PODCAST: AI for the Digital Enterprise
Episode 5: How Intelligent Operations can become prime advantage for enterprises
Listening time: 11 minutes
How Intelligent Operations can become prime advantage for enterprises
Outcomes, processes, and talent define a synergetic ecosystem for modern-day enterprises and therefore enterprises are constantly looking for opportunities to drive better customer experience, improve operational efficiency, and provide the right tools and information to their employees at work. Capturing the right signals and using them to respond to the ever-changing needs and post-pandemic times is essential. AI-led Intelligent Operations can help a lot and, in fact, already transforming these areas—be it developing smart apps for banking or using drones to do damage surveys for insurance—with its exceptional ability to detect anomalies and recommend next-best options. BRIDGEi2i AI accelerators are great examples of tools that enable Intelligent Operations, pan-enterprise, and at scale. They could help save precious time and resources and reduce cost leakages. Intelligent Operations certainly is going to be increasingly the way forward for enterprises.
Arjun: Hey, hi there. You’re listening to BRIDGEi2i’s podcast, AI to impact. My name is Arjun Shenoy, and I help companies succeed in their AI-enabled digital transformation efforts. I’m a director with BRIDGEi2i, and I focus on building assets and solutions that support execution and quick ROI on client’s digital programs. Hence, I often end up working with CXOs and senior leaders across a range of customer segments. Now in continuation of our conversation around the impact of COVID-19 on enterprises with thought leaders and industry experts today, we have with us Ronobijay Bhaumik. So Ronnie comes with about 15 years of experience in leadership positions, across technology and the media industry.
Ronnie is a director in our Digital Practice and is also responsible for several strategic digital teams at BRIDGEi2i. Thank you for taking the time to speak with us today, Ronnie.
Ronobijay: Hey, thanks, everyone. Happy to be here,
Arjun: Ronnie, through the last few months. In fact, even before the COVID-19 pandemic hit us, we’ve been hearing about the need for intelligent operations or intelligent processes.
What would those terms really mean for our customers today?
Ronobijay: That’s a great question, Arjun. So, let’s just distill those terms, you know, down to the core components. So we start with the end customer. So first and foremost, you want to drive outstanding customer experience across all of your channels, whether that’s a fulfillment issue, diagnosis and resolution, or driving engagement, either upstream or downstream.
In order to achieve that you would also need to increase your operational efficiency and effectiveness of end-to-end processes within your organization, and increasingly extend this to your partner organizations as well. The third component: your workforce, you need to make sure that they have the right tools and information to plan and execute in the safest way possible. Right. With flexibility and agility being key determinants of winning and retaining customers. We need to look at these three blocks as a synergistic ecosystem. So outcomes, processes, and talent. Now, the only way you’re going to be able to do that is with greater visibility to what is happening across the ecosystem.
That’s the critical starting point. You need to be able to capture the right signals and use AI on the signals to quickly respond to the ever-changing needs that are most prevalent right now. Now, the ability to respond very quickly, changing customer preferences, disruptions in the market, supply chain challenges means that you have to really think to what value you’re able to get to each of these singularly and together as an ecosystem. Right? So the best way to do that is if you have the right digital building blocks.
So first, the ability to capture and synthesize data signals from multiple and diverse sources as events occur.
So you don’t have to wait for a month to get data. You need to be able to capture that in real-time, as much as possible, then leveraging the power of AI to draw down those signals into meaningful insights. at scale, and do this very quickly. You can, again, wait for two weeks after an event has happened. You need to know that the event is happening and do something about it now. Thirdly human capital, the talent within your and your partner organizations that can both build these AI-led ecosystems and transform these insights to actions and outcomes. Very important to have these right, these digital building blocks in place.
Arjun: Those are very interesting points too. I’m sure Ronnie, and thank you for providing us with that perspective.
Now, one of the questions is specifically to the current time that we’re at in terms of, you know, the uncertain times that we’ve seen many enterprises looking to derive value in the short term. So what kind of application areas do you see for intelligent operations in the next few months?
Ronobijay: Sure, I think it would, you know, what used to be anathema till a few months back, you know, data transformation is real now, right?
So, even traditional organizations like banks, you know, they’re, they’re coming to the fore. So earlier customers would spend a week or two, trying to open a bank account. We would have to visit a branch possibly, you know, multiple locations, submit multiple documents. All of these would have to be physically checked, validated, then you would get an approval, you know, request, which would get triggered. You would have to respond to that. Look at the touchpoints over here. It’s a high-friction process. Now that is changing. I mean, changing very, very rapidly. So in the last two months, I’ve seen banks change their processes so that you and I can sit in the comfort of our homes interacting via an app or with another individual on the other end of the screen.
And, you know, upload a video record, a video, and the algorithm will detect whether it’s you, and also perform higher-order checks, depending on what documentation you’re providing, how you’re responding to questions. It’s a real-time interaction. And lots of triggered subsequent actions are also taken in a completely frictionless manner.
So you get your approval in minutes, or you get flagged off. If, if there’s a problem in the process, you can flag it off in minutes rather than having to wait for days. So this is a huge change in the way banks are interfacing with new customers or even with some of their existing customers.
