An Internship report submitted in partial fulfillment of requirements forMasters of Business Administration

Logistics and supply chain management25th June to 17th July, 2015

External Mentor Internal Mentor Major Gaurav Kundu GM- Distribution and Logistics Mr. Vikas Kumar Coarse Coardinator-LSCMMr. Pradeep Bhargava Manager, Supply Chain

Report on

“To develop understanding of supply chain function and demand planning in specific for

beverage Industry”

Internship report submitted in partial fulfillment of requirements forMasters of Business Administration

Logistics and supply chain management25th June to 17th July, 2015

Under the guidance ofMajor Gaurav Kundu

Internal Mentor External Mentor’s Mr. Vikas kumar Major Gaurav Kundu Assistant Professor (SS)

(GM- Distribution and Logistics) Mr. Pradeep Bhargava UPES- Dehradun (Manager, Demand Planning)

Submitted by

Sumit LoshaliSAP ID-500035310

Enrolment Number: R6000214078MBA – Logistics and Supply Chain Management

2014-2016Internship- Varun Beverages Ltd

College of Management & Economics Studies, UPES

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Student Declaration

I hereby declare that this submission is my own work and that, to the best of my knowledge and belief, it contains no material previously published or written by another person nor material which has been accepted for the award of any other degree or diploma of the university or other institute of higher learning, except where due acknowledgment has been made in the text.

Signature of the studentSumit LoshaliSAP id: 500035310Enrollment Number: R600214078 MBA-LSCM 2014-2016 College of Management & Economic Studies, UPES

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Acknowledgement

The internship opportunity I had with Varun beverages ltd was a great chance for learning and professional development. Therefore, I consider myself as a very lucky individual as I was provided with an opportunity to be a part of it. I am also grateful for having a chance to meet so many wonderful people and professionals who led me though this internship period.

Bearing in mind previous I am using this opportunity to express my deepest gratitude and special thanks to the Major Gaurav Kundu GM of VBL who in spite of being extraordinarily busy with his duties, took time out to hear, guide and keep me on the correct path and allowing me to carry out my project at their esteemed organization and extending during the training.

I express my deepest thanks to Mr. Pradeep (Manager, demand planning), Bijendra Singh(Assistant transport), Sunil Kumar Sharma( Assistant Manager), Mr. Rajesh Phogat (Manager Haryana Transport), Mr. Vikas Kumar (Coarse coordinator UPES), Dr. Neeraj Anand (HOD- LSCM), Mr. Danish (Shipping Executive) for taking part in useful decision & giving necessary advices and guidance and arranged all facilities to make life easier. I choose this moment to acknowledge their contribution gratefully.

I perceive as this opportunity as a big milestone in my career development. I will strive to use gained skills and knowledge in the best possible way, and I will continue to work on their improvement, in order to attain desired career objectives. Hope to continue cooperation with all of you in the future.Sincerely,

Sumit Loshali

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“Industry Mentors certificate”

Certificate

This is to certify that the summer internship report entitled To develop understanding of supply chain functions involved in demand planning submitted by Sumit Loshali to UPES for partial fulfillment of requirements for Masters of Business Administration LSCM is a bonafide record of the internship work carried out under my our supervision and guidance. The content of the report, in full or parts have not been submitted to any other Institute or University for the award of any other degree or diploma.

Signature of Industry mentor’s

Major Gaurav Kundu, Mr. Pradeep Bhargava Varun Beverage ltd (RJ Corp)College of Management & Economic Studies, UPES

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“Faculty Mentors certificate”

Certificate

This is to certify that the summer internship report entitled To develop understanding of supply chain function and demand planning in specific for beverages Industry submitted by Sumit Loshali to UPES for partial fulfillment of requirements for Masters of Business Administration LSCM is a bonafide record of the internship work carried out by her/him under my (our) supervision and guidance. The content of the report, in full or parts have not been submitted to any other Institute or University for the award of any other degree or diploma.

