-
Sh
an F
oods
Pri
vate
Lim
ited
2012
Sale
s Fo
rcas
ting
– R
ecip
e Sp
ice
Shan Foods (Private) Ltd. was founded in 1981 in a single room
as Shan Masala. Later, due to its popularity, the company was named
Shan Foods. It has presence in more than 50 countries today and
deals in several broad categories of offerings. Shan Foods has
capitalized on the changing market trends and consumer tastes and
through product trials, it has made sure to churn out offerings
that are best in line with consumer tastes.
S han Foods P r i v ate L im i ted
K o r a n g i I n d u s t r i a l A r e a ,
K a r a c h i , P a k i s t a n + 9 2 – 2 1 – 3 5 0 5 3 1 9 6 +
9 2 – 2 1 – 3 5 0 5 3 0 8 0
Group Leader: Adeel A. Siddiqui (GL) – 11262
Group Members: Babar Ansari – 10055
Muhammad Kashif – 9415 Raja Raffay Nizamani – 8856
Hassan Omer – 9265
-
L e t t e r o f A c k n o w l e d g e m e n t
To whom it may concern.
This Letter is to acknowledge the efforts and sincerity, offered
by the course instructor Mr. Saeed – UR – Rehman, to teach the
subject and provide adequate guidlines. The accomplishment of this
report is a result of a combine effort made by the reported and the
reporting individuals, during the term spring 2012. The objective
to write this report is to learn the methods of Sale Forecasting
used by an FMCG producer, in this case Shan Foods Private Limited.
I hereby acknowledge that I may not be able to understand and write
the content of this report without sincere guidance from Mr. Khalid
Zaki (GM International Sale, Shan Foods Private Limited), Mr. Zahir
Mirza (GM Sales Management, Shan Foods Private Limited) and their
associates, as well.
Gracias,
Group Leader: Adeel A. Siddiqui (GL) 11262
Group Members: Babar Ansari 10055 Muhammad Kashif 9415 Raja
Raffay Nizamani 8856 Hassan Omer 9265
-
L e t t e r o f T r a n s m i t t a l
To, Mr. Saeed – Ur – Rehman, Institute of Business
Management,
Dear Sir,
We are submitting this report along with a presentation on the
Sales Forecasting method used by Shan Foods Private Limited, for
Bombay Biryani, from Recipe Mix, on Monday, dated 23th
April 2012. The Purpose of this report is to provide you content
on the basis of which you are able to assess our understanding and
comprehension about the course title Sales Management. The Content
of this report is based on the information provided by Shan Foods
Private limited, for the purpose. Moreover the data and information
acquired from Shan Foods Private Limited has been composed,
structured and elaborated so that it can deliver its intended
objectives. The Report also discusses the specific procedures of
Sale Forecasting and its vitals, for the selected product.
Gracias,
Group Leader: Adeel A. Siddiqui (GL) 11262
Group Members: Babar Ansari 10055 Muhammad Kashif 9415 Raja
Raffay Nizamani 8856 Hassan Omer 9265
-
L i s t o f T a b l e s Table 1: Target Market
..................................................................................................
10 Table 2: EFE Sales
............................................................................................................
11 Table 3: IFE Sales
.............................................................................................................
11 Table 4: Forecasting Model FY'13
...............................................................................
12 Table 5: Forecasting first half FY'13
.............................................................................
13
L i s t o f F i g u r e s Figure 1: Sales
Organization...........................................................................................
4 Figure 2: Sales Forecasting Process
..............................................................................
5 Figure 3: Market Share
..................................................................................................
10 Figure 4: Sales FY'12 - Historical Trend
........................................................................
12
T a b l e o f C o n t e n t s Letter of Acknowledgement
..........................................................................................
ii
Letter of Transmittal
.........................................................................................................
iii
Table of Contents
.............................................................................................................
1
Introduction
.......................................................................................................................
3
Product Range
.................................................................................................................
3
Sales Organization
...........................................................................................................
