A week's delay in the market launch of a pharmaceutical, causes a company to lose revenue by as much as 2%. Mundane, iterative, and routine chores delay employee and team focus on more important product launches. Tasks that limit human intervention because of size, scope or location attribute to this delayed drug launch as well. These have built a strong case for robotic and enhanced process automation, and the more advanced cognitive technologies. Cognitive automation augments human intelligence to solve problems better. As enterprise leaders, you will be better off to adopt a judicious mix of robotic process automation (RPA) for immediate short term benefit realization and pilot cognitive computing technologies to tackle complex challenges in the long run. This progressive strategy for automation maturity will smoothen your organization change management journey as well.
To give you a flavor of the long term advantages of cognitive automation, you can easily
- avoid significant time-to-market delays
- leverage employee expertise for high-end and core research and development
- gain 360 degree customer insights
- identify source of malfunction of a device or service and determine corrective action
- analyze and process voluminous plain language data into structured inputs
- improve decision making from expedited data to interpretation to execution business practices
How does cognitive automation touch lives through healthcare?
If you are a researcher, cognitive analytics by pairing capacious clinical research with patient data, can provide you insights and solutions for new and more effective pharmaceuticals. For patients, this helps in early identification of risk factors and treatment. If you are attending PegaWorld 2017, you can view a demonstration of our solution emergency healthcare assistance during travel.
At a slightly less complex level, you can deploy Robotic Process Automation for account management, claims processing, underwriter support, customer support, billing, collections, reconciliation, reporting, and analytics consolidation.
How can life science leverage cognitive technologies beyond back office operations?
You will find cognitive automation impacting your life science business in the following four major areas:
Clinical trial process: Drug resistant microbes and emerging health risks with changing lifestyles place unrealistic demands on companies to accelerate pharmaceutical launches into markets. Typically, approval processes are stringent. Identifying and globally accessing specialized patient population for clinical trials can further complicate your international approval process. Advanced automation can help you achieve accuracy and speed in clinical trial processes. Here's how:
- Translating images and scanned documents into usable data
- Rule-based automation for document tracking and submission requirements
- Machine learning for product strategy and document creation
- Reaping efficiencies with routine, structured, and iterative tasks such as data collection, statistical data entry and quality oversight, regulatory submissions, and sorting compliance issues. These typically result in optimizing your outsourcing operations with contract research organizations.
Regulatory compliance: Cognitive technologies can simplify the regulatory compliance process, thats becoming more stringent by the day. Cognitive automation with built-in compliance makes actions traceable and auditable and keep pace with changing regulatory demands. For example, a case prioritization solution sifts through various case reports and automatically identifies serious cases for reporting, thereby eliminating non-compliance related penalties. We haveimplemented this for a German Pharma company.
Pharmacovigilance: If you are a pharmaceutical manufacturing organization, monitoring adverse reactions of drugs post their license for use is crucial to avoid legal liabilities and ensure patient safety and regulatory compliance. Cognitive automation helps improve accuracy in pharmacovigilance. While you can deploy rule based automation for data capture and accurate data entry, machine learning lends itself for adverse event monitoring and customer service. You will find cognitive learning handy for analysis of medical reports, quantitative findings, and quality assurance. One very common solution paradigm applicable is automation within single case processing by intelligently managing unstructured data and providing judicious insights to your case handlers. It intends to achieve better operational efficiency and consistency without compromising on quality. Maintaining or even reducing the overall spending is an added benefit.
Strategic application of data and analytics: As a life science organization, improving patient health outcomes is your sole competitive advantage. To achieve this you will need reliable data on health statistics of a particular population, total cost of disease care, and medication compliance patterns. Digitalization of such data capture and management improves accuracy ruling out human errors. As this big data moves between healthcare facility management, supply chain, and procurement systems, cognitive automation provides real-time access to this data. What's more, it enables useful interpretation of this big data to help you accelerate clinical decisions. For a Swiss Pharma company, our case narrative generation tool contextually aggregated data from multiple systems and generated a narrative in a pre-defined format.
To find out more about our cognitive automation capabilities, visit us at Booth #5, PegaWorld 2017, Las Vegas or write to us at email@example.com.