A decision support system (DSS) is an automated program that helps businesses make better decisions.
In this post, we learn what it is and how to implement one.
What Is a Decision Support System (DSS)?
Here is a concise definition of what these platforms are and why they matter:
- A decision support system (DSS) is a software system for guiding, monitoring, and controlling a decision process
- They compile and analyze large amounts of data in order to help business leaders make better decisions
- Effective use of a DSS can offer a range of benefits, from improved business performance to increased insight into the marketplace (see below)
Ultimately, the right DSS can confer a competitive advantage to organizations that use them appropriately.
How Does a DSS Work?
- Integrate a variety of data sources, such as business intelligence and competitive intelligence
- Leverage data-driven methods, such as analytics or machine learning, to generate insights based on that data
- Can be largely automated or they can incorporate more human input
- Offer predictions about that data and prescribe recommended courses of action
It should be noted that these platforms are unique, versatile, and flexible, and they can generate a wide variety of reports and outputs.
Their use cases, therefore, are equally wide-ranging, as we’ll see next.
How a DSS Can Improve Efficiency and Fuel Business Growth
The benefits of using a DSS will differ depending on how it is used, the business in question, the data the DSS has access to, and similar factors.
That being said, when used properly, a DSS can:
- Help business leaders make decisions based on data, rather than on emotions or gut feelings
- Offer insights that business leaders – or competitors – might not otherwise have access to
- Improve the outcomes of actions based on DSS-informed decisions
- Reduce guesswork and error rates
- Acclerate business growth
- Provide a competitive advantage in the marketplace
In short, a DSS can automate many of the functions that data analysts would perform, at a fraction of the cost.
How to Choose the Best Decision Support System
Though versatile, a DSS is not a generalized “virtual assistant” – these platforms have their limitations and specific use cases.
When choosing a DSS, therefore, one of the first considerations should be how it is to be used.
For instance, a DSS can be used to inform decisions around:
- Employee training and development
- Business investments
- Product development
- Sales and marketing decisions
- Customer experience development
- Digital adoption and digital transformation
Once this decision is made, business leaders should follow the same course of action they would when making any other investment decision.
Namely, it is important to evaluate vendors, those vendors’ strengths and weaknesses, their track records, price points, and related factors.
Implementing a DSS
It is important to note that implementing a DSS can be complex, since these tools are often custom-built, require integration with either internal or external data sources.
Here are a few points to consider when implementing a DSS:
1. How the DSS will be used
As mentioned, a DSS can be used in a wide range of domains, from just-in-time supply chain management to sales to competitive intelligence to radiology.
For instance, an organization building a DSS to improve the marketing funnel and the customer experience would need data such as:
- Customer experience metrics
- Marketing data
- Sales data
- Customer support interactions
- Financial data tied to these sources
By tying all of these data sources together into a single DSS, managers can then gain real-time insights and decision support functionality. This has also been called just-in-time decision support, and as computing power continues to grow, we can expect to see increased adoption of these systems.
2. The deployment process
The logistics of deploying a DSS may take weeks, months, or longer, depending on the scope and the scale of the system.
A multi-national enterprise deploying a sophisticated DSS that collects data from point-of-sale purchases, for instance, may choose to integrate new software or even new hardware.
While this may seem a bit excessive to some, this same approach is exactly what some innovative companies are doing. Starbucks, for instance, employs sensors in machines across their stores to better monitor, understand, and optimize the customer experience.
In other cases, business leaders may choose to take a smaller-scale approach or to implement the DSS through incremental change, rather than “big bang” change.
Either way, it is important to plan out the deployment process carefully, since it will require time and investment – and, as we’ll see below, it will require adaptation on the part of employees.
3. Integrating the DSS into the decision-making process
Finally, it must be remembered that change is rarely easy.
In some cases, it can even be unwelcome, so it is important to manage that change carefully.
Project leaders, therefore, should approach this change sensitively, communicate the reasons clearly, provide employee training when necessary, and do their best to maximize buy-in and minimize resistance.In short, it is important to develop a comprehensive digital adoption strategy that streamlines organizational change as much as possible – after all, in today’s changing world, the most successful organizations will be those that can stay agile and adaptable.