Laverna Philippine June 9, 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.
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.
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.
He grossed $2,000 a week for his bosses, and earned slightly less than $500 for himself. Still, the wages kept him in seeds, bowling shoes, stick pins, and a Platinum Buddy Holly Fan Club Membership. Lester‘s favorite word was ”crapola,” and he applied it to the ball bearing factory‘s antiquated data processing system in coats as thick as the olive drab membrane clinging to the smudgy glass before him. ”You piteous piece of crapola!” he‘d hiss at the computer when error messages flashed across its screen or its ancient system locked under the demand of crunching numbers to the tenth decimal point. ”Some day I‘ll throw your sorry ass into one of those melting pots out there!”
When Microsoft Excel is used to manipulate, store and analyse data it can become extremely difficult to manage, let alone efficiently work to produce any meaningful insights. This is because with data sets large and small, the data must be meaningful, logical, structured, internally consistent and clean. This holds true regardless of whether the data has been imported into excel from another system or manually entered. In this computing age, most people know that for any data set to be useable it must first be relatively structured and clean. A spreadsheet and its table layout naturally encourages data to be somewhat structured, however ensuring data is clean is also difficult.
Microsoft Excel is a phenomenally powerful calculator. You can create spreadsheets with 10,000 lines of data and calculate subtotals instantly. Indeed, if you change your data, any totals will get automatically updated. Arguably that‘s not too impressive. If we have quarterly revenues of $1m, and we secure another $20k, we can update our subtotal without summing revenues from scratch. So it‘s more impressive that Excel can do the same thing with statistical functions. If you‘ve ever plotted a chart on Excel, you may be aware that you can add a best fit line. These best fit lines are calculated using a method known as regression. Basically, you have to calculate the distance of every single point from the line, and minimise the sum. The maths is a little more sophisticated but the key point is that, every time you change the data, you need to perform the analysis all over again.
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