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02/28/2012

Thesis Chapter 4 - The Different Forecasting Techniques In Determining The Future Of The Steel Industry In Saudi Arabia


CHAPTER 4

PRESENTATION, INTERPRETATION AND ANALYSIS OF DATA

 

This part of the study shall be discussing the findings based on the collated information on the survey conducted by the researcher. This study shall be divided into four parts. The first part shall provide a general description of the respondents. Particularly, it shall discuss the respondents’ age, gender, civil status, educational attainment, and the number of years in service in their company. The second part shall be a description on the perception of the respondents regarding the forecasting methods of the company. And lastly the final part of the study shall be discussing the perception of the respondents regarding the level of effectiveness of the forecasting techniques acquired by the company.

The researcher shall also place figures for greater clarity on the discussions.

Profile of Respondents

This part of the chapter shall be discussing the general profile of the respondents. The first to be taken into consideration is the age of the respondents. The responses are summarized in the figure below. The exhibit shows that a major part of the respondents are rather mature (35 above), consisting of 30%. This might be reflected by the fact that the predominant positions of the respondents are in the managerial level, which requires a considerable amount of working experience. This is further asserted by the 27% who were in their early thirties and the 20% in their late twenties.

Exhibit 1. Age of Respondents

 

The next to be taken into consideration is the gender of the respondents. Apparently, a major part of the respondents constitute the male gender. This also states that majority of the managers of the steel industry in Saudi Arabia adheres to a more masculine perspectives. Nevertheless, a 0% of the managers are female. On the other hand, with the seemingly patriarchal culture in most Middle Eastern countries, it could be posited that females were not allowed to be in the position.

 

Exhibit 2. Gender of Respondents

 

Exhibit 3. Civil Status of Respondents

 

 

Exhibit 3. The above illustration shows the civil status of the respondents. 33% of the total respondents, which is the dominated response is single. There are only 43% who are married from the overall respondents. As the figure was interpreted, there is a little percentage of respondents who are separated or widow. Likewise, the respondents were asked for their civil status and the report shows 33% of them are single and 43% are married.  This is due to the large number of young adult in the sample as compared to those who are adult.

 

 

Exhibit 4. Educational Attainment of Respondents

 

 

Exhibit 4. Likewise, the respondents were asked for their educational attainment and the report shows 53 % of them are college. The survey indicates that most of the respondents are college that is engage to the study. The diversity of the population is further asserted when the respondents were asked regarding their professional history. This data illustrate the maturity of the respondents particularly in terms of experience. On the other hand, the apparent youthfulness of the respondents, provided by their age and their lack of professional experience could not be considered as a deterrence to their responses considering the that the researcher has made sure that the respondents have been connected with the company for at least a month. Moreover, there is a noticeable distinction of the respective positions of the younger generations in their respective perceptions towards the impact of forecasting in steel industry.

 

 

Exhibit 5. Years of Service

 

 

Exhibit 5. The figure illustrated the number of years of service of the respondents in the company. Most of the respondents are employed in the company for six to ten years i.e. 23% of the total number of respondents. On the other hand, there is also a great influence of the respondents who are serving the company for ten years or more. As the illustration shows there are 47% of the respondents who are in the company for ten years or more, it is also evident to say that the managers in steel industry of Saudi Arabia are affected by the quality of forecasting in the industry.  Furthermore, in developing a model for forecasting, it is important that its different phases must be conducted and implemented properly.

Perception of Respondents on the Forecasting Process of the Company

            The illustrations and explanations below indicate the perceptions of the respondents pertaining to the forecasting process of the company.

 

Exhibit 6. Weekly Monitoring of Sales and Constant Revision of the Forecast

 

 

            The table above shows the perceptions of the respondents pertaining to the weekly monitoring of sales and constant revision of forecast. According to the

53% of the respondents, their respective company has a weekly monitoring of sales and there is a constant revision of the forecast. Thus, most of the companies in the steel industry in Saudi Arabia are aware to the rise and fall of their weekly sales. Majority of the forecaster knew the importance of weekly forecasting. They believe that forecasting can determine the trend of sales of a certain steel company. In weekly forecasting, the company can easily adjust the marketing strategy. Let say, a certain company detected that their sales for this week are sloping downward. In this case, the company will recognize how to prevent the fall down of their sales so they will give a certain effort to increase their sales promptly.

