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Data Driven Decision Making - Coggle Diagram
Data Driven Decision Making
Data Driven Organization:
Continuously Tests theories and ideas
Has a Continuous Improvement Mindset
Is involved in Predictive Modeling, Forecasting, and Simulations
Is always looking for variables to explain the organizational processes
Uses data as critical evidence to make decision and solve problems, and influence strategy
Data Access
Data must be accessible and able to be queried
Shareable
The departments in the organization must be willing to share their data so that all steps in the organizational process can be understood and improved
Queryable
There must be tools that allow organizational users to request data and cut the data to meet the needs of all areas in the organization
Joinable
Data should be joined to other systems and key metrics in the organization
Data Collection
An organization must first decide to collect data. When collecting data it should be timely, accurate, clean, unbiased, and trustworthy. Data scientists spend 80% of time collecting and cleaning data, and 20% of time analyzing and interpreting data.
Alerting
A good data system will have alerts to notify when data points or systems are out of range or not working correctly
Analysis
Prescriptive
Answers Why?
Forward Looking
Answers Questions
Provides Insights
Gives Findings, Recommendations, Predictions
Gives Context and a Story
Analytics Maturing
Standard Reports (low)
Ad Hoc Reports
Query Drill Down
Alerts
Statistical Analysis
Forecasting
Optimization (high)
Reporting
Once data is of good quality, and accessible it must be used for reporting