4
Sales Forecasting Procedure
.........................................................................................
4
1. Factor Analysis
.......................................................................................................
5
2. Forecasting Model
................................................................................................
6
3. Data Acquisition
....................................................................................................
6
4. Estimations
...............................................................................................................
7
5. Combining Estimates
............................................................................................
7
6. Variance Analysis (Evaluation)
...........................................................................
7
Forecasting Methods
......................................................................................................
8
1. Historical Extrapolation
.........................................................................................
8
2. Sales Projections by PLC
......................................................................................
8
3. Seasonal Variations
...............................................................................................
8
-
Sales Forecasting – Recipe Spice – Table of Contents
Page | 2
4. Leading Indicators
................................................................................................
8
5. Sales force estimates (Composites)
..................................................................
9
6. Market Surveys
.......................................................................................................
9
7. External and Internal Factors listing
...................................................................
9
8. Committee Consensus
.........................................................................................
9
9. Executives Opinion
................................................................................................
9
Selected Product
.............................................................................................................
9
Forecasting for Selected Product
................................................................................
9
1. Subjective Analysis
..............................................................................................
10
1. Target Market
................................................................................................
10
2. Market Share
.................................................................................................
10
3. EFE Sales
.........................................................................................................
11
4. IFE Sales
...........................................................................................................
11
5. Seasonal Variation (Historical trend)
........................................................ 12
2. Forecasting Model
..............................................................................................
12
3. Sales Forecast for Fruit Chaat
...........................................................................
13
4. Consensus & Executive Opinion
......................................................................
13
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Sales Forecasting – Recipe Spice – Introduction
Page | 3
I n t r o d u c t i o n Shan Foods (Private) Limited is a Food
products Manufacturing and Marketing Organization. It was founded
in 1981 in a single room as Shan Masala. Later, due to its
popularity, the company was named Shan Foods. It has presence in
more than 50 countries today and deals in several broad categories
of offerings. Shan Foods has capitalized on the changing market
trends and consumer tastes and through product trials, it has made
sure to churn out offerings that are best in line with consumer
tastes.
A huge part of their sales consist of Recipe Mix Category.
Recipe Mix Category consists of 64 variants, classified into 9
ranges. The share of products from Chaat Masala in the Recipe Mix
Category Sales is significantly larger than any other range, and it
is due to the popularity of Shan Chaat Masala.
This report is to understand the forecasting methods Shan Foods
has adopted, for the regular bottle SKU (100 gm), of Chaat Masala.
But primarily, we must look into the product range and brand
portfolio and their procedure of sales forecasting, to understand
the complexity of the company’s Sales Organization.
P r o d u c t R a n g e Shan Foods have a brand portfolio of two
brand names, Shan and Delve, which are further sub divided into
several categories and ranges of different variants of products.
Primarily, it is important to understand the broad categories of
offerings by Shan Foods. Following is a summarized list.
• Shan Variants – Recipe Mix 64 – Plain Spices 16 – Oriental
Recipe 10 – Salt 2 – Pickle 7 – Paste 3 – Sauces 5 – Rice 5 –
Vermicelli 1
• Delve Deserts – Jelly Crystals 4 – Custard Powders 3 – Pudding
Mix 3
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Sales Forecasting – Recipe Spice – Sales Organization
Page | 4
Irrespective of the ranges and variants, Shan Foods practices
separate forecasting methods for their different SKU’s as well.
S a l e s O r g a n i z a t i o n Sales Organization of Shan
Foods is divided into two Departments, which are International and
Local Sales. Local Sales department is more like traditional Sales
Department. Shan Foods Sales Organization is lead by the CEO
himself. Sales as a function is monitored and advised by COO, while
the controlling is in the Scope of GM Sales Management. Under his
supervision there are RSM (North and South), ASMs, Key Accounts
Managers, Sales Executives (Head Office only), and Sales
Representatives. Reporting within the sales function is performed
on daily basis, while COO and CEO review the performance on weekly
basis with the management committee. Sales Automations are only
used by the sales team working in urban regions. To meet Sales
objectives, GM Sales has a responsibility to coordinate with other
functions within the company. For this reason, they together
develop SNOPs and budgets, respectively. Following is the
hierarchal structure for the reporting system.
