7 Data Analytics Areas

Data analytics aids businesses to convert their raw business data into actionable insights. This environment is constantly changing, hence it is important for software companies to keep up and ensure businesses have the best services.

  1. Financial Analytics

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  • Monitoring revenue, expenses, and profitability of a company.

  • Profitability analysis and financial performance management.

  • Budget planning, formulating long-term business plans.

  • Financial risk forecasting and management.

    2. Customer Analytics

  • Customer behavior analysis and predictive modeling.

  • Customer segmentation for tailored marketing campaigns.

  • Personalized cross-selling and upselling offers for extended customer lifetime value.

  • Predicting customer attrition and customer churn risk management.

  • Customer sentiment analysis for increasing product/service quality.

    3. Brand and Product Analytics

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  • Conducting product performance analysis.

  • Tracking customer interactions with a product to identify pain points leading to churn.

  • Conducting competitor benchmarking.

    4. Asset Analytics

  • Real-time asset monitoring and tracking.

  • Asset life cycle management.

  • Predictive and preventive maintenance.

  • Asset health prediction.

  • Designing asset maintenance and replacement strategies.

    5. HR Analytics

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  • Employee/department performance monitoring and analysis.

  • Employee experience and satisfaction analysis.

  • Employee retention strategy optimization and management.

  • Employee hiring strategy analysis and optimization.

    6. Supply Chain Analytics

  • Identifying demand drivers, consumer demand forecasting, and planning.

  • Supplier performance monitoring and evaluation.

  • Predictive route optimization.

  • Determining the optimal level of inventory to meet the demand and prevent stockouts, inventory planning, and management.

  • Identifying patterns and trends throughout the supply chain for enhanced supply chain risks management.

    7. Manufacturing Analytics

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  • Overall equipment effectiveness analysis and optimization.

  • Manufacturing process quality prediction and management.

  • Equipment maintenance scheduling.

  • Power consumption forecasting and optimization.

  • Production loss root cause analysis.

Conclusion

There are many areas of analytics and as software evolves, more areas will continue to develop.

For more information on data analytics and software, visit ISUCorp.ca