Read a book on XLL development something like this and build the XLL add-in using statistical libraries made on/for C++. Something that is a one-liner in R.įourth option: bite the bullet and learn C++. I haven't tried this since it seems that QuantLib is really focused on pricing derivatives and I will still have to write huge VBA code to fit a Log-Logistic distribution to data on a spreadsheet, for example. Third option: ask peers to install two Excel addins: MyLibrary.xlam and QuantLibXL to harness the power of Quantlib on statistics and use some VBA to put everything together. Nope peers won't install Python on their machines. Something similar to what I would like to accomplish would be: + our own analysis workflow.Ĭonclusion: I understand it will be (very) hard to re-write all the routines I used to do in R in a vba-xlam. I've started to work down this road BUT found myself reinventing the wheel for very basic tasks (fit a few distributions to data, eg.), and limited by the VBA capabilities on data analysis. It's easy to distribute and update, since everyone has Excel/VBA installed in their machines. I want to share my statistical analyses/workflow with them.Ġ3 - WHAT I TRIED, AND POTENTIAL SOLUTIONS:įirst option that came to mind was to write a simple UDF library in pure VBA (.xlam). Iii) R is fast enough for my purposes and data sizeįew months ago I started at a new company where my peers do not use R/Python, only MS-Excel. Ii) writing C++ code (Rcpp) is not something I've done I) I`m comfortable with the language most of the time and have written R packages for myself, but The advantages of modern BP&F software go beyond rolling forecasts, current budgets, and continuous planning sprinkle in some other advanced solutions and watch as your entire financial management becomes more secure, flexible, and potentially even more economical.I'm a typical non-programmer R user for 6+ years. For an all-too-recent example, just think about organizations today, basing their plans and strategies on data generated pre-COVID and wondering why their predictions were so far off their current revenue. Modern cloud-based systems allow organizations to update and review budgets, plans and forecasts in almost-real-time, rather than being reliant on reports generated several quarters earlier when the world looked very different. Markets, competition, trends, and sociopolitical environments now shift rapidly and unpredictably. While reporting, planning and forecasting annually may have cut the mustard decades ago, it simply isn’t fit for purpose in today’s VUCA business landscape. The primary issue with doing BP&F on spreadsheets is that it’s enormously static and reactive. Just because something isn’t defective doesn’t mean that it can’t be vastly improved upon. “If it ain’t broke, don’t fix it,” you might say. ![]() Substitute the monitor for ledger paper, and those companies are managing their financials in the same way as managers were doing it more than 100 years ago. While cloud-based SAAS solutions have improved efficiencies right across organizations, 70 percent of companies still confess to relying heavily on spreadsheet reporting for BP&F, with 40% using spreadsheets exclusively. ![]() But that’s still no excuse for still using Excel for all your budgeting, planning and forecasting. In the three-and-a-half decades since Microsoft first launched it for the Macintosh (Windows didn’t follow until two years later), Excel has undoubtedly established and cemented its reputation as one of the all-time great business tools and software. Forecasting combines planning and budgeting with historical performance and the current economic and market conditions to provide a financial prediction of a company’s performance over the next few quarters of years.Įxcel turns 35 this year.
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