Figure 1: Sales Organization
S a l e s F o r e c a s t i n g P r o c e d u r e Shan Foods
follows a standard procedure to forecast and further synchronize it
with actual and improve the Sales Forecasting Methods. Sales
forecasting is
CEO
COO
GM Sales
RSM North
ASMs
SRs
Key Acct. Mngr.
Sales Executives
RSM South
ASMs
SRs
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Sales Forecasting – Recipe Spice – Sales Forecasting
Procedure
Page | 5
performed annually, before the beginning of the Fiscal Year.
These forecasts are verified for any variances on quarterly basis,
by which these are fine tuned. Every Product and their SKU’s have
separate forecasting method.
The process of Sales Forecasting is conducted by Sales
Forecasting Committee, which constitutes of members from Strategic,
Operations, Marketing, and Sales functions. This Committee is
headed by CEO, and seconded by COO. The input from GM Sales
Management is always given the highest weight – age, amongst all
other members. Following are the Core functions and
responsibilities of the Sales Forecasting Committee.
Figure 2: Sales Forecasting Process
1 . F a c t o r A n a l y s i s Factor Analysis is the basic
function, which lays the basis for accurate forecasting. By this,
committee figures out the viability of the previous forecasting
model and its constituents, with respect to the present
circumstances. Following are some of the constituents of Factor
Analysis.
• Subjective Analysis by Territory o Target Market o Market
Potential o Sales Potential
• EFE Sales o PEST o Seasonal Variations Historical Data o CPM o
Porter’s Five Forces
Factor Analysis•Subjective
Analysis•EFE and IFE
Sales
Forcasting Model•Desiging •Testing
Data Acquisition•Primary
Sources•Secondary
Sources
Estimation•Qualitative•Quantitative Combining
EstimatesVariance Analysis
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Sales Forecasting – Recipe Spice – Sales Forecasting
Procedure
Page | 6
• IFE Sales o Resource Based View o Advertising Support o
Distribution Support o Value Chain Analysis/Capacity Evaluations o
Product Imperatives
With this information they further improve the existing or
sometimes even develop a new Forecasting Model by using a blend of
techniques.
2 . F o r e c a s t i n g M o d e l Each Offering’s sale
forecast is a significant and unique composite of estimate using
several methods for forecasting. These forecasts are assigned
percent weight – ages, and then combined to make a composite sales
forecast model. This is also dependent on the company’s strategy
for the offering. For example, if the company wants to set
aggressive targets, the committee will increase the weight – age of
Historical Extrapolation, with respect to the required growth rate.
Several Qualitative and Quantitative methods are used to collect
data and estimate forecasts. Some are listed under the heading of
Estimates.
3 . D a t a A c q u i s i t i o n To forecast sales, several
primary and secondary data sources are used to provide estimates of
forecasted sales. Some of them are as follows.
• Market Research and Survey o Primary (Conducted by Internal
Team) o Data Monitors o Nielsen Pakistan
• Previous Volume Sales and Revenue Data o Internal MIS
• Macro Economics • Marketing Intelligence
o Internal Functions o Sales Forces o Distributors o Wholesalers
o Retailers
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Sales Forecasting – Recipe Spice – Sales Forecasting
Procedure
Page | 7
4 . E s t i m a t i o n s The estimates required for forecasting
individual offering are then estimated by using following
methods.
• Quantitative o Historical Extrapolation
Industry Sales Company Sales
o Sales Projections by PLC (for New Categories) o Seasonal
Variations o Leading Indicators
• Qualitative o Sales force estimates o Market Surveys o
External and Internal Factors listing o Committee Consensus o
Executives Opinion
All the estimates from the above methods are translated into
future sales, which are then combined to give a composite Sales
Forecast.
