Currie Journal of Knowledge
Variance Analysis with Quantitative Demonstration
How to cite: Bell, T (2020). Variance Analysis with Quantitative Demonstration. Cascade Journal of Knowledge, volume 1 (1), 14:19. https://doi.org/10.46290/cjok000001
Abstract: This Knowledge Module provides an overview of Variance Analysis and how it relates to the overall budgeting process. Users gain an appreciation of the usefulness of variance analysis from an accounting perspective. A quantitative demonstration of how to compute and analyze direct labour rate and efficiency variances is demonstrated.
Keywords: Variance Analysis; Direct Labour Rate; Efficiency Variances; Accounting

Learning outcomes:

Transcribed copy of screencast

This video is all about variance analysis. By the end of the video, you’ll learn what variance analysis is, how it relates to a company’s overall budgeting process, why variance analysis is so widely used and so useful, and finally, we’ll go through an example of how to compute and analyze Direct Labour Rate and Efficiency variances. Let’s begin by explaining what variances are. Simply put, a variance is the difference between what a company planned and what actually happened. And when we talk about variances, we’re talking about numbers and we’re generally talking about money. So here’s a simple example: A company budgets, its direct labour and as you would have gone over in a budgeting chapter, budgeting is super useful! Just planning to know what you’re going to spend in various areas of your company or what you’re going to have coming in, in terms of revenue, is useful. For example, a direct labour budget of $100,000 will tell us our staffing needs, right? Whether we need to hire people or whether we need to make staffing changes. It’ll also tell us a bit about our cash flow. Because again, if we’re having staffing costs, you’re generally paying for those costs with cash, it’ll tell you about your company’s cash flows as well. So it’s useful on its own as a planning document, right? We’re planning for 2020, and we’re planning to spend $100,000 on labour. It’s just as useful, maybe even more useful as a backwards looking document. And that’s what variance analysis is all about.

It looks back and says, “Okay, well, I was planning on spending $100,000. Did I actually spend $100,000 on direct labour?” And the answer here is no. Our company when 2020 is all said and done, they look back and they say, “Oh, we actually spent $120,000 on directly labour.” You can see there is a difference between our actual in our budget, and that difference is the variance. The variance here is $20,000.

Now we need to say, “Is that difference favourable or unfavourable?” Here’s how we explain favourable versus unfavourable. If a variance will produce more profit than expected, it’s considered favourable. If a variance produces less profit than expected, it’s considered unfavourable. In this case, our costs were higher than we had planned, there were $20,000 more than what we had planned. Well, if my costs, all else being equal, my costs are $20,000 higher than I thought they would be. I’m less profitable, right? Higher costs means lower profit. So in this case, this would be an unfavourable variance.

Now it’s very often we’ll have several variances and some will be favourable and others will be unfavourable. But in this case, looking at this variance on its own, it is an unfavourable variance having higher than expected costs means lower than expected profits by $20,000.

Now, that in and of itself is useful just to look back and say, “Oh, I spent more $20,000, more than what I had planned”. What variance analysis allows us to do is dive a little bit deeper and try to figure out why. Did we spend $20,000? More simply because we were busier and we had to bring more people in? Or did we spend $20,000 more because our employees got a raise in an above what we expected? Or did we spend $20,000 more because our employees were unproductive and we had to pay them for more hours. Why did this happen? Well, that’s what variance analysis seeks to find out.

So variance analysis is all about looking at your variances and trying to discover how and why happened. Most often managers are interested in finding out why they had unfavourable variances, but sometimes favourable variances are worth investigating. Also, it’s important to know though that not every variance needs to be analyzed, variance is small or the item is meeting expectation or can be easily explained. Managers typically won’t spend a lot of time performing variance analysis on that kind of an item.

Variance analysis is reserved for larger or more material items, that a manager has a more difficult time explaining what happened. Variance analysis is also just a wonderful use of budgeting data. Budgeting data, generally forward looking variance analysis allows us to use that data looking backwards to see how and why we missed on certain budget items.

Okay, let’s jump into a variance analysis example.

The question says: “Fred’s Noodles supplies local Japanese restaurants with fresh ramen noodles. The company has 20 noodle making employees who are each expected to produce one kilogram of ramen noodles per hour. The company’s average wage rate is $14 per hour.” Okay, reading through this first paragraph, this is the company’s standards laid bare. And you can think of standards as the expected cost of producing a unit right the expectations around the per unit level. Companies determine their standards either based on past history, or just their expectations, right you can reasonably estimate how long something takes to make or how expensive something is going to be. Well, that’s how standards get established. If company has a track record, though, using that track record is a good way for a company to establish its standards.

The question goes on and says, “Last week, the company record show that employees worked a total of 880 hours produced a total of 1000 kilograms of noodles and were paid on average $15.50 per hour.” This paragraph looks like it’s examining the actual the stuff that actually happened in a given week. The question goes on to say, “Compute the Direct Labour Rate and Efficiency variances. Please note if the variance is favourable or unfavourable.”

This is the way I compute variances in my class. And I do highly recommend using a graphic kind of table like this – a chart like this just really puts the variances on display. There are other ways to do it. You can compute these using formulas, but I think this is the simplest way to remember how to do it. So let’s jump into it.

