Mind the gap
Last Updated November 26, 2018
The value of data is best understood when data can be linked to a specific impact, but sometimes that doesn’t happen due to gaps.
Design gaps can prevent data from moving to information. Design gaps include missing data, poor data quality, difficulty discovering or accessing data, and analysis challenges.
Expertise gaps can prevent information from moving to knowledge. Expertise gaps arise when data and information cannot be interpreted correctly due to a lack of knowledge.
Leverage gaps can prevent knowledge from moving to action. Leverage gaps occur when organizations have sufficient knowledge but lack the ability to move that knowledge to action.
Execution gaps can prevent an implemented action from achieving the desired outcome. This could be due to poor implementation or it could result from a design or expertise gap.
Each gap represents different challenges that must be addressed to maximize the impact and value of data (Figure 1).
Figure 1: Types of gaps that can prevent data from having an impact.