HGS Digital

Business process reengineering

The precursor to successful automation

Design first, automate next

Businesses are oftentimes looking to new technologies to help them stay ahead, even though their processes and systems are often outdated. To address this gap and ensure high efficiency in automation, business process reengineering focuses on fixing the processes before automating the tasks. Human efficiency that’s supported by bot technology is at the crux of process reengineering.

Reengineering is one of the core components of HGS’s automation process. It includes reviewing the current process and designing a new, improved process with the goal of enhancing the automation output.

At HGS, our expertise in process automation extends across hundreds of clients, domains, and processes. This experience, combined with experts around the globe, gives us a competitive edge.

Person drafts an automation process on a laptop, with superimposed images and data

Do the research, anticipate repercussions

While reengineering, It is imperative to identify any dependencies on interconnected processes to understand the repercussions of automation and how to deal with them.

Most process reengineering initiatives have the following stages:

Examine the process to understand the current scenario and the way the process functions
Review the process using tools that undertake gap analysis as well as eliminating any non-value-added steps within the process
Interview stakeholders to understand the objective, challenges faced, and the desired outcome of automation
Incorporate feedback to streamline the process
Get domain expertise and best practices to fine-tune the process as needed
Design the new process to make it nimble and linear and to remove current inefficiencies

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Why is process reengineering critical to businesses?

Technology

Process reengineering is imperative before automating, as it ensures efficiency and helps build stable bots. It allows us to iron out any inefficiencies in the traditional way of running the process and to address, at least at a preliminary level, people’s concerns.

Customer experience

Reengineering enhances customer experiences by improving the turnaround time of the processes. It also helps in fine tuning other connected processes that can serve as an input or output to the process being automated.

Data intelligence

Process reengineering has a big impact on data intelligence and the way organizations look to consume data. The output generated by bots can be used to study the data, which can be further used for decision making.

Man at an office desktop computer works on a flow chart for process reengineering at his company

Steps to process reengineering

Process reengineering can vary from business-as-usual, where organizations are simply looking for leaner processes, to strategic improvements involving a complete overhaul of the processes. Depending on the objective and scope of automation, there are multiple steps in process reengineering.

Identifying industry-wide best practices, leveraging know-how, and mapping the process to match the best practices
Using tools such as Six Sigma and Lean principles to find the gaps and remove inefficiencies to improve the process
Conducting a complete design overhaul of the current process
Using process-mining tools to get better visibility into the overall processes, identify gaps, roadblocks, handoff issues, etc.

Innovate and improve with HGS automation services

We provide end-to-end automation services.

Initially, we used RPA solutions only for clients but quickly institutionalized automation within our business. Today, we use machine learning and natural language processing (NLP) as a virtual workforce that is capable of executing tasks and learning from data sets, including decisions based on emotion detection.

Automation strategy

Identifying the scope of transformation and type of automation leading to clear business value

Automated Enterprise

Automating rule-based tasks in processes that involves a high-level interaction between software and humans

Cognitive automation

Machine-led digitization techniques for data extraction from structured, semi-structured, and unstructured sources

Interaction automation

Automated, self-learning interactions and systemic responses towards enhancing customer experiences

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