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Navigating the Future of Automation
Girish Kumar Kizhakhe Nottiath, Market Lead, TCS
Let us start with RPA that was introduced during 2012 to eliminate mundane tasks & inefficiencies in business operations. While RPA penetration is slow, its market size is expected to reach $3 Bn by 2021. Various RPA product vendors come up with strong technical capabilities and some also introduce commercial off-the-shelf products to target specific functions like sourcing and accounts payable. On the one hand, the automation platform gains core capabilities. On the other hand, organizations struggle to tap full advantage of these technologies. Business & IT functions tend to work in silos and become confused with different technologies. Eventually, only 13 percent of companies could scale up in their RPA journey.
While RPA aims at reducing repetitive tasks, Cognitive Automation and Artificial Intelligence solutions (AI) are also gaining momentum in the market to deliver customer experience and operational efficiency. For example, cognitive contact center operations to reduce average handling time through chat bots and cognitive procurement solutions to reduce maverick spend, etc. The AI market is expected to rise to $2.7 Bn by 2021. However, organizations are unable to reap the full benefits from these technological innovations. As a result, the automation adoption at an enterprise level was a major challenge. A few important reasons for this are:
• No C-Level sponsorship and long-term investments
• Lack of an enterprise automation strategy and roadmap
• Business & IT non-alignment
• Traditional delivery model & tech level demand generation
• Poor change management & increase in cost of development
• Incorrect use case or technology selection leading to no business case
• Evangelization & enterprise level communication was not in place
Cognitive Automation and Artificial Intelligence solutions are also gaining momentum in the market to deliver customer experience and operational efficiency
To achieve scale and make a paradigm leap, there is a need to adopt a thought leadership framework, which integrates technology platforms that combine assisted, institutionalized, intelligent & autonomous solutions through a “machine first delivery model™. The framework will drive the creation and execution of a Machine First strategy by sensing, understanding, deciding, responding and learning real time. It should also ensure that machine has the first right for refusal. Companies shall adopt this framework to develop enterprise automation strategy & roadmap with sponsorship from senior management plus a commitment for long term investment. The model defines a set of processes and methods for delivery execution through transition, transformation, change management and ultimately leading to autonomous solution. Automation Garage should help to incubate new use cases and test them at an organization level. Finally, it is not just RPA when it comes to Automation, organizations should combine technology stacks under a holistic framework with a strong Data Foundation and Cloud First infrastructure to deliver exponential value in the long run.
The shipping industry faces close to $150 Bn in costs due to ecosystem sustainability and they contribute 2 percent of Global CO2 emissions. A digitally connected sustainable ecosystem can help cargo manufacturers to connect seas, ports and roads through integrated intelligent platforms and create exponential value for their customers. Further, global submarine manufacturers are leveraging AR VE control centres for remote monitoring and maintenance of assets to bring a digital experience to workers. Logistic companies are also attempting to reduce their logistics footprint with route optimization solutions through AI-IoT.
Retailers have taken a strategic step towards producing power for their own consumption. It is leveraged through AI-IoT based Smart Energy Management Solutions (EMS) that offers real time descriptive, predictive, prescriptive analytics on energy consumption and facilitates energy trading. Companies can potentially save between 10 percent - 40 percent in energy costs. When it comes to Breweries, there are tremendous opportunities to reduce water consumption used to brew beers through EMS.
In the steel, painting and chemical industry, the costs of raw materials on energy is very high. For example, the RH Degassing process used to produce steel requires water, gas, electricity and steam in addition to support systems. EMS can then establish a golden cycle as a benchmark and compare against the heat cycle to reduce cost per unit.
Companies also leverage 3D printing solutions for low volume manufacturing to produce spare parts e.g. rain sensors for trains. The biggest advantage is that the production line is easier to alter than the traditional manufacturing and prototypes can be made much faster.
Intelligent Power Plant solutions which combines an AI IoT and Digital Twin system to help power-generating companies have a competitive edge in a highly dynamic energy market and industrial environment. For example, one Japanese utility provider has adopted this technology and optimized utilization of critical power plant assets like boilers and turbines to enhance reliability reduce emissions and operating costs by 2-3 percent.
The bottom line is that we are living in a Business 4.0 era where sophisticated technologies create exponential business value. Organizations that embrace risk and leverage these technologies using a Machine First framework with collaborative automation platforms will gain data as a distinct advantage in the market, gaining business agility and trust from internal and external stakeholders.
Are you ready to launch your next robot with the collaborative technologies to bring in supreme customer experience?
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