While data today has helped the world understand the situation in a better manner and be better at decision-making, it has some drawbacks and their magnitude end up causing a huge negative impact on the entity concerned. Some of the drawbacks have been explained in excruciating detail in order to comprehend them:
- Poor Alignment within teams:
There are alignment issues within departments of an organization. Only a selected members of a team are given to work on data analytics and the results are shared with only a limited number of executives. But the observations made by these teams may carry less value or have a very small impact on organizational metrics.
2. Poor commitment and patience:
Solutions of analytics are not tough to apply but they are expensive, and the Return on Investment is not quick. If the current data is not there, it may take time to put procedures in place to start collecting the data.
3. Complexity and Bias:
Some of the tools of the analytics which are developed by the company are more of a black box model. What is inside the box is not clear or the method which the system applies to learn from data and create a model is not evident.