Signature of Faculty mentor Mr. Vikas Kumar Assistant Professor (SS)UPES

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Table of ContentPAGE NO

About Varun beverages 8-9Introduction 10-12Background 13

Problem Definition 14-15Scope and Objective 15-16

Limitation of study 16Literature review 16-19

Methodology 20Sampling Method 20

Research Problem 20Business Problem 20

Data Analysis 20Visits 21-32

Learnings and observation 32-36

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About Varun Beverages

Company Varun Beverages Limited

Headquarter Gurgaon, India

Industry Consumer product/ Beverages

Employee 2000

Website www.rjcorp.in

Founded 1995

Company Overview

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Varun Beverages Limited provides bottling and distribution services for beverage manufacturers. The company manufactures and markets carbonated and non-carbonated soft drinks and package drinking water under the Pepsi brand. The company's beverage portfolio also includes 7up, Miranda, and Mountain Dew brands; low calorie drinks such as Diet Pepsi; hydrating and nutritional beverages such as Aquafina drinking water; and juice based drinks such as Tropicana, Slice, and Twister. The company also offers local soda brands. It owns franchisee for Yum Restaurants International including Pizza Hut and KFC. The company was incorporated in 1995 and is based in Gurgaon, India with additional offices in... In all Varun Beverages owns 19 plants including in overseas markets like Sri Lanka, Mozambique, Zambia and Morocco. It had acquired entire franchisee bottling operations in Morocco for an estimated $100 million foraying into the African market in 2011.Early last year, it bought out CK Jaipuria's bottling business in Delhi-NCR. CK Jaipuria is a PepsiCo bottler in Andhra Pradesh. Prior to the acquisition RJ Corp owned a small region of the Delhi market. Varun Beverges is currently held 33.93% by RJ Corp., 33.03% by RK Jaipuria HUF and family and 33.02% by Varun Jaipuria. Recently IFC was proposing to invest $85 in the company to fund its expansion plans. The $1.5 Bn RJ Corp is also present in the coffee shops and quick service restaurant businesses through Devyani International. Devyani is the master franchise in India for Costa Coffee and also the Franchisee for Pizza Hut and KFC outlets. Through Devyani Food Industries, it also manufactures and markets the Cream Bell and Disney branded ice creams. In FY 12, RJ Corp had raised around $80 Mn in two rounds from Standard Chartered PE for purchasing PepsiCo's minority stake in the subsidiary. PepsiCo trails behind its major rival Coca Cola in the country which commands a 56% market share. Post the deal Pepsi will only market and supply the concentrates to the bottling plant. Pepsi owns 10 plant in the country and currently has no plans to exit the South Indian operations. PBG is the largest bottler in the US and is owned by Pepsi. Its other major franchisee’s include Tingyi-Asahi Beverage in China and Brazil-based Ambev, a subsidiary of brewing company Anheuser Busch In Bev responsible for distributing PepsiCo beverages in Brazil and other Latin American countries. Last year PepsiCo had announced an investment of INR330 Bn along with its bottling partners by 2020 to ramp up manufacturing and go-to-market infra.

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Introduction

Effective demand planning doesn’t just happen, it requires work. To move forward, companies have to admit the mistakes of the past, implement continuous improvement programs to drive discipline, and carefully re-implement demand planning technologies.By Lora Cecere

Demand planning is a multi-step operational supply chain management (SCM) process used to create reliable forecasts.  Effective demand planning can guide users to improve the accuracy of revenue forecasts, align inventory levels with peaks and troughs in demand, and enhance profitability for a given channel or product. Estimating future demand is one of the most valuable activities in any organization. The demand plan’s impact is felt throughout the business, from sales and marketing to manufacturing and distribution.  The right plan can balance inventory levels with costs and lead to higher customer service levels and positive cash flow. However, the art and science of forecasting demand is often misunderstood and lacks the attention it requires.In the Aberdeen Group report, “Demand Planning: Renewed Focus for Companies to Drive S&OP and Operational Improvements”, Best-in-Class companies achieved a 20 point

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improvement in forecast accuracy when compared to other companies; translating into a 32% more accurate demand plan. The same report continues stating the same Best-in-Class companies are significantly more likely to invest in advanced technology to help them develop and manage their demand plans.

http://www.supplychain247.com/article/a_practitioners_guide_to_demand_planning

Technology is critical to advancing a company’s supply chain planning maturity. And, understanding how best to take advantage of the technology can transform your business. Working with many of today’s top supply chain organizations, I have realized there are four critical elements that support a company’s growing demand planning maturity. This Report explores how combing statistical demand forecasting methods with judgmental forecasts via a Sales and Operation planning process can improve inventory control through improving inventory replenishment strategies with in Varun beverage Ltd. The implementation of a Sales and Operation Planning process has enabled the company to involve all necessary functions Of the company in the demand forecasting and requirement planning process and in this way Improve the balance of inventory between demand and supply. The implementation of the improved inventory management strategies and Sales and Operation Planning process is described here-in. The constantly evolving process of the Sales and Operation Planning Process. Forecasting is the art of estimating future demand by anticipating what buyers are Likely to do under a given set of future conditions. Very few products or services Lend themselves to easy forecasting. Those that do generally involve a product with Steady sales, or sales growth, in a stable competitive situation. But most markets Do not have stable total and company demand, so good forecasting becomes a key Factor in company success. Poor forecasting can lead to overly large inventories,Costly price markdowns, or lost sales due to items being out of stock. Companies commonly use a three-stage procedure to arrive at a sales Forecast. First they make an environmental forecast, followed by an industry forecast, Followed by a company sales forecast

.

https://www.google.co.in/search?q=life+cycle+demand+planning&espv=2&biw=1366&bih=667&source=lnms&tbm=isch&sa=X&ved=0CAYQ_AUoAWoVChMI4MH3j_m7xwIVDAOOCh1tBgL3

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Complexity of the organization

Keywords: Demand Forecast, Sales Planning, Capacity planning, Inventory Planning, Demand

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Planning, Production Planning.

