2nd Scm Final

1. SAINT GOBAIN

1.1 CONCEPTION & HISTORY

Saint-Gobain is a French multinational corporation, founded in 1665 in Paris and

headquartered on the outskirts of Paris at La Défense. Originally a mirror manufacturer,

it now also produces a variety of construction and highperformance materials. Saint-

Gobain was created as part of the plan devised by Louis XIV and Colbert to restore the

French economy. Entrusted to private entrepreneurs,

the company broke with the factory tradition by organizing glass production on an

industrial basis. Thanks to the invention of glassware casting (1688), Saint-Gobain

established a near-monopoly in 17th-century Europe and ousted Venice, which was

then the leader in this sector. With the first half of the 20th century, came the

diversification of glass applications (glass wool, glass fiber, hollow glass). In 1970, Saint-

Gobain's merger with Pont-à-Mousson, the world leader in cast iron piping, gave birth

to a producer of materials and capital goods geared to the global dimension of its

markets. Since 1997, the group focuses on business sectors in which it holds strong

positions and the assets necessary for growth. The acquisition of Poliet in 1996

completed its expertise in distribution.

Saint-Gobain has also been established for many years in North and South America. In

1831, it opened its first glass sales depot in New York. In 1920, Saint-Gobain invested in

several cast glass companies in order to build up its industrial position in the United

States. After developing the TEL glass wool production process, Saint-Gobain signed its

first agreements with CertainTeed

in 1967. Following the acquisition of Norton in 1990, Saint-Gobain acquired Ball Foster

Glass in 1995.

The Saint-Gobain Group will now have completed a decade of far-reaching changes in

both business sectors and structure. The Group has focused its efforts on core business

lines which are less cyclical or less exposed to the economic fluctuations. It has

strengthened its technology and marketing skills, putting a greater emphasis on

distributing to end customers. And it has also stepped up its international expansion.

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1.2 STRATEGY

The Group has in recent years implemented the strategy for steady and profitable

growth to:

develop genuine leadership in all if its businesses

enhance its technological and sales capacities

reduce its exposure to cyclical changes and market fluctuations

increase profitability and free cash flow.

The Group intends to focus its strategy on:

prioritizing development of construction and housing related businesses, in

particular through bolt-on acquisitions in Building distribution and Construction

Products sectors

pushing ahead with R&D and innovation initiatives, particularly in High-

performance Materials and Flat Glass sectors

stepping up expansion efforts in emerging countries for all businesses.

1.3 2008 OUTLOOK & TARGETS

In 2008, the Group will have to contend with a more difficult and far more uncertain

macro-economic climate than in 2007, with a possible recession for the US economy

and growth in housing starts across Europe losing momentum due chiefly to stricter

lending criteria. However, Saint-Gobain is well positioned to face these challenging

business conditions:

a strong position on the European building renovation market,

global leadership on markets related to energy efficiency in buildings, which

account for almost 30% of Group sales,

significant contributions from Asia and emerging countries to Group operating

income (around 20%, i.e. double the North American contribution in 2007),

the positive impact on the Group’s results of further acquisitions,

a solid financial structure and high levels of free cash flow.

In view of the above, for 2008 the Group is targeting:

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modest growth in operating income at constant exchange rates (average

exchange rates for 2007) and recurring net income,

a solid financial structure and continuing high levels of free cash flow.

1.4 BUSINESS UNITS

The company is built around five business sectors: Building Distribution, Construction

Products, Flat Glass, Containers / Packaging and High-Performance Materials.

1.4.1 Building Distribution

Since its creation in 1996, the Building Distribution Sector has experienced rapid

expansion through internal growth and acquisitions, first in France with Point P. and

Lapeyre; then in the UK with Jewson and Graham; followed by Germany, the

Netherlands and Eastern Europe with Raab Karcher; and finally in the Nordic Countries

with Dahl, the leading bathroom, kitchen and heating products distributor and

Optimera. With almost 4,000 stores in 24 countries, the Building Distribution Sector is

the leading building materials and kitchen, bathroom, heating and plumbing supplies

distributor in Europe, and the leading ceramic tile distributor in the World.

