BBDI and DDBI: Bridging the Gap Between Data and Decision-Making

Building on the insights we explored in our previous post?“Decision Making with Complete Information”, let us delve deeper into a new aspect that promises to add another dimension to our understanding.

The first step is defining the objective, identify the organizations specific goals. Are you aiming to optimize supply chain decisions, improve customer service, or enhance risk management.

Depending on the type of use case you want to start with you can decide to implement DI by taking either of the approach - Business-Based Decision Intelligence (BBDI) or Decision Intelligence-Based Business (DIBB). Organizations often find a balance based on their context, goals, and readiness for change. Remember, successful implementation requires leadership commitment, stakeholder buy-in, and continuous learning.

Let’s delve into the distinction between “Business-Based Decision Intelligence” (BBDI) and “Decision Intelligence-Based Business"(DDBI).?

Choose wisely based on your organization’s context and use case requirement. BBDI enhances, while DIBB transforms.

Once you enable data driven decisioning with help of cutting edge solutions/systems to deliver insights, further actions can be automated either by creating a rule based system or using AI.

?Remember:

DI is not a one-time project; it’s a collaborative journey of continuous learning and adaptation.

Almost all organization today instinctively and consistently utilize data to aid their tasks. Instead of resorting to creating extensive, sometimes spanning several years, plans to tackle issues, they are encouraged to explore how cutting-edge data methodologies could address obstacles in a matter of hours rather than, days, or weeks.