As a continuation of my
series on Throughput Accounting, I’ve asked Bruce Nelson, my co-author for Epiphanized – Integrating Theory of
Constraints, Lean and Six Sigma, to write a posting on a subject he covered
briefly in our book's Appendix 8, On-the-Line (OTL) Charting. This is a very helpful tool to track the
state of the business on a daily basis rather than waiting until the end of the
month (or quarter) to find out. I want
to thank Bruce for writing this blog for me, especially when I only asked him
to this morning.
Recently in his blog Bob Sproull has been
writing several pieces about Throughput Accounting (TA). As a supplement to those writings Bob has
asked me to contribute a write-up about On-the-Line charting and how it applies
to TA.
Most companies who use financial metrics live
and die by the quarterly report. Some
companies are more inclined to look at it monthly as a decision tool and to get
a “feel” for the financial numbers to date.
But, even when you track and monitor the financial numbers on a
quarterly or monthly basis there are times when the interval of time seems
inadequate. It’s disheartening to review
a quarterly report and realize you have been losing ground for the last two
months and didn’t know. Even the monthly
interval can be too short to give the necessary “heads up” that a potential problem
currently exists. It is much more
preferable to have reliable information available on a much shorter time
interval. However, compiling and presenting
a useable profit and loss statement on a daily basis seems unrealistic. But, what if there were a way to compile and
analyze financial numbers on a daily basis to help with the decision making –
would you be interested? Without a
doubt, I’m sure the answer is “YES!” If
you had information available that could tell you where you are TODAY based on business
activities as of YESTERDAY
then, that would be a valuable tool.
With this kind of information you could make the necessary and accurate
daily decisions about where you are and where you need to be. It’s always much nicer to know this
information as quickly as you can, versus waiting until the end of the month,
or worse the end of the quarter, before realizing a problem is present.
In order to view this information on a daily,
enter the on-the-line chart (OTL). The
OTL is a simple concept that is based on the rules of TA to allow the user
access to the lasted information available.
Setting up an OTL is very easy.
First, you need to have an estimate for the Operating Expense (OE) on a
monthly basis. In other words, how much
does it cost you to keep your business running every month? The beauty of the OTL is that it does not
need to be accurate down to the dollar or the penny. It is understood that there can be
fluctuation in the monthly dollar amounts.
The OTL is strictly a compass to keep you heading in the right direction
and notify you of potential issues when they happen.
There are a couple of ways to get these
numbers. You could take yearly expenses
and divide by 12 to get an estimate of monthly cost, or you could take monthly
OE and divide by the number of days in the month to get a daily cost. What we want to end up with is an estimate
for the daily OE being accumulated. Once
you have that number we can plot it on a graph using Excel. Suppose, for an example we had a business
that had a monthly OE of $30,000, and we want to plot this number for the month
of June. If we take the $30,000 and
divided by 30 days then, the estimate is about $1,000 per day of OE. We would plot this in Excel as a cumulative
number, i.e., Day 1 equals $1,000. Day 2
equals $2,000. Day 3 equals $3,000, and so on.
Figure 1 gives an example of what this chart might look like.
Figure
1 – The daily plot of Operating Expense for one month.
With the information plot this graph shows
the daily cumulative totals for the entire month. It is possible that the OE numbers could
change in any month. Some employees
quit, and new employees are added. If
the variance is high then, adjust the numbers accordingly. However, what we are really trying to
establish here is the view of the OE from the ten-thousand foot level and not
necessarily the day-to-day changes.
Think BIG picture and not finite detail.
With the OE line established, we now want to
the collect the throughput data.
REMEMBER: this only works if we
are collecting and reporting throughput in accordance with TA rules. As such throughput is calculated as product
selling price – total variable costs (T=SP – TVC) while Net Profit equals
Throughput minus Operating Expense (NP = T – OE). As you probably already know but, let’s
refresh anyway, TVC is any cost associated with the product. This will include raw material, sales
commission and shipping charges. Remember
labor charges ARE NOT added into this number.