A Few Facts

2006 Sales: 17.6 billion Euros

Global Workforce: 63,000

Subsidiaries

SGBD UK

Raab Karcher

Point P.

Lapeyre

Dahl

Norandex Distribution

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1.4.2 Construction Products

The Construction Products business unit provides the following products: acoustic and

thermal insulation, façade coatings, roofing, interior and exterior products and pipes.

1.4.3 Flat Glass

Active in 39 countries, the Flat Glass business unit is targeting so-called"emerging"

countries for expansion, a market that now accounts for more than one third of its sales.

Products include self-cleaning, electrochromic, lowemissivity and sun-shielding glass.Flat

Glass is currently building a plant to produce photovoltaic cells jointly with Shell, and is

developing a pilot factory for the production of electronic glass in Spain.

A Few Facts



Businesses

Production of flat glass

Manufacturing, transformation and distribution of glass for construction,housing

and interior decoration

Manufacturing, transformation and distribution of glass for the automotive –

OEM and after-market – and transportation industries

Specialty glass: household appliances, electronics, photovoltaic applications

1.4.4 High Performance Materials

The High Performance Materials business unit has research centers in Cavaillon

(France), Northboro, MA (United States), and now Shanghai (China). The fuel cell and

the particle filter are two current projects of the research centers. New sources of

growth are appearing in areas like energy, the environment, and medicine. Overall, the

HPM sector's sales are usually made up of at least 30% new products.

A Few Facts


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Businesses

Ceramics

Grains and Powders

Crystals

Plastics

Abrasives

Textile Solutions

Composites

1.4.5 Packaging

With a workforce of 20,000 worldwide, the Packaging business unit focuses on glass

packaging for the food and beverage industry.

A Few Facts



Businesses

Glass bottles and jars

The breakdown of total sales for the group as per 2006 figures is depictedbelow.

BREAKDOWN OF SALES PER SECTOR IN 2006

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2. SAINT GOBAIN INDIA

Saint-Gobain established its presence in India by acquiring a majority stake in Grindwell

Norton in 1996, and thereafter went on to consolidate and strengthen its presence

within the country. The Group has adopted a systematic focus in launching its individual

businesses in India and currently operates in three business sectors: Flat Glass, High

Performance Materials and Construction Products.

Within these sectors, a variety of products are manufactured by eight different

companies:

2.1 FLAT GLASS

2.1.1 Saint-Gobain Glass India Ltd. (SGGI)

SGGI manufactures and markets float glass and mirrors from its plant near Chennai, and

2.1.2 Saint-Gobain Sekurit India Ltd. (SGSI)

SGSI offers a range of automotive glass products.

2.2 HIGH PERFORMANCE MATERIALS

2.2.1 Grindwell Norton Ltd. (GNO)

GNO manufactures and markets abrasives, silicon carbide, high performance

refractories and performance plastics from its four manufacturing locations.

2.2.2 Saint-Gobain Crystals & Detectors India Ltd. (SGCD)

SGCD manufactures and markets radiation detection and measurement products.

2.2.3 SEPR Refractories India Ltd. (SEPR)

SEPR manufactures and markets electrofused refractories.

2.3 CONSTRUCTION PRODUCTS

2.3.1 Saint-Gobain Weber India Ltd. (SGWI)6

SGWI offers facade and tiling solutions and technical mortars

2.3.2 Saint-Gobain SEVA Engineering India Ltd. (SGSEIL)

SGSEIL manufactures top rolls, tempering furnaces and toolings for the automotive

sector, moulds for containers and some building hardware products.

