Limitations of Predative analytics (7)

 


High Costs and technical Expertise Required 

Predictive analytics can be a great tool, but it can be costly at the same time. A system installation demands a lot of resources such as sophisticated software, fast computers, and a huge amount of data storage space. The small or medium-sized business sector is usually not able to afford these tools which can make it difficult for them to get started

At the same time, predictive analytics also necessitates a skill set of a highly-qualified staff like data scientists, analysts, and programmers. These experts are able to accomplish the task of data collection, model building, and result interpretation. Nevertheless, engaging professionals with certain skills may cost you a lot and the availability of the experienced ones is usually limited.

The job is not done once the system is installed and functioning. Continuously checking, evaluating, and changing models is necessary for them to be correct. This means spending more time and allocating more resources. If no regular maintenance is provided, the model may lose its consistency and give the wrong prediction, resulting in mistakes.

For the greater part of companies, predictive analytics is a win because it is a tool that opens up new dimensions of planning, customer insights, and savings, making the bet worthwhile. However, the financial aspects and the related work are very important to be aware of. Going for small-scale ventures at first or relying on basic tools can be a good solution for the organizations to dive into predictive analytics without creating a mess.

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