Thanks to global competition, demand situation in the economy is no longer certain. Gone are the days of certainty longer PLC’s & the low competitive intensity, today the overall environment has become dynamic. Demand has become uncertain, PLC’s have shortened & competition is intensified. Therefore in such a situation, firms are increasingly realizing that understanding demand, planning demand & linking supply with demand pays.

Forecast of future demand is essential for all strategic decisions in the supply chain. If the supply chain begins with a forecast that is substantially in error, in terms of timing or quantity, the ramification will be felt throughout the entire process. This is why forecasting has assumed significant importance and commitment to it seems to be increasing day by day

Forecasting practices are characterized by some interesting insights into changes in techniques. Research indicates that during the 1980s, despite the growing availability of computer-based forecasting systems, companies continued to rely predominantly on subjective techniques. Since the mid-’90s, companies have started using computer-based forecasting systems. What is surprising is that even among the community of those who use these models, forecast accuracy has not increased.

Why has demand forecasting acquired such a significant place today? Are forecasts reviewed and agreed upon by key departments in the organization? Are right statistical methods used in forecasting the demand for product? What horizons and time periods are used for long-term and short-term forecasting? How are statistical and judgmental considerations to be combined? These are a few questions which need to be answered in order to understand the state of forecasting in Indian Companies.

Causal & time series models have given way to rolling plans. With the changing nature of businesses and increasing complexity due to the changing nature of demand, this shift from quantitative models is understandable. But what is found surprising was that even where causal and time series models would have been appropriate, information technology-based sales force composites were used blindly. Forecasting is not owned as yet by any department, and thus a consensual approach is yet to be evolved leading to a budget-driven demand planning.

What these companies probably forget is that not all demand has become unpredictable; these are situations where demand follows a detectable and predictable pattern. Forecasting methods & models needs to be applied intelligently today to make forecast business significant. Indian firms seem to have lost their direction. Forecasting methods of companies seem to be dictated by supply chain requirements and a technology with little understanding of when, where and what to forecast. The appropriate choice of a technique depends upon the inherent uncertainty in the business environment and the factors which cause this uncertainty.

1.1 Indian Automobile Industry at Global level:

India ranks 1st in the global two-wheeler market

India is the 4th biggest commercial vehicle market in the world

India ranks 11th in the international passenger car market

India ranks 5th pertaining to the number of bus and truck sold in the world

India is the second largest tractor manufacturer in the world.

1.2 History of Automobile Industry

Invention of automobile was not done in one day by a single inventor. The history of automobile industry reflected the revolution that has taken place worldwide. It is estimated that over 1,00,000 patents created the modern automobile. First theoretical plan for making motor vehicle was drawn by both Leonardo da Vinci and Issac Newton.

In 1769, the very first self propelled vehicle that is, tractor was invented by French engineer and mechanic, Nicolas Joseph Cugnot (1725-1804). To power his vehicle he used steam engine, built under his instructions at the Paris Arsenal by mechanic Brezin. The vehicle used to stop after every ten of fifteen minutes in order to building up the steam power. The steam engine and bowler were separate from the rest of the vehicle and kept in front. The following year (1770), Cugnot built a steam-powered tricycle that carried four passengers. In 1771, Cugnot drove his first road vehicle into stone wall and became the first person who did road accident. During the early history both rail and road vehicles were propelled by steam engines only but that steam engine were so heavy that it provided bad design to road vehicle, however steam engine was very successfully used in locomotives.

1.3 Background of Tractors in Automobile Industry:

Tractor industry plays an important part as agriculture sector has a major contribution to India’s GDP. Tractors are part of agricultural machinery industry. Tractors came to India through imports and later on were indigenously manufactured with the help of foreign collaborations. The manufacturing process started in 1961-62. Indian tractor industry is relatively young but now has become the largest market worldwide.

Monsoon season is a key driver for sales of tractors. A series of good or bad monsoon can affect the sales. In recent years the industry has registered a good growth in sales, both domestic as well as exports. This is also partly because of the initiative of the government to boost up agriculture and agricultural machinery industry.

The tractor penetration level in India is very low as compared to the world standards. Also the penetration levels are not uniform throughout the country. The medium horse power category tractors, 31-40 HP, are the most popular in the country and fastest growing segment.

The tractor industry in India has developed over the years to become one of the largest tractor markets in the world. From just about 50,000 units in early eighties the size of tractor market in the country has grown up to over 200,000 units. Today industry comprises of 14 players, including 3 MNCs. The opportunities still are huge considering the low farm mechanization levels in the country, when compared to other developed economies across the world. After a downturn during last 3-4 years, the industry is back on a growth path, which we believe would sustain in coming years as well. Key concern for the industry is its dependence on agricultural income in hands of farmers and the state of monsoon.

1.4 Classification of Tractor Industry on H.P. basis

Table: 1: Classification of Tractor Industry on H.P. basis

Segments

Horse

Power

(HP)

Market

Share

(%)

Suitability

Small Tractors

21-30

23-25

Tractors suited for soft soil conditions and Preferred in well irrigated northern states.

Medium Tractors

31-40

53-56

Used in southern and western region due to hard soil conditions.

