Whitepapers

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How Industrial IoT is Influenced by Anomaly Detection & Prediction

The biggest problem facing businesses in today’s myopia is that only 20 percent of all problems or anomalies that occur are predicted and understood beforehand. This means that around 80 percent of the problems businesses face are unpredicted, and the business is not prepared to handle them because of below-par anomaly detection. Traditional methods of anomaly detection are not getting the job done. 

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5 Questions Automakers Should Ask to Improve Asset Uptime

The modern automotive industry is generating enormous volumes of manufacturing data every day. By analyzing this data, automakers can drive significant improvements in two critical areas: the initial production of their vehicles and the reliability of vehicles over their lifetimes.

Are you using your data to its fullest? This checklist will help you evaluate your existing automotive asset management strategy to ensure you’re getting the most out of your data.

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Kickstart Your Automotive Assets with Cognitive Predictive Maintenance

You lead a large automotive manufacturing unit. With the goal of keeping P&L figures on a positive trajectory, you are responsible for meeting manufacturing targets while keeping automotive asset maintenance costs under control. You are also tasked with keeping your factories operating smoothly with no unplanned outages or downtime.
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Time to Relook at Asset Reliability: Move from Reactive to Predictive

For global industrial enterprises, critical asset failure continues to be the leading operational risk. Cognitive predictive maintenance helps in accurately diagnosing your asset health, before impending issues can negatively impact asset performance. Download this whitepaper to learn more about the value of cognitive predictive maintenance.
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Revolutionizing Manufacturing with Industrial IoT

Physical and digital worlds are converging  in ways we could only imagine in the past. Learn how the Industrial Internet of Things hastransformed and redefined asset-intensive industries such as manufacturing.
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Putting the Health of Consumers in Their Hands

Enterprise health clouds (EHC) are enabling organizations across all healthcare verticals to create the innovative digital experiences that today’s patients want. This enables healthcare organizations to:
  • Improve the patient care experience
  • Encourage better health management
  • Reduce the overall cost of healthcare per patient

To learn more about how health clouds can help transform patient care, download our latest whitepaper.

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Forrester Wave Enterprise Health Cloud Report

Electronic health clouds are empowering the healthcare industry to embrace digital transformation and create more meaningful patient experiences. Progress Health Cloud is one of the industry’s leading electronic health clouds, providing healthcare organizations with an all-in-one HIPAA-compliant application development platform.

In fact, Progress received the highest score of all vendors in Forrester’s recent enterprise health cloud report. Download the full report and see why Forrester ranked us a “leader.”
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Progress HIPAA Compliance Checklist

For any organization that handles protected health information, HIPAA compliance should be a top priority. However, compliance is costly—ensuring HIPAA compliance for even a single digital application can cost healthcare organizations upward of $50,000. With built-in HIPAA compliance and security, Progress Health Cloud takes care of a lot of the compliance groundwork so you don’t have to. 

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Digital Health Case Studies

Learn about twelve examples of patient-centric and connected care digital health experiences founded on Progress Health Cloud.

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Consumer Health Engagement in Pharma Enabled Through the Cloud

Patients are morphing into healthcare consumers, and healthcare providers and suppliers face a tighter reimbursement landscape. Pharma and life science companies will cope by bringing data together from inside and outside of the traditional healthcare system, and quickly delivering solutions via a new generation of Enterprise Health Clouds.

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Top 10 Digital Use Cases for 2018

The transition to value-based outcomes, an aging population, and new mobile and wearable technologies are driving changes across every aspect of the healthcare industry.

Advances in digital health technologies hold great promise that healthcare can be delivered in smarter, simpler, and more cost-effective ways. Mobile technologies can foster patient engagement, enhance care team communication, reduce cost of delivery, and improve the health care experience for both patients and their providers.

The key is figuring out which apps to tackle first. This document outlines a few of the key use cases that are showing positive impact. While this isn’t an exhaustive list, it provides several great places to start on the digital health innovation journey.

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The Business Value of Progress Health Cloud

Many healthcare organizations have recognized that having a mobile presence is vital for remaining relevant and competitive, with many organizations establishing a mobile presence in one way or another. However, many of these initial attempts at establishing a meaningful mobile presence have fallen short of expectations.

With Progress Health Cloud, healthcare organizations can launch their Minimum Viable Product (MVP) app in record time while still creating great digital experiences with high user satisfaction.

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In the Pursuit of Operational Reliability: 5 Questions to Get There

With market pressures and competition intensifying at an unprecedented pace, manufacturers are aggressively searching for new growth opportunities. Unfortunately, they’re often forced to work around approximately 800 hours of downtime on a yearly basis—a significant expense in the face of the unrelenting pressure on their top and bottom lines.

Fortunately, the path to operational reliability via anomaly detection is based on sound logic—all you need to do is ask the right questions.
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Put a Big Dent in Warranty Costs

Most automobile manufacturing companies suspect warranty fraud, but aren’t sure of how to eliminate it. Existing detection methods are reactive, complex and expensive, with the manufacturer bearing the cost.
By taking a cognitive approach to anomaly detection and prediction, automakers can isolate fraudulent claims from the datasets. This enables auto companies to streamline warranty claim analysis and improve accuracy, resulting in better fraud detection and significant cost savings.
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