope will fall into place. ??

View other drafts Finding the "optimal" way depends on your specific context, but consider these key steps: 1. Define the model's purpose and scope: Focus on the core objectives and avoid unnecessary complexity. 2. Choose the right tools and methods: Balance power with ease of use, considering Excel, specialized software, or custom solutions. 3. Allocate time and team effectively: Prioritize tasks based on importance and expertise, ensuring efficient collaboration.Utilize automation and best practices: Leverage templates, macros, and data validation to save time and ensure accuracy. 5. Validate and verify your model: Test assumptions, sensitivity analyses, and scenario planning to build confidence 6. Continuously improve and adapt

1- Focus Areas: Prioritize critical elements like revenue forecasts and cost analysis. 2- Expertise Assignment: Allocate experienced analysts to complex tasks like risk evaluation. 3- Software Utilization: Invest in advanced financial modeling software. 4- Training Resources: Ensure continuous skill development in latest modeling techniques. 5- Data Acquisition: Emphasize on collecting high-quality, relevant data. 6- Time for Testing: Allocate sufficient time for model testing and validation. 7- Feedback Integration: Include resources for model adjustments based on stakeholder feedback.

Investors receive numerous options from startups, so they tend to quickly scan what your business is about. It's crucial to make it very clear what problem your business is solving and highlight your experience in the field. Often, you only have one chance to capture an investor's interest in the first place.

Whilst the right tools and methods are important, one has to step back and consider how re-useable and easy it will be for others to adopt (outside just the modeller or the 3rd party vendor). Great for software vendors when you need to contact them every time something changes (and it always does), so be careful putting too much reliance on third party tools that take the control of logic and free thinking away from the finance team. Any gap in software functionality will ultimately be met with an Excel solution so rather than have hybrid solutions build a robust data and financial model end to end that leverages Power Query, Excel and Power BI (incl Fabric). Outside of these no other tool is needed for modelling.

This is arguably one of the biggest challenges. Time and resources currently allocated is nowhere near enough. Period. Teams are often building models once a quarter or year and then due to inefficient models are not doing it monthly. A rolling 3-way monthly model is a MUST for all teams. It also helps when they have to build adhoc models as they have developed skills and also can re-purpose elements of the monthly rolling model. The model should be a 3-way (IS,BS,CFS) and this is absolutely possible without fancy software just using Power Query, Dynamic Arrays and a best practice design and structure. The team should build this into the monthly close process and it’s the last step of the month once the books are closed.

Leverage existing knowledge and skills within your team to build models efficiently. Promote knowledge transfer and cross-training to enhance team flexibility and resilience.

Once you have setup a model that actualises results each month and compares expected results to reality you are well on your way validating and accuracy and usefulness of the model. In addition to comparing forecasts to actuals, equally important is checking for errors, hardcoding, external links and other high risk areas. Searching, detection and auditing spreadsheets for this purpose is also key to validating model performance. All models are wrong, some are useful (George E Box) so if you are going to invest time in building it, make sure you leave time and investment to validate its working properly to extract real business value.

Many don't always agree with this, but when you are marking a financial forecast, I prefer to plan for only a 2-year scope upfront. While some prefer a 5-year forecast, in this fast-moving world, predicting accurately beyond 2 years is challenging, often involving making up numbers. Forecasts rely on the team's experience, and with constantly changing data, increasing costs, and end prices, it's more beneficial to focus on a clear, understandable overview that investors can grasp