Sidonia Serena June 1, 2021 Spreadsheet
”Happy crapola!” he exclaimed, rising from the rollered chair and scooping accordion folds of printouts into his tattered briefcase. He snatched his worn black suit coat from a hanger on the back of the office door, switched off the fluorescent overheads, and walked to the executive offices in the adjoining building. When his audit week ended, Lester typically teamed with Lance Lott for a tour of the local watering holes. Lance was a marketing guy he‘d met when he first worked the Bourgeois account. Lance also was single, and resembled Keanu Reeves on a bad hair day. Lester considered him a ”chick magnet,” and although he himself never got lucky on their semi-annual expeditions, the other always disappeared with a babe on his arm. Lester decided, tonight would be HIS night.
”Rippeto‘s Rendezvous” was only a block away, and attracted patrons from all levels of the social spectrum: Primarily fringe types, college students, and the occasional Young Urban Professional. It was near the University, and close to Civic Arena and Three Rivers Stadium. On clear nights, you could look out Rippeto‘s windows and see the Monongahela River afire in the distance. Two things are striking about Rippeto‘s when one weasels through the wall of humanity standing outside, and plasters oneself against an identical living wall inside: The smoke and the smell.
In a well-designed spreadsheet, any output can be calculated from the raw data. However, that‘s not always enough. Sometimes the output is fixed and the raw data is variable. Let‘s say you run an investment company and want to offer your clients a fixed return. An Excel expert could create a very complex model to calculate the likely return on investments over a fixed period. You could then calculate the internal rate of return being offered to clients. The problem is that you‘re not interested in the return offered to clients; that is, after all, fixed. Instead you‘re concerned with how much money you expect to draw from the investment fund, whilst still offering your investors a satisfactory return. If you have $1 and owe investors a quarter, you can calculate your profits using a simple formula.
As a set of general rules data is most useful when things like text fields hold only names as well as meaningful and validated codes, categories and classifications. Text notes and other free form text should be isolated to a dedicated notes field and thus separated from other numeric data. Numeric fields should hold only numeric values (numbers, dates, %‘s and in the correct quantum or magnitude with no text prefixes, suffixes, spaces, text elements or text notes present. You must also be careful that numeric data is not stored as text and it should be internally consistent in terms of the correct format so that it can be used in calculations or for comparison and queries. Finally, addresses should be separated out into multiple fields such as street address, town /suburb, state / province, postal code and country to allow for geographic analysis and mail outs if required. Fixing up a data set to meet these criteria is called data scrubbing, cleansing or massaging. This data cleansing process can be very time consuming even for an experienced Microsoft Excel user, database engineer, business analyst or computer programmer.
So why does data that inevitably finds its way into a Microsoft Excel spreadsheet often suffer from the problems outlined above. The reasons are many. If the data is imported, it may have been sourced from a combination of other spreadsheets, databases, systems, reports, word documents, emails or web pages. If the data has been entered manually it may have been poorly done so by an inexperienced computer users such as administrative or junior staff with a lack of understanding for data structures. Excel is easy to use and widely accessible, so an inexperienced colleague can quite easily update your spreadsheet with a false sense of confidence and inadvertently enter new data incorrectly. And finally, unlike a fully functional software system, data entry in Excel generally has no automatic validating rules, unless carefully setup by the spreadsheet‘s creator.
Unfortunately an internal rate of return is time dependent so the amount you can withdraw depends on when you take it. Suffice to say, the only way to calculate the amount you can take e.g. halfway through the life of the fund, is by trial and error. If you are evaluating a number of investment opportunities, that can be a very time consuming process. Therefore Microsoft have built the Goal Seek function to aid your spreadsheet development. Since Excel 2007, it has been available from the Data ribbon. In earlier versions of Excel, it was present from the Tools menu. It gets straight to the point. It asks you which value you would like to fix (in this case the investor‘s return), what you would like to fix it to, and asks what you would like to change. All fields can accept cell references. It will then calculate the input through trial and error.