2.3.3 India Gypsum

India Gypsum manufactures an extensive range of Gypsum boards and plasters systems

and solutions for partitions, wall panels, ceilings and internal wall linings.

In order to further its business growth in the Indian sub-continent, Saint- Gobain also

established the General Delegation for India, Sri Lanka and Bangladesh in 1996. The

Delegation facilitates the establishment of new businesses in India, ensures synergy and

co-ordination between the businesses and companies in India.

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3. GRINDWELL NORTON LIMITED

Founded in the year 1941, Grindwell Abrasives, as Grindwell Norton was then known,

pioneered the manufacture of grinding wheels in India at its plant located in a small

fishing village near Mumbai. Grindwell Norton Ltd. (GNO) came into being when a

technical collaboration in 1967 between Grindwell and the then world leader in

abrasives – Norton Company, USA, grew into a financial collaboration in 1971. In 1990,

Saint-Gobain acquired Norton Company, USA, worldwide, and six years later, GNO

became the first majority-owned subsidiary of Saint-Gobain in India.

Today, GNO is India’s leading manufacturer of Abrasives (Bonded, Coated, Non-Woven,

Superabrasives and Thin Wheels) and Silicon Carbide. It also manufactures and markets

High Performance Refractories and Performance Plastics products. GNO’s Project

Engineering Group (PEG), with its portfolio of diverse projects, is a proven engineering

resource for Saint-Gobain companies in India and internationally. Headquartered in

Mumbai, GNO has four manufacturing locations (Mumbai, Nagpur, Bangalore and

Tirupati) and 12 sales offices across the country. This broadly sums up the extensive

reach of GNO. In October 2006, GNO had the honour of featuring in Forbes Asia’s “Best

Under a Billion” list. It was one of only 23 Indian companies listed among the top 200

companies, with sales of under a billion dollars, in the Asia-Pacific Region.

GNO remains committed to the pursuit of becoming a world-class company with world-

class products and processes. It strongly emphasises cutting-edge technology, restless

innovation, customer service and operational freedom. With the distinct advantage of

being a part of the Saint-Gobain and Norton family, GNO has access to the best of

products and technology, enabling it to provide tomorrow’s products to customers

today.

3.1 PRODUCTS & SERVICES

3.1.1 Abrasives

In 1941, Grindwell made the first grinding wheel in India. It has since been offering the

best abrasive technology to Indian Industry. In the abrasives segment, Grindwell offers a

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full product range in Bonded Abrasives, Coated Abrasives and Non-woven abrasives

including grinding wheels, abrasive discs and handpads.

3.1.2 Ceramics

Ceramics, the material of the future has a wide range of industrial applications ranging

from high temperature refractories, wear parts, fused cast ceramics to filters for

chemical plants and much more. The Ceramics business of GNO is divided into HPR and

SiC.

The High Performance Refractories (HPR) division of Grindwell Norton offers complete

solutions, through it’s expertise in design engineering and manufacturing refractory

systems for high temperature and wear applications.

Silicon Carbide (SiC) is a synthetic material most commonly produced by the so-called

Acheson process in electrical resistance furnaces. SiC does not occur naturally – except

in some types of pre-solar meteorites, along with diamonds! SiC can be produced either

black or green, depending on the raw materials. The GNO SiC product range includes:

SiC MET: Products for Metallurgical Applications

SiC REF: Products for Refractory Applications

SiC ABR: Products for Abrasives Applications

SiC WS: Products for SlurryWire Sawing

SiC TECH: Products for Technical Ceramics

3.1.3 Performance Plastics

Saint-Gobain’s Performance Plastics division is a recognised authority in advanced

polymer technology. It produces and markets more than 800 standard and custom

polymer products through three businesses: Engineered Components, Fluid Systems and

Composites. Each demonstrates innovation, responsiveness to customer needs and

polymer expertise.

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Engineered Components uses advanced technology to create narrow tolerance products

such as bearings, seals used in the automotive, aerospace and chemical industries. Its

products include seals, polymer products, and bearings.

