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Cognitive Approach VS Digital Approach to Insurance

Digital transformation has gone from talk to action, with a momentum that shows no signs of slowing down. As cognitive capabilities have penetrated process, people, technology, things, augmented intelligence and decision making; the cognitive approach to insurance business is no longer considered a back-office ‘efficiency play’. 

A cognitive computing system replicates human intelligence and comes up with solutions for largely ambiguous and complex situations. Implementing this cognitive capability in Insurance enhances customer insights and deduce customer feel through interaction insights, sentiments and connectedness. 

In Insurance, where companies are constantly tweaking business models to improve profitability, the digital approach to insurance is falling short of industry expectations. The ‘Cognitive’ approach is a step ahead of the ‘Digital ‘approach to insurance, and Data is the key ingredient to going cognitive.

Cognitive Insurance a step ahead of Digital Insurance.

The word cognitive is often used interchangeably with the term Artificial Intelligence. However, there are subtle differences between the two, in terms of their purpose and application. Cognitive computing is a process used to describe AI systems that aim at implementing human thought processes such as real-time analysis of the environment, context and intent analysis; and the ability to solve problems. Where AI relies on algorithms to solve a problem, cognitive computing systems have higher goals of creating algorithms that mimic the human brain’s reasoning process to solve a number of problems with changing data and problems.

The purpose of going cognitive in insurance was created solely with the purpose of reducing human effort and refining the existing process across various insurance verticals. 

Examples of cognitive insurance use cases.

  • Traveller’s Insurance Group had sent a fleet of 65 drone surveillance operating-agents to Houston in order to assess the damage from Hurricane Harvey -the costliest tropical cyclone in recorded history
  • USAA had rolled out an Intelligent Personal Assistant, using Amazon Alexa and Clinc that has insurance industry-specific deep vocabulary and knowledge, that goes beyond the capabilities of traditional chatbots or digital solutions. 
  • Liberty Mutual introduced a new app to help drivers involved in car accidents, to quickly assess the damage to their car in real-time using a smartphone camera. The app provides damage-specific repair cost estimates. 
  • AXA Insurance implemented a Google Tensor Flow-based application by using deep analysis of customer profiles. The application can optimize pricing by predicting traffic accidents with nearly 78% accuracy. 
  • Fokoku Mutual, a large Japanese Insurance company, has replaced it’s 34 strong claims assessment workforce with an implementation of IBM Watson Explorer AI solution. The solution can analyze and interpret claim data including unstructured text, images, audio and video to decide policy payouts. 

In the past, insurance industry professionals made decisions based on experiences and historical data. A cognitive approach, to insurance business solutions, is at the helm of a new wave bringing innovation and transformation to insurance. These cognitive capabilities enable insurers to make strategic decisions based on a set of data which continuously updates in real-time, thereby leveraging AI to bring automated efficiency to insurers while delivering the best possible experience to the insured user.
  

 

 

References: 

https://www.mantralabsglobal.com/blogs/cognitive-automation-and-its-importance/ 

Use cases:
https://www.linkedin.com/pulse/cognitive-use-cases-insurance-sushil-pramanick-fca-pmp/  

https://www.lntinfotech.com/wp-content/uploads/2018/02/Moving-from-a-Digital-Insurance-Business-to-a-Cognitive-Insurance-Business.pdf  

https://searchenterpriseai.techtarget.com/definition/cognitive-computing

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Smart Manufacturing Dashboards: A Real-Time Guide for Data-Driven Ops

Smart Manufacturing starts with real-time visibility.

Manufacturing companies today generate data by the second through sensors, machines, ERP systems, and MES platforms. But without real-time insights, even the most advanced production lines are essentially flying blind.

Manufacturers are implementing real-time dashboards that serve as control towers for their daily operations, enabling them to shift from reactive to proactive decision-making. These tools are essential to the evolution of Smart Manufacturing, where connected systems, automation, and intelligent analytics come together to drive measurable impact.

Data is available, but what’s missing is timely action.

For many plant leaders and COOs, one challenge persists: operational data is dispersed throughout systems, delayed, or hidden in spreadsheets. And this delay turns into a liability.