Exhibit 7. Annual Monitoring of Sales

 

 

            The above table illustrated the perceptions of the respondents about the annual monitoring of sales of their company. 60% of them agreed that their respective company monitors their sales annually. On the other hand, 37% of the respondents or manager respondents disagree on the statement. The annual monitoring of sales of a certain company is important in order to determine the progress of their sales. A certain company needs to take consideration concerning to their annual sales so they will know if their sales can boost up to the unpredictable change of marketing standard. However, a company needs to consider not only their annual sales but also the whole standard of the company itself.

 

Exhibit 8. Evidence Before Making Any Adjustments

            The illustration above shows the perception of the respondents pertaining to the more evidence that company wanted before making any adjustments.  According to the surveyed respondents, it is very important not only to consider the forecast value but also to the possible attributes that might affect the sales. The 50% of the respondents agreed to the statement while only 33% do not believe that their companies are looking for more evidence before making an adjustment. It is very critical for a certain company to make any adjustments specially if they not consider other factors.  Moreover, the impoverishment of most companies was through the process of wrong decision. 

 

Exhibit 9. Ability to Distinguish Temporary Disruptions to the Real Forecast Errors

 

50% of the respondents believe that their respective companies can distinguish temporary disruptions to the real forecast errors. In general, the company should be more aware about the other factors that affect forecasting accuracy. Awareness of the possible errors in forecasting should be apparent so that the company will minimize wrong adjustments that will affect the progress of their sales.

 

Exhibit 10. Criteria Determining When to Revise the Forecasting

 

            It is very important to a company to organize a criterion determining when to revise the forecasting technique or model. From the surveyed respondents, 50% of them contracted that their respective companies follow a criterion in which the forecasting technique is obsolete. However, the 33% of the respondents opposed that their company do not consider any criterion. Based on previous studies, there is no such forecasting technique i.e. applicable to different marketing environment. Nonetheless, the accuracy of a forecast cannot be verified unless the time period for which it was made has passed and until the action it was used to evaluate has been taken. Thus, if some political purpose was being served by making a forecast that it need not really be correct in order for it to have its intended effect. Furthermore, if the result of the forecast was a policy intervention, it is impossible to know whether the forecast conditions would have come to pass without that intervention.

 

Exhibit 11. Accuracy of the Data

 

The presentation above illustrated the accuracy of data used in forecasting. The biggest degree of response of the managers about the accuracy of data was uncertain which is 43% of the total respondents.  Accuracy of data is one of the most important factors in forecasting in order to commit correct or wrong decision. Based on the collated questionnaires, the managers are not sure whether the gathered data are correct or wrong. Through these results the managers should be more aware about the accuracy of data since it is very vital to the marketing arena.

 

 

 

Exhibit 12. Implementation of the Best Forecasting Technique

 

 

 

The implementation of the best forecasting technique is a crucial factor in steel industry since there is a continuous change of marketing standard. From the surveyed individuals, 53% of them believe that their company selects a best technique in forecasting. Forecasting techniques will generally fall into one of three broad categories of models: time series, causal, or judgmental. Forecasting is a work by discovering underlying mathematical patterns in historic data and then extending them into the future. Regression and time series analysis are examples of two commonly used techniques whose application depends largely upon the characteristics of the data, not upon any intrinsic correspondence to the dynamics of a situation. The forecaster that understands the market's needs would do better than the one that doesn't. If they understand the customer, they understand the reasons for choosing one from among many complex new products. Complete reliance on mathematics leads to a complete failure to understand the customer.

 

Perception of the Respondents Regarding to the Level of Effectiveness of the Forecasting Techniques Acquired by the Company

 

Exhibit 13. Strategists of the Company Consider the Seasonality of the Company’s Products’ Sales.

