Decision intelligence involves a mix of different intelligence tools embedded in workflows where stakeholders feel they need them. It often involves a combination of artificial intelligence and machine learning. As a consequence, data dashboards and business analytics become more comprehensive platforms which support decisions.
An example of decision intelligence in a practical setting is a recommendation engine. These tools use analytics to suggest new products for consumers, helping them find similar interesting items to their original search. In this regard, decision intelligence becomes an extension of business intelligence. Organisations learn more about the context of a consumer’s decision, therefore building on the BI platform and providing more relevant and accessible data.
A 2021 survey by RevealBI reported 41% of companies seeing an increase in requests for data and analytics access. The most popular reason attributed to this was enabling users to make data-driven decisions – a core component of BI technologies. The survey also demonstrates an increased interest in incorporating machine learning within analytics software or dashboards.
Adding AI in this manner to a BI system develops it into a decision intelligence platform, able to provide context, predictions, and recommendations.
Gartner defines decision intelligence as a tool that enables data and analytics to inform choice models and processes for business outcomes and behaviours. In simpler terms, this means the tools use analytics to help customers, employees, and business partners to make decisions by handing over relevant data and analytics. Gartner also predicts that more than a third of larger organisations will use decision intelligence tools by 2023.
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Potential application of decision intelligence
In industries where people have to make decisions based on vast amounts of fast-moving data, AI and machine learning can help make better decisions. Certainly, this is the case where there is much potential risks for companies when making decisions. Having informed and relevant data to shape decisions will help key stakeholders feel more comfortable with their options. An example would be a cyber-security organisation, who handle information that is constantly changing and updating. Accordingly, using decision intelligence would provide confidence when making decisions through providing relevant data as it happens.
Consistency in decisions can also be achieved by using decision intelligence. Whilst employees can attend training courses to become aware of potential bias against customers, such as in a banking setting, many uncontrollable variables, such as personal emotions, can override this. These tools therefore can provide more objective recommendations for decisions, allowing a more consistent business process.
Decision intelligence is sure to become a dominant force in the BI sector in the future. The augmentation of human and artificial intelligence will create a greater opportunity for organisations to use data intelligently.