1. what direction is this ship headed? Forecasting for the Love Boat
Lots going on here. Spend a lot of time of the sales forecast, some time on the IS forecast and hurry through the BS forecasts. This is probably what happens for most analysts as well! We aren’t going to figure out all the nuances of forecasting every line item today. But from here on out, forecasting is a main part of every case. READ the Book! chapter 8, in particular.
Jackson 5 - The love you save

2. Sales Forecast: economy to industry to firm
past future
macroeconomic series
industry sales
firm sales
predictable series based on past data
unpredictable series based on past data
estimate relation
estimate relation taking competitive analysis into account
forecast firm sales
forecast industry sales
Figure 8.1 Estimating Industry and Firm Sales from Macroeconomic Data
Two types of sales forecasting approaches (that I know of). One starts at the economy and works down to the firm. the other starts at the firm and then adds in insights from the economy.
Economy-down approach:
need the macro series to be predictable and the links to the industry and to the firm to be strong. So works well for, grocery store sales, clothing sales, maybe energy, -- stuff that the aggregate total is relatively easy to predict. Nail the size of the industry and then worry about how competition will divide up the pie.
But for recreation spending, the whole size of pie is tough to predict.

3. Sales Forecast: the sales-generating units
sales come from asset investments (generally)
asset base can grow (e.g. open new retail outlets)
sales from existing assets can grow (e.g. comparable store sales growth)
sales growth =(1+asset growth)(1+comp growth)
assumes all units, new and old, enjoy comp growth
assumes all units, new and old, have same sales rate
Firm-level approach.
For a fancier model that this, see Lundholm/McVay paper on forecasting retail sales.
for a really fancy retail sales forecasting model, see Lundholm/McVay at

4. Sales assumption determines growth
Salest-1 x (1+sales growtht) = Salest growth
Salest x (Assetst/Salest)= Assetst turnover
Assetst x (Liabilitiest/Assetst) = Liabilitiest leverage
Assetst – Liabilitiest = CEt
Salest x NIt/Salest = NIt, margin
CEt-1+ NIt - DIVt = CEt
Armed with the sales forecast, what happens next? Note how sales drives growth in everything else, unless you make huge changes in turnover or leverage or margins. Also, note that net dividends are determined – you don’t get to forecast this. (You may note there is a line for this in eVal, but that’s just the common dividend – if you raise it a dollar eVal will raise the implied stock issuance by a dollar as well.)
What are some alternatives? IF we want to forecast DIV, then leave something else unforecasted to be the plug. Could NOT forecast cash or debt, and use them as plugs. We plug to DIV because common equityholders are the residual claimants – it makes most sense. But real issue is that you have to check out the implications of the plug and see if you agree; if not, then change your forecasts.
… and DIVt is determined!

5. RCL: Sunny Skies and Clear Sailing?
Sales forecast: 1) how do you want to go about it – what did you get? (list their answers on board in % terms)
Ans should be a mix of industry and firm-specific data. I will start with the “economy down” approach to illustrate it a bit, then punt and switch to the sales-generating unit approach.

6. Industry Capacity Growth
Big issue in case is that the demand for cruise vacations is growing up so is the available supply. Classic economics at work.
Is there are relation between passenger growth and berths growth? Roughly. But worried about forecasted next three years.
beware the growth in capacity exceeding the growth in passengers. The ships are definitely going to be built, so what will happen to prices if
Or, assuming 5000 berths retired each year, industry growth in berths is 8.2%, 6.1% and 7.1% over next three years,. Can demand increase at least this much?

7. demand for cruising: who cruises?
Who cruises? Older, wealthier, better educated, as compared to the population. Are these folks more or less sensitive to the economy? Are they even price-conscious? (if wealthy enough, then not sensitive).

8. demand for cruising: demographics
1999
2000
2001
How is our target set of cruise customers changing over the next three years? From US census bureau. Could build a more refined forecast model of the pool of profile cruisers.
entire US population growth is about .91% for these years.