5 . C o m b i n i n g E s t i m a t e s For every individual
product there is a certain percent weight – age, assigned to the
forecasted sales by each method, which are then combined to make
100% forecasted sales, which are agreed by the members of the
committee and approved by the Head of the Committee. These weight –
ages are fine tuned with respect to actual sales by Variance
Analysis Method, for next year sales forecasting, as an ongoing
process.
6 . V a r i a n c e A n a l y s i s ( E v a l u a t i o n )
Variance Analysis used along with Factor Analysis enables Shan
Foods to examine the variation between the actual sales and
forecasted sales and this method is applicable to examine sales
forecast from every method used for the purpose. The comparison
would be made against sales forecasts and actual sales to identify
the reasons for actual differences, which are then easily
identified and examined within the areas of concern and their
component parts. More specifically, variance analysis could be
applied to sales price and sales volume and the values of variance
can point to either of the two reasons. This Analysis is used to
fine tune the Combination of Methods, and ultimately results in
more accurate forecast in future.
-
Sales Forecasting – Recipe Spice – Forecasting Methods
Page | 8
F o r e c a s t i n g M e t h o d s Shan Foods Sales
Organization uses a separate model for every offering. Following
are the reasons behind this activity.
• Buying behavior for several offering is unique and related to
seasons, occasions, etc. For example, the sales of Shan Foods,
Chicken Tikka and Bihari Kabab Masala, significantly shows a cyclic
increase after Eid – Ul – Azha, while Chat Masala sales increases
during Ramadan till Eid – Ul – Fitr.
• Buying behavior for different SKUs of a single product, also
changes with territory, occasion, etc. For example, Bombay Biryani
Regular pack is not demanded in several areas at all, while its 15
gm Sachets are purchased on relatively higher frequency.
They use the above mentioned forecasting methods for several
significant reasons. Following are some explanations, based on
examples, which justifies the inevitability of each of these
methods.
1 . H i s t o r i c a l E x t r a p o l a t i o n The Historical
Extrapolation is used to estimate the forecast of Industry Sales
and Company Sales, both consumer and institutional. By this they
keep the required sales growth into consideration, which gives an
aggressive sales forecast figures.
2 . S a l e s P r o j e c t i o n s b y P L C Sales Projections
by PLC, helps them in keeping track of the product life cycle stage
the product is in. This provides a mediocre Sales Forecast, if the
product is at a stage of maturity.
3 . S e a s o n a l V a r i a t i o n s Seasonal Variations
shows the cyclic rise in the demand of any particular offering with
respect to year, occasion, etc.
They also consider pattern of the dates in every month, showing
increasing cycles of take offs from shelves. This helps them to
plan for acquiring the self spaces, accordingly.
4 . L e a d i n g I n d i c a t o r s Some Socio – Demographic
factor, shows significant relationships with the sale of certain
products, such as, if there is an increase in wedding ceremonies,
there is a significant increase in the Institutional sale of
Biryani Range, Korma Range, etc.
-
Sales Forecasting – Recipe Spice – Selected Product
Page | 9
5 . S a l e s f o r c e e s t i m a t e s ( C o m p o s i t e s
) Sales force estimates are the expectations of the sales
representatives, about future sale. This primarily, helps in
knowing the real picture at the grass root level, and then it is
helps in knowing the distribution of sales to the territory
level.
6 . M a r k e t S u r v e y s By Market Surveys, they recognize
the numbers of the existing and potential buyers and specific
buying behaviors they possess. These can be translated into the
expected Sales.
7 . E x t e r n a l a n d I n t e r n a l F a c t o r s l i s t
i n g External and Internal Factor listing indicate several
aspects, which can affect Sales Forecast, significantly the sales
to the institutions. For Example, if PIA is not to conduct Haj
Flights, the institutional sales of Shan Salt and Pepper, packaged
specially for PIA will significantly decrease.
