How Interoperability and Machine Learning Can Lay the Foundation for Better Decision Making

In today’s world, where technology is constantly evolving, interoperability has become a crucial element for companies to run their operations more efficiently. Successful organizations understand that data is at the core of decision-making, but many struggle to not only access the right data, but to bring it together in a way that provides actionable insights. Interoperability is the baseline for unifying systems and data.

Being able to connect systems and facilitate exchange of information between different systems, can improve efficiency and productivity significantly. When systems are integrated and interconnected, data can be easily transferred between them without the need for manual intervention. This can save time and reduce the potential for errors.

The baseline is unifying the right data, then employing the right tools to analyze, visualize, and report on the data in a meaningful way that enables your teams to identify trends, patterns, and relationships to drive better, faster decisions.

This is where machine learning (ML) comes in. Using ML to inform decision making can be a powerful tool for individuals and organizations. Through artificial intelligence (AI) that allows systems to learn from data and make predictions or decisions without being explicitly programmed to do so, interoperability and ML can help organizations gain deeper, more meaningful insights to drive better decisions. Here are 3 ways how ML can improve decision-making.

Reduce bias

One of the main benefits of using ML to inform decision making is that it can help to reduce the potential for bias. Traditional decision making processes often rely on subjective judgement and can be influenced by personal bias. By using ML, individuals and organizations can remove the potential for bias and make decisions based on factual data.

Improve accuracy

Additionally, ML can help to improve the accuracy and precision of decision making. By analyzing large amounts of data, ML algorithms can make more accurate predictions and estimations than would be possible with human judgement alone. This can help to reduce the potential for errors and increase the likelihood of success.

Automate processes

Furthermore, ML can help to automate decision making processes, making them more efficient and effective. By using ML algorithms, individuals and organizations can automate complex decision making tasks and free up time and resources for other activities.

Everything comes back to interoperability and interconnectedness to ensure that you can get to the right data and get the most from it.

Are your systems connected so you can get actionable insights for better decision-making? Contact us today to find out how we can help.