Coca-Cola was invented on May 8, 1886 by Dr. John Styth Pemberton who was a pharmacist. He sold his invention for $.05 per glass as a soda fountain drink in Atlanta, Georgia. Soon after, Pemberton became partners with Frank M. Robinson, and the two developed the name “Coca-Cola”. Typical advertising slogans in 1886 were “Drink Coca-Cola” and “Delicious and Refreshing”. Sales averaged nine drinks per day in Atlanta in 1886. In 1888 Pemberton died and by 1891 local businessman, Asa G. Candler purchased the company for $2,300. Candler used a variety of marketing tactics to sell his product. Promotional giveaways, coupons, and extensive advertising helped the company soar. Candler and his brother, along with Robinson, expanded the business and formed a corporation; The Coca-Cola Company. By 1894, a second manufacturing plant was built in Dallas, Texas. Then another was built in Chicago and one in Los Angeles. By 1895 Coca-Cola was being distributed everywhere in the United States. In 1919, Candler sold his company to Ernest Woodruff for $25 million.

Today, Coca-Cola owns Minute Maid, Nestle S.A., and Duncan Foods. In 1995 it was estimated that Coca-Cola products were consumed throughout the world 573 million times per day. Today, in the United States, over one billion Coca-Cola products are sold each day.

The Mission of Coca-Cola

Coca-Cola's mission statement is: "We exist to create value for our share owners on a long-term basis by building a business that enhances The Coca-Cola Company's trademarks. This is also our ultimate commitment." (www.cocacola.com)

Future Opportunities of Coca-Cola

Globalization is a key factor in gaining market share. Coca-Cola recognized the need to go global very early on in their existence. This has played a significant role in Coca-Cola's strength today and for the future. Coca-Cola became global successfully only fourteen years into its existence, in 1900, by distributing to England, Cuba, and Puerto Rico. From that point on, they continued to expand globally at a rapid pace. During World War II, Coca-Cola was being bottled on either side of the conflict, in forty-four countries. Today, Coca-Cola is distributed everywhere around the globe. This company is divided into six operating units which include: the Greater Europe Group, the Middle East and Far East Group, the Latin America Group, the Africa Group, the North America Group, and the Minute Maid Group.

In the first decade of the new century, we face the challenge of a new environment, which is driven by a fundamental shift in international economic dynamics, the growing influence of technology, and the fact that people increasingly expect more of large corporations. That challenge demands innovation. While we will always be disciplined by our purpose and our ideals, we must intensify our focus on innovation and create new ways to deliver the promise of Coca-Cola. In fact, in an era that is increasingly international and interconnected, we must pioneer a movement from a homogenous global approach to a highly tailored approach reflecting the unique character of our markets. (www.cocacola.com)

It is interesting to recognize the fact that companies in the soft drink industry do not expect their target market to expand since distribution has reached all locations on the globe. Instead, they focus their efforts on getting consumers to choose their product more times a day. This amounts to fierce competition among the players in this industry.

THE SALES DATA OF COCA-COLA

03/00

06/00

09/00

12/00

03/01

06/01

09/01

12/01

(millions)

$4,256

$5,487

$5,413

$4,733

$4,479
$5,293

$5,397
$4,923

SALES FORECAST

Revenue for Coca-Cola Company during the past 8 quarters is depicted below:

Periods

Mar-00

Jun-00

Sep-00

Dec-00

Mar-01

Jun-01

Sep-01

Dec-01

Revenues

($Million)

$4,256

$5,487

$5,413

$4,733

$4,479

$5,293

$5,397

$4,923

Linear Time Trend Line

Through Excel, the linear time trend line is estimated as: Ŷ_t= 4804.5 + 42.917T

Where Ŷ_t = the estimated net operating revenues measured in millions dollars

T = time (in quarters)

The forecasted net operating revenue for the first quarter of 2002 will be:

Ŷ₉ = 4804.5 + 42.917 * 9 = 5190.753

That is, $5,190.753 million.