Fluid Systems produces silicone and thermoplastic tubes and hoses, connectors, process

vessels etc. for critical fluid handing in demanding applications - pharmaceutical,

medical, food, beverage and laboratories.

Composites business products include specialty films, composite foams and coated

fabrics.

3.1.4 Project Engineering Group

The Project Engineering Group (PEG) is a division of Grindwell Norton Ltd. established in

the early seventies. It was primarily established for setting up Grindwell Norton's plants

and equipment in-house. PEG has come a long way and has several achievements to its

credit. Over the years, it has set up large scale complex projects for Grindwell Norton

and for other Saint-Gobain group companies in India and abroad. PEG has two sub-

divisions – Projects & Building Products & Solutions.

Projects Today, PEG resources are available from concept to commissioning, be it a

green-field venture or design and manufacture of special purpose machines. PEG

provides services in the field of Design & Engineering, Planning, Project Management,

Environmental Management / Consultancy / Total Solutions, Construction and

Supervision, Erection and Commissioning.

Along with design and development, the planning and management of the entire

project is carried out through meticulous detailing and documentary back up, inclusive

of budgets and time schedules. Specialized Project Management Software is utilized for

the timely and economical execution of the Projects. With a wealth of experience and

expertise, PEG ensures the completion of projects to specifications, within budget and

as per schedule.

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PEG is headquartered at Bangalore, within the Grindwell Norton campus and is

equipped with modern infrastructure for design and engineering and a Design center

with advanced software.

Building Products & Solutions The PEG actively markets Building Hardware in the Indian

sub-continent, through the Building Products and Solutions (BPS) business group. This

sub-division of PEG offers a wide range of products to customers with reliable techno-

economic solutions, thus ensuring an array of repeat customers. The present range of

products is listed in the BPS section, and the major strategy for this business focuses on

expansion of the product range with synergistic products.

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4. THE PROJECT

4.1 PROJECT

Forecasting and Reordering Model for source products for Coated Abrasives Business

4.2 PROJECT INTRODUCTION

Grindwell Norton Limited manufactures and markets abrasives, silicon carbide, high

performance refractories and performance plastics from its four marketing locations.

However many of GNO’s products are sourced from other Grindwell Norton locations

outside India. In sourcing these materials from abroad, GNO incurs many costs such as

Purchasing Cost, Transportation Cost, Storage Cost, Interest on Held Capital, Ordering

Cost.

Since these materials have a growing market in India, the company can’t afford a stock-

out. At the same time, over-ordering and storage of the materials with its associated

costs will make the business unviable.

This project therefore aims at developing a sales forecasting model for the highest value

sourced Stock Keeping Units (SKUs) of the coated abrasives business of GNO, and

thereafter devise a reordering model so as to minimise ordering and storage costs.

4.3 PROJECT OBJECTIVES

Developing a sales forecasting model for each of these SKUs depending on the

sales pattern shown in the past taking care of the trend, business cycle and

seasonal effects.

Projecting the future sales for each identified SKU for next two years.

Recommending the reordering point alongwith the safety stock for each SKU as

per the required service level.

4.4 PROJECT PROGRESS

4.4.1 Development of Sales Forecasting Model

Forecasting is the process of estimation of unknown situations. Forecasting is required

because of the time lag between awareness of an impending event or need and

occurrence of that event. Now since each area of an organisation is related to others, a 12

good or bad forecast can affect the entire organisation. Some areas, in which forecasting

plays an important role are production planning, scheduling and resource acquisition.

In this specific case, GNO sources some of its products from overseas, and therefore the

lead time is quite high. Since overstocking will lead to holding up of capital, and

understocking will cause business opportunity loss, maintaining the correct inventory

for these items is important for GNO. Herein forecasting steps in, and tries to give a fair

estimate of future demand of these items to the manager so that their purchasing can

be planned accordingly.

