Data Delivery

Data delivery is as important as the development of world-class analytics: data that does not suit the use or the capabilities of its recipient will not impact an organization and will not help a business realize value.

Effective data delivery requires understanding: (1) the range of usages to which the data is to be put; (2) the technical capabilities of the user of the data delivery object; and (3) the business impact the data is intended to produce.

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The diagram shows a range of Data Use Scenarios; those  in green illustrate specific requirements for a particular application while Text Analytics, in grey, was introduced as an option for consideration. Often an organization will acquire a Business Intelligence or BI technology focused on Descriptive Analytics without considering the wide range of usage scenarios an organization needs. The range of Data Use Scenarios also affects the Technical Architecture required to support them.

Technical capabilities of users are important also. This is the reason data visualization is so popular: it represents information visually so it is conveyed more effectively. A failing of many BI implementations is the reliance on multiple drill-down clicks to get to the information needed, an approach that may not bother power users but tries the patience of many users to the point they avoid using the analytic solution.

The bottom line is that value realization can only occur when the data that is delivered has a beneficial business impact. This requires aligning the intended business impact with the appropriate Data Use Scenarios and the capabilities of the business people who will need to turn the analytic results into a business benefit.