The forecasted net operating revenue for the second quarter of 2002 will be:

Ŷ₁₀ = 4804.5 + 42.917 * 10 = 5233.67

That is, $5,233.67 million.

Forecast Revenues for the first two months of the following period

The linear time trend line per quarter is estimated as: Ŷ_t= 4804.5 + 42.917T

The monthly equation for net operating revenue becomes: M = 1601.5 + 14.306t

Where M = the forecasted monthly net operating revenue (in millions dollars)

t = is a time code for month.

The forecasted net operating revenue for January and February of 2002 are as follows:

January, 2002: M₁ = 1601.5 + 14.306 * (1+3 * 8 + 1)

= 1973.456, that is $1,973.456 million.

February 2002: M₂ = 1601.5 + 14.306 * (1+3 * 8 + 2)

= 1987.762, that is $1,987.762 million.

Single Moving Average (let n=2)

	(in millions)		The forecasted net operating revenue for the first quarter of 2002 will be: F₉ = (5397 + 4923)/2 = 5160 That is, $5,160 million. The forecasted net operating revenue for the second quarter of 2002 will be: F₁₀ = (4923 + 5160)/2 = 5042 That is, $5,042 million.
Time	A_t	F_t
1	$4,256	-
2	$5,487	-
3	$5,413	$4,871.50
4	$4,733	$5,450.00
5	$4,479	$5,073.00
6	$5,293	$4,606.00
7	$5,397	$4,886.00
8	$4,923	$5,345.00

Single Exponential Smoothing (let α=0.4)

	(in millions)		The forecasted net operating revenue for the first quarter of 2002 will be: F₉ = αA₈ + (1-α) F₈= 0.44923 + 0.65132.87= 5048.922 That is, $5,048.922 million. The forecasted net operating revenue for the second quarter of 2002 will be: F₁₀=αA₉+(1-α)F₉=045048.922+0.65048.922= 5048.922 That is, $5,048.922 million.
Time	A_t	F_t
1	$4,256	-
2	$5,487	$4,256.00
3	$5,413	$4,748.40
4	$4,733	$5,014.24
5	$4,479	$4,901.74
6	$5,293	$4,732.65
7	$5,397	$4,956.79
8	$4,923	$5,132.87

MULTIPLE REGRESSION MODELS

We will use the following six regression models to make forecast for Coca-Cola’s revenue in future quarters. However, the first step is to examine the models and choose the best one for forecast.

1. Y=Bo+B1T+B2T*T

2. Y=Bo+B1X1+B2X2+B3T

3. Y=Bo+B1X1+B2T

4. lnY=Bo+B1lnX1+B2X2+B3T

5. lnY=Bo+B1lnX1+B2T

6. lnY=Bo+B1T

Summary of Regression Results

	Y	lnY	B0	T	T²	X1	X2	lnX1	R²	R²
1	X		4532.9821 (743.7424)	205.8274 (379.1911)	-18.10119 (41.12905)				0.0852	-0.2807
2	X		-27234.7372 (39699.2865)	-333.8861 (499.7012)		1.40075 (0.58305)	0.0044541 (0.0059812)		0.6265	0.3464
3	X		2317.0749 (1040.5737)	35.63837 (56.1636)		1.16898 (0.47056)			0.5747	0.4046
4		X	-1.02388 (9.815957)	-0.060217 (0.110404)			0.0000008224 (0.0000013206)	0.53945 (0.26106)	0.5615	0.2326
5		X	4.9969866 (1.591704)	0.008057 (0.01224)				0.45381 (0.20788)	0.5189	0.3266
6		X	8.4691 (0.078714)	0.009691 (0.015588)					0.0605	-0.0960

Where Y = sales (in million dollars)

X1 = advertise and administrative expenses (in million dollars)

X2 = personal consumption expenditures (in million dollars)

T = time (in quarters)

Models 1-3

Adjusted R² is the key to determining which model is good. The higher the value of a model’s adjusted R², the better the model. Among models 1 to 3, the first one is definitely the worst. If we use the R², the second model is better, but if we use the adjusted R², the third model is better. However, the second model contains more independent variables than the third one, so we will use the adjusted R² to determine which model is the good one, since the adjusted R² considers the quantity of independent variables used in the equation.