4.4.1.1 Selecting a Forecasting Method

Forecasting is mainly done relying on the information of past sales data. In this case,

with the time series of sales figures obtained in the previous exercise, analysis will be

done to develop individual forecasting models. For developing such models, various

methods are used. Some of the questions that must be considered before deciding on

the most appropriate forecasting technique for a particular problem are the following:

What are the characteristics of the available data?

What time period is to be forecast?

What are the minimum data requirements?

How much accuracy is desired?

A general idea can be had from the following table about the capabilities of different

forecasting techniques, and their applicability.

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Data Pattern: ST, stationary; T, trended; S, seasonal; C, cyclicalTime Horizon: S, short term; I, intermediate; L, long termType of Model: TS, time series; C, casualSeasonal: L, length of seasonality

T a b l e 1 : C ha r a c t e r i s t i cs o f v a r i ou s F o r e c a s t i n g M e t hods

As can be observed from the figure, the sales pattern is trended upwards with strong

seasonal variations. For example, there is a definite upward spike in the month of

November, and sales are particularly down in the month of January.

Similar analysis was done for all the 17 selected items, and they all tended to show a

trend, and seasonal variations. Taking this into account, the Winter’s Exponential

Smoothing Method was used for projecting future sales. Here, even Box-Jenkins

Method could have been used but Winter’s Method was chosen above it because of

the following reasons:

Box-Jenkins Method is suitable for forecasting for short smaller time horizons,

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MethodData

PatternTime

HorizonType ofModel

Minimum DataRequirements

Non- seasonal

Season al

Naïve ST, T, S S TS 1Simple Averages ST S TS 30Moving Averages ST S TS 4-20ExponentialSmoothing

ST S TS 2

Linear ExponentialSmoothing

T S TS 3

Quadratic Exponential Smoothing

T S TS 4

Winter’s ExponentialSmoothing

T, S S, I TS 2 x L

Simple Regression T I C 10Multiple Regression C, S I C 10ClassicalDecomposition

S S TS 5 x L

Box Jenkins ST, T, C, S S TS 24 3 x L

while Winter’s Method can be used for medium term forecasts also, which was the

requirement.

Box-Jenkins Method is considered to be more accurate than Winter’s Method

of forecasting, but it is not adaptive, and a new model has to be developed after each

time period.

The time consumed in developing a model by Box-Jenkins Method is very time

consuming, and since in its case, the model is required to be built every time-period,

the overall investment is quite high.

Winter’s Method can be easily programmed into a computer program for

automatic model building, while it is not possible to do it in Box- Jenkins Method

since it requires human judgement.

The accuracy required for the job can be easily achieved by Winter’s Method,

which makes it imprudent to make substantial investment in developing models by Box-

Jenkins Method.

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4 . 4 . 1 .2 W i n t e r ’s M e t hod

Winter’s Forecasting Method is actually an improvement over the Exponential

Smoothening Method of Forecasting so that it takes care of the Seasonal & Trend

components. One of the main advantages of the method is that it is adaptive, implying

that the model developed tends to improve itself with each data point added into

the data base. So, it with time the estimated components of level, trend, and

seasonality change, the model detects that and modifies itself accordingly.

The Winter’s Model assumes the following pattern:

S yst e m a t i c C o m ponen t o f D e m an d = ( Le v e l + Tr e n d ) x S ea s on a l F a c t o r

To begin, the model needs estimates of level (L0), trend (T0) and seasonal factors

(S1, S2, …..Sp), where p is the periodicity of demand. These initial estimates are

obtained using regression techniques on the initial data-figures of sales. Then, further

data-figures are employed to refine these initial estimates.

