2021 has been a prominent year in digital transformation across industries. As per Zinnov Hyper-Intelligent Automation Landscape Report 2021 – “enterprises spent about $1 trillion on digital transformation globally. Whilst the automation spend during the same time is estimated to be $16 billion, it is forecasted to rise to $120 billion by 2026 at CAGR of 50+%”.
Most organizations are attributing this hype to enterprise readiness to leverage structure and unstructured data, need to scale using process standardization, and of course, the pandemic re-defining future of work with increased pressure on cost and volume.
However, while businesses are realizing automation mid-term gains in increased cost-savings, accuracy, and productivity. setting up and industrializing intelligent automation company-wide still seems to be a big challenge for most of companies. Industry analyst HFS Research states: Only 13% of RPA adopters can scale their automation.
As we engage customers across IT, business, and operations
The roadblocks swing to and from lack of comprehensive governance framework to execute step-by-step implementation, ability to manage heterogeneous technologies, inadequate platform selection, lack of enterprise-level financial & efficiency metrics reporting, and inadequate process identification & definition. Yet, in most engagements where we are deep-rooted, our findings suggest that “managing change” and ability to collaborate by various automation stakeholders stands out as the most challenging barrier to overcome IA adoption.
What really matters in intelligent automation roadmap
Intelligent Automation as a capability, focuses on making organizations zero or near zero-touch operations and enables technology rationalization via harmonization and standardization of processes.
For organizations to design an end-to-end program, they first need to recognize that IA is not a technology program but a discipline that requires process excellence mindset and business alignment at every step of the way. Most of our automation programs at large customers are designed with these critical dimensions.
One: Define incremental journey of impact and value
Transformational impact changes the way business is done and creates an entirely new experience for all as long automation is approached as an incremental journey. It must start with 1.0 or automation enablement where organization concentrates on automating processes or steps within those processes, primarily to improve cycle-time, quality, and compliance. Once the business, IT and Operations is, not are, ready to take the leap-forward to 2.0 or process transformation, the focus needs to shift to automating intelligent decision making that directly reduces expensive manual operations, resulting in increased uptime and process standardization.
This then helps enterprise build a circle of trust and a framework to bounce to what really matters – Automation 3.0 or Business Innovation. This phase focuses on the first principle thinking on revenue growth and market disruption that leads to not only scalable functions at the enterprise level, but increased job satisfaction for all impacted employees, and in turn change the way business is done creating new experiences for customers including employees, partners, and end customers.
However, because automation benefits sometimes are so attractive, organizations tend to try and leapfrog within these three horizons. While deploying this incremental blueprint at one of the fortune 500 pharma customer, we realized the continuous delivery of value across three phases had to be gate-locked and clocked on enterprise technology maturity and behavioral economics. This led to deciphering a critical element as a pre-requisite for institutionalizing automation program:
Two: Build a culture of user-centered innovation (UCI) led automation
For automation to be non-threating and sustainable beyond technology improvement, it is imperative for businesses to implement organizational change via a user-centric approach. As surprising as it may sound, a year into automation driving more than $25M savings via RPA, chatbots, IDP and cognitive intelligence implementation at a customer we embarked on devising an automation adoption and organizational change via design-led approach to help program re-prioritize experience.
For automation to be truly successful, digital workers are required to work seamlessly with digital agents (BOTs). While process and technology improvement plan are relatively recognizable, user adoption to the program is directly proportional to a right-fit people-first plan that creates an optimal experience. It also requires a left-shift approach to problem identification as customers relates more to problems than solutions and hence become the change champions to drive enterprise-wide adoption. The increase in idea funnel, better prioritization, business outcome driven KPIs, organization redesign, and retraining acceleration are some of immediate benefits realized along the way if this is covered early in the game.
Finally: Opportunity is bigger than the problem
Automation is an infinite continuum from enablement to innovation that largely depends upon business willingness to change and adapt along the way. In a utopian state, a fully automated enterprise must yield to the next big thing in its industry.
However, it is equally critical for enterprises to assess and prioritize what they require to approach a cohesive automation program and embed the learnings of each phase in future-proofing business investment and outcomes.
As originally published on BTOES:
Global Business Head – Life-Sciences and Automation Advisory, Marlabs LLC
Arjun Ahlawat is Vice President and Global Business Head of Life-Sciences and Automation Advisory at Marlabs. A strong believer and leader of Artificial Intelligence & Automation, Arjun leads advisory and evangelization across customers around the globe for AI-driven Hyper-Intelligent Automation. Prior to Marlabs, Arjun spent much of his career in digital practice at Cognizant and Aeris.