Therefore, the best model is Model 3 → Y = B0 + B1X1 + B2T
→ Y = 2317.0749 + 1.16898X1 + 35.63837T

By using single moving average, the predicted advertising and administrative expense (X1) for the next two periods will be:

Period 9 = (2394 + 2247)/2 = 2320.5

Period 10 = (2247 + 2320.5)/2 = 2283.75

So the predicted sales for the next two periods will be:

Period 9 = 2317.0749 + 1.16898*2320.5 + 35.63837*9 = $5350.4383 million

Period 10 = 2317.0749 + 1.16898*2283.75 + 35.63837*10 = $5343.1167 million

In Model 3, the coefficient X1 (1.16898) tells us that if the advertising and administrative expense was changed by one unit (one million dollars), sales would change in the same direction by $1.17 million. The coefficient T (35.63837) tells us that sales would increase $35.64 million each period (three months), due to inflation or market expansion.

Models 4-6

Again, adjusted R² is the key to determining which model is good. The higher the value of a model’s adjusted R², the better the model. Among models 4 through 6, the last one is definitely the worst. If we use R², the fourth model is better, but if we use the adjusted R², the fifth model is better. However, similar to the logic we used in models 2 and 3, the fourth model contains more independent variables than the fifth, so we decided to use the adjusted R² to determine which model is the best one, since the adjusted R² considers the quantity of independent variables used in the equation.

Therefore, the best model is Model 5 → lnY = B0 + B1lnX1 + B2T
→ lnY = 4.9969866 + 0.45381lnX1 + 0.008057T

By using single moving average, the predicted advertise and administrative expenses (X1) for the next two periods will be:

Period 9 = (2394 + 2247)/2 = 2320.5, thus lnX1 = 7.749538

Period 10 = (2247 + 2320.5)/2 = 2283.75, thus lnX1 = 7.733574

So the predicted sales for the next two periods will be:

lnY₉ = 4.9969866 + 0.45381*7.749538 + 0.008057*9 = 8.5863174398

→ Y = 5357.8467 millions --- Period 9

lnY₁₀ = 4.9969866 + 0.45381*7.733574 + 0.008057*10 = 8.5871298169

→ Y = 5362.2011 millions --- Period 10

In Model 5, coefficient lnX1 (0.45381) tells us that if the advertising and administrative expense was changed by 1%, sales would change in the same direction by 0.45%. The coefficient T (0.008057) tells us that sales would increase 0.81% each period (three months), due to inflation or market expansion.

Evaluation of Accuracy – Magnitudes of Error

The following results were gathered through the use of Excel:

	Linear Time Trend Line	Single Moving Average	Single Exponential Smoothing	Multiple Regression
Forecast Revenue (millions)	$5,190.75	$5,160.00	$5048.922	5350.438
MAE	399.8775	578.75	544.29	252.3638
MSE	184,498.6	345,220.2	395,241.72	82,576.425
MAPE	8.147% ($422.89million)	11.572% ($597.115 million)	10.443% ($529.857 million)	5.275% ($282.246 million)

The mean absolute error (MAE) tells us that: the linear time trend forecast may be off by $399 million in either direction, the single moving average forecast may be off by $578.75 million, and the single exponential smoothing forecast may be off by $544.29 million. The linear time trend has the least degree of absolute error and therefore, in this instance, the linear time trend should be the most accurate for forecasting.

The mean squared error (MSE) weighs large errors heavier and it tells us that: the linear time trend forecast may be off by 184498.6, the single moving average forecast may be off by 345220.2, and the single exponential smoothing forecast may be off by 395241.72. If we were to use mean squared error to decide upon a forecasting method, we would choose linear time trend, as it should provide us with the most accurate forecast.

