Body

This study focuses on identifying and measuring the perceived effectiveness of the decision support systems within organizations. The digital support system is an analytical tool that is used by most of the managers in critical situations. This support system process all the inputs like important managerial models, theories and provides best solutions as outputs. Thus, the main purpose of the study is to find out the effectiveness of this system and how it impacts the overall performance of the organization. The study is done with the help of secondary research based on thematic analysis where three important themes have been selected and analyzed properly to conclude appropriate solutions regarding the various research questions highlighting the topic.

Decision making is a prolonged process along with innumerable pros and cons to be considered. Thus, to make a best decision which is worthy to be effective, requires a lot of thinking, communication, brainstorming and similar efforts. The best product which comes out with the help of science and art is the most fruitful.

Managers are decision makers though they have a support system or technology to help them. The technology combine various models and techniques. It is an interactive software that compiles all the raw data (documents, measurements, knowledge, models, etc) and use the information available to solve the problem (“Examples of decision support systems (DSS) aiding business decision-making”, 2019). 

The objectives known facts are as follows:

• Decision support system (D.S.S) is a marvelous technology which employs all the models, raw data to deliver the solutions for the companies.
• The technology does not connect with human behavior and may take wrong emotional decisions.
• The system is technologically upgraded to attain the best decisions by the managers and decision makers and every department, category or organization has a customized system to meet the criteria.

The article here addresses to some core questions. They are:

• What are the various kinds of Decision support system used in different processes of an industry
• What is the impact and value addition due to the technology and who all uses it inside the company?
• What is the effect on the performance of the company holistically and individual employee performances?

Answering these questions are highly relevant as the decision support system costs high for the company. Therefore, calculating the value addition towards the company performances is highly important. The employee perspective towards the system is also a crucial factor to be noted as this may decide the growth in the future.

Conducting the research took 6 weeks. The research onion is used in order to understand the research effectively and efficiently.

 

Figure1: Research Onion

(Source : Quinlan et al., 2019)

The research has used positivism philosophy, exploratory design has been used, using the secondary data (articles), deductive approach has been followed.

Thematic analysis has been conducted on the following themes and the data has been collected from various article sources.

Decision support system comprise the most effective tool in order to take decision for the delegates of the company. The system can be segregated under six heads (Ada & Ghaffarzadeh, 2017). They are text oriented system, database oriented system, spreadsheet oriented system and solver oriented system and hybrid system. The support system can be further classified into Personal support, Group support and organizational support. It is widely used in almost every sector. It is used as a clinical support system in medical diagnosis industry, production development in various production and manufacturing industries. The automotive industry has been extensively benefitted through usage of technology in taking various decisions (Dweiri et al., 2016). The energy resource industry has a huge application and has been benefitted in a numerous ways (Kumar et al., 2017). It is also used in forest management and other industries which make things easier for the industry. The companies are able to save a lot of time and add value to the operations and boost the performance of the company (Saha et al., 2017). 

Strengths and Weaknesses

The technology has helped in a huge way as it delivers authentic decisions employing the best data and the information obtained from the company. The most benefit has been in the factor time. The delegate in all department use the technology either to sort things out in the team or any similar other factor (Wang Kung & Byrd, 2018). Change applied with the use of management skills and the decision support system gives a high amount of precision and helps growth in the long run.

The organizational performance has no doubt reached its peak in all the industries. The Canadian national railway system has improved a lot due to the use of the decision support system (Shin & Konrad, 2017). The management has been proved highly effective amongst all other railway maintenance sectors in the world. Though it is evident that system is highly effective the use of it depends on the data the system is fed in. In many cases there have been found out that the employees are unhappy with decisions. As proper amount of communication has not been employed or may be the management has not found it necessary for a discussion with the employee which has hurt the employee emotionally.

According to the findings the Decision Support System is the best tool that can be employed to save time and decide on some serious and complex issues which have been critical to decide by the delegates of the company (Soltani et al., 2015). Though the managers should keep in mind the emotional factors relating to the employees. 

