Introduction Hindustan Unilever Ltd. (HUL) is India’s largest Fast Moving Consumer Goods (FMCG) Company touching the lives of every two out of three Indians. HUL mission is to “Add vitality to life” through its presence in over 20 districts in home, personal care products, food and beverages. HUL is a 51% owned subsidiary of the Anglo-Dutch giant Unilever. The product portfolio of the company includes household and personal care products like soaps, detergents, shampoos, skin care products, color cosmetics, deodorants and fragrance. It is also the market leader in tea, processed coffee, branded wheat flour, tomato products, ice cream, Jams and squashes. Company growth strategy had been guided by two primary considerations. First HUL prioritized opportunity which built upon existing Assets and Capabilities. Second they avoided spreading their management talent to thinly. HUL always had a focus on innovations, and was proud of many of their accomplishments. Many have increased living standards in India. As per results declared on 31 July 2008, HUL has a Market Cap of 522.2 Billion.
(In Billions)
Industry Analysis
The Indian FMCG sector is the fourth largest Fast Moving Consumer Goods in the economy with a total market size in excess of US$ 13.1 billion. The FMCG market is set to treble from US$ 11.6 billion in 2003 to US$ 33.4 billion in 2015. Penetration level as well as Per Capita Consumption in most product categories like jams, toothpaste, skin care, hair wash etc in India is low indicating the untapped market potential. With 200 million people expected to shift to processed and packaged food by 2010, India needs around US$ 28 billion of investment in the food processing industry. An average Indian spends around 40% of his income on grocery and 8% on personal care products. The large share of FMCG products in total individual spending along with the large population base is another factor that makes India one of the largest FMCG markets.
Equity Research
(In Millions)
Year to
CY
CY
CY
CY
CY
December
03
04
05
06
07
CAGR (%) (CY05-07
Net Sales
11546 2
12388 7
13889 1
16345 4
18724 4
16.1%
Adj.
14181
15898
18800
19461
22020
8.2%
Net Profit
13559
18905
19149
19123
21664
6.4%
EBITDA
12.3%
12.8%
13.5%
11.9%
11.8%
NPM
11.7%
15.3%
13.8%
11.7%
11.6%
6.2
8.7
8.8
8.8
8.9
Margins (%)
Per Share Data Adj. EPS
Using Statistical Tools 1.Mean 2.Standard Deviation
Co-efficient of Variance 4. Correlation 5.Regression HUL 3.
Year
Income
X=(X-Mean X)
X2
2003
13559
-4921
24216241
2004
18905
425
180625
2005
19149
669
447561
2006
19123
643
413449
2007
21664
3184
10137856
∑x=92400
∑x2 =35395732
Mean =92400/5 =18480
Standard Deviation Mean=∑x/N =92400/5 =18480 S.D. = (35395732 /5) ½ S.D. =2660.66 C.V= S.D./Mean*100 C.V. =2660.66/18480*100 C.V. = 14.39%
P&G Year
Income
X=(X-Mean X)
X2
2003
39951
2892.4
8365977.76
2004
39244
3599.4
12955680.36
2005
40238
2605.4
6788109.16
2006
43377
-533.6
284728.96
2007
51407
-8563.6
73335244.96
∑x=214217
∑x2 =101729741.2
Mean=214217/5 =42843.4 S.D. = (∑x2 / N) ½ S.D. = (101729741.2/5) ½ S.D. = 4510.64 C.V. = S.D./Mean*100 C.V. = 10.53%
Correlation ( In Billions) Net sales(X)
X=(X-Mean X)
X2
Net Profit(Y)
Y=(Y-Mean Y)
Y2
XY
115.5
-30.3
918.09
13.6
-4.9
24
148.5
123.9
-21.9
479.61
18.9
0.4
.16
-8.6
138.9
-6.9
47.61
19.2
0.7
.49
-4.83
163.5
17.7
313.29
19.1
0.6
.36
10.62
187.3
41.5
1722.2 5
∑x=729.1
21.7
3.2
10.2 4
∑y =92.5
∑x y=278.5
Correlation(r) = ∑x y / (∑x2 ∑y2) ½ r= 278.5/ (729.1*92.5) ½ r= 0.79
Regression Year
Profit(Y)
X
XY
X2
2003
13559
-2
27118
4
2004
18905
-1
18905
1
2005
19149
0
0
0
2006
19123
1
19123
1
2007
21664
2
43328
4
16428
∑x2 =10
∑ y=92400
132.8
∑y /N= a = 92400/5 =18480 ∑x y/∑x2= b =16428/10 =1642.8 Y= a+ b x So the regression line is in the form of =18480+1642.8(x)
We are calculating profit for the year 2008, so we will be calculating it with the help of above regression line, so the profit for the year 2008 will be, For the x= 3 Y= 18480+1642.8(3) Y=18480+4928.4 Y= 23408.4 Why we have calculated above mentioned techniques: 1. Mean- One of the powerful tools of analysis is to calculate the single
average value that represents the entire mass of data. The objective of calculating the mean is: a) To get one single value that describes the characteristics of the entire data. b) To facilitate the comparison. Here we are calculating the mean of profits of the last five years so that we can get the average of the profits of the P&G earned during these years. 2. Standard Deviation - The standard deviation measures absolute variation of distribution of profits. The distribution that has the smallest standard deviation has the more representative mean. Hence, it is extremely useful in judging representativeness of mean 3. Variance-Here we are calculating the standard deviation two companies of same nature and same goods P&G and HUL in terms of income earned during the period of five years. The coefficient of variance is being calculated in order to know the variability of the two companies. 4. Correlation- There is a high degree of positive correlation between
Net Sales and Net Profit. It means that with an increase in Net sales the increase in Net Profit proportionatelymore. It shows the relationship between net sales and net profit 5. Regression- With the help regression technique, a company can estimates their future sales and thus the profit that will be generated in the future based on their past data.
Conclusion
The field of FMCG market is opening up and the competition is increasing day by day. Many players like ITC, Nestle etc. are expanding their business at a large scale. And the use of statistical tools is becoming very popular in the organization. There are various officers being appointed in the organizations. Companies are finding various ways to cope up with the competition within the market. The continuous research on quantitative scale will help the HUL to review their past Performance in quantitative terms and helps them to make further important Decisions. •
•
•
The sales of the company are increasing for the past five years so is the net profits. So the company will follow the same policy which was followed earlier. How much more capital is more to be invested? The solution for this is the regression lines. We can easily find out the amount required for earning of any desired revenue. By computing correlation we can say that the company is earning profit at increasing rate. So it is good method of judging the company before investing.
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