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Data Driven Decision Making

What is Data Driven Decision-Making?

Data-driven decision making (DDDM) is an approach to business governance that values decisions that can be backed up with verifiable data rather than making decisions that are intuitive or based on observation alone, supporting competitive advantage.

The success of the data-driven approach is reliant upon the quality of the data gathered and the effectiveness of its analysis and interpretation.

Business intelligence tools are a strong resource to analyze the data and allow easy dashboards customization to display the important information in real time. The changes in how data can be mined and visualized allows business executives who have no technology backgrounds to be able to work with analytics tools and make data-driven decisions.

Business Intelligence to support Digital Processes 

Business Intelligence (BI) is a set of processes, architectures, and technologies that convert raw data into meaningful information that drives profitable business actions.  

BI has a direct impact on organization's strategic, tactical and operational business decisions. These tools perform data analysis and create reports, summaries, dashboards, maps, graphs, and charts to provide users with detailed intelligence about the nature of the business, supporting fact-based decision making. 

 

Performance Dashboards Development 

Defining the dashboards and using business intelligence will allow you to have a very nice visual appeal to the different levels of the organization that will help you to monitor the performance of your business with a reduction of the administration effort. These dashboards will require the definition of the lead and lag key performance indicators, data collection and analytics tools. 

A Key Performance Indicator (KPI) is a measurable value that demonstrates how effectively a company is achieving key business objectives. 

 

Alerts, Alarms and Predictive Processes 

Predictive analytics can be defined as the procedure of condensing huge volumes of data into information that humans can understand and use. 

Descriptive analytics based on obtaining information from past events has evolved into predictive analytics, which attempts to predict the future based on historical data. With this ability it is possible to set alerts and alarms that will indicate when the equipment function is degrading and when you need to replace the spare. When linked to the CMMS should trigger a Work Order and information to the Technician or supervisor to execute the work and ensure the equipment is working again with the smallest downtime possible. 

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