5 common mistakes when building financial models

Critics of financial modelling will always tell you that there are simply too many moving parts and interdependencies within a company to arrive at an accurate prediction of the future.  They’ll point to how easy it is to adjust an input assumption and completely change the entire scope of what the model outputs.  And to a certain extent – they’re right.

We don’t have a crystal ball. We don’t know how the future will play out.  And our models are never going to be perfect.

But that doesn’t mean that we shouldn’t try to make this as accurate as possible.  A popular aphorism in the world of statistics says that “all models are wrong, but some are useful” and this really encapsulates the value here.  The objective is not to create a financial model that is 100% accurate – but rather to go through the planning process so that we can make informed decisions about how to move our companies forward – both understanding the risks and opportunities that face us.

To help you optimize this planning process and arrive at financial models that are useful – let’s look at 5 of the most common mistakes that get made when working through an FP&A process.  If you can avoid these mistakes, you’ll put yourself in a good position to get the most out of your financial predictions.

  1. A lack of clarity on what you’re trying to solve for.  Financial models are only useful if they inform the key decisions that you can control.  Too often companies will build overly complex and cluttered models in an attempt to be more precise without actually understanding what they’re solving for.  Try to be ultra-clear about your goals and objectives upfront so that you can build with the end in mind.  Apliqo really helps with this by helping to identify the KPIs and drivers that really matter as well as pulling them all into your system dynamically.
  • A siloed approach.  A financial model should take into account all of the complexity that lives within your organization.  If you are only going to look at specific sections or departments – you’re going to miss out on a lot of the context that makes financial models worth it.  You need a holistic approach that covers all your bases if you are to get truly insightful analysis that can align with strategic worldviews.
  • Hidden assumptions.  A good financial model is dynamic and responsive to changes in inputs.  You want to work with a system that can handle changes to assumptions and drivers with ease so that you can see what impact it makes.  Poor models have unconscious assumptions built in and hard-coded that don’t reflect reality or the fact that things can change.  This is where using a dynamic database like IBM Planning Analytics / TM1 can be so powerful.  You want your assumptions to be malleable and ultimately testable so that you can verify how accurate your model actually is.
  • Lack of sanity checks.  Financial modelling is an art and a science which means that errors can creep in no matter how much attention you pay to the details.  To avoid these, be sure to build various sanity checks into your process to catch those things that seem strange.  At the very least, these checks might draw your attention to those aspects of your business that require special attention to understand why they are behaving in the way that they are.
  • Ignoring domain expertise.  Financial modelling should be a collaborative effort and it’s best practice to pull insights from your various departments who have a better sense of what is happening on the ground.  If the finance team runs with the model without checking in with other stakeholders, they risk injecting unrealistic ideas and evaluations that aren’t grounded in reality.  Leverage the experience and knowledge of the people around you so that the model is as complete as it can be.

These mistakes are easily avoided if you’re aware of them and they can have an outsized impact on how useful your financial model ends up being.  Having worked with a wide array of clients here at Apliqo, we’ve seen first hand just how powerful these best practices can be, especially in a dynamic software environment like TM1 enables.

If you’d like to explore an alternative to Excel that can help you arrive at more useful financial models, then get in touch.  Apliqo offers an intuitive and powerful interface that can take your predictive modelling to the next level without compromising on data quality or complexity.

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