8 . C o m m i t t e e C o n s e n s u s After applying the above
mentioned methods, percent weight – ages, the committee members
discuss, review, decide and agree with the Sales Forecasts.
9 . E x e c u t i v e s O p i n i o n The Sales Forecasts are
then presented in front of the Board of Directors, along with CEO
and COO, for revisions and approvals.
S e l e c t e d P r o d u c t To understand the forecasting
method, adopted by Shan Foods Private limited, we selected a Shan
Foods Fruit Chat Masala (100 gm Bottle) from the Chat Masala Range,
within Recipe Mix Range. Recipe Mix Range consists of 64 different
variant with 4 to 8 different SKU’s for each. All these products
and SKU’s have different forecasting methods and its
associations.
F o r e c a s t i n g f o r S e l e c t e d P r o d u c t
Following is the Sales forecast for Shan Foods Fruit Chat Masala
(100 gm Bottle), which is not actual. The purpose of this forecast
is to give an example that how the above elaborated process can be
performed.
-
Sales Forecasting – Recipe Spice – Forecasting for Selected
Product
Page | 10
1 . S u b j e c t i v e A n a l y s i s
1. Target Market The Target market is defined in the following
table.
Table 1: Target Market
Demographics Age - 11 ~ 20 21~ 35 36 ~ 50 - Family Size 1 - 2 3
- 4 5 - 6 - - SEC Class A1 A2 B1 B2 C Gender Male Female - - -
Occupation Students Professionals Clerical Retired Housewives
Region North South - - -
Psychographics Personality Ambitious Family
Oriented Quality Conscious Health
Conscious Taste Conscious
Occasions Special Occasions
Guest Visits Small Gatherings Meals
Picnics/ Travels
Snacks
2. Market Share
Figure 3: Market Share
10,800,000
10,800,000
2,400,000
Shan
National
Others
-
Sales Forecasting – Recipe Spice – Forecasting for Selected
Product
Page | 11
This Product is at its Maturity Stage therefore the Market
Potential is assumed to be saturated, and instead Market Share must
be considered.
3. EFE Sales EFE Sales is a factor listing of the external
forces which may affect expectations of sales.
Table 2: EFE Sales
Key External Factors % Change % Weight Opportunities Annual
Population Growth 6% 6% 5% Disposable Income Increase 5% 5% 5%
Trends, Healthy and Quality Product 15% 15% Buying Branded Spices
15% 20% Threats New Competitors Entering 5% 1% Fast food and
restaurant Trend 25% 17% Out off Home Iftar Trend 35% 35%
Substitute Potential Growth 5% 2% Total 100%
4. IFE Sales IFE Sales is a factor listing of the internal
forces which may affect expectations of sales.
Table 3: IFE Sales
Key Internal Factors % Change % Weight Strengths Production
Capacity Increase 15% 5% Value Chain Improvements 10% 5% Urban
Distribution 1.5% 15% Average customer Purchase 15% 20% Weaknesses
Advertising Efforts 5% 1% Rural Distribution 25% 19% Less
attractive Sales promotions 35% 35% Total 100%
-
Sales Forecasting – Recipe Spice – Forecasting for Selected
Product
Page | 12
5. Seasonal Variation (Historical trend) Fruit Chat Masala shows
an 85% of the annual sales in the months of Shaban and Ramadan,
which begin to increase from the mid of Shaban and decrease to the
level of normal sales by the end of Ramadan. Highest Sales is
observed during the first week of Ramadan. The increase in sale can
be observed in the Graph of FY ‘12below,
Figure 4: Sales FY'12 - Historical Trend
2 . F o r e c a s t i n g M o d e l This Forecasting model is
designed on the basis of Variance Analysis with keeping Subjective
Analysis, EFE and IFE Sales in consideration. The Company’s
Strategy is aggressive towards selling Fruit Chart Masala therefore
the weight – ages assigned to Historical Extrapolations have been
increases accordingly.
