Decision Making with Complete Information

Being part of a data and analytics product organization allows me to discuss with the customer their data initiatives. Most of the tier 1 organization have a transformed data foundation layer while others are moving towards the transformed data layer with data on cloud in cloud data platforms. According to Gartner “by 2025, data ecosystems will be embraced by 55% of IT organizations, resulting in a 40% consolidation of the vendor landscape.”?

But Data literacy is still a big challenge. Business Intelligence is democratized, and business analysis is mostly done using BI tools and excel, business users use these tools themselves to get what they want. Organizations are prioritizing data and analytics investments to aid better decision making.

?Increasing use of AI/ML and now Generative AI being the buzz of the industry, information management teams are trying to productize the information consumption layer shifting the controls to the business users right from data exploration to insight generation on the fly. More and more business users want to go beyond “What has happened”, to “Why it has happened” and “What could happen next”, increasing the quality, speed and accuracy with more aiding in data based decisioning or rather than supporting the decision with data.

?In today’s rapidly evolving and competitive market to ensure success data has emerged as an important asset for making decisions. Even though the business leaders realize the importance of data-based decision making, more than 70% decision makers rely on gut to make decisions and back it up with data to support the decision.

?While taking to customers and prospects there are various factors, we discussed on the ability of the business users to use the information/insights for decision making. Here are some reasons.

Transformation in decision making

definition – Decision-Making

the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options.

?definition – Intelligence

the ability to learn from and adapt to novel situations and to use that knowledge to create a desired outcome

?“Bringing together the art and science of data, insights and cognitive aids to aid take smarter decisions” is what we call Decision Intelligence (DI)

Data-driven decision making for the business

Decision Intelligence is a transformative approach it’s an advanced form of business intelligence that provides insights, predictions, and recommendations in a unified view, rather than just presenting raw data. By bringing together diverse perspectives, decision intelligence empowers us collectively, allowing for fresh voices unencumbered by traditional field-specific limitations. DI operates at three levels:

1. Decision Support: Utilizes tools like analytics and alerts to inform decisions.
2. Decision Augmentation: Employs machines to proactively aid in decisions based on analyzed data
3. Decision Automation: Enables machines to autonomously make and execute decisions based on predefined criteria. While automation is still evolving, current tools provide insights that help humans make better decisions.

DI not only supports informed decision-making but also enhances speed, accuracy, and strategic foresight. While challenges like data literacy persist, the shift towards cloud platforms and democratized data tools empowers business users to explore, understand, and predict outcomes effectively. As we continue to navigate the complexities of modern data ecosystems, adopting a tailored DI approach will be essential for sustained success and competitive advantage.

Remember that each organization’s context is unique, and addressing these challenges requires a tailored approach. By proactively addressing these issues, organizations can pave the way for successful implementation!

“May your choices reflect your hopes, not your fears.” – Nelson Mandela

Stay tuned for more insights on implementing DI and its diverse applications across industries.