Today we can’t help but notice a rapid growth in adoption of Artificial Intelligence (AI) innovations across industries such as financial services, healthcare, transportation, telco and retail. As AI leads the next big wave in computing, many organizations are focused on becoming insight-driven, now more than ever.
At our Insight-Driven Organization Event in NYC last month, trends, challenges and best practices were discussed on how to become an insight-driven organization with esteemed representatives from Avaya, Intel, and Capgemini.
We’ve compiled a recap of the highlights here for you who could not attend.
Bernard Gutnick, Senior Director, Engagement Product Marketing @Avaya
Bernard presented how exceptional customer experience and customer lifetime value begins with a single interaction and lasts the entire customer journey. From a technical perspective, he explained how in-memory databases play a critical role in empowering contact center operators to provide agents with a 360-degree view of customers. “With the rapid adoption of smart devices and anywhere and anytime information, never before has customer experience been more valued,” said Bernard. “82% of companies recognize customer experience as a competitive differentiator and 62% want to switch to phone from web chat.”
Avaya believes that each customer interaction, regardless of the channel that the interaction takes place over, contributes to the overall customer experience. The better the experience the higher the Customer Engagement and the higher the Customer Lifetime Value. Bernard explained that in order to create the right customer experience today, you require a platform that is focused on knowing everything about your customer and making the right multimedia and business connections.
Bernard demonstrated how GigaSpaces, which helps power the Avaya platform, plays a crucial role in Avaya’s omnichannel contact centers, which are used in 95% of Fortune companies. With GigaSpaces, Avaya is able to present the agent with the most relevant information about the customer, quickly.
With Avaya’s business logic, the customer is routed to the best automated live agent, for example in the case of call centers, Life Alert or IoT.
Fadi Zuhayri, Director & Big Data Technology Evangelist @Intel
Fadi talked about unleashing intelligence and data insights at scale. “Today, there is unprecedented growth in daily data generation for several categories: people as well as “things”” said Fadi. “Soon, “things” will outpace the connections and data generated by people.”
By 2020, 50B devices and 212B sensors will join the internet and 47% of total devices and connection will be Machine to Machine. In 2020, it is expected that the average internet user will generate ~1.5 GB of traffic per day (Up from ~650MB in 2015), a Smart Hospital will generate 3,000 GB/day, and a connected plane will generate 40,000 gigabytes per day. All of this data will need to be analyzed and interpreted in real time.
This data, by itself, is actually not interesting, Fadi explained. The most critical idea is how to extract “insight” from the data. And it is that insight that is now being used as the new competitive advantage for companies. Insight helps you reduce cost, helps you better understand customers, create new innovations, launch new businesses, and react more quickly in today’s digital economy.
“With the influx of data, businesses must develop ‘intelligent data practices.’ This requires businesses to think strategically about the creation, storage, movement, and analysis of data. Where should the data be stored? Where should the analysis happen? These decisions have a significant impact on data accessibility and data economics,” said Fadi.
As for the next revolution, Fadi believes Artificial Intelligence is not only the next big wave in computing, but that it’s poised to usher in a better world, on the order of major transformations before it — like the agricultural revolution, industrial revolution, and the information age. This is thanks to new breakthroughs in Data Science, exponential growth of training data, and innovations in computing. These 3 trends and recent developments in each of them have created an inflection point that is driving the adoption of AI at an unprecedented level.
Fadi went on to discuss how Intel is driving a broad and holistic approach to power advanced analytics and artificial intelligence workloads and unleashing intelligent and scalable insights from the edge-cloud-to the enterprise. And how Intel works with partners, such as GigaSpaces, to create compelling reference architectures and solutions that can accelerate time to market for new analytics and AI concepts.
He presented Intel’s BigDL framework for Apache Spark and writing deep learning applications as standard Spark programs for model training, prediction, and tuning. And how you can now use your existing CPU infrastructure to scale deep learning with very high performance. “You not only save time and money with your infrastructure, but it’s also more seamless to maintain your existing data flow and to integrate AI into your overall analytics application.”
Arindam Choudhury, VP & Global Leader for Big Data in Financial Services @Capgemini
Arindam discussed how the rapid growth in AI and Machine Learning capabilities has opened up new opportunities for all Banks. In his presentation, Arindam walked us through some major industry trends and discuss key opportunities for banks to become more Insights driven organizations.
Arindam spoke about how analytics help enhances customer loyalty and CSV as well as improve efficiencies and effectiveness. For the bank, this means increased revenues, prevention of risk related loss and overall reduced costs.
Agreeing with Bernard, from Avaya, Arindam referenced the digital customer journey and the importance of the omni-channel bank. He spoke about Capgemini’s smart analytics solution which brings a 720-degree customer view with data from both within the enterprise and external interaction points to create a uniform digital identity “The availability of unstructured data created transparency, alerts potential friction and brings additional insights,” said Arindam. “The data-insights based approach enables customer-centric strategies.”
Arindam focused on the insight-driven bank, fraud detection and the growing need to integrate analytics into the Know Your Customer (KYC) process. According to Arindam, most fraud happens in the happens in the range of $9900 and under, because it won’t trigger any alarms, so you get a ton of transactions under this range. That’s why you need advanced analytics to be able to tell when they’re dangerous. Also cited were actual AI deployments including chatbots, contract intelligence and fraud detection.
Capgemini believes that banks and other organizations need to look to pre-integrated stacks to save time and money.
Lastly, Arindam predicts that Google or Facebook will enter the world of banking in the next year or two
Adi Paz, CEO @GigaSpaces
Adi reviewed how GigaSpaces In-Memory Computing portfolio is transforming many enterprises with a dramatic competitive advantage through fast data, real-time analytics, and mission critical transactional processing. He related to today’s high-speed world, it’s becoming essential for businesses to transform how they collect, manage, and analyze data to make decisions.
He spoke about a common theme across all of our customers; in retail, eCommerce, telecommunications, transportation, finance, health which is the need to shift towards using real-time (hot) data to make real-time decisions.
Adi discussed the complexity of the network architecture and the requirement for simplicity. He spoke about how GigaSpaces InsightEdge leverages the complete Apache Spark ecosystem. “By fusing Spark and the in-memory data grid together, we allow any real-time application deployed on the data grid and its data to be readily available as data frames, RDDs or Spark entities,” said Adi. “Any results derived from Spark during data transformation, machine learning, and model training can be saved to the data grid and immediately referenced in the real-time application for instant impact.”
Customer case studies were referenced from Finance, Retail, and IoT (predictive maintenance).