The research done here can be used in future using the data collected from the secondary research. Again for an extensive research a primary research can also be considered along with a secondary research. Again the data was not ample to give an in depth knowledge. Therefore in future with a better amount of data the research can be more explicit.

The decision support system is an all-time solution for making the best decision in the company (Dutta et al., 2018). But I disagree to that. Technology cannot replace human brain. Therefore, at conditions where the emotional factors needs to be counted in, technology may not understand but humans can. Therefore application of the support needs to kept limited and emotional value of the decision should also be considered.

.Again, the company’s growth occurs due to the decisions given by the system (Be?ikçi et al., 2016). I do not solely agree to the fact. The company cannot meet the heights due to only the decisions. The decisions taken were performed and co-related with the key role by the employees. The employee co-operated with the decisions to make things work for the company. Though I completely agree with Haz?r, here he has stated that the system is effective and has made things easier for the company which may benefit the organization in the long run (Haz?r, 2015).

STRENGTH	WEAKNESS
· Employs data, models, graphs and analyze for output · Logical system and technology aims in perfect calculation · Up gradation of technology has improved the performance of the organization	· Do not possess emotional values · Do not consider the employee ‘pros and cons’ · Operated by top level management which misses out information of the lower level managements and/or employees · Do not consider the real life consequences

Table 1: Strength and Weakness of Decision Support system

 (Source : Created by the author)

The performance level has improved and the organizations take more precise and correct decisions. The delegates save time which adds to value of the organization. Though the overall impacts are great, but it should be kept in mind that emotional factors are not considered in the process. The employees may not be satisfied with the decisions implied upon which can affect the turnover in long run. Again due to the technological advancements many has lost their jobs which may be cost effective for the company but the goodwill have been affected as a whole. 

Conclusion  

Concluding lastly, digital support system has proved to be the most effective in providing various managerial decisions. It has provided various assistances and guidance to managers in the way of taking most strategic decisions with reference to proper theories and models. However, it failed to consider the importance of employees, their views and opinions while making managerial decisions, which is important for the accomplishment of tasks. This article focusses on the secondary research of different types of D.S.S used, who uses it and the impact and effectiveness due to the use of the system. 

References

Ada, ?., & Ghaffarzadeh, M. (2017). Decision making based on management information system and decision support system. TRANS Asian Journal of Marketing & Management Research (TAJMMR), 6(1), 25-38.

Be?ikçi, E. B., Arslan, O., Turan, O., & Ölçer, A. I. (2016). An artificial neural network based decision support system for energy efficient ship operations. Computers & Operations Research, 66, 393-401.

Dutta, G., Gupta, N., Mandal, J., & Tiwari, M. K. (2018). New decision support system for strategic planning in process industries: Computational results. Computers & Industrial Engineering, 124, 36-47.   

Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 62, 273-283. a

Examples of decision support systems (DSS) aiding business decision-making. (2019). Retrieved from https://searchbusinessanalytics.techtarget.com/tutorial/How-decision-support-systems-DSS-can-help-business-decision-making

Haz?r, Ö. (2015). A review of analytical models, approaches and decision support tools in project monitoring and control. International Journal of Project Management, 33(4), 808-815.

Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., & Bansal, R. C. (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596-609.  

Quinlan, C., Babin, B., Carr, J., & Griffin, M. (2019). Business research methods. South Western Cengage.

Saha, C., Aqlan, F., Lam, S. S., & Boldrin, W. (2016). A decision support system for real-time order management in a heterogeneous production environment. Expert Systems with Applications, 60, 16-26.

Shin, D., & Konrad, A. M. (2017). Causality between high-performance work systems and organizational performance. Journal of Management, 43(4), 973-997.

Soltani, A., Hewage, K., Reza, B., & Sadiq, R. (2015). Multiple stakeholders in multi-criteria decision-making in the context of municipal solid waste management: a review. Waste Management, 35, 318-328.

Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13.