EVP at Virtusa’s Global Digital Business, responsible for technology practices in UX, mobility, social, cloud, analytics, big data and IoT.
If 2020 taught us anything, it’s that technology is the foundation of everything we do. During the pandemic, our existence became completely dependent on technology functioning in new and often surprising ways: telecommuting, telemedicine visits, remote learning, online shopping, contactless everything and curbside pickup.
The pandemic pushed the boundaries of technology out of necessity, which has resulted in both innovation and paradigm changes that will be with us long after the pandemic subsides.
Here are a few ways the pandemic has changed technology for the long-term.
Remote working extends to virtual collaboration.
Nothing was more of paradigm change than the acceptance of remote working. This new hybrid working model has changed the way we communicate, collaborate and innovate. The increased flexibility has enabled new choices around where to live, increased work/life balance and eliminated wasteful commuting time.
Collaboration platforms such as Microsoft Teams, Cisco WebEx, Google Hangouts, etc., have enabled much of this transformation and will continue to play a vital role in the future of work. Extended reality (XR) technologies that have been adopted in entertainment to create more immersive digital experiences (i.e., Snapchat filters, Pokemon Go, etc.) will soon be applied to collaboration environments to create a mixed reality (MR) experience where your work colleagues can interact with digital objects placed in virtual collaboration rooms with new platforms like Figma, Bluescape and Eloops.
Real-time, AI-based analytics power everything.
The use of analytics and AI was significantly accelerated during the Covid-19 pandemic. Companies needed to quickly pivot to engage customers through digital channels and re-constitute their product catalogs to be online. Additionally, organizations have altered the way they manage their data assets to maximize their value to remain competitive. In practical terms, this requires tightly integrated data and analytics strategy and involves drastically accelerating cloud-based data and analytics solutions.
Migrating data to the cloud increases competitive advantage by eliminating the high cost and rigidity of on-premise data environments. Even more critical has been embedding AI capabilities directly into these enterprise analytics solutions to unleash even deeper insights in the data.
The pandemic forced organizations to set up central nerve centers to monitor and inform near real-time business decisions. Cross-functional teams had to rapidly deploy new reports, integrate new data sources and even establish new data streams from new suppliers or partners. These new insights were critical to understanding the future of their supply chains, customer needs and buying patterns, and to support employees in key decision making.
Prior to the pandemic, many analytics programs were perceived to be overly complex, inhibited by the siloed organizational structure and lacking the data maturity and quality that was needed to build next generation analytical capabilities. However, during the crisis, organizations assembled cross-functional teams, empowered front-line decision making, adopted agile methods and a minimal viable product (MVP) mindset to quickly deploy new solutions. The result has been that analytics capabilities that once might have taken months or years to build came to life in a matter of weeks.
The future of analytics will require a different skillset to what most data and analytics teams within enterprises have today. Organizations will need to create independent analytics pods, rooted in data science, that are capable of conducting more agile, data pipelining and DevOps tasks to rapidly create solutions. Real-time data is preferred over analyzing historical data patterns, which will require tighter integrations with social and commerce data. Data sharing between partners and even competitors will become regular as companies strive for more granular behavioral data on their customers.
Low code becomes the catalyst for digital transformation.
As a result, many organizations are turning to low-code platforms as a fast and expedient alternative to legacy technology that requires significant investments in manpower, time and specialized development skills. Low-code development platforms typically feature graphical, drag-and-drop user interfaces, prebuilt functions, predefined workflows, out-of-the-box integration and adapters, allowing for quick development of enterprise and customer-facing applications. Low code makes it easy to quickly connect siloed, legacy systems built on mainframe platforms and embed modern technologies like cloud, analytics and AI.
The promise of low-code platforms has been around for decades. Technology visionary James Martin published one of the first books on the topic, Application Development Without Programmers, in 1981. Throughout the 1980s and 1990s there were a series of coding waves, such as fourth-generation programming languages (4GL) and rapid application development (RAD), that promised to revolutionize software development. Today’s low-code platforms are powerful, feature-rich, cloud-based environments with built-in security and controls that accelerate the application process without increasing risks.
But it’s important to note that low-code platforms are not a panacea. They won’t replace traditional methods of creating software but rather become an important component of all future application development. Not all solutions are a good fit for low code. Low code excels in “purpose-built apps” or “single-purpose apps” where a process or user needs to respond to an event or complete some direct function or task. Low code breaks down as the complexity of the solution increases. In these cases, more traditional off-the-shelf platforms or custom application development may be the better choice.
Post-pandemic agility will remain an important business imperative, low-code platforms will also remain an important part of the application development landscape.
The future of your business starts now.
The pandemic disrupted a global economy and uprooted many existing paradigms. To remain competitive and relevant post-pandemic, organizations must invest in deeper collaboration tools to ensure team productivity. Digital transformation has accelerated so integrating low-code platforms into your application development methodology is ciritcal to increase speed to market. Finally, it’s critical to embrace new customer buying patterns and use the power of analytics and AI to quickly pivot to new areas of opportunities.