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Forecasting Demand for Flat Steel - A Study on A Steel Rolling Mill in India

CASELET, OPERATIONS MANAGEMENT
IMT - Ghaziabad, 7 Pages
AUTHOR(S) : Dr. Gunjan Malhotra, Assistant Professor, Decision Sciences and Operations Area, IMT Ghaziabad

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Forecasting Demand for Flat Steel - A Study on A Steel Rolling Mill in India


A Forecasting Demand Dilemma

It was a cold winter morning in the first week of January 2016 in Chandigarh, Punjab, India. Shivam Goyal (Goyal), the partner of Singla Steel and Allied Industries in Punjab, was anxiously awaiting in his office to meet Virat Saxena (Saxena), a leading consultant in the Indian steel industry whom he had met at a conference in Delhi. He had invited Saxena to his company.

Goyal established his manufacturing company about 30 years ago and in the recent years had encountered wide fluctuations in the demand for his flat steel roll products. As a result, it was almost impossible for him to plan and operate efficiently and profitably. He had briefly shared his concerns with Saxena who had promised to help him. His senior management team had prepared a presentation for Saxena, based on its experience over the last few years, the conclusion of which was that
nothing could be done to improve the situation.................

Exhibits

Exhibit I: Annual demand for Steel Industry in India

Exhibit II: The Monthly Demand for Steel Bars at Singla Steel and Allied Industries

Teaching Note Preview

Forecasting Demand for Flat Steel - A Study on A Steel Rolling Mill in India


Synopsis

Singla Steel and Allied Industries (Singla Steel) was established 30 years ago near Chandigarh, Punjab a Northern State of India. The company had been manufacturing steel flats and bars using hot rolling process mainly for agricultural implement sector in Punjab. The average production of flat steel bar was approximately 300 metric tonne (t) per month. According to Shivam Goyal (Goyal), business partner, the demand for flat steel products was volatile. To partly meet the variation in demand the company was keeping a stock of approximately 600 t. Being a highly competitive industry, Goyal wanted to seek an advice from an industry expert to meet the demand efficiently.

Prerequisite Readings

  • • N. Balakrishnan, B. Render, and R.M. Stair, “Chapter 11: Forecasting Models,” Managerial Decision Modelling with Spreadsheets, 3rd ed. (Pearson Education Delhi, 2013), 475-525.
  • • John E. Hanke and Dean W. Wichern, “Chapter 1, 3, 4 & 5.,” Business Forecasting, 8th ed. (Pearson Education Delhi, 2005), 1-12; 58-210.
  • • Gardner, E. S. Jr., “Exponential smoothing: The state of the art,” Journal of Forecasting, Vol. 4, Issue 1 (1985): 1-28, accessed January 10, 2017, http://onlinelibrary.wiley.com/doi/10.1002/for.3980040103/pdf.
  • • John C. Vhambers, Satinder K. Mullick, and Donald D. Smith, “How to Choose the Right Forecasting Techniques,” Harvard Business Review, July 1971. Last assessed on November 26, 2016. https://hbr.org/1971/07/how-to-choose-the-right-forecasting-technique.
  • • William Barnett, “Four Steps to Forecast Total Market Demand,” Harvard Business Review, July 1988. Last accessed on September 10, 2016, https://hbr.org/1988/07/four-steps-to-forecasttotal- market-demand.
  • • Cecil Bozarth (2011). “Measuring Forecast Accuracy: Approaches to Forecasting: A Tutorial”, NC State University. Last assessed on Jan 21, 2017. https://scm.ncsu.edu/scm-articles/article/measuring-forecast-accuracy-approaches-to-forecasting-a-tutorial

 

Learning Objectives

The learning objective of the case are as follows:

• To understand the various components of forecasting demand
• To understand the factors affecting demand behaviour
• To understand the various forecasting methods and to compare the forecasting accuracy of various models

Case Positioning and Setting

The case is designed for the Operations Management course for BBA, MBA or executive MBA students. The course may be intended to be used at the middle-level or end of the course in Demand Forecasting module. Before dealing with this question, it is advised that instructor should have discussed what is forecasting technique, different models available and how the company may select the best possible method. After the discussion in the class the instructor may provide the case to the students and ask them to run different forecasting methods and to come up with the final solution which will provide minimum errors to the company.

Assignment Questions

I. Elaborate the importance of demand forecasting for Singla Steel and Allied Industries.
II. Plot the data on a graph paper and find out if there are any trends or seasonality in demand data for Singla Steel and Allied Industries. Discuss your findings.
III..............

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Abstract

Singla Steel and Allied Industries (Singla Steel) was established 30 years ago near Chandigarh, Punjab, a Northern State of India. The company had been manufacturing steel flats and bars using hot rolling process mainly for agricultural implement sector in Punjab. The average production of flat steel bar was approximately 300 metric tonne (t) per month. According to Shivam Goyal (Goyal), business partner, the demand for flat steel products was volatile. To partly meet the variation in demand the company was keeping a stock of approximately 600 t. Being a highly competitive industry, Goyal wanted to seek an advice from an industry expert to meet the demand efficiently.

Pedagogical Objectives

  • To understand the various components of forecasting demand
  • To understand the factors affecting demand behaviour
  • To understand the various forecasting methods and to compare the forecasting accuracy of various models

Case Positioning and Setting
The case is designed for the Operations Management course for BBA, MBA or executive MBA students. The course may be intended to be used at the middle level or end of the course in Demand Forecasting module. Before dealing with this question, it is advised that instructor should have discussed what is forecasting technique, different models available and how the company may select the best possible method. After the discussion in the class the instructor may provide the case to the students and ask them to run different forecasting methods and to come up with the final solution which will provide minimum errors to the company.



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