Background

The ultimate purpose of running a for-profit organization is to maximize the profit for shareholders. In other words, all organizations are trying to increase their revenue and reduce costs at the same time. Excessive production and plant capacity fully not utilized is the largest single investment in assets for most manufacturers. As such, the associated cost of carrying inventory represents a significant portion of the costs of running most businesses reducing inventory levels and therefore cost associated with carrying inventory contributes to increasing profits within an organization. As an important component of the business, inventory serves the organization in achieving economies of scale, balancing demand and supply, as protection against uncertainty, and as a buffer throughout the supply chain. As a result, it is critical to control inventory at appropriate levels in order to pursue the greatest profits for the organization Cycle stock and safety stock account for the major part of inventory. Cycle stock can be controlled by managing order frequency. However, the safety stock level varies significantly depending on a range of differing uncertainties. In reality, the uncertainties associated with demand cause management to consider the trade-offs between inventory carrying costs and stock-out costs. Cycle stock and safety stock account for the major part of inventory. Depending on a range of differing uncertainties. In reality, the uncertainties associated with demand cause management to consider the trade-offs between inventory carrying costs and stock- out costs. Demand forecasts can be improved by different approaches, such as a naive forecast method which forecast demand based upon the historical data. Nowadays, M s e x c e l computer technology automates the calculation process of naive model However, Naive forecasts alone are not enough to determine appropriate Forecast due to the high seasonality characteristics of the beverage industry. It is imperative to improve demand forecast accuracy through the addition of marketing intelligence input. Introduction of a Sales and Operation Planning (S&OP) process provides a good opportunity to communicate between the functions of supply chain, finance, marketing and sales and thereby achieve the optimal demand forecast. PepsiCo is an beverage marketing and Varun beverages is a bottler of PepsiCo who takes care of production and distribution. Mission is to ‘build consumer brand equity and profitability through sustainable growth, differentiation, and consumer participation and employee innovation’. As a distribution company, In terms of its supply chain, Varun beverages utilizes a future demand forecast to determine the level of capacity and inventory and therefore is considered to be an organization with a predominant push supply chain process Company ST reviews its sales

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forecast and performance as compared to its sales target every month. Therefore its inventory level is also reviewed on a monthly basis to ensure product is available to meet projected depletion targets. Cycle stock can be controlled by managing order frequency. However, the safety stock level varies significantly

P ro bl e m Defi n i t io n

Some of the factors that influence demand planning and forecasting

• Seasonality • Market input (Promo)• Weather condition• Types of goods• Level of competition• Price of goods• Economic viewpoint

Seasonality

Seasonality refers to fluctuations in output and sales related to the seasonal of the year. For many (or even most products) there will be seasonal peaks and troughs in production and/or sales. In some cases there will be fluctuations over the week or even within the working day but the time based fluctuation that produces the greatest problem concerns fluctuations related to seasons of the year.

Market Input (promotions)

Sales promotions are marketing strategies companies use chiefly to increase sales temporarily to gain sales volume and market share. They are occasionally used to clear out year-end inventory before new models arrive in showrooms as is often done in the automobile industry. Sales promotions are also used as a competitive strategy to undercut competition by offering a lower price or other incentive. Although sales promotions usually produce sales volume over and above what is typically the case, they do not build brand identity and loyalty.

Weather condition

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Change in weather can impact sales of the beverages industry.

Types of goods

Information regarding the demand, substitutes and level of competition of goods is known only in case of established goods.It is difficult to forecast demand for the new goods. Therefore, forecasting is different for different types of goods.

Competition Level

In a highly competitive market, demand for products also depend on the number of competitors existing in the market. Moreover, in a highly competitive market, there is always a risk of new entrants. In such a case, demand forecasting becomes difficult and challenging.

Price of Goods

The demand forecasts of organizations are highly affected by change in their pricing policies.

Economic Viewpoint

If there is a positive development in an economy, such as globalization and high level of investment, the demand forecasts of organizations would also be positive.

The following will therefore be explored in research.

How can a demand forecast be improved through applying Time series forecasting? What is the relationship between inventory levels and a demand forecasting? How should the optimized inventory levels be determined?

