In this course, you will explore how to use accounting to allocate resources and incentivize manager and employee behaviors in using these resources. You will also learn how financial and non-financial accounting information facilitates strategic performance measurement and how to integrate this information to continuously improve strategy. Upon successful completion of this course, you will be able to: • Understand the role of managerial accounting information in common business decisions • Differentiate relevant and irrelevant information • Avoid common pitfalls in business decisions • Prepare a master budget and its key components • Describe the iterative and interrelated nature of budgeting • Evaluate capital investments via a variety of measures • Understand how upper management uses variance analysis • Calculate, interpret, and investigate variances • Understand decentralization and its advantages and disadvantages • Compute and interpret financial performance measures • Communicate the role of non-financial measures and strategic performance measurement systems • Identify issues associated with performance measurement and incentives • Understand the nature and role of subjective performance evaluation This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu.
An Example Scenario
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From the course by University of Illinois at Urbana-Champaign
Managerial Accounting: Tools for Facilitating and Guiding Business Decisions
304 ratings
University of Illinois at Urbana-Champaign
304 ratings
Course 2 of 7 in the Specialization Value Chain Management
From the lesson
Standard Costing and Variance Analysis
After establishing goals, setting targets, and the budget, upper management uses variance analysis to compare, assess, and investigate differences between actual and expected performance. In this module, you will learn how upper management uses variance analysis to motivate and monitor managers and employees, how to perform variance analysis on any aspect of the organization, and ultimately understand the power of this important tool for planning and control.
Meet the Instructors
Gary Hecht, Ph.D.Associate Professor of Accountancy
Department of Accountancy, College of Business
[ Music ]
>> So now let's exercise this generic framework
for revenue variances
and calculate a few using our cookie based example.
For our company in this situation, we are provided
with budgeted and actual information all related
to revenue type components,
so first off we received budgeted information.
We know from this information that we manufacture
and sell three different types of cookies, chocolate chip,
oatmeal raisin, and macadamia nut.
We have selling prices that we plan to charge
for each cookie that we sell.
For chocolate chip the selling price is 4 50.
For oatmeal raisin it's $5 and for macadamia nut it's 6 50.
And then we have projected, or budgeted,
or expected sales volumes of cookies over this time period.
We expect to sell 45,000 units of chocolate chip cookies,
25,000 units of oatmeal raisin, and 15,000 of macadamia nut.
Now, one thing that we can see, that's not actually listed here,
is that we expected to sell in total 85,000 cookies, in total.
That's the 45,000, 25,000, and 15,000 combined.
Now we also, at the end of the period,
acquire actual revenue information.
For the same three cookie lines,
we learn that our actual selling price
for chocolate chip was what we planned it to be $4.50,
for whatever reason we charge a slightly higher price on average
for our oatmeal raisin cookies than we had planned, at 5 20.
And we also raised the price compared to what we had budgeted
on the macadamia nut cookies,
and charges $7 per unit for those.
Our sales volumes were different than expected.
We sold 57,600 units of chocolate chip cookies,
18,000 of oatmeal raisin, and 21,600 of macadamia nut.
You can see for the different cookies that we sold,
may be more or less, than what we had planned.
But the total that we ended
up actually selling comes out to be 97,200.
That's 57,600 plus the 18,000 plus the 21 6.
So now let's calculate the revenue variances for one
of these cookies, and let's focus on the chocolate chip.
So, in using the budgeted information,
and using our generic framework
for calculating revenue variances, we can start
over at the completely budgeted column.
All information is as planned.
Per the information on the previous slide,
the selling price that was budgeted
for chocolate chip cookies was $4.50 per chocolate chip cookie.
The proportion of our overall sales that we expected to sell
for chocolate chip cookies was 45,000
out of the 85,000 total cookies that we expected to sell.
And then of course, the total quantity of cookies
that we would sell was our 85,000.
When we multiply these three components,
we get what we expected to earn in terms of revenue
from just the chocolate chip cookie line,
and that comes out to be $202,500.
Now, turning one dial at a time and trying to parse
out the different components, or sources of difference
between budgeted revenues and actual revenues,
allows us to move from right to left to the third column.
Generically we refer to that as flex.
We leave our budgeted price to be the same,
$4.50 per chocolate chip cookie.
We'll assume that we had the same mix,
45,000 out of the total 85,000 that we had planned to sell.
