Charlotte Lison May 4, 2021 Spreadsheet
First – History/Budget – what kind of a history do you have from your last convention? Did you fill out forms that showed all the results of your meeting? You started with a contract that specified sleeping rooms and scheduled functions, but did you update those numbers at the conclusion of your convention? This is important! You really do need to know what happened last year including your exact sleeping room pick-up, registration numbers with total income generated, specific meeting expenses and the number of attendees that attended each function. Without these numbers you are just guessing.
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.
Lester‘s temporary office at the Factory was glassed on all sides, and surrounded by the sights, sounds, searing temperatures, and smells of the smelting and pouring areas. Originally, the cubbyhole had been used for storing coal and coke until the plant converted to gas-fired furnaces in the mid-‘50s. Over the next three decades a succession of plant superintendents used the room to boink their secretaries, which necessitated its windows being painted a squalid olive drab. During 10 years of performing this chore every six months, Lester had scraped two panes clear, so now he could gaze into the murky, smoky, smelly pit outside as he waited for the grinding computer and clackety printer to spit out a stream of spreadsheets.
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.
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.
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.
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