S cop e a n d Obje c ti v es

The purpose of this study is to evaluate methods of learning Demand Planning/Demand forecasting/ Capacity forecasting/ production planning in the beverage industry by improving demand forecast accuracy. The below key areas are concentrated on during this study:

Understanding the factor Involved in Demand planning Inputs required for demand planning.

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Expert opinionHistorical dataSales estimateMarket researchLife Cycle analysis

Study of Annual operation plan. Analysis of final demand plan.

Implementation steps critical to successful use of Sales and Operations Planning within a business. The relationship between inventory level and demand forecast with the use of mathematic tools (MS-excel).

Lim it at i o n o f St u dy

Because the study is based on a specific business model, the outcome of this research has the following limitations:

1. The outcome is limited to observations from a single company in the beverage.2. The time period for the study is very limited two months only.

3. The outcome is only applicable to companies with relatively certain lead times in their supply chains because this study focuses on the uncertainty of demand forecasts only.

Li t e r a t u r e R e v i ew

The following areas of literature are reviewed in this section:

The relationship between Demand planning, demand forecast and demand uncertainty.How to improve demand forecasts through the use of best forecasting method coupled with an S&OP process.

The impact of forecast errors

Forecast errors contain valuable information and must be analyzed carefully for two reasons.

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First, managers can use forecast error analysis to determine whether the current forecasting method is predicting the systematic component of demand accurately. As long as the observed errors are within historical error estimates, companies can continue to use their current forecasting method. Second, all contingency plans must account for forecast error. There is significant research and literature suggesting the negative impact that forecast errors can have on a business. Forecast inaccuracy had severe cost impacts on organizations because forecasts are a major driver for all strategic allocation plans. Research also showed that in many companies, 10% or more of net gross profit is lost because forecast errors cause overages and shortages in inventory an inaccurate forecast causes procurement re-planning that, in turn, creates purchasing, financing and scheduling difficulties. Forecasters must consider how the forecast is to be used to reduce the adverse effects of forecast errors. From an internal perspective, the marketing mix, or 4Ps (price, product, place and promotion), are the primary factors that cause forecast errors. General economic conditions (i.e. unemployment rate, income, etc.) could also cause forecast errors from the external environment.

Combining forecast methods

Some literature also advises on how to measure and minimize forecast errors. Forecast errors can be quantified by a ‘time series method’. Systematically measuring forecast errors could improve forecast accuracy. Forecasters must understand the sources of forecast error to understand why the error occurred. Combining different forecasting models could improve forecast accuracy. First of all, since forecasting errors always exist, combining them has been found to make the net effect smaller. Secondly, unstable or changing patterns or relationships cause single models to be unreliable, but combining several models has been found to improve their accuracy. Lastly, combining models usually minimizes past data errors that were poor predictors of future demand. Improving forecast accuracy by using various forecasting techniques and by using empirical findings to help with formulation of the model. This method is a simulation forecast method, where future demand can be indicated by the historical demand as well as affected by the related environment. In the simulation scenario, a business can combine time series and casual forecasting methods to predict future demand. The systematic component measures the expected value of demand and consists of the following factors. It can be calculated by the following equation.

Equation: Systematic Component = (Level + Trend) x Seasonality

Where:

Level is the current de-seasonalised demand; it represents the demand that would have been observed in the absence of seasonal fluctuations. Trend is the rate of growth or decline in demand for the next period Seasonality is the predictable seasonal fluctuation in demand.

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https://www.google.co.in/search?q=demand+pattern&espv=2&biw=1366&bih=667&source=lnms&tbm=isch&sa=X&ved=0CAYQ_AUoAWoVChMI0r-sgPu7xwIVQ1mOCh0-MAW4#tbm=isch&q=demand+pattern+horizontal+trend+seasonal+cyclic&imgrc=4L5qEaMVRCJsmM%3A

Given the large amount of data involved and the complexity of the demand and supply components in systematic demand forecasting, it is necessary to utilize an information technology (IT) systemfor forecasting. Forecasting software developers havemade significant progress in the area of automation, scalability, and the incorporation of judgment into a forecast. The random component is that part of the forecast that deviates from the systematic part. All a company can predict is the random component’s size and variability based on their marketing intelligence. The knowledge and information that exists internally and externally would, if brought together into a single more accurate forecast, have the support of the entire supply chain.

Improve forecast accuracy by combining time series and causal forecasting methods with judgmental forecast

There is also literature that illustrates that combining just ‘time series forecasts’ and ‘causal forecasts’ is not enough to generate an optimal forecast. Rather, it is more beneficial if these are taken into account with use of a ‘judgmental forecast’ combining models with judgmental inputs gives forecasters the best information on past data patterns. Judgmental forecasts had been shown to improve forecast accuracy because humans may be better able to detect patterns in time series data and integrate outside information. Understanding of ‘how and why’. Judgmental forecasting improved the forecast required a better understanding of the cognitive process involved.

