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Critique Of Hard And Soft Assessment Answer

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Key Topics

You are a newly-appointed senior Business Analyst, taking up a role within a recently created Business Analysis Practice within Corporate Services in a large university (You can discuss with the teaching staff, if you wish to select another context for the assignment). The university has for many years relied primarily on a variety of hard approaches to problem analysis and modelling, but the Head of the Business Analysis Practice believes that the addition of soft approaches to the BA toolkit is necessary. Her specific concerns relate to poor communications amongst diverse stakeholders and difficulties in adequately analyzing problems before ICT solutions are found. You were the preferred candidate because of your knowledge of a variety of hard and soft approaches to problem analysis and modelling. You have been asked to prepare a report for your management team, discussing a number of soft approaches to modelling, and ultimately making recommendations as to which, and how such approaches could be incorporated into the activities of business analysts employed within the BA practice.

Specifically, in your report, you should:

• Briefly describe and critique the different philosophical perspectives and underlying assumptions of hard and soft approaches to problem analysis and modelling
• Select a soft modelling approach and examine the strengths and weaknesses of that approach.
• Discuss the types of contexts and problems for which that approach is best suited.
• Evaluate the limitations of the dominant hard modelling approaches that are currently used in the university. (Please make assumptions as to the specific hard
approaches currently used.)
• Analyse in detail, and provide an example of how the soft and hard approaches could be used in combination to improve the practice of business analysis in the university.


Include a consideration of the benefits of adopting soft approaches and mixing them with more traditional hard approaches. Discuss the implications for the roles and
practices of business analysts.
• Make recommendations to management, and include thoughts on how soft approaches could be incorporated into the BA Toolkit.

Critique of Hard and Soft Modeling Approaches

EXECUTIVE SUMMARY

In order to solve the business issues and complex problems in proper manner it is necessary to undertake right form of approaches. Hard and soft are the two different approaches which can be taken into consideration to deal with contemporary issues linked with business analysis. The present report outlines the analysis of different approaches which can be used for problem analysis and modeling. In case of soft modeling approach, it is assumed that the issues are problematic and pluralistic in terms of nature. According to the soft approach, it is also assumed that defining a problem or issue is not a straightforward process and the process is considered a very problematic one. Thus, the main and most important assumption of soft approach is that it emphasise on end means On the other side of this, problems are being assumed as unitary and straightforward in the hard approach of problem analysis and modeling. Here, emphasise is on developing and creating something which has the potential to satisfy the identified needs in every possible manner 

System dynamics is the soft approach which has been selected and the objective behind selection of this approach is that it represents continuous systems. The strength of system design approach is that it has the potential to incorporate the acknowledged complexities under one model. The benefit of using system dynamic approach is that it allows the users to study a system and determine what directions can be used to manage the entire system in the best possible manner. It is recommended that Before adopting hard or soft approach it is necessary to evaluate the pros and cons of each approach so that it is possible to adopt 

INTRODUCTION 

In the present era, effective management of systems is vital for the long term growth and sustainability of universities. Hard and soft are the two different approaches which can be taken into consideration to deal with contemporary issues linked with business analysis (Luong, Pham, & Manning, 2015). The present report outlines the analysis of different approaches which can be used for problem analysis and modeling. In addition to this, the strength and weakness of hard and soft approach of system modeling are also mentioned in this study. The limitations linked with hard modeling approach along with benefits associated with the use of soft modeling approach are also explained in this study.

Assumptions of hard and soft approaches to problem analysis and modeling

Hard and soft are the two different approaches which are used in modeling and problem analysis. Considering the case of soft modeling approach, it is assumed that the issues are problematic and pluralistic in terms of nature. According to the soft approach, it is also assumed that defining a problem or issue is not a straightforward process and the process is considered a very problematic one (Rus & Tolley, 2015). Furthermore, framing and naming are the two reasons because of which problems are emerged. The soft approach to problem analysis is also considered as a critique of the traditional approach of engineering which is establishing a need before beginning the activity or work. Thus, the main and most important assumption of soft approach is that it emphasise on end means. The soft approach is also assumed as a approach which is used for creating debates and getting detailed knowledge and insight about the real world. 

On the other side of this, problems are being assumed as unitary and straightforward in the hard approach of problem analysis and modeling. Here, emphasise is on developing and creating something which has the potential to satisfy the identified needs in every possible manner. The key differences between hard and soft approach to problem analysis and modeling is that hard approach focus on how whereas the soft approach is more concerned with defining what. It is assumed that hard system approach is used to deal with problems which are of both qualitative and quantitative nature. Here, a step by step procedure is used to address the problem and ensure smooth functioning of the systems (Stokes et al. 2014). 

The process starts within identification of opportunity or problem and in the next stage current systems and situations are being examined. In the third stage, changes in existing system are proposed and then routers are being developed to carry out smooth flow of all system and processes. It is also assumed that the model in hard approach provides representation of the real world and the outcome of this approach are recommendations or products. In comparison with the hard approach, it is assumed that soft approach is more effective and suitable to manage complex systems.

Select a soft modeling approach 

System dynamics is the soft approach which has been selected and the objective behind selection of this approach is that it represents continuous systems. The selected approach includes four major elements which are influences, variables, compartments and flows. Considering the strengths of the selected soft approach of problem analysis and modeling, it can be expressed that it has the capability to acknowledge the complexities associated with sustainable structure (Zhu, & Azar, 2015). Furthermore, the strength of system design approach is that it has the potential to incorporate the acknowledged complexities under one model. Appropriate knowledge and information about the interdependencies among systems can be also collected with the help of the selected approach and this can be termed as the system’s another major strength. 

On the other side of this, it can be critically argued that the weakness of the selected system is that modeling of such complex situation is very difficult. Another weakness which has been identified from analysis of the system dynamic approach is that it consumes lots and lots of time. Defining every component present in the sub system is essential requirement of this model and lots of time is consumed during the same (Mas et al. 2015). Emergence of issues related to uncertainty and understanding of the system along with data unavailability are some other weakness of the selected soft approach of problem analysis.

The types of contexts and problems for which that approach is best suited

The selected approach which is system dynamics is that mainly suitable for the modeling systems which emphasise on finding their feedback loops. It can be expressed that system dynamics is commonly used to deal with problem which deal with problems related to sustainability. The basic and even complex problems related system can be resolved with the help of approach which is system dynamics. The statement can be justified by the fact that the tool emphasise on dealing with problem through system behavior which is counter intuitive. 

All the problems related to the sustainability of systems can be managed and overcome easily with this help of using soft approach i.e. system dynamics (Zeng, Phan & Matsui, 2015). Apart from this, problems which are tricky and complex in nature can be also resolved with the help of the selected tool. The selected system is also useful in dealing with faceted problems which are commonly encountered during the usage of the same. 
The benefit of using system dynamic approach is that it allows the users to study a system and determine what directions can be used to manage the entire system in the best possible manner (Colli, Gilardi, Rocca & Sprekels, 2015). Other than this, the selected system is also very useful in addressing issues linked with complex managerial and social system. The system is very beneficial in dealing with problems which are faced in the dynamic systems that consists of mutual interaction and interdependency. Here, the major sources of information are taken into consideration and the sources are expert knowledge of system participants, written database and numerical data. 

The limitations of the dominant hard modeling approaches 

The key and most important limitation associated with the present hard modeling approach in the University is that the approach is flexible, not standardized. At the present, the university has variety of flexible techniques which can be used to deal with complex system problem but a standard technique to deal with all issues and problems related to system is missing. Apart from this, the present approach is not considered as effective or suitable because it is not capable of recognizing the differences which lies in the existing systems. 

The university is present using the hard approach because the approach is supporting in offering a plan of action which is orderly and efficient (Zhu et al. 2015). The approach is also providing good control basis for system and this is a major reason because of which the university is using this approach. However, it can be critically argued that the selected hard approach is over conceptual and therefore, creating issues for the university in managing its system in the desired and best possible manner. In addition to this, the existing approach is also considered as unpractical and this is another major drawback or limitation associated with this approach. It can be expressed that the hard system approach cannot be applied directly to the problems which are practical in nature.

How soft and hard approaches can be mixed 
In order to effectively utilize the benefits of hard and soft approach it is required to mix the two concepts so that its elements can benefit in resolving the business issues in the best possible manner (Vrugt, 2016). Considering the overall nature of the soft approach it has been identified that in this type of approach the problems of the business are considered to be messy where the problems of the company are interpreted differently by every stakeholder associated with the company. Moreover, soft approach mainly relies on the human factors and they are very important. In short, to resolve any form of business issue like within the universities any issue is faced linked with developing learning plan for the student or any other then in such case involvement of human factors is must. For example to identify the root cause of the problem and identifying best possible alternative human factors are considered.

It is creative as one of the best and the intuitive approach to problem solving that helps in identifying the best possible solution of the problem being faced within the workplace. On the other hand the overall elements present the hard system approach are somehow different where its key assumptions involves technical factors are present, scientific approach is mainly adopted for problem solving etc (Zhu, & Azar, 2015).
Within universities and in other form of areas hard along with the soft approach can be mixed through proper planning. Firstly it is necessary to understand the nature of the problem that is being faced (Martre, et al. 2015). It is possible to mix both the approach by integrating their elements in the best possible manner. For instance if in case both the human and technical factors are undertaken for solving any issue linked with the university then it can be said that mixture of both the approaches is used and through this the best possible solution can be identified easily. Further, it is a well known fact that some problems are quite crucial and in turn one specific approach such as hard or soft cannot assist in resolving the issue faced within the university. So, in such case integration is necessary where scientific approach is applied to solve problem along with the intuitive approach so that best possible outcomes can be identified easily. 

Combination of the structure methods along with the involvement of human factors can contribute a lot in making effective utilization of both the approaches and its mixture will be highly beneficial (Greasley, 2017). For instance if university is facing issue linked with developing learning programs for the graduate students then in such case technical factors can be undertaken such as different systems can be used and along with this human factor can assist in its implementation. So, with the help of this it can be clearly stated that mixture of both the approaches can surely assist in identifying the best possible solution of the problem that is being faced and in turn the challenges that will be faced in near future also will also be tackled through correct combination of both the approaches.

Benefits of adopting soft approaches 

Applicability of soft approach for resolving the issues faced within the university provides numerous benefits (Davis, 2018). One of the main advantage is that it undertakes the human factors knowledge, skills and expertise that different people possess can be easily applied in resolving the issues faced with the universities. Further, it is a well known fact that every individual has some sort of expertise along with different skills and its utilization is possible with the help of soft approach that is mainly adopted for resolving the university issue in the best possible manner. 
This approach is based on the belief that the problems of the firm are poorly defined and so through this it can be stated that the advantage of this approach it helps in defining the problems of the business in proper and systematic way so that every individual can know about it in proper manner (Morecroft, 2015). For instance within university and the staff and other individuals are unable to understand the problem and they are poorly defined then in such case through soft approach it is possible to understand issue in corrective manner and accordingly solution can be identified. So, this is also one of the crucial benefit of soft approach that makes it much more effective as compared with the hard approach. 

As mentioned the main outcomes associated with soft approach involves better understanding, learning etc (Alglave, Maranget & Tautschnig, 2014). So, in case for resolving any issue within the university soft approach is applied then in such case after resolving the issue the teacher and other form of individuals in the university will be able to learn such as the nature of problem, best ways to resolve any problem etc. Therefore, applicability of this approach will surely contribute in enhancing the knowledge level along with the understanding of the individuals in the university. 

Another key advantage of this type of approach is that it assumes intuitive problem solving where it has been identified that majority of the people are intuitive problem solvers where they focuses on adopting definition of the problem with obtaining descriptive data (Coakley, Raftery & Keane, 2014). So, through the applicability of the soft approach adequate amount of descriptive and other form of information is obtained that contributes a lot in resolving the issues that are faced within the universities. So, in this way these are some of the main advantages associated with the soft modeling approach especially from the point view of resolving issues.

Recommendations to management

Hence from the overall analysis there are some recommendations that can be easily adopted for dealing with the key issues faced within the university. Below are some of the key suggestions:

• It is necessary for the management of the university to identify the nature of the problem on the priority basis so that the issue faced can be understood in the better manner. It will assist a lot in knowing whether to adopt soft or hard approach for dealing with the challenge faced.
• Before adopting hard or soft approach it is necessary to evaluate the pros and cons of each approach so that it is possible to adopt 
• Instead of using hard approach soft one can be taken into consideration as in case of complicated systems that are associated with the businesses this type of approach is more feasible and beneficial too. 
• Before selecting any form of approach such as hard or soft it is necessary to provide gain proper knowledge about the approach so that best possible advantage can be gained through applicability of one specific approach.
• Before applicability of any approach proper descriptive information must be gathered for resolving the issue

CONCLUSION

Hence from the overall analysis it has been identified that the selected approaches such as soft and hard can contribute a lot in resolving the most complicated issue faced within the university. In comparison between both the approaches it has been identified that soft one is most effective as it is more appropriate in handling the complex situations and in turn involvement of human factors are present. This is the real positive contribution of this approach. No doubt hard approach can also be adopted where it depends on the scientific approach to problem solving. First and the foremost thing is to understand the nature of the problem and through this further analysis can be carried out in the most effective manner. It depends on the understanding of university’s staff like which approach they prefer to undertake for analysis of the business issue that can bring favorable results.

References

Alglave, J., Maranget, L., & Tautschnig, M. (2014). Herding cats: Modelling, simulation, testing, and data mining for weak memory. ACM Transactions on Programming Languages and Systems (TOPLAS), 36(2), 7.
Coakley, D., Raftery, P., & Keane, M. (2014). A review of methods to match building energy simulation models to measured data. Renewable and sustainable energy reviews, 37, 123-141.
Colli, P., Gilardi, G., Rocca, E., & Sprekels, J. (2015). Asymptotic analyses and error estimates for a Cahn-Hilliard type phase field system modelling tumor growth. arXiv preprint arXiv:1503.00927.
Davis, M. H. (2018). Markov models & optimization. Routledge.
Greasley, A. (2017). Simulation modelling for business. Routledge.
Luong, M. T., Pham, H., & Manning, C. D. (2015). Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025.
Martre, P., Wallach, D., Asseng, S., Ewert, F., Jones, J. W., Rötter, R. P., ... & Hatfield, J. L. (2015). Multimodel ensembles of wheat growth: many models are better than one. Global change biology, 21(2), 911-925.
Mas, S., Bendoula, R., Agoda-Tandjawa, G., de Juan, A., & Roger, J. M. (2015). Study of time-dependent structural changes of laponite colloidal system by means of near-infrared spectroscopy and hybrid hard-and soft-modelling multivariate curve resolution–alternating least squares. Chemometrics and Intelligent Laboratory Systems, 142, 285-292.
Morecroft, J. D. (2015). Strategic modelling and business dynamics: a feedback systems approach. John Wiley & Sons.
Rus, D., & Tolley, M. T. (2015). Design, fabrication and control of soft robots. Nature, 521(7553), 467.
Stokes, A. A., Shepherd, R. F., Morin, S. A., Ilievski, F., & Whitesides, G. M. (2014). A hybrid combining hard and soft robots. Soft Robotics, 1(1), 70-74.
Vrugt, J. A. (2016). Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation. Environmental Modelling & Software, 75, 273-316.
Zeng, J., Phan, C. A., & Matsui, Y. (2015). The impact of hard and soft quality management on quality and innovation performance: An empirical study. International journal of production economics, 162, 216-226.
Zhu, Q., & Azar, A. T. (Eds.). (2015). Complex system modelling and control through intelligent soft computations. Germany: Springer.
Zhu, Q., Wang, Y., Zhao, D., Li, S., & Billings, S. A. (2015). Review of rational (total) nonlinear dynamic system modelling, identification, and control. International Journal of Systems Science, 46(12), 2122-2133.


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