Large Tractors

41-50

17

Rich farmers with larger land holdings, especially in Punjab and Haryana.

Large Tractors

>50 Hp

7-12

Used in Turnkey project sites such as building sites for canals, dams and civil constructions projects.

(Source: Data collected from Internet)

LITERATURE REVIEW:

Here author carried out secondary literature to understand Forecasting methods used in different Industry are presented in tabulated form in Tab.2 as shown below:

Author, Year

Context

Conclusion & Finding

Hyndman (2009)

Business Forecasting Methods

Several methods & advancement in forecasting are discussed.

Singh, R (2009)

Predicting Demand

Case of several industries is taken into consideration like Tractor industry & factors affecting demand are taken into consideration.

Armstrong and Green (2006)

Demand Forecasting: Evidence-based Methods

Stress is laid on Statistical and Judgmental Forecasts.

Tab.2

Any nation is well known for its transportation system and for the continuous and rapid development and growth of economy well networked transportation system is very essential. As India’s transportation system is growing at a fast pace, Indian Automobile Sector is also growing. Also this automobile industry has provided employment to large section of society. Thus, the role of automobile industry is very essential in Indian Economy.

Over a period of time more than two decades the Indian Automobile Industry has been driving its growth through phases. Indian automobile industry has grown by leaps and bounds since 1898. (time when car had touched Indian streets for the first time).

Research Statements/Research Hypotheses:

Objective of conducting the study is to

Forecasting sales of tractors in Uttar Pradesh

Analyzing Factors affecting forecast in the region.

Determining the contribution of tractors to automobile industry.

RESEARCH METHODOLOGY

This research is a qualitative research as well as quantitative research since various research papers would be studied in order to understand the history of automobile industry and various other facts about Tractors in automobile industry and about studying the demand forecasting for the industry. It would be an exploratory research as various facts will be explored about the factors in demand forecasting for tractors in automobile industry through various research papers, websites as well as by personally visiting to some of the companies/sales team of Tractors.

Following research methodology will be used for studying Demand Forecasting techniques for Tractors in automobile industry.

(a) Research: Exploratory & Causal research

The research designs for the nature of our project i.e.to provide insights and understanding of the aforesaid topic.

(b) Data Sources: Primary and secondary data

Primary data: Questionnaire design for

a) Companies

b) Expert opinion

Secondary data: from internet, Research papers (literature available), Books on the topic

(c) Research Approach: Survey method

(d) Research Instrument: Questionnaire

(e) Type of Questionnaire: Structured non-disguised

(f) Type of Questions: Close/ open-ended questions

(g) Sampling Plan

Sampling Procedure: Judgment sampling (Sample will be taken by discussion with industrial mentor

(h) Contact Method: Personal Interview

(i) Mode of Collecting data

The respondents will be chosen randomly and requested to grant interviews. The questions will then be asked in a pre­determined (structured) sequence. The secondary data will be collected from various books, journals, business magazines, reports (both published and unpublished), websites etc.

(j) Data Processing

A number of tables to be prepared to bring out the main characteristics of the collected data.

Inferences to be drawn from the data collected. Statistically tool will be used for hypothesis testing. ( Regression analysis, Mean, Standard Deviation, t-test, z-test)

.

Framework for Research

RESOURCES NEEDED TO CARRY OUT RESEARCH

Online journals.

Access to data of various companies.

EXPECTED FINDINGS AND CONCLUSIONS

Market share of respective players

Forecasting well in advance the sales of the tractors in Uttar Pradesh.

LIMITATIONS

Difficulty in accessing the data of various companies.

Authenticity of the data provided.

REFERRENCES

Armstrong, J. S. (2001b), “Extrapolation of time-series and cross-sectional data,” in J. S. Armstrong (Ed.) Principles of Forecasting. Norwell, MA: Kluwer Academic Publishers, pp. 217-243.

Armstrong, J. S. (2001c), “Evaluating forecasting methods,” in J. S. Armstrong (Ed.) Principles of Forecasting. Norwell, MA: Kluwer Academic Publishers, pp. 365-382.

Armstrong, J. S. (2001d), “Combining forecasts,” in J. S. Armstrong (Ed.) Principles of Forecastings. Norwell, MA: Kluwer Academic Publishers, pp. 417-439.

Armstrong, J. S., Adya, M. and Collopy, F. (2001), “Rule-based forecasting: Using judgment in time-series extrapolation,” in J. S. Armstrong (Ed.) Principles of Forecasting. Norwell, MA: Kluwer Academic Publishers, pp. 259-282.

http://www.ibscdc.org/Case_Studies/Strategy/Industry%20Analysis/INA0018.htm

http://www.articlesbase.com/automotive-articles/competition-landscape-in-indiasautomotive-

and-auto-parts-sector-229799.htm

Auto Components- Markets & Opportunities, Indian Brand and Equity Foundation, www.ibef.org

NSW, May 2007, Simple Procurement

Mickey Howard, Richard Vidgen, Philip Powell and Andrew Graves, 2002, are hubs the centre of things?, e-procurement in the automotive industry

http://www.automotive-online.com/

Predicting Demand In An Uncertain World – by Rakesh Singh from Business Line October 6, 2005

http://www.forecastingprinciples.com/