HR Tech Interview with Ram Chakravarti, Chief Technology Officer at BMC Software

Journey into Tech

Please tell us about your role at BMC Software. 

As Chief Technology Officer for BMC Software, I oversee the BMC Innovation Labs as well as the company’s overall technology strategy, and corporate development. My background involves expertise in technology strategy, product innovation, enterprise software development and implementation, merger management, digital strategy, and operating model design.

Which deep technologies are you keenly following and why? 

As companies continue to pivot and adapt in response to the pandemic, more of them have turned toward automation, artificial intelligence, and machine learning to help streamline business processes and better prepare for future “what if” scenarios. It’s no longer enough to simply automate certain functions. The latest automation technologies include a degree of cognition, analysis, and learning that can benefit the entire business.

Extensive technology-enabled automation will also become even more pervasive, leading to “hyperautomation,” or the continuous integration of automation into business operations—or, in other words, more machines doing more things. With more sources of information and more sensors, data volumes will increase exponentially, which will require AI and machine learning capabilities across the organization to operationalize the data. In 2023 there will be ample opportunity for organizations to leverage each piece of data to move faster than their competitors, to create an exciting workplace for their employees, and ultimately, better serve their customers.

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Which technologies would you advocate to the CIOs in 2023?

Edge computing will present a huge opportunity for organizations to differentiate themselves from their competitors. According to Statista, the edge computing market is predicted to reach $275 billion by 2025, which is complemented by the growth in the IoT space with connected devices projected to grow three-fold to 30 billion devices by 2030. This nascency of edge computing is where we see opportunity for CIOs. The explosive growth in edge computing technologies and the amount of IoT devices, introduces additional complexity with the need to manage it all. Organizations will need to double down on edge management and take advantage of devices that produce new, and not yet harnessed, data and turn the data generated by those machines into valuable insights.

Please tell us about what an Autonomous Digital Experience (ADE) is. What kind of impact has it made since its inception? 

The Autonomous Digital Enterprise is the framework for the digital-first business. It comprises distinct tech tenets and operating model characteristics that support a tech transformation with the success criteria being actionable insights, business agility, and customer centricity. An organization’s journey to an ADE requires your enterprise to progressively leverage more automation and AI/ML capabilities, among other tech capabilities, to thrive amid the rapid transformation we continue to experience.

The ability to adapt to these changes, increase investment in tech transformation, and evolve to new business models will enable companies to better prepare for a future of growth. Organizations that adapt the ADE framework will become more growth-oriented, replacing manual and redundant tasks with automated intelligence that frees up people to be creative, serve customers, and collaborate on higher-level pursuits.

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Tell us a bit about an ADE’s role in enterprise software management and AI adoption?

Organizations that are well on the path to becoming ADEs share a key characteristic—their customer interactions and business operations are radically automated. This results in lower costs, reduced errors, much faster execution, fewer mundane tasks for employees, and ultimately, better customer experiences. They embrace the idea of technology as a complementary business function that works with—not in place of—human workers. AI is the foundational requirement for every Autonomous Digital Enterprise, and companies will succeed by delivering value that is enabled by agility and actionable insights, with a focus on customer centricity.

Business process automation is getting a big boost from different machine learning capabilities. Please tell us how you see ML platforms simplifying automation deployment in the near future? 

Automation is most effective when applied within strictly defined processes and workloads that are manual and repetitive. Machine Learning reduces the amount of time that highly skilled engineers devote to these tasks, and it allows them to focus on higher-value initiatives within the organization. ML helps IT teams address complex challenges and cater to exponential data growth, automating the entire IT operations process across hybrid environments to create an accurate inventory for machines to correlate data points independently, and detect patterns across key practice areas.

The key to harnessing ML and ML-enabled data analytics solutions, like AIOps, will be having a strong data management foundation. Understanding what a business’ “normal” operations looks like across the enterprise, in a single end-to-end view, can empower IT teams to identify needs, opportunities, and threats as they arise. This is critical to intelligent operations and truly data-driven business.

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Thank you, Ram! That was fun and hope to see you back on HR Tech Series soon.

[To participate in our interview series, please write to us at sghosh@martechseries.com