The leftmost prong of my chart h times a our actual hours time, the actual rate. I’m going to look for my actions. How much did I pay my employees in actuality For that week’s work, well, they worked at 180 hours at an average wage rate of $15.50 an hour. 880 hours is my AH my AR $15.50 per hour. That’s in dollars, of course, 880 times 15.5 is $13,640. That’s the amount actually paid to employees.

Let’s move over to the middle prong. AH times SR the AH just carries over. It was a 880, it remains 880 hours. The standard rate, well that’s going to come from my standards I expect to pay employees $14 per hour.

So AH 880 hours times $14 per hour. 880 times 14 is $12,320. Now I have the makings of a variance here I have two prongs, they have different amounts. Let’s figure out the difference. This is a variance. So the difference here 13,640 minus 12,320 is a difference of 1,320. This is a variance. How do I know which variance it is? I look at what’s different between my options, my AH and AH are the same. So this isn’t a difference in hours. It’s a difference in rates, my actual rate 15.50 and my standard rate, that’s what’s different in the formulas.

So, I actually paid employees $15.50 an hour for work that I would normally pay or expect to pay $14 an hour. I paid more than expected. I paid more than my standard. This means my cost is higher than the standard. If I would have paid them $14 an hour, my cost would have been lower. Because the cost is higher. This is an unfavourable variance. This is called the Direct Labour Rate Variance. That shouldn’t be surprising. The rate is what’s different here. So this is the DL Rate Variance.

Moving over to the other side, Standard Hours times Standard Rate is our final calculation over here. The standard rate remains $14 per hour. My standard hours tends to be the trickiest one. It’s most often not given in the question, you kind of got to do a bit of digging here. Here’s the question I always ask my students to answer for standard hours:

“Given the actual level of output – that is, given the actual number of units I made – in this case, the number of kilograms of ramen noodles. How many hours should it have taken?”

So, how many kilograms of ramen noodles did I make? The actual level of output – 1000 kilograms. What would I expect that to take before the month?

If you told me I was gonna make 1000 kilograms of noodles? How many hours would I have guessed my direct labour workforce would have worked?
Well, employees are each expected to produce one kilogram of ramen noodles per hour. So if they make 1000 kilograms, I would have thought that would have taken 1000 hours right? One kilogram per hour 1000 kilograms of noodles. One thousand times one gives us standard hours of 1000 hours.

That again answers the question: “Given the actual level of output, how many hours should it have taken?” It should have taken 1000 direct labour hours.

1,000 hours times $14 an hour is $14,000. The difference between these two items 14,000 minus 12,320 is 1680. This is the efficiency variance because it measures how many hours something took, right? Did it take less time? And were we more efficient than we would expect? Or were we less efficient? And the answer here is we were more efficient. We would have expected this task to take 1000 hours, it only took 880. These employees were much more efficient than expected. This is a 1680. favourable direct labour efficiency variance.

Now our overall direct labour variance is the total of the two. It can also be gotten by taking the difference between 13,640 and 14,000. Our total direct labour variance, our DL variance is 1680 favourable minus 1320 unfavourable, it’s 360 favourable.

Okay, so we’ve gotten the direct labour variance – 360 favourable, that breaks down into 1320 unfavourable for rate. We paid more than we would expect 1680 favourable for efficiency, our employees worked way more efficiently than we would have expected. What does it all mean?

Well, part B of the question asks: “Normally, Fred’s noodles uses the staff of 10, Senior noodle makers and 10 Junior noodle makers. Last week, the company experimented by using 15, Senior noodle makers and only five Junior noodle makers. Was this a success?”

I think our answer is yes. And it certainly explains the variances, right. We use more senior people, we paid them more. So that explains the unfavourable rate variance. More senior people tend to be paid more. However, more senior people tend to be more efficient. Was the trade off worth it? Right? Paying the people more? Was it worth the efficiency gain? The answer here, I think is explained in the direct labour variance of 360 favourable. And the answer here is, yes, this was a worthwhile experiment.

Okay, let’s wrap this up. So to summarize some of the things we’ve learned, a variance is the difference between what we planned to have happen and what actually happened. And when we talk about variances in accounting, we’re talking about money and numbers, the financial difference between the budget and the actual. Variance analysis says, “Okay, let’s look at some of those key differences and try to figure out why they happen trying to explain them.” So it can inform us on how to behave in the future. It’ll help us make future decisions if we know why and how the variance has happened. The final thing we did was we learned was to compute labour variances, we learned the Labour Rate Variance, and the Labour Efficiency Variance, and that using this table is a helpful way to compute our variances.

I hope this video has been helpful to you in better understanding variances.

Tony Bell

Thompson Rivers University, Canada
tbell@tru.ca

Tony Bell is an Associate Professor Teaching of Accounting in the School of Business and Economics at Thompson Rivers University.

References:

Bell, T., & Fergus, A. (2015). Mouat’s Trading Company. Journal of Case Research and Inquiry. Volume 1, 2015.

Bell, T., & Fergus, A. Cat & Joe’s Pig Rig: Should We Stay or Should We Go? (2014) IMA Educational Case Journal. Volume 7, Issue 3, September.

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