The mean absolute percentage error (MAPE) provides us with a percentage of error that we can expect our forecast to be off by. In this instance, the linear time trend forecast may be off by 8.15%, the single moving average forecast may be off by 11.57%, and the single exponential smoothing forecast may be off by 10.44%. If we were to use mean absolute percentage error to decide upon a forecasting method, we would choose linear time trend, as it should provide us with the most accurate forecast.

However, if we examine the result of multiple regressions, linear time trend line would not be a clear choice. Model 3 is the best among the model 1 through 3, and when we compare its MAE, MSE, and MAPE with linear time trend line, the regression model seems to be a better model than linear time trend line. Therefore, we chose the regression model 3 and use its predicted values to do the financial planning for the Coca-Cola Company.

FINANCIAL ANALYSIS

Liquidity

	12/01	09/01	06/01	03/01	12/00	09/00	06/00	03/00
Current ratio	0.851	0.874	0.877	0.818	0.710	0.721	0.685	0.667
Quick ratio	0.221	0.285	0.283	0.276	0.195	0.266	0.240	0.221
Average payment period	231.87	216.06	230.90	266.19	252.30	234.33	232.33	250.56

² Current ratio = Current assets/Current liabilities
Current ratio represents the ability of a company to cope with sudden changes, so, the higher, the better. Since current assets can be transformed into cash quickly, the more current assets the company owns, the lower risk of bankruptcy it’s going to face. We can see that the current ratio is increasing; it is a good trend for Coca-Cola.

² Quick ratio = (Cash + Accounts receivable)/Current liabilities
Quick ratio is like current ratio, but more focus on real cash. The quick ratio of Coca-Cola keeps steady and seems to have a regular pattern that it is increasing gradually during the first three quarters and drops in the fourth quarter.

² Average payment period = Accounts payable/(COGS/90)
Originally, the formula should be accounts payable/(COGS/365), but because the data we are using is quarterly, 90 days would be better. If average payment period is longer, the company does not have to pay its suppliers immediately. The advantage is that the company can have money in its pocket longer, earning greater interest and spending it more efficiently.

Financial Leverage

	12/01	09/01	06/01	03/01	12/00	09/00	06/00	03/00
Total debt to total assets	0.493	0.511	0.535	0.551	0.553	0.574	0.605	0.599
Total debt to equity	0.972	1.045	1.151	1.225	1.236	1.350	1.532	1.496
Equity multiplier	1.972	2.045	2.151	2.225	2.236	2.350	2.532	2.496
Interest coverage	22.691	19.864	19.649	14.066	7.697	11.058	10.798	2.424

² Total debt to total assets = Total liabilities/ Total assets
The lower this ratio the better, because if the company has fewer liabilities, the lower risk of bankruptcy. We can see that the ratio of total debt to total assets keeps falling; it’s good for the Coca-Cola Company.

² Total debt to equity = Total liabilities/Stockholder’s equity
This ratio is also like the ratio of total debt to total assets, the lower, the better. Moreover, the trend is good, because the ratio is also decreasing.

² Equity multiplier = Total assets/SE
When the value of this ratio is 1, total assets are equal to stockholder’s equity, and that means the company doesn’t have any liabilities. It is impossible, but then we know if the value of this ratio is closer to 1, the company will have less liability. From the table, it is obvious that Coca-Cola has less and less liability, and so its risk of bankruptcy is falling as well.

² Interest coverage = EBIT/Interest expense
This ratio represents the ability of a company to cope with its debt. When we borrow money, we have to pay interest. Before a company borrows money, it must consider its ability to cover the interest. This ratio is increasing rapidly; that means the ability of Coca-Cola to cover its debt is growing, so its risk of bankruptcy is dropping.

Profitability

	12/01	09/01	06/01	03/01	12/00	09/00	06/00	03/00
Operating profit margin	0.254	0.243	0.286	0.286	0.177	0.245	0.234	0.056
Net profit margin	0.186	0.199	0.211	0.193	0.051	0.197	0.169	(0.014)
ROA	0.041	0.047	0.050	0.039	0.012	0.046	0.040	(0.003)
ROE	0.080	0.097	0.107	0.086	0.026	0.108	0.101	(0.007)

² Operating profit margin = EBIT/Net sales
This ratio is increasing slowly; that means the Coca-Cola Company is operating more efficiently gradually. So its profitability will become better and better.

