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Posted on Posted in Digital transformation, General topics Tagged with , , , , , ,

In the age of disruptive business models and constant competition, the travel and hospitality industry, like most industries, needs to deliver services in real-time. The Covid-19 pandemic has created a significant shift in the industry with a greater demand for competitive pricing to prevent loss of market share, targeted marketing to build loyalty, optimizing company staff, real-time inventory tracking, all of which require real-time data analysis. Companies must reinvent themselves into agile, connected travel platforms that go beyond the realms of smart phones and other wearable devices. 

Technology advances can enable highly personalized user experiences across a host of devices. For instance, form factors would not be limited to AR/VR glasses alone but extend to other wearables like contact lenses as well. Hearing devices could cater to selective hearing or provide real-time translation. However, these personalized experiences will further increase the need for heavy data management and processing as well as requirements for improved data privacy and security.

Meanwhile, customer preferences for better sanitary facilities, improved travel insurance coverage on trip cancellations, medical coverage, health checks and screening, touchless payments, etc. have also increased pressure on the industry.

Driving change to anticipate your needs

The travel and hospitality industry has risen to these concerns and opportunities in a revolutionary way, with cloud at the center. Here are a few purpose-built solutions targeted to anticipate customer needs.

Personalizing experiences  

Processing data at scale and generating predictive insights can help deliver highly personalized experiences to surprise and delight customers. Towards this, cloud partners like AWS use a comprehensive range of AI/ML services coupled with targeted communications, marketing campaigns, and tailored recommendations across a variety of channels, to deepen brand loyalty.

For instance, McDonald’s says it has enabled a faster, easier, and more rewarding drive-through experience using AWS technology. 

Staying connected 

An IOT suite of products can help achieve seamless connected experiences across a host of devices. Computer-vision technology that analyzes images and videos, aids in identity verification and surveillance during travel. AI-enabled chatbots with natural-sounding human speech capabilities, engage with customers to manage bookings, field inquiries, collect feedback, and deliver 24×7 automated assistance. AWS provides customers omnichannel engagement, over scalable cloud solutions with reliable and personalized customer service.

For instance, Priceline, a leading online travel company, states that it has optimized customer service during 3x call volume increase.

Optimizing operations and IT 

The airline industry uses forecasting for crew scheduling, fleet, and equipment management. Similarly, hotels predict guest inflow, make inventory adjustments, and release dynamic pricing offers. With real-time streaming and data processing capabilities, apps can be built to analyze video streams and live feeds from IOT devices. These detect fraud, which improves security and operational efficiency. AWS’ forecasting capabilities also provide actionable intelligence, based on ML, to help companies meet upcoming demands. It reduces IT costs by offering access to unused compute capacity at discounted prices and providing serverless technologies with pay-for-use billing model. 

For instance, Domino’s Pizza says it has increased the speed of its service delivery by using AWS for predictive ordering.

Reducing carbon footprint

Hotels use smart IOT sensors and automated systems for facility management, energy management, predictive equipment maintenance, and water metering. AWS brings together AI, ML, and IOT devices to make travel more sustainable. By monitoring fuel consumption, AWS provides recommendations that can be used to reduce emissions. Route optimization using AI/ML models reduces flight lengths and therefore fuel use.

For instance, Qantas Airlines cloud-based flight simulator helps to save millions of dollars in fuel costs each year.

The travel and hospitality industry has witnessed a massive slowdown due to the Covid-19 crisis. However, the cloud has presented effective ways to swiftly innovate, deliver personalized connected experiences, improve security, and contribute to a greener environment.

Author Bio

tcs

E-mail:  u.sircar@tcs.com

Ujjal Sircar is a technology leader within the Travel Transportation & Hospitality unit at TCS. Ujjal and his team helps enterprises build their digital transformation roadmap to enhance customer experience, increase operational efficiency, and enable digital growth. He along with his team have built solutions primarily for the Travel & Hospitality industry that enable enterprises to remain viable through agility and innovation. In his 20+ years of progressive IT career, Ujjal has assumed various responsibilities which include technology consulting, delivery direction, program management, and agile coaching. He is a distinguished Contextual Master in TCS and has a successful track record of working with leading enterprises spanning domains like Travel, Manufacturing, Life Sciences, and Human Resources.