Labor costs are part of the operating expense. Suppose for our example the product we make
has a selling price of $90.00 and a TVC of $25.00. That means for each product sold we have a
throughput value of $65.00 ($90.00 (SP) – $25.00 (TVC) = $65.00 (T)). With this
information we now know that in order to break even on the OE we must make 15
or more product per day. With 16, or
more, product per day we start to make a profit. It is interesting to note that the CA rules
will tell you that you are making a profit with each product sold. TA counters with the realization that profit
does not and cannot begin until the 16th product is made. It is a vastly different financial concept to
think of products, product pricing and product margins using TA.
If you track the daily throughput from the
system and, calculate throughput correctly, you should have a pretty good idea
where your company stands right now.
Figure 2 shows the impact of throughput to OE after 17 days of tracking.
Figure 2 – This figure shows Throughput
track to the OE line.
Using throughput accounting and looking at
this chart on a daily basis can give a General Manager or department manager
accurate and useful information. The
analysis is simple. If throughput is
tracking below the OE line
then, you aren’t making enough money to cover the OE expense. The management team can determine the issues
causing the lower than necessary throughput and initiate corrective actions to
bring the throughput line up. If the
throughput line is tracking above
the OE line then you are making a profit and possibly no actions are required.
The OTL is a great tool to track and monitor
the OE and T on a daily basis. It gives
you a good “Kentucky wind age” analysis to determine where you company is today
– right now. No need to wait for the
month end, or quarterly reports to figure out what happened – good or bad. Using the OTL you can have a pretty good
estimate of how the company is doing, and make corrections, as necessary, to
get back on track for revenue and on-time-delivery.
I
hope this has been a helpful explanation of the On-the-Line chart and how it
can be used for a daily assessment of where your company is.
Bruce
H. Nelson
Thanks again Bruce for your excellent posting.
Bob Sproull
7 comments:
this article is just what I was looking for to bring the OE and TH concepts together to sell the TH concept to management
the last comment was from Alex Fedotowsky about bringing the OE and TH together....etc.
Loosely to this article: Don Wheeler writes about numerical naivete and how decisions are based on falsely monthly reports. Changes are shown in percents and no-one knows monthly variation. Is this just normal noise or is there a signal telling true change in system? If you ground your decisions on noise you are totally wasting time.
To Vellu: I received the following comment from Bruce Nelson in response to your posted comment on 8/21/2012.
"I agree that data that is not accurate leads to useless decisions and wastes time. However, I think we stressed the need for accurate data input! Any system(s) that collects data to be used in reporting MUST maintain accuracy, or at least high ethics to input data correctly. The old adage is true - "Garbage in - Garbage out!" This is not to say that data must be pristine to be useful, but rather close enough to make solid and accurate decisions. Data collection is usually dynamic and not static to any system. Most companies that use data pick a point in time and measure on that day or that time, or whatever the rule is. Not unlike banks and other institutions who track checking account and other things. After they run a statement the data can and does change with additional checks written, or deposits made - it is dynamic in nature, but they pick a point in time and take a snap-shot at that point. It can go up or down from that point based on the action taken (withdrawal or deposit)."
Hi,
Maybe I wrote little badly, sorry I'm from Finland and english is not my native.
My point was that collected data can be absolutely accurate but there's always natural variation in any system. And you must know that. If you make decisions based on last month without knowing the variation you could just waste your time. So if next month looks different was it just variation or action taken?
Put the data in process behavioral chart (like XmR) and then base you decisions on that what the chart tells you about the system.
Vellu,
Here is Bruce's response to your comments. "Any system will exhibit variation and that should be seen with the collected data. I believe what we were talking about was the distribution and resupply model ?? The variation is based on usage and can certainly vary by the day, week, or month. The distribution is a system to react daily to changes. X-MR (to me) is more to predict stability (X) and predicatability (MR). If 10 are used then, put 10 back in the system. I don't see this as a predicitve tool but, rather a replenish tool. We aren't trying to make decisions about future buys but, rather if we replaced what was used. From an X-MR stand point I'm not sure it would apply?? The X (stability) comes from the replenish. The MR (Pedictability) come from the distribution (usage). I think X-MR would add complexity, while Distribution and Replenish creates simplicity."
Bob
I was writing more general about metrics, how managers are numerical naive and "go panic" based on one bad month. Not directly to this article. Sorry if I was confusing...
The OTL tool is great, simple and works well as "eye-opener".
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