² Net profit margin = Net income/ Net sales
This ratio is also like operating profit margin, and the Coca-Cola Company performs very well, the ratio is even from negative to be positive. It shows that the Coca-Cola Company improves its performance very well and very quickly.

² ROA = Net income/Total assets
The higher the company’s ROA, the more efficiently the company is using its assets to make money. We can see that Coca-Cola’s performance is pretty steady, except during the first quarter of year 2000. In addition, the average ROA for the industry is about 3%, and it seems that Coca-Cola (17.7%--year 2001 , 9.5%--year 2000) is doing much better than the industry.

² ROE = Net income/Stockholder’s equity
If a firm’s ROE is greater than its ROA, it indicates that the firm operates its business efficiently by borrowing money. In addition, the average ROE for the industry is about 10%, and Coca-Cola (37%--year 2001 , 22.8%--year 2000) is doing much better than the industry.

FINANCIAL PLANNING FOR COCA-COLA

At first, we decided to use linear time trend line to forecast revenues for the next two periods. However, after we used MAE, MSE, and MAPE to measure the efficiency of the models, we found that the multiple regression model is better. Moreover, we found that the variables of administrative expense and time are both significant factors on revenues. Thus, with either time passing, or with increased spending on advertising and administration, revenues will increase.

Now that the revenue we predicted is increasing, how would this result affect the Company’s liquidity, financial leverage, and profitability? With regard to liquidity, the average payment period and average collection period will decrease. Coca-Cola Company will not have more time to pay, and will get customer payments in shorter time. In addition, the ratio of inventory turnover and asset turnover will increase. It means that Coca-Cola Company would manage inventory efficiently and use its assets to generate sales efficiently.

With regard to profitability, the EBIT and net income will increase so that operating profit margin and net profit margin will rise. It means the amount of each dollar of revenue that results in total net income will increase. In addition, ROE and ROA will rise, so the return on each dollar invested by the common shareholders in Coca-Cola Company and the amount earned on each dollar invested in assets will increase.

We’ve included on the following pages, the income statement and the balance sheet over the next two periods. We have used the predicted revenues from the multiple regression model and the percentage-of-sales to forecast the Company’s financial performances.

Forecasted Income Statement

(In million of USD, except for per share items)

	Mar. 2002		Jun. 2002
Net operating revenues	$5,350.44		$5,343.12
Cost of goods sold	$1,552.16	29.01%	$1,550.04	29.01%
Gross profit	$3,798.28	70.99%	$3,793.08	70.99%
Selling, administration & general expenses	$2,441.94	45.64%	$2,438.60	45.64%
Operating income (loss)	$1,356.34	25.35%	$1,354.48	25.35%
Interest income	$106.47	1.99%	$106.33	1.99%
Interest expense	$59.92	1.12%	$59.84	1.12%
Equity income (loss) - net	($16.05)	-0.30%	($16.03)	-0.30%
Other income (loss) - net	$17.66	0.33%	$17.63	0.33%
Inc bef inc taxes & cum eff accounting change	$1,403.96	26.24%	$1,402.03	26.24%
Income taxes	$410.91	7.68%	$410.35	7.68%
Net income (loss)	$993.58	18.57%	$992.22	18.57%

Forecasted Balance Sheet

(In million of USD, except for per share items)