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Improving Demand Forecast Accuracy and Controlling Inventory Through a S&OP Process

S&OP Process Overview

It is critical for the business to choose the proper approach to implement the forecasting method of combing a time series forecast and a causal forecast with a judgmental forecast. A wide array of literature indicates that an Executive Sales & Operation Planning process is the best way of achieving this. S&OP process can benefit business by balancing supply against future demand. Via an S&OP process, the business is able to have visibility of any projected imbalance between demand and supply early enough so that any potential imbalance problems can be identified and eliminated or minimized before they become actual problems .S&OP process can also help organizations reduce forecast errors by aligning supply to demand forecasts. There is an explicit and clear relationship between the quality of an S&OP process and demand forecast accuracy. Holistically, an S&OP process introduces tools such as scenario-based modelling into the decision process so that rapid judgmental decisions can be made.

S&OP ProcessS&OP process can be defined as a five step process of data gathering, demand planning, supply capacity planning, a Pre-Meeting, and the executive meeting. The first step, gathering data, includes three elements: updating the files with data from the month just ended, generating information for sales and marketing teams to use in developing the new forecast, and disseminating this information to the appropriate people. This step is to be completed within a day or two after the end of the previous month. The second step, demand planning, includes an analysis of last month’s variances, the new statistical forecast, field sales input, marketing intelligence, new product plans, promotional plans, planned price changes, competitive activity, industry dynamic, economic conditions, and seasonality. Demand forecasting needs to be finalized by a short meeting of senior level sales and marketing people to get their buy-in, allow them to challenge the new forecast and make any necessary amendments. An unconstrained demand forecast is established in this step. The third step, supply capacity planning, is in order to modify the operation plans for any product families or subfamilies that require it and verify that sufficient capacity exists. The outputs of supply capacity planning include updated operation plans, related capacity planning reports and a list of supply problems. The rough-cut and constrained demand plans are also developed at this step. The fourth step, the Pre-Meeting, generally involves five steps, which include making decisions regarding the balancing of demand and supply, resolving problems and differences by making a single set of recommendations to be presented in the executive S&OP meeting, identifying the areas where agreement cannot be reached, developing scenarios and showing an alternative course of action to solve a given problem, and setting the agenda for the executive S&OP meeting. The key participants of a Pre-Meeting should include personnel from demand planning, product development, operations, representatives from finance, and the owner of the executive S&OP process. Finalising the alignment of the demand and supply plans at this step.

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M e t h o do logy

The research strategy used is classified as a descriptive study. A descriptive study is a study that sets out to describe a phenomenon or event as it exists the aim was to design a study that would help address the research question in the best possible way.

Sampling MethodConvenience sampling method

Research Problem

Research problem is to how much extent factors will affect the demand and how to minimize error rate of forecasting.

Business Problem

How do competitor’s level, Price of goods, Economic view points, and seasonality will affect the demand of product. And how to minimize the forecasting errors to fulfill the demand of market. Complexity matrix keeps on evolving and resolving

Primary data collection: Primary data will be collected through historical data and SAP & observations.

Secondary Data Collection: Secondary data will be collected from old reports and magazines and data provided by Varun Beverages.

Data A n al y s i s

The measurement scale determines what type of descriptive measure should be used. Descriptive measures are particularly useful for comparing the response pattern for different groups or different questions .The mean is the average of the data. It is the most important measure for the data that are symmetric or near symmetric because it utilizes all the information that is available. The standard deviation is the most important of the measures of variability when the mean is used as the measure of center. In other words, the standard deviation is the best measure of variability only for variables with a symmetric or near-symmetric distribution. The standard deviation measures the square root of the average deviation from the mean, using squared distances to emphasise the influence of unusual data

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Same like this forecasting of 2016 is done with respect to 2014 data keeping seasonality and growth as a major factor. As shown in the above picture how forecasting is done of Rajasthan A and Rajasthan B. In the same way Himanchal, Delhi, Chandigarh, Nuh, Haryana forecasting is done In excel spread sheet. Using the same procedure AOP ( Annual operational plan) can be made, Here in the above image only 4 months (jan, feb march, april) data calculation is done.

Now when we have the AOP we can plan the monthly production of different plant. Lets take

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Nuh plant of varun beverage.

