Penn State University’s John Jordan described the challenges with Business Analytics: there is “a greater potential for privacy invasion, greater financial exposure in fast-moving markets, greater potential for mistaking noise for true insight, and a greater risk of spending lots of money and time chasing poorly defined problems or opportunities.” Other challenges with developing and implementing Business Analytics include…
- Executive Ownership – Business Analytics requires buy-in from senior leadership and a clear corporate strategy for integrating predictive models
- IT Involvement – Technology infrastructure and tools must be able to handle the data and Business Analytics processes
- Available Production Data vs. Cleansed Modeling Data – Watch for technology infrastructure that restrict available data for historical modeling, and know the difference between historical data for model development and real-time data in production
- Project Management Office (PMO) – The correct project management structure must be in place in order to implement predictive models and adopt an agile approach
- End user Involvement and Buy-In – End users should be involved in adopting Business Analytics and have a stake in the predictive model
- Change Management – Organizations should be prepared for the changes that Business Analytics bring to current business and technology operations
- Explainability vs. the “Perfect Lift” – Balance building precise statistical models with being able to explain the model and how it will produce results
Business Analytics Best Practices
Adopting and implementing Business Analytics is not something a company can do overnight. But, if a company follows some best practices for Business Analytics, they will get the levels of insight they seek and become more competitive and successful. We list some of the most important best practices for Business Analytics here, though your organization will need to determine which best practices are most fitting for your needs.
- Know the objective for using Business Analytics. Define your business use case and the goal ahead of time.
- Define your criteria for success and failure.
- Select your methodology and be sure you know the data and relevant internal and external factors
- Validate models using your predefined success and failure criteria
Business Analytics is critical for remaining competitive and achieving success. When you get BA best practices in place and get buy-in from all stakeholders, your organization will benefit from data-driven decision making.
For further information on Business Analytics, check out the posts below: