I get it. We accountants were born with spreadsheets, and our birth certificates already have Excel license keys printed on them. And yes, I get that Excel is great when you need to crank out non-routine stuff such as calculating/breaking-down the impact of complex audit adjustments that go back to prior periods. But spreadsheets for routine and repeatable tasks? I'd like to think there's a better way.
One gripe about "routine spreadsheets" is that the absence of automated workflows. Your accounting team, for example, distributes your PBC spreadsheet to dozens of team-members via email. Everyone does their thing, and now you need this big manual effort to figure out who was assigned what, who hasn't submitted their stuff, etc. This method is old school, and it stinks when you're under the gun trying to gather PBC's for your auditors before they start field-work.
More importantly, as an analytically-oriented accountant, it bugs me how much data we lose from all these routine spreadsheets we use. Think about your bonus accrual schedules. We whip up this massive spreadsheet to calculate our accruals each period - but because the data is stuck in la-la-land (i.e., nowhere), how can we easily calculate the accuracy of estimated accruals by period over the course of time? How can we track which departments have a bad habit of underestimating, how accurate C-level estimates are, etc.? Of course we can create another large spreadsheet to try to calculate this (by gathering data from each period's spreadsheets), but the effort in this wouldn't pass the cost/benefit test.
We built Gappify as a first step to eliminating routine spreadsheets. I may be biased, but I'd like to think that we accountants are valued more for our analytical skills and talents (versus just being spreadsheet elves). This is especially important in today's environment, where the volume of business/financial data being generated is exponentially increasing. Businesses will need us not only to efficiently capture all of this data, but also to help partner with them to better understand what this data means to the business. More on this later...