Be it the steam engine, electric bulb, computer or robot, machines have been at the core of industrialization evolution from the late 18th century through today’s Industry 4.0. They have been there for us when volume and coverage mattered. Machines have delivered faster, cheaper, and better; consistently and precisely. However, this digital economy, accelerated by automation, robotics, and artificial intelligence, demands a delivery paradigm vastly different from the conventional one. This new machine first model for delivery will be hinged on human-machine collaboration. Human ingenuity together with machine precision and power will be the guiding force for elevated growth and success in this Business 4.0 era.
This is something that we have always known. Healthcare industry has been one of the forerunners with robotic surgery. While the machine’s precision greatly helps in conducting a flawless surgery, it is the human intellect that guides the robotic arm. Machines, by themselves, are not good at responses to unknown situations or making judgements. Here’s how the human-machine collaboration can drive some business differentiators for an enterprise to succeed in its Business 4.0 transformation journey.
Improved Customer Experience
Human-machine collaboration is expected to drastically improve customer experience and therefore their delight. Customer experience can go up by notches when sophisticated, data-driven, self-service platforms like chatbots can reduce the number of human interaction contacts significantly. Cognitive call centers that employ virtual agents and virtual assistants enable human customer support agents to be smarter, better, and faster. Add predictive communication capability to this mix and you can rest assured that your online customers will not go elsewhere for want of better options.
Service desk automation that deploy self-service tools or chatbots is a great example in IT industry. Personalized workplace automation with a right digital framework can do wonders to increase an employee’s productivity. Testing, data analytics and insights, marketing, employee onboarding, leave logs, policy queries are few instances that can be easily taken over by machines and a human’s time and effort can be diverted to take care of far complex work. End user computing automation such as automated software distribution, deployment, and patch updates can save valuable work time for employees and for the IT department of an enterprise.
Better Mass Personalization
Machine learning algorithms, predictive analytics, and human creativity – a potent combination enterprises can leverage to achieve personalization to a segment of one individual across multiple channels. Coca Cola’s launch of Cherry Sprite is a starting point of such personalization. Personalized apparel, footwear, personalized implants, marketing automation, are some early applications of machines learning from humans for hyper personalization. For low risk appetite industries such as insurance, the human-machine collaboration has come in handy to satisfy their customers with personalized risk and loss estimation data.
Increased Speed to Market
Human-machine collaboration on the production line has become more flexible, versatile, and therefore more productive. Today’s robots are much more capable of learning tasks that they couldn’t perform well earlier such as moving around objects placed chaotically and sorting out complex wiring issues in industries like aerospace. While humans can take on monitor and control tasks on the manufacturing floor, machines can be engaged for physically exerting tasks. This greatly reduces safety risks of human workforce. Lacking in emotions, machines are best employed to perform iterative tasks, which humans find monotonous and so causing productivity loss. The plug and play feature of machines, makes them user friendly and easy to deploy. The human-machine collaboration, therefore, is the best choice to improve a product’s speed to market and realize exponential value as you progress in your Business 4.0 transformation journey.
New Business Models
According to one of our studies that involved about 835 business leaders from companies around the world, leading corporate investors in artificial intelligence (AI) outspent others by a factor of five, resulting in a 16% or more increase in revenue. Given such transformative benefits, it will be hard for enterprises to ignore AI. As human-machine collaboration evolves, businesses will have to rethink the way they operate. Traditional pricing models need to be thought anew in the context of multi-fold efficiency benefits offered by a human-machine synchronized automation service. The centaur model that takes into consideration the hybrid human-machine intelligence along with a business process, is bound to redefine business models.
Automation, a millennial dominated workforce, and evolving strategies such as crowd sourcing will disrupt workforce models as well in the near future.
Enterprises will do good to seek partners that can consult them on choosing the right business models. A right partner can help enterprises to harness the abundance in the ecosystem around them and lead them on their Business 4.0 transformation journey.
About the author(s)
PR Krishnan (PRK) is Executive Vice President & Global Head, Enterprise Intelligent Automation & Artificial Intelligence at Tata Consultancy Services (TCS). In this role, PRK helps business and technology leaders drive innovation and integrate digital technologies – AI, smart automation, machine learning and cognitive computing – into their business model for growth and transformation.
PRK has strategized innovations that drive human - machine collaboration that serve as the guiding force for elevated growth and success in the Business 4.0 era. PRK spearheads the MFDM™ (Machine First Delivery Model) initiative in TCS to institutionalize the Machine First™ approach across client engagements and within TCS.
PRK’s team creates new opportunities for, enabling the world’s leading enterprises to harness human ingenuity together with machine precision.
For more than 35 years, PRK has played a pivotal role in coaching large teams, demonstrating thought leadership and innovation towards uncovering insights and creating exponential value for large enterprises.
Prior to leading the EIA & AI portfolio, PRK served as Global Head of the IT Infrastructure Services, overseeing the expansion of the TCS services portfolio. In this role, he successfully led several of TCS’ global delivery centers (GDC), paving the way for the creation of the company’s Global Network Delivery Model (GNDMTM).
Starting in 2004, he was responsible for creating and running the telecom delivery centers for TCS, where he built a 3000+ strong practice servicing over 40 customers, growing the practice in a time when the telecom industry was just beginning to embrace technological advancements.
PRK has contributed significantly towards leading a very successful SEI CMM Level 5 assessment that became a new benchmark and model across TCS.