What are the most successful decision support implementations?

1 Define the problem

The first step in any decision support implementation is to clearly define the problem you want to solve or the goal you want to achieve. This will help you identify the relevant data, criteria, and alternatives that you need to consider. A well-defined problem also helps you communicate and align with your stakeholders, who may have different perspectives and preferences. A good way to define the problem is to use a problem statement that summarizes the situation, the challenge, and the desired outcome.

2 Choose the right tool

The next step is to choose the right tool for your decision support implementation. There are many types of DSS, such as data-driven, model-driven, knowledge-driven, or user-driven. Each one has its own strengths and limitations, depending on the nature and complexity of the problem, the availability and quality of data, the level of expertise and involvement of the users, and the desired functionality and features. You should evaluate the pros and cons of different options and select the one that best suits your needs and resources.

3 Design the interface

The interface is the part of the DSS that interacts with the users and presents the information and options. It is crucial to design the interface in a way that is easy to use, intuitive, and engaging. The interface should provide clear and relevant feedback, guidance, and explanations, as well as allow the users to customize and control their input and output. The interface should also support collaboration and communication among the users, especially if they are working in teams or across different locations.

4 Test and validate

Before launching your decision support implementation, you should test and validate its functionality, accuracy, and usability. You should conduct various tests, such as unit tests, integration tests, system tests, and user acceptance tests, to ensure that the DSS works as intended and meets the requirements and expectations. You should also validate the results and recommendations of the DSS, by comparing them with other sources, methods, or experts, and by assessing their impact and value.

6 Learn from examples

Exploring successful decision support implementations from different domains is a great way to gain insight. In healthcare, a Clinical Decision Support System (CDSS) at Brigham and Women's Hospital in Boston reduced adverse drug events by 55% and increased compliance with best practices by 40%. In business, a Revenue Management System (RMS) at Marriott International increased revenue by 5% and occupancy by 2%, through dynamic pricing and forecasting models. In education, the ASSISTments system at Worcester Polytechnic Institute improved math achievement by 75% and reduced dropouts by 50%, through adaptive tutoring and scaffolding techniques. Thus, decision support systems can help clinicians diagnose, treat, and prevent diseases; managers optimize their operations, strategies, and finances; and teachers and students enhance their learning and teaching.