But we'll change the total quantity
from our budgeted number to the actual number.
And as I suggested on the previous slide,
that total number of cookies
that we sold during this accounting period
in actual terms was 97,200 cookies,
that's all three lines combined.
So, given the total number of cookies that we actually sold
across all three lines, but assuming that we were in line
with the budgeted mix and charged the budgeted price,
would yield a total of 231,565,
with a little bit of rounding in there.
Again this is how much revenue we would have expected
to collect, had we sold the budgeted mix,
at the budgeted price,
of the actual total quantity of cookies sold.
Moving on to the next variance,
we can change the next level or next component.
We'll leave the price the same at 4 50,
we'll leave the total quantity at its actual terms
of 97,200 total cookies, but now let's take
into account the actual mix.
The actual proportion of our total quantity that were
of the chocolate chip variety, and that was the total number
of chocolate chip cookies sold.
That's 57,600 out of the 97,200 total cookies sold.
Multiplying the 4 50 times the actual mix,
times the total quantity actually sold, yields 259,200.
And finally let's look at the column where all
of the components are in their actual versions.
So, the actual quanti-- actual revenues that we have earned.
We are changing the budgeted price into the actual price.
But if you recall from the given information we didn't change the
actual price from budgeted.
We actually charged the same as what we expected, so,
that number is 4 50, but it's reflected
of what we actually charged, not what we budgeted.
The actual mix is 57,600 over the 97,200,
that's the proportion of our total cookies sold that was
of the chocolate chip variety in actual terms,
and the actual total quantity 97,200.
Multiplying those three components together yields the
actually revenue earned
from chocolate chip cookies during this accounting period,
and that is 259,200.
So now, we can calculate the individual variances
on the revenue side of this business.
The difference between the first
and the second column is the selling price variance,
it actually is $0.
The reason again, we didn't have a fluctuation
in the selling price for chocolate chip cookies,
so therefore there is no variance on that level.
The difference between the second the third column,
referred to as the mix variance, comes out to be $27,635.
And the difference between the third and the forth column,
which has to do with the fluctuation
from budgeted towards actual total cookies sold,
comes out to be $29,065.
Now, just like with cost variances we can classify these
individual variances as favorable or unfavorable.
Looking at the volume or activity variance
on the sales on-- for chocolate chip cookies,
you can see that the budgeted world,
the column where all the information is budgeted,
is being compared to two budgeted pieces of information,
but then also one actual piece of information.
So for purposes of classifying this variances favorable
or unfavorable, the flex column is the pseudo actual world,
and the budgeted world, budgeted column, is the budgeted world.
In this case, the revenues
in the more actual column are greater than the revenues
in the more budgeted column.
This would mean from a revenue perspective hat all else equal
net income would be higher than what was expected, so therefore,
this variance is classified as favorable.
Now, moving to the comparison between the second
and the third column, the mix variance,
we can see that what we had thought was going
to be the proportion of the chocolate chip cookies
out of the total was, was different
than what actual occurred.
So there is a bi-- there is a variance there.
The flexible column represents the pseudo budget world
because it has two pieces of budget information
and only one actual, the budgeted price has one piece
of budgeted information and two actual.
So the budgeted price column total of 259,200,
the more actual piece of information,
is greater than what we have in the comparison that's more
of the budgeted piece of information.
Again, all else equal, this would suggest that our rev--
our net income is higher than what would be expected,
so just like for the activity variance, or quantity variance,
we have a favorable variance there.
And when we have a $0 variance we call it neither unfavorable
nor favorable.
But that's actually quite a rare occurrence anyway.
Ultimately using this framework, you can calculate the same set
of variances for all of our other cookie types,
and you'll start to see interrelationships
between the different cookies.
For instance, the budgeted mix for cookie--
for chocolate chip cookies, was lower than the actual mix
of chocolate chip cookies.
This insinuated that there was a favorable variance
on that level.
We have-- we sold a greater proportion
of chocolate chip cookies than we did-- than we planned.
But for another cookie type, that insinuates
that we sold less proportion,
because we sold more chocolate chip cookies than we thought,
we probably sol-- we, we,
we did sell less other types of cookies.
So therefore there's going to be a budgeted--
there's going to be a sales mix variance for another type
of cookie that will be unfavorable it won't equate
to this dollar amount because other factors influence what
that dollar amount is, but from that you can start
to see the interrelationships
between those types of variances.
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