The technology is overpowering the traditional business models, and each sector is gradually going the digital way to meet the evolving customer expectations. Life insurance is a sector that is still in the nascent stages of digitization due to the amount of complexity and sensitivity it involves. Insurance startups are hell-bent on leveraging the new technologies to remodel the design and delivery of the life insurance.

Insurance startups are making use of analytic and digital tools to develop life insurance products that are flexible and fast to deliver. The goal of these InsurTech innovations is to decrease the total time for the application process and create a comfortable setting for the customers. The key to implementation of these innovations is that they should be compliant with the insurance law and regulations.

The InsurTech innovations for life insurance will include:

1. RPA and AI for core processes:

The automation of core processes is essential as it helps to speed up the processing of the policies and servicing customer requests. RPA (Robotic process automation) and AI work together to process the structured and unstructured data respectively. AI backed Insurance chatbots can help the consumers to chat and converse with their providers and get solutions to their queries immediately. InsurTech as a service need to handle large volumes of data obtained from connected devices like the social media and other resources which can be easily done through automation. As there is a lot of paperwork involved with life insurance policies, automation is a great way to avoid human errors and save some time.

2. Smart contracts:

Blockchain has deeply impacted the technology sector and the blockchain based smart contracts are a game changer in automating the life insurance policy claims. It works on the concept of the decentralized ledger where each customer has a copy of the ledger, and he can commit to a transaction independently. The smart contract can be processed automatically based on a set of pre-defined conditions. It is a great way to enhance the operational efficiency and process the claims quickly.

3. Predictive analysis:

Predictive analysis plays an important role to analyze the needs of the current as well as future customers. Life insurance companies can make use of the actionable analysis to find the past as well as the real-time trends and accordingly plan out their strategy. It helps to design personalized offerings based on the inputs from the customers. InsurTech consulting services need this information for providing meaning consultancy to their customers.

4. Advanced analytics for fraud prevention:

The reports suggest that insurance companies suffer losses of at least 3% due to fraudulent activities. So, the insurance companies are determined to leverage the benefits of advanced analytics that is backed by AI for a more trusted, reliable and transparent environment with their customers. The customer data from various resources like mobile devices, social media channels are analyzed and monitored continuously for any behavioral patterns anomaly.

5. Cloud technology:

Life insurers are also leveraging the capabilities of the cloud for it is capable of handling huge volumes of data from varying sources like the wearables or the social media channels or any other electronic devices. The cloud is also beneficial when it comes to saving IT deployment costs due to the inflexibility of IT infrastructure, in cases of underuse and under capacity.

Technical innovation in the field of life insurance has just started to evolve. The above-mentioned technical aspects will form the foundation of InsurTech innovation and will even go far beyond it in the coming future. We can wait and see how it will transform the life insurance sector in the near future.

Know the Mantra Labs capabilities in InsurTech and reach out to us for any query.

References:

https://www.jdsupra.com/legalnews/insurtech-innovations-in-life-insurance-69458/

https://www.capgemini.com/wp-content/uploads/2017/12/life-insurance-top10-trends-2018.pdf

https://www.capgemini.com/2018/06/insurtech-opens-new-life-insurance-frontiers/

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

By : Divyanjali Gupta

Published on Jul 31, 2025

Data Science Manufacturing Analytics Smart Manufacturing

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

Aspect	What You Should Know
1. Why Static Reports Fall Short	Delayed insights after issues occur Disconnected systems (ERP, MES, sensors) No real-time alerts or embedded decision logic
2. What Real-Time Dashboards Enable	Track OEE and downtime in real-time Predictive maintenance using sensor data Dynamic inventory heat maps Quality linked to operators
3. Dashboards That Drive Action	Role-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 Dashboards	Unified 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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