In period t, given estimates of level Lt, trend Tt, and seasonal factors St,

…..St+p-1, the forecast for future periods is given by:

Ft+1 = (Lt + Tt) St+1 and Ft+l = (Lt + l.Tt)

St+l

On observing the demand for period t+1 (Dt+1)we revise the estimates for

level, trend and seasonal factors as follows:

Lt+1 = α (Dt+1/St+1) + (1- α) (Lt +

Tt) Tt+1 = β (Lt+1 – Lt) + (1 – β) Tt

St+p-1 = γ (Dt+1/Lt+1) + (1 – γ)

St+116

Where α is the smoothing constant for the level, 0 < α < 1; β is the smoothing

constant for the trend, 0 < β < 1; and γ is the smoothing constant for seasonal factor, 0

< γ < 1. These smoothing constants determine the rate at which the estimates of level,

trend and seasonality are updated by the model. For determining suitable values of

these constants, hit-and-trial method is used, wherein several combinations of

smoothing constant values are tried on the past sales data to observe the forecasting

error. Thereafter the combination of values of these constants, which minimises the

forecasting error is used for actual estimation of future sales.

4 .4 .1 .3 Mode l De vel op ment

Using the Winter’s Method explained above, a model was developed for each of the

selected items using their past sales data. The individual models for each of these

items are shown hereunder in tables 3 to 19.

Calculated Figures

Level 12594.44Trend Factor 158.93

Seasonal Factors

Month 1 1.58Month 2 1.13Month 3 2.33Month 4 1.57Month 5 1.35Month 6 1.94Month 7 2.25Month 8 1.11Month 9 1.31Month 10 0.76Month 11 1.28Month 12 1.99

Adjustment Factor Alpha 0.0000Adjustment Factor Beta 0.0000Adjustment Factor Gamma 0.3000

T a bl e 2 : F o re ca sti ng Mod el fo r ANS57

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Calculated Figures


Seasonal Factors



T a b l e 3 : F o r e c a s t i ng M od e l f o r A N S 60

Calculated Figures


Month 1 0.53Month 2 0.09Month 3 0.37Month 4 2.06Month 5 1.09Month 6 0.51Month 7 1.43Month 8 0.56

18

Seasonal Factors

Month 9 0.08Month 10 0.49Month 11 0.83Month 12 0.97


T a bl e 4 : F o re ca sti ng Mod el fo r AOP23

19

Calculated Figures


Seasonal Factors




Calculated Figures


Seasonal Factors



T a b l e 6 : F o r e c a s t i ng M od e l f o r A O P 26 20

Calculated Figures


Seasonal Factors




T a b l e 8 : F o r e c a s t i ng M od e l f o r A O P 28

21

Calculated Figures


Seasonal Factors



Calculated Figures


Seasonal Factors



T a bl e 1 0: F or e ca sti n g Mode l fo r AOP29

Calculated Figures


Seasonal Factors



T a b l e 1 1 : F o r e c a s t i n g M ode l f o r A O P 30

22

Calculated Figures


Seasonal Factors




Calculated Figures


Seasonal Factors




23

Calculated Figures


Seasonal Factors




24

Calculated Figures


Seasonal Factors




25

Calculated Figures


Seasonal Factors




Calculated Figures


Seasonal Factors




26

Calculated Figures


Seasonal Factors




4.4.2 P ro j e c t i n g F ut u re S a l es

Using the sales forecasting models developed for each SKU, their respective future sales for

next two years were projected. These figures feature in the “Forecasted Figures” part of the

“Input & Output Sheet” for each item as shown in Appendix 1. Also, a table showing

consolidated projected sales figures is given in the appendix.

4.4. 3 R ecomm en di ng R e or der P oi n t & O rd er Qua nti ty

4 . 4 . 3 .1 R eo r de r P o i nt

The reorder point for replenishment of stock occurs when the level of inventory drops

down to zero. In view of instantaneous replenishment of stock the level of inventory jumps to

the original level from zero level. But in real life situations one never encounters a zero lead-

time. There is always a time lag from the date of placing an order for material and the date on

which materials are received. As a result the reorder level is always at a level higher than

zero, and if the firm places the order when the inventory reaches the reorder point, the new

goods will arrive before the firm runs out of goods to sell. The decision on how much stock to

hold is generally referred to as the order point problem, that is, how low should the inventory 27

be depleted before it is reordered.

