How to Use Data Driven Decision Making Tools

The article explains that in modern organizations, data-driven decision-making tools must provide a centralized, enterprise-wide analytic platform that supports all stages of the decision lifecycle—from data modeling and discovery to sharing insights—enabling diverse users across departments to collaborate securely and efficiently, unlike limited personal BI tools that lack governance and scalability.

In today’s organizations, more individuals are making decisions that were traditionally made by executives. The fast-paced business environment requires quicker action, and organizations can no longer wait for busy executives to make every single business decision. It is crucial that these new decision-makers have access to accurate, centralized data to make the best business choices possible.

At data-driven organizations—those that use BI solutions at every stage of the decision lifecycle—multiple users across different departments are able to access, explore, and collaborate on numerous data models. They are also confident that the data they are using to make decisions is the same data that others are using to make their own separate decisions.

Many personal productivity-based BI tools cannot support today’s data-driven organizations because they don’t provide a complete enterprise framework. They operate at the desktop level and make it difficult for employees to share data and insight. Only an analytic platform featuring a structured and governed end-to-end workflow can provide the structure required for BI deployments that support many different users, from analysts to everyday business users.

True analytic platforms support every stage of the decision lifecycle. They can model data and prepare it for analysis. They have data discovery capabilities that allow users to analyze the data, understand risks, predict certain outcomes, evaluate numerous courses of action, and decide on the best one. They also give users of all types the power to assemble curated data in a dashboard environment where they can share it meaningfully with others and even securely broadcast it to others within the organization.

Not only should the analytics platform support the entire decision lifecycle, but it should also be so simple that all types of users can use it, no matter their role.

IT Professionals/Administrators should be able to manage security, user access, and infrastructure.
Power users should be able to create content and build reports, and connect to multiple data sources to conduct advanced analysis.
Decision-makers should be able to access and reuse content created by other users to conduct analysis and make decisions; they need to have full trust in this content.
Knowledge workers should be able to visit the platform a few times a week depending on their specific needs and be able to explore content and find the information they need easily.

True platform-based analytic solutions are fundamentally different than personal productivity tools because they enable all users across an organization to engage in the decision lifecycle. Personal productivity tools exist on individual users’ desktops, and there is no reliable way for employees to collaborate or ensure governance. An ideal deployment is managed by IT, but allows self-service. This results in an environment where more users can participate in the decision-making process.