Technology projects should be in line with business goals: Bhaskar Ghosh

In an interview, Ghosh talked about his book and explained how intelligent automation, which involves the application of smart machines leveraging various artificial intelligence (AI) technologies, can help enterprises identify problems and solve them. Learn how to develop your abilities. , Edited excerpt:

Estimates show that enterprises have automated only 15-20% of what can be automated. Even though enterprises are experimenting with intelligent automation, why aren’t they getting full value?

When we talk about automation, we talk about driving four aspects—cost, scale, quality and productivity. But in today’s context the basic expectation is something else. What we expect from automation in the future is to create a differentiated experience for users, make better decisions and most importantly help grow the business. Now, it is possible, and it is driven by some fundamentally new technologies that have evolved significantly over the years, such as cloud, data, artificial intelligence (AI) and machine learning (ML).

When we started talking to our various customers, we were surprised that they already understood the power of data and artificial intelligence. Most of them have done some prototypes which have also been successful. The challenge is that they are getting stuck going from prototyping at the enterprise level to large scale. Once you do that, you will find that the percentage you mentioned will improve significantly.

Let us talk about some of the common barriers to implementing automation as discussed in the book, such as lack of talent and skills, cultural resistance in organizations, fear of job loss, outdated policies, unclear metrics, and no roadmap or strategic not plan.

It is very important to understand the constraints and what prevents implementation even when the management is committed and wants to invest. Once you use an artificial intelligence-based system, the data acts as the backbone. One of the bottlenecks comes from legacy systems – too often, the data sits in different systems and doesn’t talk to each other.

The second major obstacle is culture and its human aspect. Too often, people think that automation is a technical project while it is actually a change management project. You can bring a lot of technology, but people need to adopt it in the organization to be successful.

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

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

Too often, people think that automation is a one-time project. Today’s automation is driven by artificial intelligence, where the more the system learns and the more intelligent it becomes. This is an ongoing project. You need to ensure that your data is not biased, and that your system continues to behave ethically. It is important to understand and apply these constraints.

At Accenture we have had the opportunity to implement this on a large scale within our organization. We realized that when you try to implement on a large scale, it’s not just technology; You need to consider all aspects of implementation. Otherwise, it will never succeed.

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 being implemented for this. Every organization has a different system. Sometimes, ROI is not strictly measured if it is an internal project. We also need to have some checks and balances in internal projects like what we do for our clients for external project. So, the ROI is off at the beginning, and we try to deliver that ROI at the end of the project.

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

We are talking about expanding the business. Since the whole paradigm of automation is different now, business results should be defined first before investing in automation projects.