Now when we know how much to produce from each plant, we have to calculate capacity of each line of every plant and if the capacity is not fulfilled from plant, then we have to produce the remaining from the nearby plant. Capacity of nuh plant line

Plant NUH

200ml/300ml 600ml 1.25ml 2.00ltPET1 0 24000 32000 32000PET2 0 0 32000 32000Glass 18000 0 0 0

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VISITS

Nuh PlantLocation Nuh

Date 2nd June 2015Time 12pm Departure

Mentor For a day Mr. Rajesh Phogat

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Nuh plant of Varun Beverage’s limited is of 40 acres is one of the newly build and most advance plant of VBL out of 11 plants all over India. Nuh plant was 60km away from VBL head office that is in Gurgaon, total number of fleet that VBL has was 16 (primary) from this they transport to 9 to 10 district.

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Pack is a person who writs order, checking of the credit limit of distributor is done and then Purchasing Order is raised. Purchasing order is generated and the order is shipped.In the peak season time company hires 50 to 60 fleet more these are called secondary vehicles.

Production of products are done in Nuh plant

1. Mountain dew2. Pepsi cola3. Pepsi diet4. Lehar soda5. Miranda orange6. Aquafina water7. Evervess soda8. 7 up

These product are packed in different types

1. BIB2. CAN3. RGP

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4. TETRA

Customer name

1. A.G traders2. Kaya enterprise3. S.t.tradors4. AAA beveges

ETC

PET

PepsiCo was the first and only major consumer packaged goods company to incorporate post-consumer recycled content into its polyethylene terephthalate (PET) plastic, beginning in 2004.Recycled PET comes from plastic that has already been used for packaging, such as plastic bottles. Prior to being transformed into a new plastic bottle, the plastic is sorted and cleaned, in accordance with food safety standards.

ADVANTAGE

PET PROTECTS BEVERAGES AND PREVENTS WASTAGE

PET IS SAFE AND NON-TOXIC

PET saves resources

PET reduces carbon footprint

PET IS FULLY RECYCLABLE

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HOT FILL

CARBONATED DRINK

Carbonating beverages, introducing CO2 into the drink mix under pressure, makes the drink slightly more acidic (carbonic acid), which serves to sharpen the flavor and produces a slight burning sensation.  It also helps preserve the drink longer without going bad.

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RETAINABLE GLASS BOTTLE

In the Nuh plant there was 3 lines of production

Plant NUH

200ml/300ml 600ml 1.25ml 2.00ltPET1 0 24000 32000 32000PET2 0 0 32000 32000Glass 18000 0 0 0

This representation explains Nuh plant has 3 lines of production PET1 can make 600ml, 1.25lt, 2.00lt. For these PET has different capacity as as shown above.

PET2 can make 1.25lt as well 2.00lt with a capacity of 32000. And line 3 can make a 200/300ml with a capacity of 18000.

Understanding the value chain of the soft drink industry

Soft drinks constitute a major part of the Indian food and beverage industry. Syrup or concentrate producers and bottlers (VBL) play a vital role in the value chain of the soft drink industry.Bottling and distribution network

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Companies in the soft drink industry reach the end market in two ways. One way is by selling finished products, made at company-owned bottling facilities, to distributors and retailers.

Another, is by selling beverage concentrates and syrups to authorized bottling partners (VBL), who then make the final product by combining the concentrates with still or carbonated water, sweeteners, and other ingredients. The bottlers then package the product in containers and sell these beverages to distributors or directly to retailers. Also, both bottling partners and companies manufacture fountain syrups and sell them to fountain retailers. Fountain retailers include restaurants and convenience stores, which produce beverages for immediate consumption.

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Different types of distribution/ Mapping of supply chain In nuh plant

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PlanTNUH

CNF

Distributor

Depot Retailor

Retailor

Whole sale market eg-Bigbazzar

Consumer

Consumer

ConsumerRetail Market

Once Tata was one of the biggest vendor of fleet but later problem started coming with their fleet.Now company buy fleet of all companies.

Nuh plant aims at achieving

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1. Zero losses 2. Zero defects3. Zero break down4. Zero accident through total employee involvement5. Self-managing abilities

Running product when we reached

SHIFT AFLAVOR Mountain DewSIZE 1250ml (1.25lt)MRP 55 /-PLANNED QUANTITY (cases) 35000START DATE 25/05/15TIME 8:00am

In this day We finds opportunity to meet –

1. Mr. Danish – Shipping executive2. Mr. Anurag Jain- Plant Head3. Mr. K.K pandey- HR Head4. Mr. Amerik Singh- Commercial head5. Mr. Rajesh Phogat- Transport manager haryana

As per the conversation with Mr. Danish product is kept maximum 3 to 4 days maximum in season time on plant warehouse. Capacity of warehouse is 3 lakh carat.Nuh plant has 3 warehouses these are as follows

PET Trading ItemPET Trading ItemRGB For Retainable glass bottle

Miranda orange and seven up was having the finch demand (Less demand) in the time we visited

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Plant.