Now, another application area where worker safety and security take precedence is remote inspection using drones; you can capture images and videos of buildings, very large work sites. I mean, these go across hundreds of acres at times, and this footage can be analyzed by trained algorithms with only the anomalies needing to be flagged off for human intervention. But this will also save you hundreds, if not thousands of man-hours, which would otherwise have been spent in a potentially hazardous environment.
So AI engines can identify failure points, give out alerts, make recommendations, or even take actions depending on the kind of sensors that we use if a situation arises. So, you know, think about an insurance company. I mean, you can safely inspect sites remotely to assess for damage and adjust claims and premia all of it from the safety of a control room, rather than having to physically visit every site for every single claims request that comes in.
For organizations who have, I would say tactically assess the impact of COVID-19 on their operations, that are now beginning to look at that the next six to 12 months cycle. One of the most impactful areas for AI-led intelligent operations is machine learning-based analytics applied towards increasing their operational efficiencies.
So for example, you would want to deploy connected devices throughout your infrastructure to continuously sense the health of the infrastructure, detect and report anomalies, and then be able to trigger preventive action needs very quickly to the right individuals, and then you can prevent unplanned downtime.
So resources instead of spending time having to manually inspect every single item along the production line, you can divert those resources towards mitigating any of your mid-term supply-side challenges that you’re facing and also focus on reinvigorating your demand. All of these areas, you can see, you know, the value of intelligent operations very quickly provided you have the right digital building blocks in place.
Ronobijay: And I know that you’ve been driving somewhere of these, you know, development of these digital building blocks for our global customers over the last couple of years. So, you know, what critical needs that you see, you know, boiling up?
Arjun: Absolutely. So only continuing with the observations you just made around intelligent operations. What we are hearing more and more from clients is their need to reduce cost and risk while increasing operational efficiency. Now at a high level, there are two questions that most of these clients are asking—one, can we proactively alert our business managers to anomalous trends across the value chain?
And B, can we recommend actions to mitigate these business anomalies? Right? These are the two broad questions that most of these businesses are asking, Right?
So to answer those two questions, we have to be able to deploy solutions quickly. We have to be able to deploy them within existing approved technology stacks or business systems that are currently available in the current environment.
And three, we have to be able to make it easy to consume insights, right? Now where our AI accelerators are coming into the picture. Now, let me give you an example. So one of our recent client engagements, this client wanted to plug costs leakages in their procurement processes. Now, this is a problem area that, you know, and Watchtower accelerator is built to solve.
So once we deploy the Watchtower, it automatically identifies business anomalies and their root causes. And in this case, it would alert to any form of, you know, cost leakages and indicate reasons for the same. Now the Watchtower accelerator is an AI engine that’s fluid enough to be deployed onto an approved tech stack and can integrate within existing front ends of business systems.
So in this case, we were able to deploy it on their Azure approved services and they had Power BI. So we were able to integrate it into, you know, some of that existing Power BI dashboards and all of this we were able to do within a few weeks’ time. Now, if you look at it from a business user’s perspective, it almost seemed like, you know, they’re consuming a set of new insights within the existing applications that they already have, right? So, it’s a seamless integration into their existing business environment. Now we’ve what we’ve been able to do is by implementing this, we’ve almost done you know, five X times faster from their existing systems in terms of, you know, identifying the cost leakages, without seeing any disruptions within the value chain.
Ronobijay: Wow! That’s great, Arjun. I mean intelligent operations certainly are going to be increasingly the way forward as businesses come out of COVID-19 and start planning for resilience and agility in the coming months.
Arjun: Absolutely. Ronnie, you said it, perfectly, it was an absolute pleasure talking to you today and thank you for joining us on this.
Ronobijay: Thanks, Arjun. Always a pleasure.
Arjun: Thank you so much for listening to this episode of the AI to Impact podcast, do subscribe to our channel. We will continue these conversations with experts and thought leaders in our upcoming episodes. Till then. Bye. Stay home and stay safe.
The upswing in AI adoption and the impact of Digital initiatives in enterprise transformation have reached staggering heights, but there is still a lot of skepticism around the value realization of AI. BRIDGEi2i, a transformation partner to several large enterprises, has been spearheading an enterprise-wide movement on “Making AI Real.” In this series, we bring together reputed thought leaders, practitioners, and influencers of the industry as they discuss trends, predictions, and best practices on extracting tangible value from AI to embark on transformational journeys.
Ronobijay Bhaumik, Director of Digital Practice, BRIDGEi2i
Ronobijay, Director of Digital Practice, is also responsible for several strategic digital teams at BRIDGEi2i. He comes with about 15 years of experience in leadership positions across technology and the media industry.
Arjun Shenoy, Director of Product Management, BRIDGEi2i
Arjun leads the Solution & Product Management practice for the technology vertical at BRIDGEi2i. The role involves building AI/ML solutions, enabling end-user consumption, and driving change management to adopt AI within enterprises. He has earlier worked at tech majors like GE and Honeywell.