Table 4: Forecasting Model FY'13
Methods Previous Forecast
Actual Sales % Variance
Previous Weight
Modified Weight
Industry Sales 24,500,000 24,000,000 -2.1 30 35 Company Sales
11,000,000 10,800,000 -1.9 30 53 Projection by PLC
9,000,000 10,800,000 16.7 20 2
Sales Force Estimates
9,5000,000 10,800,000 12.0 20 10
Composites 10,307,500 10,800,000 100 100
0
10
20
30
40
50
60
Sales FY'12
Sales FY'12
-
Sales Forecasting – Recipe Spice – Forecasting for Selected
Product
Page | 13
3 . S a l e s F o r e c a s t f o r F r u i t C h a a t
Following is the sale Forecast for two quarter, assuming that the
second Quarter holds the months of Shaban and Ramadan.
Table 5: Forecasting first half FY'13
Methods Weight – age
Qtr 1 Qtr 2 Forecast W. FC Forecast W. FC
Industry Sales 35% 4,320,000 1,512,000 24,480,000 8,568,000
Company Sales 53% 1,944,000 1,030,320 11,016,000 5,838,480
Projection by PLC 2% 1,555,200 31,104 8,812,800 176,256 Sales Force
Estimates
10% 3,800,000 380,000 21,533,333 2,153,333
Composite 100% 2,121,824 12,023,669
Now the Sales forecast for Quarter 1 is 2,121,824. Whereas due
to the expected sales in the month of Shaban and Ramadan, Quarter 2
shows sales is 12,023,669 units
4 . C o n s e n s u s & E x e c u t i v e O p i n i o n
Before finalizing the Sales Forecast Report, the members of the
committee discuss it in meeting and draw a consensus.
After finalizing the Sales Forecasting Report, it is presented
to the Board of Director, for review
-
10/4/2012
1
Shan Foods Private LimitedRaja Raffay
Nizamani
•
Shan Foods (Private) Limited is a Food products Manufacturing and Marketing Organization. It was founded in 1981 in a single room as Shan Masala. Later, due to its popularity, the company was named Shan Foods. It has presence in more than 50 countries today and deals in several broad categories of offerings. Shan Foods has capitalized on the changing market trends and consumer tastes and through product trials, it has made sure to churn out offerings that are best in line with consumer tastes.h
f h l f•
A huge part of their sales consist of Recipe Mix Category. Recipe Mix
Category consists of 64 variants, classified into 9 ranges. The share of products from Chaat
Masala
in the Recipe Mix Category Sales is significantly larger than any other range, and it is due to the popularity of Shan Chaat
Masala.
•
This presentation is to understand the forecasting methods Shan Foods has adopted, for the regular bottle SKU (100 gm), of Chaat
Masala. But primarily, we must look into the product range and brand portfolio and their procedure of sales forecasting, to understand the complexity of the company’s Sales Organization.
Shan Foods Private Limited
-
10/4/2012
2
CEO
COO
GM Sales
RSM North
ASMs
SRs
Key Acct. Mngr.
