As the coronavirus dominates global headlines, it is emerging as an unprecedented human tragedy that will have long-lasting and far-reaching implications. The pandemic is bound to transform forever business models and operational strategies for industries and governments alike. While it is still unclear how long this crisis will last, the uncertainty is accelerating the transition toward embracing enabling technologies and positioning digital transformation at the front and center of global business dynamics.
A recent survey by IDC in China found that while the COVID-19 crisis led businesses to face critical challenges such as the inability to visit customer, declining sales, and stalled production, it also drove organizations to improve the ability of long-distance collaboration, recognize the value of new-age technologies, and enable online and digital formats of business development and operations.
Digital tools are imperative today, and there is an urgent need to shift the focus on investing in emerging tech to build long-term resilience. Simply digitizing traditional processes will not help organizations make the cut. The focus must be on using technology to do things in a new, improved way, and fully embracing that digital transformation will be fundamental in realigning their business in the post-COVID-19 era. But what technologies will drive growth as we cut through this crisis?
With social distancing becoming the norm, businesses will need to automate their operations as much as possible. It is especially relevant in the manufacturing sector with Industry 4.0 framework enabling firms to continue their factory operations without much human involvement. Automation is also a precursor to enhancing productivity, ensuring superior quality of products while keeping costs under control. Further, Robotics Process Automation helps in improving customer experience by application, add-ins, and application-based solutions.
Automation of regular network tasks can enable communications service providers to minimize the involvement of its workforce in managing the network bringing down the scope of human error and enhancing efficiency and quality of services. Besides, engineering automation also reduces manual efforts of repetitive tasks in the product development life cycle. The scope for automation across drafting, meshing, testing, technical publications, NC programming, first article inspection, and software testing is fairly significant.
As businesses begin to operate in the new normal, developing and embracing a data mindset and appreciating its strategic value will differentiate the leaders from the laggards. From gathering information to inferring insights for tangible returns, businesses must look to align themselves to the Four-D principle of data management:
- Data Collection – gathering and measuring information on targeted variables in an established, structured system
- Data Storage – transforming how information is handled on the cloud or at the edge
- Data Analytics – inspecting, cleansing, processing, and modeling input. Dashboarding and generating insights to act
- Data Monetization – generating measurable economic benefits from available data sources and insights
By leveraging data right, businesses can be more proactive and anticipate future actions and customer expectations, deliver more relevant products, ensure personalized services, optimize processes and efficiency, and mitigate risks. The outcome of your data would be directly proportional to its “three Vs”—volume, variety, and value. Utilizing data ensures an improved customer journey and is imperative to enhanced customer experience. With the right technology, infrastructure, and analytics in place, organizations can unlock the full potential of their data for tangible business outcomes.
When the coronavirus crisis hit, the market for IoT applications had just inched ahead of the proof-of-concept phase it had been in for a few years. Businesses that deployed IoT technologies had increased from 13% in 2014 to about 25% in 2019. And the worldwide number of IoT-connected devices was projected to increase to 43 billion by 2023, an almost threefold increase from 2018.
However, businesses that continue to leverage the power of IoT will emerge as the winners in enabling visibility into manufacturing or field operations. This is especially true for remote monitoring and product and process diagnostics when even local travel is not an option. From creating actionable insights for connected equipment and increasing productivity and minimizing costs with smart asset management to enabling intelligent supply chain solutions, analytics and IoT use real-time machine data to unlock new revenue opportunities and enhance the customer experience. Track and trace of assets, equipment, tools, and people are critical for the businesses to become truly next-gen. This would be more relevant in the post-COVID-19 era.
Cloud or Edge Computing
As IoT devices become more powerful and widespread, businesses are preferring to bring compute and analytics power close to where the data is making a clear case for edge computing. That said, decisions on whether to opt for edge or cloud computing are not an either/or question and not mutually exclusive.