Procurement procedure- Buying of new truck

STEP1 Select VendorSTEP2 Financial quotation STEP3 DocumentationSTEP4 Modification of body

If in case demand is from different state plant cannot send directly to other state it has to pass through company owned depot

OPEN body Only to dealerClose body PMX, Fridge, Pepsi machinesRack body Tertiary sale to CNR, DealerParadise Direct loading is done

LEARNINGS AND OBSERVATION’S

WHY DEMAND PLANNING?

Demand planning is a vital part for improving your company’s value chain. It helps you create more accurate demand forecasts that tie together all aspects of your business, from production to sales. It enables your company to do more with less waste. Most importantly, it provides executives with comprehensive and timely information on how the business is actually running and where improvements can be made. A common misperception is that demand planning merely involves forecasting that can easily be done using Excel spreadsheets. This approach usually leads to many problems, such as various divisions using their own product terms and metrics, which in turn forces the planners to spend weeks cross checking the data simply to create a master document. When so much time is spent on just interpreting data, there is very little time left for analyzing the results or making improvements to the plan.

“Because the system knows a promotion was an added-in forecast, it makes sure that it will not repeat in the following year. If you try to do that with a spreadsheet, it can get very messy”. Gregory Miller Litehouse Inc

According to Gregory Miller of Litehouse Inc., “Using Excel you can make linear forecasts, but there aren’t a lot of things that you can do. That’s why a demand planning system is so exciting. It has all kinds of algorithms, looks for patterns and two years of history, as well as seasonality. It reviews forecasting models and picks the best fit. It does that by plotting a model out, looking backwards, comparing the variances between the difference models and selecting the best.” Some may question the resources needed for this upfront investment. A better question is: Can we afford to have inaccurate and incomplete forecasts that result in shortages, overruns, shrinking profit margins, and unhappy customers? A recent study by a leading planning organization found that among medium to large-sized companies, a mere 1 percent improvement in forecasting accuracy led to over a million dollars in savings. For example, a company with annual revenue of $100 million annual sales could realize a $1 million reduction in costs simply by improving its

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forecasting accuracy a negligible amount. Now, imagine the possible savings if invested in the tools and strategies that increase forecasting accuracy a lot. Demand planning real improvements in the company can be made because they have accurate information on how the company is actually operating. For example, they can provide a graphic report that shows the trends over a certain period that helps the chief executives see where funds should be allocated and when, such as increasing marketing spending or decreasing the production of a certain product, even helping determine if a plant should be expanded to increase the profit margin.

DEMAND PLANNING FOR BEVERAGE INDUSTRIES

The food and beverage industries have exceptionally thin margins, which means accurate planning and forecasting are vital to maintaining a competitive advantage. Seasonality is not only relegated to production but supply costs as well, since the commodities market is fluid. These companies are also significantly affected by transportation costs that makes them squeeze every dollar in production costs. In addition to these challenges, food and beverage companies must also factor in when it is best to plan changeovers in their factories. In addition, because life science companies have to take their Demand planners in the beverage industries must contend with new product lines being introduced on a regular basis, as well as certain products being discontinued. Delivering the correct amount of the right product and the right time is critical, perhaps more so than any other industry. They are a made to-order business that needs to predict seasonality, promotions, changes in customer demand, and the switch to different product sizes. For these reasons, the food and beverage industries are ripe for demand planning who can find hidden opportunities and cut costs from the system by enabling manufacturing facilities to produce accurate demand forecasts. They need to be the hub that has visibility into all aspects of the business and provide that information to executives who will use it to make decisions that drive profitability.“Products can’t make any money sitting in a warehouse; they have to be on the floor where they can be bought”. Gregory Miller Litehouse Inc.

Identifying Stakeholders

Too often companies have a silo approach when it comes to demand planning. Demand planning , however, know that to achieve results the process must be truly integrated across the company. In order to create an accurate and dynamic forecast, the right participants from different areas of the company must be included. The first step is to identify these stakeholders. The stakeholders are groups that are loosely tied together, including virtually any group with an interest in the annual budgeting process. They can range from executive management, the finance team, schedulers and planners, marketing, and the sales team. All of them have different input roles and expectations from the forecasting process. These stakeholders are also interested in the annual and/or monthly forecasts, depending on their role in the company. The most common stakeholders in a demand planning process include: a. Sales team leaders (e.g., the V.P. of Sales and various regional team

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leaders) who provide information from sales pipelines b. Operations and manufacturing team leaders who provide the link to the company’s operating targets and product sourcing c. Marketing team leaders who provide information on upcoming promotions and changing market dynamics d. Finance executives who maintain the linkage of planning and operations to the financial objectives and constraints of the company e. Major Customers. Do not underestimate the impact your top customers have. Working closely with them has benefits for company and customers. Each stakeholder should own their part of the planning performance and be able to easily understand the forecast measurements. A senior executive does not have the time to sort through pages of data before making a decision. For example, sales people are concerned with their customers and will often not implement a process that is too cumbersome. By getting buy-in and agreement in the planning stages, you are more likely to achieve the results you expect.