9. demand for cruising: more vacations?
Does this mean that US pop. Will start vacationing more? OR does it reveal us as losers? The baby-boomer generation has traditionally spent more on recreation than prior generations, so this looks good.

10. building an industry growth model
Start with GDP, since get nice forecasts of this from CBO or Conference Board. PCE maps closely with GDP because it is 2/3 of total (the rest being gov’t, private domestic investment, net export). Note that rec spending growth always dominates. Does it follow economy as well?

11. estimating industry growth
% Rec growth = %GDP growth
Yes, rec spending growth maps well with GDP growth.
We could estimate the relation and then use the CBO forecasted GDP to forecast rec spending.
R-squared is about 61%. 3.0, 2.1, 1.9 are the forecasted % real GDP growth, so fitted values are 6.65, 5.62, 5.40.
Then compute relation between rec spending and cruise spending (which we have the data for), then figure out RCL’s market share. But, as we said at beginning, the size of the pie is hard to predict here, I think, so this approach is unlikely to work.

12. the trouble is… no relation!
Trouble with this approach is that, cruise industry doesn’t seem to track rec spending! So hard to predict size of the cruise$ pie, so pointless to try to figure RCL’s share of it. This kind of thing always happens – it is where analyst reports start to wave their hands. (no statistical relation between growth in passengers and rec spending, or anything else!).
use the insight you gain about the industry to qualitatively guide your forecasts when doing the “sales-generating units” approach.
Question is, can the industry demand rise to meet the capacity increase of 8%,6%, 7% (or more if 5000 berth retirements don’t happen) and do so without creating competition between players?
no relation!

13. Building a Sales-Unit Model
assume that % sales growth =
(1+growth in berths)(1+growth in rev/berth) – 1
Revenue model – who sends them money for what? the sales-generating unit is the ship, or more generically, the berth. The rate is the occupancy times the price/day times 365.
NOTE that occupancy percentage takes into account % of 365 days that have a paying customer, so don’t need trip length – can use berths * 365 * occupancy.
weighted average # berths based on what quarter they come online (as reported in 10-K). It is only ¼ of 3100 for 1999 because the new ship doesn’t come into service till November In 2000 ½ of 3100 plus ¾ of 2000 arrive in 2000 (plus now have all of the 1999 vessel), and ½ of 2000 in 2001.
berth forecasts from RCL

14. growth in berths
In 1999 ¼ of 3100 new berths arrive. In 2000 get other ¾ of 3100 plus ½ of a new 3100 plus ¾ of a new 2000.

15. Occupancy – How full is the boat?
RCL for 1998 computation is 11,607,906/10,877,000 = Not exactly what they report because of timing of selling one ship and buying another.
Are CCL’s boats fuller? Probably, but this stat is based on double occupancy, even when cabin sleeps 4. So if CCL has more cabins that sleep 4 then they could look better for this reason alone. The trend might be more useful, although they CCL acquired Cunard in 1998, and they may have a different mix. They say in MDA that occupancy on existing lines dropped .6%.
Can RCL’s boats get fuller? Doesn’t seem like a lot of room to grow, but I give them a bit of movement toward CCL, reasoning that the newer boats have more 4-person staterooms (and that they ALWAYS leave the port full).
Forecast Occupancy for RCL

16. Margins and Pricing Forecast for RCL 1999 2000 2001 236 242 248
RCL MDA for 1998 – “36% increase in revenue due to 31.2% increase in capacity and a 3.6% increase in Yield (rev/berth, so a combination of price increase and occupancy increase). Price per passenger day increase is 2.7%.
CCL MDA for 1998 – 23.9% increase in cruise revenue… say that, at existing lines, price increase was 7%, so purchased vessels must have higher prices than existing ones (as they do). Overall Price per passenger day increase is 12.1%.
IT seems like RCL has room to increase prices. They offer a quality mix that seems at least as good as CCL and have higher operating costs. And they have had Celebrity for a year now, so can start to increase prices. In the good news forecast I give them all of CCL’s price plus inflation. HOWEVER, I fear the increase in capacity at the industry level! So my bad news forecast moves the prices down to near Carnival’s lower prices.
Forecast for RCL
bad news forecast
good news forecast
CCL price of CPI of 2.3%
increase by CPI of 2.5%
increase of CPI of 2.4%