 

The illustration shows that 50% of the respondents considers the seasonality of company’s product sales. Through forecasting, the company will be acquainted with the right timing when to give an increase on the supply needed by the costumer during a certain period. The results show that most of them are familiar to the right timing of sales sudden increase. Most commonly, forecasts are actually projections. Using recent trends in many underlying causal variables, the future values of some other dependent variables are modeled. Since all the causal variables are presumed to be following their historical trends, the forecast is not a vision of the future at all--it is rather a foreseeable consequence of intersecting trends.

 

Exhibit 14. The Intention of Forecasting in the Company is Primarily to Guide Short-term Decisions such as Purchase of Raw Material, Storage Requirements, or Hiring of Part-time Personnel

           

Exhibit 15. Perception of the Respondents Pertaining to the Intention of Forecasting in the Company, Primarily to Guide Long-term Decisions such as Union Contracts, or Expansion of Facilities and Equipment.

 

Exhibit 16. Perception Towards the Intention of Forecasting in the Company, Primarily to Guide both Long- and Short-term Decisions

 

 

Exhibit 14,15 and 16 signifies the responses of the respondents about the intention of forecasting in steel industry of Saudi Arabia. According to the dominated response, forecasting is not only for guide short-term decisions but also for the progress of the company in long-term instances. However, forecasting can help the company in formulating short-term decisions. There are also other considerations to look into in the process of forecasting. Not only do companies need the suitable method of forecasting to accurately predict outcomes, they also need to mull over the external aspects of the industry. To illustrate, they must also take into consideration the market where their particular product dwell. Saudi Arabia’s steel industry must have attributed its continuous growth to forecasting methodology. There are two main approaches to forecasting. Either the estimate of future value is based on an analysis of factors which are believed to influence future values (the explanatory method) or the prediction is based on an inferred study of past general data behavior over time (the extrapolation method). It is possible that both approaches will lead to the creation of accurate and useful forecasts, but the former method is often more difficult to implement and validate than the latter approach. As with other businesses, forecasting techniques in steel industry are used to further boost the industry’s market share. These techniques often determine the survival and fall of an industry.

 

Exhibit 17. Perceptions of the Respondents about Forecast Experts who Establish Specific Parameters of the Forecast

 

 

 

            In forecasting it is very important to a forecaster or forecast experts to establish specific parameters of the forecast so that the basis of possible adjustment in steel industry is reliable. According to the collated data, 47% of the total surveyed individual agrees that their respective forecaster uses a certain parameters. On the other hand some of the forecast experts do not consider the idea of parameter.  In some industry the use of parameter is not a primary factor to consider but a good forecast statement should have a basis to follow.

 

Exhibit 18. The Forecaster and the Company Negotiate Before an Appropriate Forecast was Developed

 

 

            The above table shows 57% of the respondents believe that their company and forecaster negotiate first before an appropriate forecasting was develop. The importance of negotiation between the forecaster and company should be present in order to determine the concerns of the company. 

 

Exhibit 19. The Manager Influences the Decisions of the Forecaster.

 

 

 

            The illustrated presentation above shows that the managers did not influence the decision of the forecaster. According to the 47% of the respondents, they believe that a good forecasting is not bias. Meaning to say, the result of forecasted computation should be base on the real factors to be considered specifically the factors in steel industry.

 

Exhibit 20. The Company Adapts a Forecasting Model that Suits the Intentions of the Forecasting.

 

 

 

            The illustration shows the response of the respondents if their company adapts a forecasting model that suits the intentions of forecasting. The 37% of individual are uncertain if their respective companies are using a forecasting model. The use of a certain model is also practical since the reliability of it is not questioned.  However, the reliability of a certain model depends upon if it suits to the data to consider. Therefore, the need of devising another forecasting model is also recommended unless it ensembles to the applicability.  Forecasting techniques will generally fall into one of three broad categories of models: time series, causal, or judgmental.

 

 

Exhibit 21. The Forecaster Shares the Initial Forecast Figure to the Manager.

 

 

            According to the surveyed individual i.e. 40% of the overall respondents, the forecaster shares the initial forecast figure to the manager. It is very important to the manager to consider the initial forecast figure since he is the one responsible for the possible adjustments in the company. The responsibility of the initial forecasted value is very vital since the stability of a certain company will be agitated.

Exhibit 22. The Manager Agrees to the Initial Forecast Figure Most of the

Time.