Sales Executives
RSM South
ASMs
SRs
Adeel A. Siddiqui
Factor Analysis•Subjective Analysis
Forecasting Model
Data Acquisition
Estimation•Qualitative Combining Variance
•EFE and IFE Sales •Designing •Testing
•Primary Sources•Secondary Sources
•Quantitative Estimates Analysis
-
10/4/2012
3
Factor Analysis•Subjective Analysis
Forecasting Model
Data Acquisition
Estimation•Qualitative Combining Variance
•EFE and IFE Sales •Designing •Testing
•Primary Sources•Secondary Sources
•Quantitative Estimates Analysis
Factor Analysis•Subjective Analysis
ForcastingModel
Data Acquisition
Estimation•Qualitative Combining Variance
•EFE and IFE Sales •Desiging•Testing
•Primary Sources•Secondary Sources
•Quantitative Estimates Analysis
Factor Analysis•Subjective Analysis
Forecasting Model
Data Acquisition
Estimation•Qualitative Combining Variance
•EFE and IFE Sales •Designing •Testing
•Primary Sources•Secondary Sources
•Quantitative Estimates Analysis
-
10/4/2012
4
Babar Ansari
Hassan Omar
-
10/4/2012
5
-
10/4/2012
6
Shan Chaat Masala
(10 gm Bottle)Muhammad Kashif
DemographicsAge - 11 ~ 20 21~ 35 36 ~ 50 -Family Size 1 - 2 3 -
4 5 - 6 - -SEC Class A1 A2 B1 B2 C Gender Male Female - -
-Occupation Students Professionals Clerical Retired Housewives
Region North South - - -
PsychographicsPersonality Ambitious Family
Oriented Quality Conscious
Health Conscious
Taste Conscious
Occasions Special Occasions
Guest Visits Small Gatherings Meals
Picnics/ Travels
Snacks
Others, 10%
Shan, 45%
National, 45%
Key External Factors % Change % WeightOpportunitiesAnnual
Population Growth 6% 6% 5%
Disposable Income Increase 5% 5% 5%
Trends, Healthy and Quality Product 15% 15%y y
Buying Branded Spices 15% 20%
ThreatsNew Competitors Entering 5% 1%
Fast food and restaurant Trend 25% 17%
Out off Home Iftar Trend 35% 35%
Substitute Potential Growth 5% 2%
Total 100%
Key Internal Factors % Change % Weight
StrengthsProduction Capacity Increase 15% 5%
Value Chain Improvements 10% 5%
Urban Distrib tion 1 5% 15%Urban Distribution 1.5% 15%
Average customer Purchase 15% 20%
WeaknessesAdvertising Efforts 5% 1%
Rural Distribution 25% 19%
Less attractive Sales promotions 35% 35%
Total 100%
40
50
60
Sales FY'12
0
10
20
30
Jul‐11 Aug‐11 Sep‐11 Oct‐11 Nov‐11 Dec‐11 Jan‐12 Feb‐12 Mar‐12
*Apr‐12 *May‐12 *Jun‐12
Sales FY'12
-
10/4/2012
7
Methods PreviousForecast
ActualSales
%Variance
PreviousWeight
ModifiedWeight
Industry Sales 24,500,000 24,000,000 -2.1 30 35
Company Sales 11,000,000 10,800,000 -1.9 30 53
Projection byPLC
9,000,000 10,800,000 16.7 20 2
Sales ForceEstimates
9,5000,000 10,800,000 12.0 20 10
Composites 10,307,500 10,800,000 100 100
Methods Weight –age
Qtr 1 Qtr 2Forecast W. FC Forecast W. FC
Industry Sales 35% 4,320,000 1,512,000 24,480,000
8,568,000Company Sales 53% 1,944,000 1,030,320 11,016,000
5,838,480Projection by PLC 2% 1,555,200 31,104 8,812,800
176,256Sales ForceEstimates
10% 3,800,000 380,000 21,533,333 2,153,333
Composite 100% 2,121,824 12,023,669
1 - Sales Forecasting Methods - Shan Chaat MasalaLetter of
AcknowledgementLetter of TransmittalList of TablesList of
FiguresTable of ContentsIntroductionProduct RangeSales
OrganizationSales Forecasting ProcedureFactor AnalysisForecasting
ModelData AcquisitionEstimationsCombining EstimatesVariance
Analysis (Evaluation)
Forecasting MethodsHistorical ExtrapolationSales Projections by
PLCSeasonal VariationsLeading IndicatorsSales force estimates
(Composites)Market SurveysExternal and Internal Factors
listingCommittee ConsensusExecutives Opinion
Selected ProductForecasting for Selected ProductSubjective
AnalysisTarget MarketMarket ShareEFE SalesIFE SalesSeasonal
Variation (Historical trend)
Forecasting ModelSales Forecast for Fruit ChaatConsensus &
Executive Opinion
1 - Sales Forecasting Methods - Shan Chaat Masala -
Presentation