Life is all about choices, but you can’t choose the maximum amount in all spending categories. These guidelines are only recommended ranges.
You may also notice that if you spend the maximum amount in every category, you’ll exceed 100% of your income. It’s important to know there is nothing wrong with exceeding this limit as long as your budget balances (your expenses don’t exceed your income).
However, if you happen to have young children in daycare, have high education costs, take nice vacations, tithe, or have hobbies or recreational interests that aren’t cheap, you’ll quickly exceed the suggested maximum for this category. The guidelines suggest you spend 5 – 10% of your income in this category. The category in these guidelines that people will most commonly exceed is the “Personal & Discretionary” expense category. Don’t rely on credit for these unexpected expenses.
You’re allocating some money towards savings (savings are absolutely necessary for life’s many unexpected expenses. You’re not spending more than you earn, and. If finances aren’t strained in your household, you can choose to be more relaxed and go beyond the guidelines in areas as long as you’re careful to do two things: These guidelines have been created for someone who really needs to put together a tight budget. Plus, the side-by-side comparison is not as direct, and it takes double the space in comparison with the bullet chart.How to View These Budgeting Guidelines to Get a Hold of Your Spending Habits Cluster bars are not bad, but I can’t color those regions based on the conditional of being above or below budget. The bar-line combination chart is better, but with the labels overlapping, it's hard to tell which numbers are for what and where exactly the point on the lines fall. But our focus here is point-to-point comparison, and the line chart can’t accomplish that. The line chart is great for showing and comparing trends. How about other chart types? A line chart, combo chart, or a cluster bar chart perhaps? The latter is particularly useful when you have more regions or other categories of data on the axis. With straight bars, the bullet chart is more precise in presenting data, and more compact. The key difference is afore-mentioned straight bar vs. However, whether you use them is up to your unique data and audience: if your customers are accustomed to it and love it, why change?Īn great alternative to the gauge chart is the bullet chart. Additionally, it's worth it to note that some experts criticize gauge charts, saying that the curved bar is not as accurate as the straight bar in presenting data. It's appropriate when you only have a few visuals on the page, and their underlying metrics are valuable enough to spotlight. This chart type does take space and attract attention though. London is the only region that is below budget, and the South region greatly overspent their budget. Can you now answer above questions much faster? Absolutely. Now your datasets are thoughtfully ranked, colored, and labelled, making it easy for users to quickly find insight. It's not very intuitive, right? A simple thing you could do to fix this is to add a variance column and color the regions by above or below budget.Īnother tactic you could use is to turn your table into a visualization, like the gauge charts shown below. Or is it? Not if you care about your users and want to maximize your data’s consumability for them! Let’s take a moment to see how quickly you can find out which region is below budget, and which region has the largest variance above budget. We put actuals and budgets in the columns, and regions on the rows, and it seems fine. For example, here we have a very small dataset about operational expenses and budget. With cross tabs, the process can be quite easy and straightforward. But which visual type is the best choice to represent your findings? Microsoft Design & Data Visualization Lead Miranda Li reviews some likely candidates, and talks about why some visuals can work better than others for your audience.Ĭomparing actual numbers against your goal or budget is one of the most common practices in data analysis. Comparing your data against target goals is one of the fundamental tactics of data analysis.
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