NEW DELHI : Bhaskar Ghosh, Accenture’s chief strategy officer, handles all aspects of the company’s strategy and investments, including ventures and acquisitions and Accenture Research. In his new book The Automation Advantage, Ghosh explains how automation works, inherent challenges, and how to seek a return on investment from automation. More importantly, he explains why automation should not be treated as just a technology problem.

In an interview, Ghosh talked about his book and explained how intelligent automation, which involves the application of smart machines that leverage various artificial intelligence (AI) technologies, can also evolve their own capabilities to recognize problems and figure out how to solve them for enterprises. Edited excerpts:

Estimates show that enterprises have automated only 15-20% of what can be automated. Though enterprises are experimenting with intelligent automation, why are they not deriving the full value?

When we talk about automation, we talk about driving the four aspects—cost, scale, quality, and productivity. But in today’s context, the fundamental expectation is different. What we are expecting in the future from automation is to drive differentiated experiences for the users, better decision making, and most importantly, to help grow business. Now, this is possible, and this is driven fundamentally by some of the new technologies which have significantly developed over the last few years, such as cloud, data, artificial intelligence (AI) and machine learning (ML).

When we started talking to our different clients, to our surprise, we learned that they already understood the power of data and artificial intelligence. Most of them have done some prototypes that have also been successful. The challenge is that they are getting stuck in moving from prototype to scale at the enterprise level. Once you do that, then you will find that the percentage that you have referred to will significantly improve.

Let’s talk about some common barriers to implementing automation as discussed in the book, such as talent and skills shortage, cultural resistance in organizations, fears of job loss, outdated policies, unclear metrics, and no roadmap or strategic plan.

It is very important to understand the barriers and what stops the implementation even when the management is committed and wants to invest. Once you use an artificial intelligence-based system, the data acts as a backbone. One of the barriers comes from legacy systems—a lot of the time, the data sits in different systems and don’t talk to each other.

The other big barrier is the culture and the human aspect of it. A lot of time, people think that automation is a technology project when it is actually a change management project. You can bring lots of technology, but people need to embrace that in the organization to be successful.

The third thing is the clarity in the scope. Any technology project has to align with the business goal because that whole paradigm has shifted, and it is no longer just about cost-cutting. It is about transforming the business and better decision-making that will impact it. So, one needs to understand the areas where investment is required and the right project that can get the quick result that is measurable. To overcome some of these barriers, one needs to understand and take proactive steps; otherwise, you will find there is passive resistance, sometimes active resistance.

What are your thoughts on myths about automation, such as not wanting to be the first or thinking of automation as a one-time project?

A lot of the time, people think automation is a one-time project. Today’s automation is driven by artificial intelligence, where the system learns and becomes more intelligent the more you use it. It is a continuous project. You need to make sure your data is not biased, and your system continues to behave ethically. These barriers are important to understand and implement.

We at Accenture had an opportunity to implement this at scale within our organization. We realized that when you try to implement at scale, it is not just technology; you need to consider all aspects of implementations. Otherwise, it will never be successful.

How should companies evaluate return on investment (RoI) from intelligent automation?

When you start an automation project, you need to make sure that the RoI is clear. It is not implementation for the sake of it. Every organization has a different mechanism. Sometimes, RoI is not measured strictly if it’s an internal project. We need to put some checks and balances even in internal projects like what we do for our customers for the external project. So, the RoI is locked in the beginning, and we try to deliver that RoI at the end of the project.

We first try out a lot of projects internally. For every application, we believe there should be a clearly-defined objective that will drive the outcome. In the past, it was just the cost. But now, we are not talking about productivity improvement only.

We are talking about growing the business. Since the whole paradigm of automation is different now, the business outcome is the first thing one should define before investing in automation projects.