Economics homework help
Economics homework help. Instructions for Variance Analysis Assignment
You’re a budget analyst doing a variance analysis for the same department in Arapahoe County that you’ve analyzed already for the Cutback Scenario and Forecasting assignments. There are separate spreadsheets in the Assignment folder named for each department. For example, the Assessor’s Office spreadsheet is called “ASSESSOR 2016 to 2019 Variance.xls” and it’s the same convention for the other departments. Pick the one with your department’s name.
The basic question that’s answered by a variance analysis is how closely the actual spending for the years 2016-19 (see the “Arapahoe County Actual Expenditures” section of the spreadsheet, in B16 through E24) follows the budgets (see “Arapahoe County Adopted Budgets” in B3 through E11). If there’s a sizable change between the budget and the actual, that’s a failure to execute the budget. In government it’s called budget execution because the budget isn’t just an initial plan or guideline. How much an agency (like one of our Arapahoe County departments) budgets is how much it’s expected to actually spend, give or take reasonable variances. Thus, variance analysis!
The place to devote virtually all of your attention is the “Arapahoe County Budgeted vs. Actual” section of the spreadsheet in B29 through G37. When “% Variance” is positive it means that the budgeted amount is greater than the actual (meaning overestimated or under-spent). Negative “% Variance” means the reverse (underestimated or overspent).
The whole reason for this analysis is to highlight potential areas for questioning your department on budgeted amounts vs. actuals. Questions that variance analyses answer include the following:
- Do positive variances in particular spending categories or the total budget raise concerns about “executing the budget” (spending all budgeted funds)? If they regularly can’t or don’t spend a significant portion of the budget (double-digit variances are often a red flag!), that may point to sloppy assumptions about the coming year during budget development. Don’t worry about relatively small positive variances (a guideline is single-digit percentages, especially low single-digit percentages), which may arise because there’s intentional padding. But large positive variances, say, double-digit percentages, can exceed reasonable margins and actually cause other departments not to get funding they need.
- Do negative variances in particular spending categories or the total budget raise concerns about exceeding the budget? Overspending is obviously a big deal. Try that at home, and find your credit ruined! Accordingly, the guidelines are even tighter: low single-digit percentages (under -5%) may be okay, but nothing larger. Negative variances shouldn’t be chronic, repeating year after year. For example, unexpected increases in price or volume, such as salt supplies during an especially snowy winter, are an actual surprise! So are overtime wages for drivers to operate the machinery. If such “surprises” occur year after year, it’s more likely to reflect a breakdown in the processes for producing projections.
- How efficiently can you communicate to readers the picture of what’s happening in your department? If there’s a general tendency toward large positive variances, say, that makes it possible to more quickly communicate the results for spending categories that follow that general tendency: it’s just a question of how much for each category. To help accomplish this efficient communication, pay particular attention to columns F and G. You’ll find averages for 2016-18 variances in F29 through F37. And the averages of 2017-19 variances are in G29 through You almost never need to talk about both averages. And you certainly don’t want to throw 4 years of variances per category (plus the total) at your readers. Chances are they won’t retain any single figure if you flood them with dozens of figures. ONE CAUTION: Sometimes the averages don’t mean what they appear to mean. For example, if there’s a negative percentage and a roughly equal positive percentage for two of the values and the third one is close to zero, then the average of those 3 values also will be close to zero (the larger negative and positive values cancel each other out and the value close to zero doesn’t move the average much one way or the other). But a near-zero average percentage doesn’t accurately describe what’s going on. A very large percentage can also skew the average, by overwhelming more moderate variances in the other years, leaving the average variance mathematically accurate, but misleading nevertheless. In those types of cases, you should highlight one or two of the individual years’ values, particularly focusing on the most recent year.
Now write a memorandum as in previous 3 assignments, paying attention to the questions above. Once again, you’ll need to provide a brief context and explanation of what the analysis is doing. Distinct from the other assignments, the remainder of the memo has to do just one thing: address the variances for the spending categories and the total budget, bearing in mind the guidance from (a), (b), and (c) above.