$Billions are invested in BI & Analytics each year yet there is evidence of disappointing returns- operational & financial- see "Damning analysis of Analytics".
One reason is definitely lack of planning which is covered in the article link below. Others are:-
- Line of Business People licensing products with no idea about data sources and integrity
- No access to important data- especially unstructured.
- Focus on pretty visualisation rather than actionable insights
- Lack of context- unless embedded in enterprise apps analytics are remote and ignored
- Cognitive bias- the tendency to want BI & Analytics to reflect a person's biased ideas.
I explore these themes at www.analytics.world
If you want to be effective decision makers at least ,make sure you plan well as described below and don't even think about AI, predictive analytics, streaming data, big data analytics until you do so.
...much of the focus is put into the technical requirements of connecting the tool to the data source. However, these steps are only a bare minimum for successful business analytics. It is equally important to create a comprehensive plan for the day-to-day usage of the BI solution. This is especially true in large enterprise deployments, where there can be many different stakeholders, goals and requirements involved in the implementation. After the technical requirements are met, the final phase of BI implementation begins. This phase requires working with a more business-oriented team, such as executive management and financial analysts. It is up to business analysts to elicit requirements from the BI tool stakeholders, to develop meaningful business outcomes, and to write business requirements which clearly communicate all relevant technical and design details to report writers.
https://www.sisense.com/blog/requirements-elicitation-enterprise-business-analytics/
