Importance of R&D in Software Product Development and the Future of AI and ML in Business Management
The discussions encompassing technology will only increase, thanks to the real-world applications that it brings about. In a recent interaction with the editor of siliconindia, Dr. Rama Jayanti, Center Head and VP R&D, SAS India, shared her insights about the importance of R&D in software product development. Dr. Jayanti also emphasized the future of artificial intelligence (AI) and machine learning (ML) in business management.
Research and development are undoubtedly significant for growing today's business. Please tell us how are R&D efforts aligned with corporate goals in developing software products?
Research and development (R&D) is essential for the short-term and the long-term growth of an organization. The two limbs—R that represents research and D that represents development—are essential to ensure the success of any company. Research focuses on elevating the leadership position in the market, whereas development focuses on delivering outcomes. These outcomes are majorly driven by research, customers, partners and market.
R&D is the main engine that propels businesses to gain and maintain a competitive edge. In an increasingly competitive global marketplace, the impact of competition cannot be ignored or undervalued.
Developing new products and services innovatively not only underscores the success of R&D but is essential for ensuring leadership and relevancy in the market.In addition, R&D through on-going process improvements drive long-term productivity and profitability.
R&D promotes employee engagement and boosts employee morale by investing in cutting-edge technologies and innovation. Instead of working on the same procedures, processes, and methods, R&D challenges employees to constantly learn and grow.
R&D is also essential for analyzing market trends and identifying customer requirements. Applied research is invaluable for developing new products and improving existing products in accordance with customer requirements.
Tell us how R&D assists in unlocking the potential to improve software reliability.
Software or technology is an enabler for most enterprises. It drives their strategic imperatives. Hence, it is essential that in addition to being capable of solving customer-specific business problems, software products are maintainable, reliable, performant, and scalable.
Designing and building systems that can operate at scale is an essential part of the R&D delivery process. Ensuring that software systems and sub-systems support customer’s non-functional requirements is an integral part of the software development life cycle. In addition to functional testing, the R&D teams perform other types of testing. For example, they also test the product for performance, scalability, security, resilience, deployment, and chaos. These aspects are incorporated all the way starting from the design phase to the testing phase, and then finally during the product release.
How is AI and ML positioned to deliver radical improvements to businesses worldwide?
AI has been around since the 1950s, but it is really finding its place in mainstream applications because of the explosion in data volume of the Internet of Things (IoT), high-speed connectivity, and high-performance computing. Today, AI uses a variety of statistical and computational techniques. Machine learning (ML), a subset of AI, identifies patterns and anomalies in data from smart sensors and devices, without being explicitly programmed where to look. Over time, machine-learning algorithms learn how to deliver more accurate results. As such, ML outperforms traditional business intelligence tools and makes operational predictions many times faster and more accurate than the systems that are based on rules, thresholds, or schedules. Technologies such as natural language processing, computer vision, deep learning, and ML in time-tested forecasting or optimization make AI an essential complement to not just IoT but business domains such has retail, health care, and logistics. AI separates signal from noise and induces the usage of advanced IoT devices that can learn from their interactions with users, service providers, and other devices in the ecosystem. The real value of IoT is achieved when devices learn from their specific use or from each other and then automate actions.
AI and ML introduced unprecedented possibilities, especially for business. Tell us how leveraging them can give companies a competitive edge?
I think COVID is a great example. Given the gravity of the pandemic, speed was essential to ensure timely and focused intervention. Governments across the world relied on data and analytics to predict how the pandemic will evolve and made attempts to contain, gear up and provide support to people. Another related example is that of public safety and emergency where several state governments in India have used technolgy such as SAS®Analytics to help them make the right decisions to contain the pandemic. The government of Odisha is one such example.
Business in the space of supply chain, logistics, and retail use AI and ML very effectively. The power of forecasting by using AI and ML technologies enables larger retailers to manage their inventory efficiently, thereby reducing waste and cost without compromising on customer’s demands.
How are AI and ML helping businesses expand their horizons?
As AI continues to move into the mainstream, companies are combining AI and big data to design products that enable enterprises to be nimble and respond promptly to the changing market needs. One of the biggest benefits of AI technology is to take over mundane, administrative, and low-involvement tasks, and enable organizations to focus on strategic initiatives. For example, insurance and banking organizations use the power of AIto detect and prevent fraud. Similarly, retail companies use the power of AI to forecast demand and optimize inventory. In the manufacturing space, with the notion of smart manufacturing, smart and connected technologies are being embedded in organizations and assets, and moreover in people in the case of wearable devices. These technologies are taking advantage of the emerging capabilities from robotics and AI to quantum computing, additive manufacturing, and IoT.
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