会计信息是一个组织的命脉，因为它促进、影响着那些达成组织目标的运营性和战略性决定。会计以3种角色来帮助组织进行决策：衡量、控制、沟通。\n\n这门课将介绍会计是如何帮助经理人制定、实施、并优化组织战略。特别的，你将会学习非财务和财务信息是如何被创建和处理，如何影响经理人进行战略决策及衡量战略是否成功。这门课还将介绍会计是 to be continued..

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会计之商业决策：战略评估与控制

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会计信息是一个组织的命脉，因为它促进、影响着那些达成组织目标的运营性和战略性决定。会计以3种角色来帮助组织进行决策：衡量、控制、沟通。\n\n这门课将介绍会计是如何帮助经理人制定、实施、并优化组织战略。特别的，你将会学习非财务和财务信息是如何被创建和处理，如何影响经理人进行战略决策及衡量战略是否成功。这门课还将介绍会计是 to be continued..

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Module 1: Managing Capacity

In this module, you will explore different measures of an organization's capacity and understand their implications for many different decisions, including product pricing.

- Gary Hecht, Ph.D.Associate Professor of Accountancy

Department of Accountancy, College of Business

Welcome to the first lesson.

By the end of this lesson, you should be able to define capacity.

Identify and apply different measures of capacity and

recognize the implications of those different capacity measures for

a variety of decisions, especially those related to product costs.

Let's start off with the basic definition of capacity.

Generically, capacity refers to the volume of production that

an organization is capable of.

It's usually defined according to a given time period.

Now the length of that time period is up to the decision, the scenario or

the manager or employee making that decision.

So it could be a matter of an hour or it could be an entire day, a week,

a month, a quarter, a year.

However you'd like to define capacity, you're free to do so, but

it's important to identify that specific time period to which we're measuring.

And finally, the notion of capacity is determined by many factors.

You can think about capacity being determined by the size of the factory or

the number of machines that we have to produce our product.

You could think about capacity in the sense of how many employees we've hired at

the current moment.

The size of our labor force influences how productive we can be.

The list goes on and

on in terms of the factors that influence the size of our capacity.

So just keep that in mind, as we work through these initial concepts.

Now to think back when I was a child,

one of my favorite things that I used to do was go to see a movie.

Even if the movie were terrible, the experience was usually great.

So, let's go back to that example.

Let's imagine that we own a movie theater and

we are assuming that we're thinking about capacity in a 24-hour time period.

So say, midnight at Friday morning all the way to 11:59 PM that night.

We also thinking very simply, we have a single theater building.

It's not one of these huge multiplexes with multiple screens, just a single

room with the single screen and we have a nice round number of seats at 100 seats.

So, it's not huge.

We're also assuming that we're focused on

a two-hour movie just to keep things nice and even and simple.

So let's imagine, how many tickets can we sell in that 24-hour period?

Well, theoretically speaking, in 24 hours, we could show that 2-hour movie 12 times.

We can start one at midnight and start the next one at 2 AM, 4 AM, 6 AM, etc.

And for each showing, we have a 100 seats that people could sit in.

So theoretically,

we have 12 movies at 100 seats of piece within that 24-hour time period.

In other words, we have 1,200 tickets that we could sell.

Now notably, I keep using the word theoretically and

that's exactly what we'll call this version of capacity.

Theoretical capacity.

Theoretically, we could sell 1,200 tickets for

that same 24-hour time period and that's the maximum capacity that can be supplied.

However, thinking more practically,

can we really show the movie 12 times per the 24-hour time period?

If we were to start a movie at 12 AM,

the people who finished that movie about 2 AM would have to leave the theater and

the next showing would have to have people come in.

So we have this natural logistics that enter into

play that might preclude us from having movie starts at 12, 2, 4 and 6.

We might have to instead start the movie at 2:15 or 2:30 and so

on throughout the day.

We also have clean-up.

I don't know if you've ever seen the floor of a theater after a movie showing,

but it's not anything that you want to eat dinner off of.

So cleaning up the popcorn and the spilled drinks and so on is necessary, as well.

And of course, the machinery that's required to show the movies

needs repairs and maintenance.

So obviously, there are these logistics and

other factors that preclude us from reaching that theoretical capacity.

And so we have a revised, more realistic measure of the amount of capacity that

we could provide and we've labeled that practical capacity.

Again, that's more realistic.

It's supply-based and it takes into account normal logistics, and

other operations.

Now, theoretical and practical capacity are supplied-based measures of capacity.

That means that's how many tickets in our movie theater that we could reasonably

sell, but what about the number of tickets that are demanded?

In other words, are 100 people going to show up for that 4 AM movie?

So, we have demand-based measures of capacity and there are two types.

The first is something generically referred to as normal capacity.

This is average demand for

our organization's product using the existing capacity.

So you might think of multiple weeks of 24-hour time periods and

the average number of tickets that are demanded of our capacity

over those multiple weeks, and then we have budgeted capacity.

Budgeted capacity is period-specific demand for

an organization's product using that existing capacity.

So, you might think about a specific Friday when a brand new movie comes out

and maybe we would sell tickets to a 4 AM showing.

That might be a different story on a different time period say,

a Monday when there are no new movies coming out and

then the 4 AM showing is tough to sell tickets for.

So, these demand-based measures of capacity take into account

what our market is demanding of our existing capacity.

Now relatively speaking, we can think about the relative sizes

of each of these different measures of capacity.

By definition, theoretical capacity will always be the largest.

That's the 1,200 ticket version, 24 hours worth of movies,

2 hours each selling all 100 tickets.

The most we could possibly have is the 1,200.

That's theoretical capacity and that's the most that we could possibly supply.

Practical capacity, by definition, because it takes into account logistics,

repairs and maintenance and other factors is usually less than theoretical capacity.

By how much depends on the nature of those logistics and those repairs, and

maintenance.

Demand-based measures are less than or equal to practical capacity.

Even though the demand might be greater, we can't supply any more than what it is

that we have in terms of our practical capacity.

And then of course, normal and budgeted capacity vary in terms of their ranking.

Sometimes, a specific time period that we've budgeted for

is less than that average normal capacity that's demanded.

And sometimes, a specific time period is more than what average is.

So normal and

budgeted might reverse in terms of ranking, depending on a specific scenario.

Now, let's have a check point to make sure that we are all in the same page

regarding these concepts.