	Mar. 2002		Jun. 2002
Cash & cash equivalents	$2,027.82	37.90%	$2,025.04	37.90%
Marketable securities	$73.84	1.38%	$73.74	1.38%
Total cash & securities	$2,101.65	39.28%	$2,098.78	39.28%
Inventories	$1,146.60	21.43%	$1,145.03	21.43%
Prepaid expenses & other assets	$2,499.73	46.72%	$2,496.31	46.72%
Total current assets	$7,793.45	145.66%	$7,782.79	145.66%
Equity method invests Coca-Cola Enterprises	$856.61	16.01%	$855.43	16.01%
Equity method invests Coca-Cola Amatil Ltd	$469.77	8.78%	$469.13	8.78%
Equity method invests HBC S.A.	$859.82	16.07%	$858.64	16.07%
Other, principally bottling companies	$3,387.90	63.32%	$3,383.26	63.32%
Cost method invests in bottling cos	$319.42	5.97%	$318.98	5.97%
Other assets	$3,034.23	56.71%	$3,030.08	56.71%
Total investments & other assets	$8,927.21	166.85%	$8,915.00	166.85%
Land	$235.95	4.41%	$235.63	4.41%
Buildings & improvements	$1,969.50	36.81%	$1,966.80	36.81%
Machinery & equipment	$5,304.96	99.15%	$5,297.70	99.15%
Containers	$211.88	3.96%	$211.59	3.96%
Property, plant & equipment, gross	$7,721.76	144.32%	$7,711.19	144.32%
Less allowances for depreciation	$2,882.28	53.87%	$2,878.34	53.87%
Property, plant & equipment, net	$4,839.47	90.45%	$4,832.85	90.45%
Goodwill & other intangible assets	$2,803.10	52.39%	$2,799.26	52.39%
Total assets	$24,363.23	455.35%	$24,329.90	455.35%
Accounts payable & accrued expenses	$3,998.38	74.73%	$3,992.91	74.73%
Loans & notes payable	$4,067.94	76.03%	$4,062.37	76.03%
Current maturities of long-term debt	$169.61	3.17%	$169.38	3.17%
Accrued income taxes	$925.09	17.29%	$923.83	17.29%
Total current liabilities	$9,161.02	171.22%	$9,148.49	171.22%
Long-term debt	$1,324.77	24.76%	$1,322.96	24.76%
Other liabilities	$1,044.41	19.52%	$1,042.98	19.52%
Deferred income taxes	$480.47	8.98%	$479.81	8.98%
Common stock	$948.63	17.73%	$947.34	17.73%
Capital surplus	$3,825.56	71.50%	$3,820.33	71.50%
Reinvested earnings	$25,478.26	476.19%	$25,443.40	476.19%
Accum oth comprehensive inc & unearned	($3,029.95)	-56.63%	($3,025.81)	-56.63%
Total shareholders' equity bef treasury stock	$27,223.04	508.80%	$27,185.79	508.80%
Less treasury stock, at cost	$14,869.94	277.92%	$14,849.60	277.92%
Total shareowners' equity	$12,353.10	230.88%	$12,336.20	230.88%

Asset Adjustments

In order for the forecasted sales to be realized, days’ sales in receivables, inventory turnover, and days’ sales in inventory will need to be improved. In other words, finished products should be moved from warehouses to store shelves faster. Coca-Cola is in need of a just-in-time inventory system or, at the very least; some type of logistical analysis to better streamline inventory processes is in order.

Sales Affects on Profitability

Depending on what it takes the revenue to increase, profitability will be affected. If significant advertising costs are required to boost sales, gross profit margin, operating profit margin, and net profit margin will be affected negatively. If the sales forecasts become a reality without the help of additional investments, gross profit margin, operating profit margin, and net profit margin will be affected positively and should increase.

Sales Affects on Financial Leverage

The forecasted sales would affect financial leverage by improving (decreasing) the debt to equity ratio, so long as the equity is available. Increased sales should also cause the financial leverage index to increase. If the equity is not available to increase the revenue, Coca-Cola will be under financial stress and the increased revenue may adversely affect the company as a whole.

CONCLUSION

Coca-Cola has been a leader in the soft drink industry since the company’s inception. They have maintained leadership by consistently renovating their marketing efforts, advertising strategies, product lines, globalization, mergers and acquisitions, and improving financial strength. Through their attention to improving business strategies and continuous improvement, Coca-Cola has maintained leadership and is expected to continue to be a leader in the soft drink industry.