17. sales % growth forecast
my sales forecast
sales % growth forecast
bad news forecasts
good news forecasts

18. Forecasting Costs: economies of scale?
slope of less than one implies economies of scale.
estimated slope of line:
%DSGA = .90(%DSales).
implies that SGA/Sales ratio changes by the factor (1+.9g)/(1+g), where g is the %DSales.
Note that this is a little hard to do just looking at theses ratios because the sale growth isn’t the same size each period. Estimate the economies of scale with a regression of %dSGA on %dSales. A coef of 1 implies no economies of scale. Here, get .9 (using only last 5 yrs from eVal). Just eye-balling the CGS data shows do relation. The estimate implies that the next year’s sga/sales ratio will be this year’s ratio times (1+.90g)/(1+g), where g is the sales growth rate.
If can change prices without changing costs, then a direct effect on the CGS margin. Suppose price increases 3%. Then new CGS/Sales = Old CGS/Sales/(1.03).

19. My Income Statement Forecast Assumptions
bad news forecast
price decreases of 3%, 2%, 2%, so CGS99 = .605/(1-.03) = 62.37% etc.
SGA% declines in 2000 and 2001 due to economies of scale, computed as 2000 ratio times (1+.9*(.158))/(1.158).
X’ord item for $47.7M for 9/11/2001 as given in case, = 1.2% of sales.

20. My Balance Sheet Forecasts
the .037 amort rate on intangibles is set to match the depreciation rate. but difference is that not replacing this asset, while replacing the PPE.
Case then asks, if/how RCL can raise the cash implied by this. using the eVal model already open, show the pro forma SCF. Remember that this is closing the loop.
kept operating cash high because left interest revenue on income statement. Other current liabilities are the Customer Deposits – set at 23.7% as the average of past 5 years. Set Ending PPE so as to hit the capX amounts of 996M, 1196M and 1368M given in MD&A, as shown in SCF. Amortized Intangibles balance down by (1-.037). Held Preferred Stock a constant at $ (use Goal Seek in Excel).

21. So What Happened?
ships (berths) occurred almost exactly as forecast; occupancy and prices fell.
forecast
I backed into prices to hit the actual rev. If do their rev/passenger days, get higher #s, but this is true throughout the data for both companies in every year – if plug in their actual data get higher rev est than they report. I think the 365 is wrong. That is, I think that occupancy is computed against some lower standard than 365 days, but I don’t know what it is. And I know for MDA that prices did drop, so not too sloppy.
actual

22. But profitability held up
While sales fell, profitability remained okay. The NOI margin is much better because their CGS/Sales was 58.8, 57.7 and 61.5 (way below my range). SGA was actually higher, at about 14.5 each year. Also, the PPE/Sales was higher than my forecast (230.1, and 273.6), but not by much except for year 2001 when they took the option on a whole new ship.
implied price of my eval forecasts is about $28, which is close to the price they were trading at the end of Price then rose to $50, then fell to 20 in 1999 (with sales decline) and 10 after 9/11/ back up to about $40 now.
But profitability held up

23. “The reason for the discounting: A glut of luxury ships were ordered during the booming ’90s.”

24. Beginning balance $ 402,926 + Cash collected + $?????
Estimating the amount of cash collected from customers in 1999, assuming ending balance of customer deposits was $515,308 (and sales forecast is 2,710,151):
Beginning balance $ 402,926
+ Cash collected $?????
- Sales $2,710,151
= Ending balance $515,308
 Cash collected=2,822,533
T-account is opposite the normal AR. Here
deposits bb
sales pay for ticket eb

25. Estimating the ending balance of PP&E for 1999, assuming capX=$810,261 (and depr rate is 3.7%):
Beginning balance of PP&E $5,073,008
+ capX $810,261
- Depreciation
(3.7%x5,073, %x 810,261/2) - $202,691
= Ending balance $5,680,578