What are the differences between business model types?

What are the differences between business models used for (a) FP&A and corporate finance, and (b) investment banking and management consulting?

A key intention for FP&A and corporate finance models is to build them flexibly and fluidly. These models should be able to import new data, remove outdated data, and perform syntheses without the mechanics of the models causing ineffectiveness. Dynamic modeling is what allows us to reference key assumptions, datasets, drivers, and inputs very quickly and very easily without concern that the underlying mechanics will break.

Investment Banking and Management Consulting Business Models:

Throughout my career in consulting and transactional work, the nature of the work has been very engagement focused. In other words, there’s a scope of work and a mandate. When the mandate is met and the work product is completed and delivered, the engagement concludes and it’s on to the next one. The same framework and models can be applied again and again, albeit in different contexts and circumstances.

Because of the specific objectives and usage of business models in investment banking and management consulting, the work files often have contained data that often isn’t frequently updated nor rolled forward. It doesn’t need to be. The time periods covered tends to be static in that once the transaction closes or the mandate has been completed, the model gets put to bed. Because of these limiting factors, the work files tend to require limited maintenance, at least when compared to FP&A models.

Because of the contained data and specific usage, these models tend to require:

Less-frequent updates
Less flexibility
Fewer dynamics

I rarely apply dynamic modeling techniques for transactions or limited consulting engagements.

FP&A and Corporate Finance Business Models:

In contrast to ibanking and consulting models, FP&A and corporate finance business models often have a broad scope and use. They’re leveraged and applied in a multitude of different ways. If you have a business model, forecast, analysis, or other work product that:

Needs to live for weeks, months, quarters, or years
Needs to be replicated across business units
Needs to have new data coming in and old data falling out

It likely does need enhanced flexibility and you need to think a bit differently.

Because FP&A and corporate finance often require broader scope and use, growing data sets, and evolving time periods, they require more ongoing maintenance. If a company is putting together a 2022 forecast, that forecast will eventually need to roll into 2023, 2024 and beyond. Why recreate the model every year if we don’t have to?

The differences in our modeling objectives require a different mindset and model-build. These models tend to require: