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How do you customize and adapt decision support systems to different contexts and users?

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Decision support systems (DSS) are computer-based tools that help users analyze data, generate alternatives, and make informed choices. DSS can be applied to various domains, such as business, health, education, and environment. However, not all DSS are created equal. Depending on the context and the user, different DSS may have different features, functions, and formats. How do you customize and adapt DSS to different contexts and users? Here are some tips and trends to consider.

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1 Know your problem

The first step to customize and adapt a DSS is to define the problem that you want to solve or the decision that you want to make. Different problems may require different types of DSS, such as data-driven, model-driven, knowledge-driven, or communication-driven. For example, if you want to forecast sales based on historical data, you may need a data-driven DSS that can perform statistical analysis and visualization. If you want to optimize the allocation of resources based on multiple criteria, you may need a model-driven DSS that can simulate various scenarios and trade-offs.

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Randell McNair, D.B.A.

Practitioner-Scholar / Research Consultant
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When faced with a delay in construction of an off-shore production process plant being built in Angola, a multinational project team based in Houston was able to use a digital process simulation model of the original design to reengineer a cost effective temporary bypass of the plant and develop step-by-step plans to reroute the output from a newly commissioned wellhead platform to an on-shore facility. This enabled a revenue stream to help project investors navigate a sudden unforeseen drop in commodity prices that could have otherwise jeopardized funding for completion of a this multibillion dollar complex facility. The use of this DSS to empower the project team to come up with a creative solution to a wicked problem was inspirational.

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2 Know your user

The second step to customize and adapt a DSS is to understand the user who will use the DSS. Different users may have different preferences, needs, and skills. For example, some users may prefer a graphical user interface (GUI) that is easy to navigate and interact with, while others may prefer a command-line interface (CLI) that is more flexible and powerful. Some users may need a DSS that can provide explanations, recommendations, and feedback, while others may need a DSS that can support collaboration, negotiation, and learning.

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Randell McNair, D.B.A.

Practitioner-Scholar / Research Consultant
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This is where the recent convergence of technologies such as artificial intelligence, machine learning, IIoT, AR/VR/MR, advanced simulation, predictive modeling, 2D, 3D, 4D… 8D systems of interoperable ecosystems in the form of digital twins can serve as valuable DSS throughout the lifecycle of complex assets. We are no longer constrained by what any individual user might demand as an interface to the DSS. Thus, cyber-physical systems communicate with one another in real time, human-machine interfaces become ubiquitous components of a “connected worker”, orientation and training of users within advanced immersive meta-realities improves learning retention, just to name a few of the #informingpossibilities of digital twins as a DSS.

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3 Know your technology

The third step to customize and adapt a DSS is to leverage the technology that is available and suitable for your problem and user. Technology is constantly evolving and offering new possibilities and challenges for DSS development and deployment. For example, artificial intelligence (AI) and machine learning (ML) can enhance the capabilities and performance of DSS by enabling data mining, natural language processing, computer vision, and intelligent agents. However, AI and ML also raise ethical, social, and legal issues that need to be addressed and communicated.

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David Withnell

Chief Risk Officer at AXA – Global Healthcare
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The ethical and social issues of an AI or ML solution must be addressed at the outset. You ignore those and you have unstable and possibly dangerous foundations to your approach.

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4 Know your design

The fourth step to customize and adapt a DSS is to design the DSS in a user-centered and context-aware way. Design is not only about the appearance and functionality of the DSS, but also about the user experience and the value proposition of the DSS. Design involves multiple aspects, such as usability, accessibility, reliability, security, and aesthetics. Design also involves multiple methods, such as prototyping, testing, evaluation, and iteration.

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5 Know your evaluation

The fifth step to customize and adapt a DSS is to evaluate the DSS in terms of its effectiveness, efficiency, and satisfaction. Evaluation is not only a final step, but also an ongoing process that can provide feedback and insights for improvement and innovation. Evaluation can be done in various ways, such as experiments, surveys, interviews, observations, and analytics. Evaluation can also involve various stakeholders, such as users, developers, managers, and experts.

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6 Know your trends

The sixth and final step to customize and adapt a DSS is to keep up with the trends and developments in the field of DSS research and practice. DSS is a dynamic and interdisciplinary field that is influenced by various factors, such as technology, society, economy, and environment. Some of the current and emerging trends in DSS include cloud computing, big data, blockchain, internet of things, social media, gamification, and personalization.

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How do you customize and adapt decision support systems to different contexts and users?

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6

1 Know your problem

2 Know your user

3 Know your technology

4 Know your design

5 Know your evaluation

6 Know your trends

Decision-Making

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How do you customize and adapt decision support systems to different contexts and users?

1

2

3

4

5

6

1 Know your problem

2 Know your user

3 Know your technology

4 Know your design

5 Know your evaluation

6 Know your trends

Decision-Making

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