Home Critical engine Data Quality, COVID Response, Coral Reef Safeguard and More at Transform’s Summit on Data, Analytics and Smart Automation

Data Quality, COVID Response, Coral Reef Safeguard and More at Transform’s Summit on Data, Analytics and Smart Automation

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The Transform 2021 Data, Analytics and Intelligent Automation Summit, presented by Accenture, delved into how data, analytics and intelligent automation can contribute to the common good, bottom lines and more .

The day started with the Big Bytes in AI & Data Breakfast, presented by Accenture. Executives at Accenture, American Express, Opendoor, Evernorth and Google ultimately agreed that the data quality of their AI solutions was not negotiable.

As Valerie Nygaard, Product Manager at Google Duplex, said, “You can make tons of technological innovations, but most of the time they are all about the quality of the data, that precision, the standardization, the processing and the handling.”

American Express’s credit and fraud risk group uses machine-learning-based models to monitor $ 1.2 trillion in annual fees globally and make 8 billion risk decisions in real time, said Anjali Dewan, vice president of risk management, consumer marketing and corporate personalization. decision science at American Express.

“Having the discipline to make sure that the quality of that data is consistent, from evaluation to putting it into production, is a key competitive advantage,” she explained.

Opendoor’s valuation models, which serve over 90,000 clients and enable over $ 10 billion in real estate in 30 markets, are only worth their data, said co-founder and CTO Ian Wong . To ensure coverage and accuracy, they created custom inspector apps that use a human expert to collect first-party data and then feed it back into their central repository in real time.

It takes time to collect and manage data, ensure it’s high quality and governed, and then organize it to generate insight, said Mark Clare, head of strategy and data activation at Evernorth. / Cigna. But the new agile and collaborative processes and the visual discovery they helped a financial services company implement led the company’s global manager to discover an eight-figure attrition risk in under 30 minutes.

A big takeaway for Ahmed Chakraborty, global managing director, head of applied intelligence for North America at Accenture, is that when you take a data-driven journey in the enterprise, it’s a journey of change, and a big part of change is about fostering adoption.

“I call it the last mile connection,” he said. “Data control is essential. Elevating your entire business insight to understand data, understanding what you can do with data, is so essential in the long-term journey of driving adoption and change in your culture.

“Cloud to survive. AI to Thrive: How CXOs Embark on Data-Driven Reinvention “

The Summit’s opening keynote featured Hari Sivaraman, Head of AI Content Strategy at VentureBeat, in conversation with Sanjeev Vohra of Accenture, Global Head of Applied Intelligence.

After the pandemic, there has been a massive shift towards data, AI, and the cloud to create more good, more revenue, and more efficiency.

Vohra has identified four key fundamental changes that he and his team have seen, especially over the past year. First, the cloud and data have become superpowers. On the one hand, he explained, is the proliferation of the cloud which offers much higher levels of computing power and the flexibility to scale up and down, as needed. This is combined with the vast amounts of data now available both within companies and obtained from third parties.

“Data and the cloud is a huge trend that we see powering the entire planet and it really has progressed during the pandemic,” he said.

The second trend is that the C suite of companies across industries are now looking at these technologies and how they can be used to generate business value. “It came out of the experimentation area, or pilot area,” he said, “to be used on a large scale”.

Speed ​​is the third trend. As Vohra explained: “No one wants to spend two years, three years trying to generate value. [Business leaders] are really starting to say what can be done in six months.

The latest trend is talent. It is rare and the demand comes from everywhere. As a result, companies now have to make important decisions about how much investment is required for construction personnel and how much is spent on in-house construction versus outside recruitment.

Later in the discussion, Vohra shared one of the projects that she is particularly excited about. Along with Intel and the Philippines-based Sulubaai Environmental Foundation, Accenture is saving the coral reef with cutting-edge AI and computing that monitor, characterize and analyze the resilience of coral reefs. Accenture’s Applied Intelligence Video Analysis Services (VASP) platform detects and classifies marine life, and the data is then sent to a surface dashboard. With real-time analytics and trends, researchers are making data-driven decisions that help the reef move forward even as we speak (or as you read).

Cigna C-suite Executives Discuss Impact of AI and Digital Interactions in Transforming Customer Health

During the AI ​​in Health panel, Gina Papush, Global Head of Data and Analytics at Evernorth / Cigna, had a conversation with Joe Depa, Global Managing Director of Accenture, about how they are using actionable intelligence. to make healthcare more predictable and efficient. , and above all effective.

Their main focus over the past year and a half has been to understand the impact of COVID geographically and on different segments of the population.

“One of the things we found out is that there are definitely differences in terms of the impact of COVID on different groups of customers, and particularly black and Hispanic customers,” she said.

The organization has partnered with its clinical and client experience teams, working with local employers in these markets, to provide concerted, data-driven efforts to drive awareness. They proactively distributed PPE and information on infection prevention and disease management. And as the vaccinations rolled out, they worked with client employers to get them to vaccination sites.

Once they focused on studying the post-COVID effects, especially long-term COVID, they found that in patients with long-term COVID, many clients had pre-existing chronic conditions such as heart inflammation and heart disease, which are prevalent at higher rates. in communities of color. Now, they’re focusing on identifying risks, and data science teams are building models and applying models to identify those who might be at risk post-COVID for serious complications.

“It is essential that post-COVID care continues, and our predictive analytics allow us to be more precise in directing that care to the right people,” Papush said.

Understand consumer behavior with Big Data and deliver AI-powered products that deliver personalized recommendations

This Retail AI panel, presented by Accenture, exposed the ultra-personalization trend with AI leaders DoorDash, Nike and Accenture.

“It has become more evident every day that the post-pandemic acceleration of digitization has changed the way people consume and interact with products in all categories,” said Lan Guan, head of AI for global solutions. of applied intelligence at Accenture. “AI has exceeded expectations to meet consumer demand for exactly what they want, when they always want it. This is ultra-personalization.

For DoorDash, this personalization centers on what the company calls “the restaurant selection problem,” said Alok Gupta, head of data science and machine learning at DoorDash.

Consumers come to DoorDash with a specific food in mind. Their data scientists are focused on understanding this desire and identifying potential new catering partners who can help make the DoorDash app’s restaurant and dish selection as robust as possible.

With the explosion of digital demand at Nike, their entire model had to change, said Emily White, vice president of corporate data and analytics at Nike. The company used AI and machine learning to automate internal processes to gain speed and launch a new distribution facility to fully meet their growing digital demand.

His team created a replenishment engine to read the signal, identify inventory available at all Nike distribution centers and stores, and determine which products should be allocated at the Adapt facility in Tennessee to better serve the Southeast region. . This is their largest distribution center in the world, designed to distribute the company’s Nike and Jordan products to individual consumers, wholesale customers and Nike’s retail channels as efficiently as possible in the new digital world. .

“The result is reduced transportation time and costs, improved sustainability, and faster response to our local demand,” she said.

One of the clients of Accenture, a fashion brand, used AI and an ultra-personalization approach to move from a passive offering of a few clothing collections a year to a response to what’s still hot. on the market. They collect real-time consumer feedback across all social media platforms using AI and machine learning. In just a few hours, designers translate this information into product ideas and send them to micro-studios for experimental production.

“Two quick results here,” Guan said. “A 25% growth in annual turnover and an increase of more than 29% in turnover per visit, all thanks to this ultra-personalization. “

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