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

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

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

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

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

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