Creating Measurement Criteria

The saying “That which gets measured gets improved” is an easy way to underscore the importance of measurement. A good forecast measurement process should help find exceptions quickly, determine the accuracy of the forecast, and provide insight in how to deal with variables. You will need to determine with the stakeholders what measurements should be included in the forecast and where those metrics should be tracked, such as: • At the customer forecast level, and/or Item forecast level, and/or product family level, etc. • Exception conditions and alerts • The sensitivity of the measurements based on contribution stratification • The frequency. These measurements are unique to each company. The days of simply reviewing the actual vs. the forecasted once a year are long gone. Different stakeholders may review accuracy at different intervals; however, a demand planner will usually review the forecast accuracy weekly or monthly to ensure everything is going according to plan. To summarize 1. Identify the business units, teams, and individuals who will have input into the process (e.g., V.P. of sales and marketing, regional sales teams, etc.) 2. Determine their individual roles in the process and interests, such as monthly and/or annual forecasts, overall company forecast or rolled-down divisional forecasts, etc. 3. Develop a measurement criteria 4. Present the data in a variety of different ways to help various stakeholders better understand the data as well as a crosscheck to make sure everything is going according to plan or if adjustments must be made.

“Aptean’s Ross ERP’s Demand Planning Module presents data in a variety of ways to help users visualize customer demand “

OBTAINING DATA FOR ACCURATE FORECASTING

Integrate sales, marketing, operations, and financial targets in the demand planning process integrating the sales data with the demand plan they will get more accurate data in an ongoing manner

Step’s when dealing with data:

Link the data from the ERP system to the demand planning process

Use a good software tool to gather, analyze, and distribute data

Implement a process that coordinates planning and decision making across the company.

Develop a strategy that links day-to-day operations to the overall company goals

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Linking Data from the ERP System

Data, with rare exception, is almost always obtained from the ERP system. While it is possible to implement the demand planning system prior to integrating it to the ERP system, most demand planners have found it is much easier and less time-consuming to integrate the demand planning system with the ERP system prior to implementing it. An example of the ERP integration process includes mapping from the ERP system(s) that involves all the components of the demand planning pyramid.

Essential Data • Master data (products, customers, etc.) • Customer order history • Shipment and back order history • Historical promotions • Current open customer orders Integrating the essential data with Ross ERP’s Demand Planning Module has been easily and successfully done in many companies.

Finding a Good Software Program

Once the data is extracted from the ERP system, the next step is to determine how to manipulate this enormous amount of data. Without tying each company or division’s processes with the overall demand planning process, annual forecasting is tedious and less accurate. Companies stuck in the tactical rut almost always rely on clunky Excel spreadsheets and fail to benefit from advanced software based on statistical forecasting models. Whether you are a multinational company that deals with the same product being given different names in different languages or a smaller company that gets input from different business units that use different formats, trying to do efficient and accurate planning using Excel makes forecasting an extremely difficult and time-consuming process.. The scalability of a good demand planning system simplifies the process. Companies must also make sure their demand planning software has the capabilities to allow data to be input in local currencies, and then converted to a standard currency depending on the company’s need (US Dollar, Euro, etc.).data from the sales pipeline is incorporated into the demand planning process through the right software to increase the accuracy of the data. By creating a spirit of integrated team work and choosing the right tools that deliver detailed information, they can help the chief executives make the decisions that really count. A subpar software tool will not provide the detailed, customer-level and product-level data that both sales and manufacturing need in order to better forecast sales and production levels. Without this knowledge, they cannot determine the best course for how to squeeze more out of every dollar and make the adjustments they need to achieve the company’s overall goals. If you have the right tools and the right data, you are only two-thirds of the way to your goal. To make it to star status, company need to turn that information into action. Action that shows where to cut costs, increase top line revenue, and how to maximize profitability.A good demanding planning tool provides the ability to present information to the various stakeholders, which motivates them to take action.

Bullwhip effect.

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CentralizedM0- Current month- FixedM1-Next month-Rolling

On the 25 day of month (M0) demand planner ask for the forecasted data from sales, M1 that is the next month production is planned according to it, data is compiled by a demand planner and send it to HOS ( head office sales)/ MUGM and COO. And should be told that sales has forecasted this data and according to our forecast it seems like this. Suggestion is asked from them. As soon as the suggestion and feedback is received M1 that is next month final forecasting is done. It is further divided in plant wise and. Production is planned plant wise.

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