While the explosive growth of IoT devices and applications continues to drive edge-computing systems and transforming how data is handled, processed, and delivered, the cloud offers tremendous benefits to organizations that use a traditional client/server network. Both computing approaches have their pros and cons. However, by integrating edge computing with centralized cloud computing (fog computing), organizations can maximize the latent qualities of both while minimizing constraints. And many of them will seek to do so by co-locating their IT infrastructure with a data center.
Uncertain times and tight, competitive markets make it even more critical for organizations to access the right data points, analyze them thoroughly, and make insights-driven and informed decisions. By leveraging data analytics-based solutions, businesses have the scope to be more proactive and responsive to the evolving situation. From improving asset management to ensuring highly sensitive supply chains, analytics play a crucial role in optimizing operations. Further, predictive maintenance algorithms also enable enterprises to identify risks and take remedial action before any impact on the system. That said, diagnostic action based on prognostic data requires a new mindset, tools, and technologies to support it.
Artificial Intelligence and Machine Learning
Artificial Intelligence (AI) is adept at identifying patterns from big data, and this aspect elucidates how it is significant in managing the coronavirus crisis. The features of AI applications such as predictive analytics, natural language processing, speech recognition, image recognition, video analytics, and chatbots are not only helping healthcare workers diagnose but also trace the spread of the pandemic and monitor vaccine development.
Besides supporting healthcare workers, AI today is also helping to sustain critical infrastructure that includes asset-heavy industries such as medical equipment manufacturers, utilities, oil & gas, and transportation. Companies that leverage AI technology can apply predictive analytics to map the real-time and historic data transmitted by IoT sensors on their equipment. This enables them to identify the slightest deviations in time and prevent failures before they occur, while also understanding and eliminating the root cause of problems.
At a time when only limited personnel can be allowed on sites, power generation companies must ensure a flawless supply of energy to their customers, including hospitals that are actively managing the crises. They need customized AI and IoT tools to study their assets’ health and remove any impending defects. The technologies also make this process quicker, more efficient, and secure.
While data can offer immense value to organizations on their products, services, customer expectation, and market demand, how they can extract tangible benefits that impact the bottom line is critical. A McKinsey Survey on data and analytics found that an increasing number of companies are using data and analytics to generate growth and thinking more critically about monetizing their data, as well as using data in more ways to create value for customers. Successful data monetization requires a careful approach that focuses on the highest-value opportunities consistent with an organization’s overall strategy.
Most companies have discovered how data can be leveraged in day-to-day operations to reduce costs and grow revenues. Yet, only one in twelve is making optimal use of their data for enhanced decision-making and revenue benefits. Businesses can improve their “earnings per byte” by not only maximizing value creation internally (through cost reduction and revenue growth) but also create a market for their highly valuable data and insights. This two-pronged approach will imply that they are reinventing the game and securing market dominance early on.
With several economies in lockdown and a significant chunk of the global workforce working from their homes, technologies such as augmented reality (AR) and virtual reality (VR) can drive remote collaboration and build resilience. From providing an effective alternative to workforce training needs to enabling maintenance and repair, product service, product development, production operations, field audit, inspection, and sales and marketing functions, AR/VR can enable real-time information sharing across organizations. This is especially relevant for aerospace, energy, and manufacturing sectors.
AR/VR is the keystone example of how businesses will redefine their processes for real business benefits going forward. The growing deployment of these technologies has encouraged engineering service providers to explore their full potential and bring more AR/VR-assisted products, services, and business models to the market.
COVID-19 is not a short-term crisis. This pandemic has highlighted the need for innovative ways of managing business and new strategies that organizations must deploy to ensure and even address future challenges. In this time of uncertainty, companies need to start using technology strategically to be able to make well-informed decisions and to manage their business operations better. COVID-19 situation is the right time to fast-track the digital transformation and leverage digital tools to rethink business models and stay a step ahead of the competition.
Cyient’s bespoke digital solutions are enabling our customers to automate manufacturing operations, enhance asset management, streamline supply chains, and improve decision-making for business continuity. In addition to helping companies navigate through their current challenges, we deliver the services that allow them to build stronger resilience for the future.