The Steps to Initiating a Data Analytics Program
1. Technology, data connectivity, and data security are critical to the success of all data analytics programs.
2. Data privacy and security policies must be made a priority, planned for, implemented and after implementation, complied with.
3. Data collection can be simplified when included in a full project plan with each task carefully defined. When working with an experienced project team with expertise, innovation, and respect for data security protocols. Data collection and compliance go hand in hand and planning for both in parrellel can reduce the risks associated with this aspect of analytics implementation.
4. Data warehouses and that provide organization of data elements and definition are essential to preparing data for analysis.
5. Strategy, goals, and realistic timelines for observing campaign results is important for a clear evaluation of an analytics program, and organizations should be prepared to add or delete data fields and measure results to determine if changes result in improvement.
6. Test data and results through reporting and scrutiny to assure that data are loaded as planned, computation results are accurate, and analytics are measuring what they are intended to do. Most importantly, can your results be relied on for validity and providing results and insights that can be used to inform and improve performance.
7. Make sure to have “buy-in” from senior leadership, and “adoption” from staff members. These are two strategic tactics that increase the value of the analytics investment.
8. Moving to a data-driven organization is a strategic initiative which may not be appreciated or understood by all. Keep in mind that change management should be announced from the top in order for all management and staff to acknowledge the changes. It is prudent to anticipate questions and perhaps some initial resistance. However, remember that perseverence wins the race in implementation of the analytics program.
9. Analyze results and publish the analytics so management and staff can understand results. Collaboration on results fosters process changes toward performance improvement and goal attainment.
10. Keep in mind that an analytics program is perpetual and a “live” activity. A program crafted with measurements, clear goals and objectives at both the operation and analytics levels is a optimistic beginning. A monitoring program that measures data and model accuracy can increase the liklihood of a program’s success.