 

30% of the respondents are uncertain about this statement. In general, the initial forecast figure depends upon the data gathered by the forecaster. However, the manager do not agrees to the initial forecast figure if the reliability of data gathered is questionable. In all cases, gathering of data to be considered in forecasting is very vital since all the effort in forecasting technique is useless if the data is incorrect.

Exhibit 23. The High Level Management Usually Alters the Initial Forecast.

 

            The uncertain response of the respondents in this statement is in great dominion that is illustrated by 30% of the total respondents. Essentially, the high level of management depends upon the stability of the company in marketing arena. In some cases, a certain company increased the level of management if they detected from the initial forecast figure that their sales are sloping down.

 

Exhibit 24. Product Managers and Sales Managers who do Forecasting are as better as Full-time Forecasters.

 

            The illustration above shows the perception of the respondents pertaining to the better forecasters. The figure illustrated that 34% of the respondents are uncertain when it comes to the statement about the better forecaster. From the illustration, there are 40% of the respondents who agrees to the statement and that is because managers know how to adjust their marketing style even without forecasting. In some cases, managers are better than forecasters when it comes to forecasting because managers sometimes detected some factors in management that might affect the increase or decrease of sales.

 

Exhibit 25. Overall, Forecasting within the Company has resulted to Increased Sales.

 

            84% of the total respondents agree on this statement.  These results show the effectiveness of forecasting in steel industry of Saudi Arabia. Forecasting models are used in order to allow companies to look into possible outcomes of certain undertakings fundamentally to minimize losses in the operation of the company. The result also signifies that forecasting is a great tool to increase sales.

 

Summary of Perceptions of the Respondents

 

SA

A

U

D

SD

Weighted mean

Interpretation

1. The company monitors the sales weekly and is constantly revising the forecast based on the most recent sales result.

10

6

2

11

1

3.43

Uncertain

2. The company monitors the sales annually.

14

4

1

9

2

3.63

Agree

3. The company wants more evidence before making any adjustments

12

3

5

6

4

3.43

Uncertain

4. The company is able to distinguish temporary disruptions to the real forecast errors.

11

4

6

7

2

3.50

Agree

5. The company has criteria that determine when to revise the forecasting.

8

7

5

7

3

3.33

Uncertain

6. The forecasting technique presently used in the company often produces inaccurate data.

3

6

13

6

2

3.07

Uncertain

7. The company is implementing the best forecasting technique.

11

5

5

3

6

3.40

Uncertain

8. In forecasting the strategists of the company consider the seasonality of the company’s products’ sales.

10

5

3

7

5

3.27

Uncertain

9. Presently, the intention of forecasting in the company is primarily to guide short-term decisions such as purchase of raw material, storage requirements, or hiring of part-time personnel.

2

4

8

11

5

2.57

Uncertain

10. Presently, the intention of forecasting in the company is primarily to guide long-term decisions such as union contracts, or expansion of facilities and equipment.

11

5

8

2

4

3.57

Agree

11. Presently, the intention of forecasting in the company is primarily to guide both long- and short-term decisions.

8

1

10

3

8

2.93

Uncertain

12. Forecast experts establish specific parameters of the forecast. 

9

5

3

7

6

3.13

Uncertain

13. The forecaster and the company negotiate first before an appropriate forecast can be developed.

13

4

6

6

1

3.73

Agree

14. The manager influences the decisions of the forecaster.

1

6

9

11

3

2.70

Uncertain

15. The company adapts a forecasting model that suits the intentions of the forecasting.

9

4

11

2

4

3.40

Uncertain

16. The forecaster shares the initial forecast figure to the manager.

8

4

7

4

7

3.07

Uncertain

17. The manager agrees to the initial forecast figure most of the time.

4

6

9

8

3

3.00

Uncertain

18. The higher-level management usually alters the initial forecast.

7

6

7

4

6

3.13

Uncertain

19. Product managers and sales managers who do forecasting are as better as full-time forecasters.

9

3

10

7

1

3.40

Uncertain

20. Overall, forecasting within the company has resulted to increased sales.

15

10

1

1

3

4.10

Agree

 

The above table shows the complete results of the perception of the respondents about the effectiveness of forecasting in steel industry of Saudi Arabia. The interpretation shows that the dominant response was uncertain, however, there are some factors or statements that has an Agree response. Meaning to say, most of the respondents believed that forecasting was a great tool to be use in determining the future of steel industry in Saudi Arabia. They believe that forecasting can determine the trend of sales of a certain steel company. In weekly forecasting, the company can easily adjust the marketing strategy. Let say, a certain company detected that their sales for this week are sloping downward. In this case, the company will recognize how to prevent the fall down of their sales so they will give a certain effort to increase their sales promptly. The annual monitoring of sales of a certain company is important in order to determine the progress of their sales. A certain company needs to take consideration concerning to their annual sales so they will know if their sales can boost up to the unpredictable change of marketing standard. However, a company needs to consider not only their annual sales but also the whole standard of the company itself. It is very critical for a certain company to make any adjustments specially if they not consider other factors.  Moreover, the impoverishment of most companies was through the process of wrong decision. Awareness of the possible errors in forecasting should be apparent so that the company will minimize wrong adjustments that will affect the progress of their sales. Nonetheless, the accuracy of a forecast cannot be verified unless the time period for which it was made has passed and until the action it was used to evaluate has been taken. Based on the collated questionnaires, the managers are not sure whether the gathered data are correct or wrong. Through these results the managers should be more aware about the accuracy of data since it is very vital to the marketing arena. The implementation of the best forecasting technique is a crucial factor in steel industry since there is a continuous change of marketing standard. The forecaster that understands the market's needs would do better than the one that doesn't. If they understand the customer, they understand the reasons for choosing one from among many complex new products. Complete reliance on mathematics leads to a complete failure to understand the customer. Through forecasting, the company will be acquainted with the right timing when to give an increase on the supply needed by the costumer during a certain period. The results show that most of them are familiar to the right timing of sales sudden increase. Saudi Arabia’s steel industry must have attributed its continuous growth to forecasting methodology. In forecasting it is very important to a forecaster or forecast experts to establish specific parameters of the forecast so that the basis of possible adjustment in steel industry is reliable. The importance of negotiation between the forecaster and company should be present in order to determine the concerns of the company. The result of forecasted computation should be base on the real factors to be considered specifically the factors in steel industry. The use of a certain model is also practical since the reliability of it is not questioned.  However, the reliability of a certain model depends upon if it suits to the data to consider. Therefore, the need of devising another forecasting model is also recommended unless it ensembles to the applicability. It is very important to the manager to consider the initial forecast figure since he is the one responsible for the possible adjustments in the company. The responsibility of the initial forecasted value is very vital since the stability of a certain company will be agitated. In all cases, gathering of data to be considered in forecasting is very vital since all the effort in forecasting technique is useless if the data is incorrect. Essentially, the high level of management depends upon the stability of the company in marketing arena. In some cases, a certain company increased the level of management if they detected from the initial forecast figure that their sales are sloping down. In some cases, managers are better than forecasters when it comes to forecasting because managers sometimes detected some factors in management that might affect the increase or decrease of sales. Forecasting models are used in order to allow companies to look into possible outcomes of certain undertakings fundamentally to minimize losses in the operation of the company. The result also signifies that forecasting is a great tool to increase sales.

The table shows the great impact of forecasting to the steel in industry in Saudi Arabia. However, most of the items are in uncertain degree which signifies the unbiased response of the respondents regarding to the application of forecasting in their respective companies.

 References:

Creswell, J.W. (1994) Research design. Qualitative and quantitative approaches. Thousand Oaks, California: Sage.

El Danaf, M. A. (2002) Interview with Gulf News. November.

Gentry, B. (2003) Arab mining sector poised for growth. Accessed at [www.arabdatanet.com]. Accessed [002/09/03].

Harris, R. I. D. (1995) Using Cointegration Analysis in Econometric Modeling. Hertfordshire: Prentice Hall/Harvester Wheatsheaf.

Rollof, C. (2003) Forecasting Techniques. Accessed at [www.wissenschaft.com]. Accessed [02/09/03].

Walliman, Nicholas and Bousmaha Baiche. (2001) Your research project. SAGE Publications

 

 

 

 

 

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