The two factors that determine the appropriate order point are the procurement or

delivery time stock which is the Inventory needed during the lead time (i.e., the difference

between the order date and the receipt of the inventory ordered) and the safety stock

which is the minimum level of inventory that is held as a protection against shortages.

T he r e f o r e R eo r d e r P o i n t = N o r m a l c o n s u m p t i o n d u r i n g l e ad - t i m e + S a f e ty S t o ck .

Several factors determine how much delivery time stock and safety stock should be held. In

summary, the efficiency of a replenishment system affects how much delivery time is needed.

Since the delivery time stock is the expected inventory usage between ordering and receiving

inventory, efficient replenishment of inventory would reduce the need for delivery time stock.

And the determination of level of safety stock involves a basic trade-off between the risk of

stock-out, resulting in possible customer dissatisfaction and lost sales, and the increased costs

associated with carrying additional inventory.

Normal consumption during lead time is calculated as

D0 x L0

where D0 is average demand per period during lead time, and

L0 is average lead time

And Safety Stock is calculated is

2 2 2 ½

F.(L0.σD + D0 .σL )

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where F is a factor pertaining to the service level required

σD is standard deviation of demand per period, and

σL is standard deviation of lead time

For the project, the service level considered was 95%, therefore the value of F used is 1.96.

4.4.3.2 Order Quantity

Order Quantity is an important variable in Inventory Management. This is because a lot of

cost drivers are dependent on the order quantity.

o the more the order quantity, the more the capital held up in inventory

o the more the order quantity, the more storage space required

o the more the order quantity, the more chances of pilferage and obsolescence

o the more the order quantity, the more discounts available

o the more the order quantity, the less follow-up required

o the more the order quantity, the less the over-all transportation cost, and so

on.

In general, with increase in the order quantity, total holding cost for inventory increases and

total ordering cost for inventory decreases. Therefore, one needs to strike a balance

between the holding cost and the ordering cost by changing the order quantity so as to

minimise total cost.

Generally, in cases where the lead time is not very high, firms calculate the Economic Order

Quantity (EOQ) for the items and order them accordingly. EOQ is that level of inventory that

minimizes the total of inventory holding cost and ordering cost, and is calculated as:

EOQ = (2.R.CO/CH) ½

WhereR is the total item demand for the year

CO is the ordering cost (fixed cost associated with processing each order)

CH is the holding cost per piece of item per year.

In other cases, where the lead time is quite high, sometimes the EOQ is not even able to

take care of the product demand in the lead time for the next order. In these cases, the

order quantity is taken to be same as the product demand in the lead time.

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4.4.3.2.1 Ordering Cost

The ordering cost includes all incremental costs associated with placing or receiving an extra

order that are incurred regardless of the size of the order. For the project, the Ordering Cost

was calculated taking care of the following components.

Buyer Time

Transportation Costs

Receiving Costs

Fee, tax and other applicable charges

The ordering cost was finally calculated as INR 1550 for sea transported consignment and

INR 550 for air transported consignment.

4.4.3.2.2 Holding Cost

Holding Cost is estimated as a percentage of the cost of a particular product and is the sum

of the following components.

Cost of capital

Obsolescence Cost

Handling Cost

Occupancy Cost

The handling cost of the items in the project was calculated as 13% of item cost.

4.4 . 3. 3 C a l c u l at i o n o f R e or d e r P o i n t ( R O P ) a n d O r d e r Q u a nt i ty

For ready calculation of ROP and order quantity, an excel model was developed, which

calculated both the figures given some required inputs. The features of the Excel Model

are:

The model integrated with the sales forecasting model, making things easier.