Real-time dashboards help uncover critical answers:

  • What caused downtime during last night’s shift?
  • Was there a delay in maintenance response?
  • Did a specific inventory threshold trigger a quality issue?

By converting raw inputs into real-time manufacturing analytics, dashboards make operational intelligence accessible to operators, supervisors, and leadership alike, enabling teams to anticipate problems rather than react to them.

1. Why Static Reports Fall Short

  • Reports often arrive late—after downtime, delays, or defects have occurred.
  • Disconnected data across ERP, MES, and sensors limits cross-functional insights.
  • Static formats lack embedded logic for proactive decision support.

2. What Real-Time Dashboards Enable

Line performance and downtime trends
Track OEE in real time and identify underperforming lines.

Predictive maintenance alerts
Utilize historical and sensor data to identify potential part failures in advance.

Inventory heat maps & reorder thresholds
Anticipate stockouts or overstocks based on dynamic reorder points.

Quality metrics linked to operator actions
Isolate shifts or procedures correlated with spikes in defects or rework.

These insights allow production teams to drive day-to-day operations in line with Smart Manufacturing principles.

3. Dashboards That Drive Action

Role-based dashboards
Dashboards can be configured for machine operators, shift supervisors, and plant managers, each with a tailored view of KPIs.

Embedded alerts and nudges
Real-time prompts, like “Line 4 below efficiency threshold for 15+ minutes,” reduce response times and minimize disruptions.

Cross-functional drill-downs
Teams can identify root causes more quickly because users can move from plant-wide overviews to detailed machine-level data in seconds.

4. What Powers These Dashboards

Data lakehouse integration
Unified access to ERP, MES, IoT sensor, and QA systems—ensuring reliable and timely manufacturing analytics.

ETL pipelines
Real-time data ingestion from high-frequency sources with minimal latency.

Visualization tools
Custom builds using Power BI, or customized solutions designed for frontline usability and operational impact.

Smart Manufacturing in Action: Reducing Market Response Time from 48 Hours to 30 Minutes

Mantra Labs partnered with a North American die-casting manufacturer to unify its operational data into a real-time dashboard. Fragmented data, manual reporting, delayed pricing decisions, and inconsistent data quality hindered operational efficiency and strategic decision-making.

Tech Enablement:

  • Centralized Data Hub with real-time access to critical business insights.
  • Automated report generation with data ingestion and processing.
  • Accurate price modeling with real-time visibility into metal price trends, cost impacts, and customer-specific pricing scenarios. 
  • Proactive market analysis with intuitive Power BI dashboards and reports.

Business Outcomes:

  • Faster response to machine alerts
  • Quality incidents traced to specific operator workflows
  • 4X faster access to insights led to improved inventory optimization.

As this case shows, real-time dashboards are not just operational tools—they’re strategic enablers. 

(Learn More: Powering the Future of Metal Manufacturing with Data Engineering)

Key Takeaways: Smart Manufacturing Dashboards at a Glance

AspectWhat You Should Know
1. Why Static Reports Fall ShortDelayed insights after issues occur
Disconnected systems (ERP, MES, sensors)
No real-time alerts or embedded decision logic
2. What Real-Time Dashboards EnableTrack OEE and downtime in real-time
Predictive maintenance using sensor data
Dynamic inventory heat maps
Quality linked to operators
3. Dashboards That Drive ActionRole-based views (operator to CEO)
Embedded alerts like “Line 4 down for 15+ mins”
Drilldowns from plant-level to machine-level
4. What Powers These DashboardsUnified Data Lakehouse (ERP + IoT + MES)
Real-time ETL pipelines
Power BI or custom dashboards built for frontline usability

Conclusion

Smart Manufacturing dashboards aren’t just analytics tools—they’re productivity engines. Dashboards that deliver real-time insight empower frontline teams to make faster, better decisions—whether it’s adjusting production schedules, triggering preventive maintenance, or responding to inventory fluctuations.

Explore how Mantra Labs can help you unlock operations intelligence that’s actually usable.

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