Boeing’s 737 Max issues highlighted the company’s sacrifice of safety for financial performance, resulting in a tarnished reputation. The prioritization of profit over core values also damaged the FAA’s credibility and revealed a lack of accountability for top executives. This downfall serves as a reminder of the importance of maintaining core values and prioritizing them over short-term financial gains.
I was recently talking with a friend who was presenting on “Risks within Your Business” to company directors. This topic made me think of all the companies that I had worked with over the years and what was the most significant unrealized threat they faced within the organization. Upon reflection of all of 2 minutes, I concluded that it was Excel!
Yes, it is Excel! Excel has taken over our corporate environments where it is used by finance, marketing, sales, HR, etc. to do everything from planning, budgeting, forecasting, pricing, reconciliation, and analysis. While Excel is a marvelous tool, which undoubtedly made many of these tasks much more manageable, the problem is that anyone can use it and change a model without anyone else realizing it.
There are three areas of concern:
1. Incorrect models.
Many people within organizations develop Excel models to solve problems that they are currently facing. However, many of these models are built using the improper practices that I’ve highlighted in previous blogs. As a result of these practices, other users of the models are not always aware of the model’s shortcomings but still rely on the output to make significant decisions.
In one case, the model’s author had linked all but two of the assumptions to the assumptions page, thus changing the assumptions all but two of them change within the model. As a result, no one was aware that these two assumptions when “off-line” for the model and were making decisions based on incorrect conclusions. While appearing to be an insignificant problem, the lack of connection of these assumptions led to the approval of some projects because they had positive NPVs and good IRRs, but in reality, were terrible projects with negative returns.
2. Hard-Coded Models.
Many models are built using the corrupt practices I have mentioned before. While I have come across many of these, I cannot meet the example given by my friend Rob Brown in his blog post. To have an organization making decisions with an error in their spreadsheet of the order of magnitude of $200 million that no one was aware of is scary. Do you have one of these in your company? Before you answer “No,” are you sure!
3. “Fixed Models.”
More worrying are those models where there is a good model, but then hard-coded change is made to prevent a #N/A or #DIV/0! result. Unfortunately, no one tells anyone about this change, and it left unnoticed for ages. As a consequence, massive errors can arise.
Recently I was working with a company whose budgeting model had some hardcoded adjustments in formulas to adjust sales, compensation, and other budget items. When reviewing this model with the company’s finance department, there was no explanation of why they made these changes. When asked how good the design was for budgeting, the answer I received was, “Last year was a horrible surprise!” As a result, I wrote CEOs Beware: Problems with Financial Modeling. At last check, the company was still using the model!
Recently I was working with a Fortune 500 company that had a model to drive dashboards for the executive team. Somewhere the data had not all been supplied, and so there was a #DIV/0! result. Rather than fix this, someone had changed some formulae to exclude the offending cells and their related data. However, when entering proper results into the offending cells, the dashboard didn’t update to reflect this. The dashboard continued to exclude these outcomes in the actual and historical averages. Who knows how many ad campaigns and how much marketing spend resulted in improving the results when the results were probably already exceeded expectations.
So what to do?
Companies, departments, etc. should review all their models regularly. This review involves someone checking all the calculations, cell references, and links to ensure that the model is performing as expected. A painful task, but undoubtedly better than to keep walking off the cliff, hoping you can survive the landing.
© 2015 Marc Borrelli All Rights Reserved
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