Automation Is Everywhere. But Where Do You Start?

Many organizations are looking at automation as a solution that unlocks value and efficiencies across business processes. However, while the promise of intelligent automation is vast, for many companies this remains a case of “easier said than done.” Recent research from Accenture underscores just how important automation has become to business success and sustained growth. We’ve watched how the pandemic has impacted companies’ technology strategies and performance. We’ve seen some companies step up investments in intelligent automation and other technology in order to leap beyond their peers and grow their businesses five times faster.

The mandate for the IT department lately seems to be “do more with less.” In a world of scarce budgetary resources, IT organizational capacity, and managerial attention, determining how automation fits into the IT architecture can be a considerable challenge. If a management team is serious about realizing the potential of intelligent automation, there must be a way to identify opportunities that are data driven. Based on what we have seen work in most business settings, there are several core steps that allow companies to bring control, structure, and strategy to their intelligent automation projects, ensuring that the full value of these projects can be realized.

1. Find your North Star

The first step is to identify the priorities for automation in terms of what will make the enterprise more successful. Will it be by creating new offerings and customer-facing capabilities that generate revenues? Will it be by improving the efficiency of existing processes and applying automation to reduce the number of repetitive tasks performed by people? Is intelligent automation the answer to greater speed, lower cost, or better service? Having clarity on enterprise goals from the outset allows potential use cases to be mapped against the current corporate strategy and specific opportunities to be prioritized.

One luxury automaker, for example, set a clear business goal for their intelligent automation efforts: achieve higher productivity in manufacturing through the proactive prevention of issues that might stop production. Every project entails a cost, so the imperative is to look at the projected return on investment. There must be a business case for any automation with considerations on financial return considerations and broader business value.

2. Scope your processes

This is a good time to take inventory of business processes. Every business has processes that are redundant or unnecessary and can be eliminated for improved efficiencies before automation is even brought on. During this mapping phase, it will become apparent that some processes need to be completely reimagined in order to make them more effective or reflect new operational realities. This work needs to be done before moving ahead with automation, otherwise you will still have the same inefficiencies -- they’ll just be automated now.

One of our favorite stories came from a client that had a monthly process that took 17 days to complete. But as we looked more closely, we found that exactly zero users had accessed the application over the past six months! The decision was made to decommission the process, saving time and resources for more valuable projects.

3. Start with the obvious

In general, applications that present themselves as automation opportunities will have some common characteristics: they may require frequent manual updates or scaling, data extracts, or a high degree of personalization.

If an application relies on data, it is a natural candidate for artificial intelligence, such as machine learning for self-evolution. Be wary, however, of greenlighting too many projects. It is easy to become so enamored of emerging technologies that you invest in automation for automation’s sake.

The first candidates for automation can be chosen based on potential business impact. A process improvement methodology such as Lean Management or Six Sigma often helps point the way. An analysis using Six Sigma’s cause and effect and design thinking-based prioritization matrixes, for instance, can reveal processes that should take priority based on criteria including their frequency, effort required to automate, criticality to the business, and potential time savings. Once values are assigned to each of these factors, it is a simple matter using the matrix to calculate totals and determine how high on the list of potential automation projects a given process should go.

4. Assess your organizational maturity

Before making a start, evaluate the company’s current automation maturity, as this will impact the ability to execute on its automation plans. In other words, an idea may have incredible potential, but can you pull it off?

An automation maturity assessment is basically an exercise in benchmarking, comparing what one’s own company is doing and capable of doing versus what can be observed at peer companies. Frankly, many companies overestimate the maturity level. Good questions to ask at this stage are: How would we change our business and processes differently to take advantage of automation? And how different is this vision from the current reality?

For instance, a retailer with foundational automation would be running a basic ecommerce site. To move up a level, the retailer could add robotic process automation across its operation to check inventory numbers and prepare orders for vendors. One more level up, and the retailer is using analytics to support better decision making by its merchandisers by predicting demand for new product launches.

5. Draw your automation roadmap

The roadmap charts the projected journey of a company from current to future goals and is inclusive of the scheduling of automation projects, the pace of change, and deployment strategies. This is the long-term journey of automating everything that should be automated, at the right time, and in the right way to best serve the business goals. It’s also a journey of building the deep expertise and new IT skills needed across the workforce, developing these in a structured manner, and creating an “automation first” culture. And don’t forget to include how success will be tracked and measured. It’s important to have established a baseline at the outset to be able to measure the ROI on automation.

Study, strategize and solve

While intelligent automation requires real work and commitment, the key to success isn’t that complicated. The key is to study, strategize, and solve. How can a team go about finding and assessing automation opportunities? It starts with gathering inputs and as much information as possible about existing processes, systems, and data. Then get clear on overall business priorities. Then study, strategize, and solve -- that is, the team should generate insights from data analytics and benchmarking that point to good automation opportunities. Strategize which of those opportunities to prioritize based on their business impact; then design specific automation solutions in line with the organization’s capacities for developing and embracing new technologies. The result: automated and optimized processes that bring in value and contribute to business success.

About the Authors:

Dr. Bhaskar Ghosh (@DrBhaskarGhosh) is the Chief Strategy Officer at Accenture. Gayathri Pallail is an Associate Director for Automation Strategy and Deployment at Accenture. Rajendra Prasad (@rp_automation) is the Global Automation Lead at Accenture and heads a team that helps organizations across the globe successfully implement and scale intelligent automation transformations. They are co-authors of the book, The Automation Advantage.