To learn more, visit us here. 

Cloud Computing

Posted on Posted in Digital transformation, General topics Tagged with , , , , , ,

Real World Evidence (RWE) refers to the analysis of Real World Data (RWD), which is used by life sciences companies and healthcare organizations to securely obtain, store, analyze, and gain insights about the functioning of a drug or medical invention. RWE helps medical professionals and other stakeholders demonstrate the value of a particular drug’s effectiveness in treating medical conditions in a real-world setting.

Today, life sciences companies have a huge opportunity to unlock the potential of RWD and improve patient outcomes.

Why the buzz around RWE?

For some time now, the use of mobile devices, computers, and different mobile equipment to collect and store massive amounts of health data has been accelerating. This data has the potential to allow life sciences companies to conduct clinical trials more effectively.

Moreover, the introduction of more sophisticated and modern analytical capabilities has paved the way for advanced analysis of the data acquired and its application in medical product development and approval.

The ever-changing healthcare sector

Even today, healthcare payors and governments continue to face enormous data management and storage capacity challenges. Drug prices are increasing, owing to development costs and an increase in demand for personalized treatments, which is placing unimaginable pressure on life sciences companies.

These companies are focusing on the development of integrated solutions and therefore are moving “beyond the pill” and becoming solution providers. With a renewed focus on offering value to various stakeholders, these companies are creating new commercial models. RWE helps them respond to these trends successfully.

Harnessing the power of cloud

With AWS cloud, it is now easier for pharma companies to derive huge datasets from a vast pool of sources. Companies are equipped with the organizational intelligence to understand the needs of stakeholders and mitigate the challenges of large-scale data storage, data analytics, and sharing.

The best way to maximize the utility of RWE is to successfully integrate disparate data types. Life sciences companies must store, search, analyze, and normalize data of different types and sizes coming from different sources, including medical devices, wearables, genomics reports, data claims, clinic trials, and electronic medical records.

One common solution for these disparate data types is a data lake, which allows organizations to store data in a centralized repository — both in its original form and in a searchable format. One benefit of the AWS data lake is that data can be stored as-is; there is no need to transform it into a predefined schema. Unlike with a data warehouse, companies do not need to structure the data first. They can use the data for tagging, searching, and analysis without worrying about its original format.

When it comes to pharma companies, the artificial intelligence and machine learning capabilities of AWS help process data for real-world evidence, such as:

Quick access to all types of data like genomics, clinic trials, and claimsThe integration of new RWE data to existing data in the data lake

Advanced RWE analytics use predictive and probabilistic causal models, unsupervised algorithms, and machine learning to extract deeper insights from these data sets. These help in building large data sets with significant information on thousands of patient variables.

With the on-premise data repositories getting replaced by cloud-based data lakes, pharma companies now have access to a scalable platform that provides cutting-edge analytics. These companies will be at the forefront of technological innovation, as RWE becomes the big picture in the world of pharma in the years to come.

Author Bio

TCS

Ph: +91 9818804103
E-mail: a.goel1@tcs.com

Dr. Ashish Goel is a molecular oncologist from Johns Hopkins University, with more than 23 years of experience across different facets of the pharmaceutical industry ranging from new drug discovery to decision support analytics. He has held leadership positions in Pharma/pharma-centric organizations assisting in key decisions ranging from designing NCE like Lipaglyn (Zydus) to Revenue Forecasting and lately Real-world Evidence and HEOR (IQVIA and TCS). He currently leads the Value Demonstration team in TCS, focusing on business transformation via evidence generation management and automation. He has published extensively in peer-reviewed international journals; owns patents and has been invited speaker to conferences and thought leadership forums/interviews.

To learn more, visit us here.

Cloud Computing

Posted on Posted in Consulting, Knowledge Management Tagged with , , , , , , , ,

For decades, organizations have tried to unlock the collective knowledge contained within their people and systems. And the challenge is getting harder, since every year, massive amounts of additional information are created for people to share. We’ve reached a point at which individuals are unable consume, understand, or even find half the information that is available to them.