The model provides updated results every time the sales history is updated

with recent data.

The model not only suggests the ROP and order quantity, but also

recommends the mode of order transport that would be economical taking

care of the capital costs and product demand.

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Since the foreign exchange rates and even prices of the items keep varying frequently,

no fixed values for the ROP and order quantity were provided. It was recommended

that inventory level of the items be regularly kept track of, and ROP and order

quantity be calculated each time an order is to be placed.

The model however, is depicted in Appendix 2 (with hypothetical figures).

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5. INPUTS & SOURCES OF INFORMATION

For progress of the project, data and information was obtained from various parts of the

organisation. The sources of all required information are given hereunder.

5.1 SALES FIGURES

The month-wise sales figures for each SKU was sought from the marketing department. The

department uses a central software database that keeps tracks of the sales figures of all

SKUs.

5.2 LEAD TIMES

For the purpose of calculating safety stock and reordering point, the lead times for each

were required. Information regarding sources of individual items, alternative modes of

transportation, and standard deviation in lead times of each item was required. All this data

was provided by the Customer Service Department which is responsible for tracking the

inventory levels and ordering items as and when required.

Complete history of past orders placed, along with order date and date of arrival was

provided by the department, which was then used to calculate the required figures. Other

modes of information gathering, like interviews were also made use of for getting a clearer

picture.

5.3 HOLDING COST

The holding cost for items contains many different components as discussed earlier.

o the main component of holding cost was discovered to be the Capital Cost,

standing at 12.9%. The data regarding the WACC for the company was

collected from the Finance Department.

o since the products have no practical expiry, that part required no care.

o In as much as GNO has a large storage space with no incremental cost for

individual items, no addition in holding cost is made.

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o handling costs per item were calculated, and they contributed little to the

overall holding cost.

Finally the value of CH was set to 13% of item cost.

5.4 ORDERING COST

Ordering Cost again is an aggregate of various costs. These individual cost data was

collected from various sources.

the main component of the ordering was discovered to be the per order fee

paid to the Consignment Clearing Agents employed. The agents charge a

fixed sum of INR 5000 for clearing of sea transport consignments and INR

1000 for clearing of air transport consignments.

other major component of the ordering cost is a fixed fee paid to the

customs department for warehousing of consignments

finally the contribution of buyer’s time was added in the ordering cost to get

the final figure

All this time, information was sought from various departments including Accounts

Department, Stores Department etc.

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6. CONCLUSION

Inventory Management is an important aspect of any business involving manufacturing &

marketing because of the sheer magnitude of its impact, may it be positive or negative.

Recently, some businesses have based their business strategy itself on better management

of inventory.

Sales forecasting is an important of inventory management. It gives the management an

overview of the things to come in the future, and therefore readies them for eventualities –

including inventory management.

In the project, improvement in inventory management system of the company has been

endeavoured through future sales projections, and then calculating the Reorder Point and

Order Quantity for many items.

From the project, finally the following outcomes have been found:

A generic Excel® program for forecasting of sales (for any item) based on past sales

data

Calculated values of sales forecasts for selected items in a consolidated table

A generic Excel® program for finding the ROP and order quantity (for any item)

based on sales forecasts generated by the program described in (ii).

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7. REFERENCES

Box, E.P. and Jenkins, G.M. (1976), Time Series Analysis: forecasting & control,

Holden-Day Inc., San Francisco

Hanke, J.E. and Reitch, A.G. (1981), Business Forecasting, Allyn & Bacon, London

Spyros M.; Wheelright S.C. and Hyndman R.J. (1998), Forecasting: methods and

applications, JohnWiley & Sons Inc., Singapore

Chopra, Sunil and Meindl, Peter (2003), Supply Chain Management: strategy,

planning and operation, Pearson Education, New Delhi

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Documents

2nd Scm Final