Data & AI
Data analytics implies building an infrastructure for data aggregation, analysis, and reporting. An experienced provider of data analytics services, Nabla Infotech delivers on simple and complex needs with tailored business analytics solutions.
Nabla Infotech helps businesses from different industries integrate, aggregate, and analyze various data types from multiple data sources to address their most deliberate needs at department and enterprise levels.
Retail Analytics
• Retail business performance analysis, monitoring sales and profitability.
• Demand analysis and forecasting.
• Multi-echelon inventory optimization.
• Assortment and merchandising planning and optimization.
• Data-driven recommendations on optimal product promotion activities.
Healthcare Analytics
• Patient health condition monitoring, condition-based alerting.
• Patient treatment optimization.
• Assessment of patient risks and personalized care plan recommendations.
• Proactive care (defining trends and patterns in patient condition requiring a doctor’s attention).
• Fraud detection in healthcare insurance.
• Medical staff workload prediction and work shifts optimization.
• Optimization of clinical space and equipment usage.
Manufacturing Analytics
• Overall equipment effectiveness analysis and optimization.
• Manufacturing process quality optimization.
• Equipment maintenance scheduling.
• Power consumption forecasting and optimization.
• Production loss root cause analysis.
Transportation And Logistics
• Operational capacity planning and optimization based on the analysis of incoming shipments, customer delivery schedules, vehicles availability, and personnel shift schedules.
• Predictive analytics for vehicle maintenance (failure prediction, recommendation of maintenance actions, etc.).
• Vehicle demand forecasting.
• Predicting optimal amounts of fuel needed based on the analysis of driving patterns.
• IoT data analytics (data on cargo temperature, humidity, etc.; data on driver behavior, data on vehicle condition, etc.) for safe cargo delivery.
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.
HR Analytics
• Employee/department performance monitoring and analysis.
• Employee experience and satisfaction analysis.
• Employee retention strategy optimization and management.
• Employee hiring strategy analysis and optimization.
• Labor cost analytics.
Asset Analytics
• Real-time asset monitoring and tracking.
• Predictive and preventive maintenance, developing asset maintenance strategies.
• Planning asset investments.
• Asset usage analytics, planning and scheduling asset modernization/replacement/disposal strategies.
Sales And Product Analytics
• Sales channel analytics.
• Pricing analytics to design pricing strategies.
• Identifying and predicting sales trends.
• Conducting product performance analysis.
• Tracking customer interactions with a product to identify pain points leading to churn.
• Conducting competitor benchmarking.
Customer Analytics
• Customer behavior analysis and predictive modeling.
• Customer segmentation for tailored sales and marketing campaigns.
• Personalized cross-selling and upselling offers for extended customer lifetime value.
• Predicting customer attrition and customer churn risk management.
• Customer sentiment analysis.
Financial Analytics
• 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.
Consulting
1. Strategic roadmap definition
2. Governance Setup
3. Technical consultancy
4. Operationalize Analytics
Insights
1. Business context mapping
2. Exploratory Data Analysis (EDA)
3. Identifying Trends
4. Data driven insights
5.Presenting insights to Business
Model creation and Model Enhancement
1. Problem definition
2. Data mining
3.Algorithm selection
4. Model training, assessment, testing and support
5. Model upgrades
Scaling
1. A/B testing
2. Optimization
3. What-if analysis
4. Model performance management
Artificial Intelligence
1. Recommendation engine
2. Opinion analysist
3. Named entity recognition
4. Media analysis
Contact
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