Julita Lily-Rose June 5, 2021 Spreadsheet
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.
Spreadsheets such as Microsoft Excel are well suited to tasks involving the manipulation of small amounts of related data. Working out a budget, producing visual reports, organizing lists and calculations that involve many variables are all tasks well suited to a spreadsheet. There are some data related tasks however that spreadsheets such as Microsoft Excel are not suited for. Tasks involving the processing and combination of large sets of data for example are generally not well suited to spreadsheets. There is another technology with a long history and theoretical background that specializes in these sorts of tasks. That technology is relational databases. The most common way people insert data into and extract data from relational databases is via the language of Structured Query Language.
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.
Whilst Excel cannot clean or structure all of your data for you it does come with some useful functionality for manipulating and analysing clean and structured data sets. This in-built functionality includes pivot tables, sorting and filtering. Filtering alone is a powerful tool and can help to quickly isolate data based on specified criteria. But what happens if your data is clean but not very structured (a common problem). For instance what if you, a client or your team is using colours, fonts or some kind of formatting to classify data in an Excel spreadsheet. In short, you wont be able to filter the data, because Excel‘s in-built filtering logic requires rules based on numbers, dates and text only. It will not perform filtering based on formats. In addition Excel filtering only applies down rows. It will not perform filtering across columns.
Here‘s a very simple budget set up. Keep a simple income spreadsheet. List all the sources by name in column A. List how much each brings in in column B. And then, any notes you have for the income (like if it is temporary) in column C. You don‘t need to get very detailed with the income, because it only needs to be accounted for so that we can budget for it‘s use. And, the incomes use is in our expenses spreadsheet. This spreadsheet will be much more complex than the income one. You‘ll need a field for income that you carry over from the income sheet. You‘ll also need a field for a total expenses budgeted for. A third field will give us the budget surplus. We get that by subtracting the budgeted amounts from the income amount. A final field will subtract the actual amount spent from the income, and will serve to tell us where we stand in our budget. If you like, you can add another field that subtracts the actual amount spent from the amount budgeted.
Angel Investors are typically much better investors for a long-term business plan that Venture Capitalists, although they do not come usually with the incredible network to help you succeed. Venture Capitalists are more interested in themselves and making money on their investment then what you get out of it or the future of the business with you in it. An angel investor is interested in you, the future of the business and the possibility of making a whole lot of money on their investment. Please consider all this when presenting your business plan to an Angel Investor.
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