Suman Jillella is the Director – Big Data, Analytics and Emerging Technologies at CBTS. Suman is part of the Consulting Services practice, where his roles include helping customers leverage Big Data, open source development, and new technologies including Machine Learning and Artificial Intelligence.
Suman is a passionate technologist with more than 11 years of experience in planning, execution, design, development and product/project management. Before joining CBTS, Suman held IT leadership positions at Luxottica and Citi. Suman helps enterprise customers understand how Big Data and emerging technologies can drive business results. He regularly shares his thought leadership with CBTS enterprise customers and colleagues.
Start with a basic example. Let’s say you are in manufacturing, and have machines that are programmed to move autonomously along the floor in one your shops and deliver specific services. If those machines come across an unexpected obstacle on the shop floor, they might stop or trip over the obstacle, which affects the entire process.
Machine Learning involves feeding those machines information or code that will enable them to recognize obstacles with certain dimensions. Based on that model, the next time a machine is moving on the warehouse floor and scans an obstacle that meets certain dimensions, it can be programmed to avoid the obstacle and continue its work. That’s an example of Machine Learning.
The business case is clear. The manufacturer is depending on those machines to deliver a certain outcome on the shop floor. If the machines stop because of an unexpected obstacle, it slows down production and reduces efficiency.
Many retailers are using chatbots in their contact centers to improve the customer experience. For example, a customer might reach out to a retailer using a digital platform like Facebook messenger. Retailers are programming chatbots to engage with the customer and take them through the same interactive process that a human customer service agent would use. Chatbots have the advantage of being available 24/7, and can be programmed for additional functionalities such as the ability to instantly answer a customer’s questions about available inventory.
Again, leveraging this technology is about achieving a desirable business outcome. In this case, the chat bot is using Artificial Intelligence to provide customer support 24/7 and efficiently answer a customer’s question, which improves the customer experience and provides flexibility for retailers in the contact center space.
The technology is being applied across all verticals and has a broad range in terms of its sophistication. In the health care space, for example, a chatbot tool might greet a patient when the patient arrives for a regular checkup, and check the patient in with the same processes that a receptionist uses – confirming insurance information, validating health history, securing the necessary signatures to meet regulatory requirements. These are relatively basic applications.
Now think about the intersection of Artificial Intelligence, Big Data, and wearable technology in health care. Take a patient with diabetes. A health care provider can track that patient’s day-to-day activity and send push notifications reminding the patient that it’s time to exercise, stand up, take medication, remind them of healthy food options … in other words, encourage the patient to change a behavior or reinforce a positive behavior. And the health care provider can collect, aggregate, and continually analyze all of those data points from the wearable technology to ultimately provide better care for the patient and improve long-term outcomes.
Absolutely. A machine learns and develops intelligence based on the data it receives. Say you’re delivering packages using drones. The weather is going to have a big impact on your operation. As you run that business, you’re going to constantly be collecting internal and external data points that help you understand how changes in the weather impact your ability to deliver packages.
You need to collect all those data points in a centralized location, continuously analyze the data, and feed the data into the Artificial Intelligence and Machine Learning models that will allow your drones to automatically adjust to changes in the weather and deliver packages in an efficient manner.
There are widespread use cases in every industry. As you can imagine, some of the use cases can be extremely complex. Our job at CBTS is to help customers think through the use cases, then identify the necessary resources for projects using Big Data, Machine Learning and Artificial Intelligence to drive a business outcome or solve a problem.
We work with multiple Fortune 500 companies across industries. So we know a resource with expertise in helping manufacturers leverage Big Data is not going to be the right fit for a health care provider doing similar work. That resource might have the right technical skillset, but we understand every industry and company has specific needs. Understanding Big Data is one thing. Applying that understanding to a specific vertical and determining the right strategy is a separate skill. CBTS is here to serve as a strategic partner and help our customers find the right resources.
Whenever I meet with a customer, I always start with this question: What problem are you trying to solve? We are first and foremost strategic partners, and we can’t serve in that role until we have a deep understanding of the customer’s needs and challenges.
I’ll give you an example of our process. We recently met with a large client that was ready to jump into a project involving Big Data. We asked a lot of questions and conducted several white boarding sessions. This helped the customer identify parts of the project it still needed to think through before launch, and helped the customer really define the problem it was trying to solve.
Now that we have this baseline understanding, CBTS can help this customer identify the necessary resources to complete the project. It may involve staff augmentation. It may involve a piece of hardware or specialized software. But that’s now how we started the conversation. We started the conversation by working with the customer to identify their problem and identify the right solution. That’s what we mean when we say CBTS is a strategic partner.