Need for a customized approach to automation
One of the ways to accelerate digital transformation is through a realistic automation strategy. The challenge, however, does not lie in simply hopping on board the automation express, but to use it in the business’s best interest.
Initially, automation was restricted to simple, straightforward, rule-based, structured processes – in other words, robotic process automation (RPA). Over time, there grew a need for a more intelligent approach for dealing with unstructured or semi-structured data.
As automation evolves, enterprises need to refresh their strategies and establish an automation center of excellence (CoE).
At HGS, we cocreate an automation CoE for our clients. At the ground level, we emphasize design over technology. We create a high-ROI implementation plan with a multi-parameter-based prioritization approach and provide the necessary support to create a CoE.
An automation CoE at the core
At the core of the strategy lies the study of objectives and success criteria—defining the metrics, measuring the value realized, identifying the right candidates for automation, and creating compelling business cases.
A good governance structure is focused on ensuring sponsorship, defining roles and responsibilities, establishing a clear roadmap to scale depending on the automation goals, and creating a change management process at an organizational level.
Depending on the organization size and setup, there are two basic types of operating models – centralized or blended. At HGS, we help define the right operating model for an IT- or business-driven organization.
It is important to build the core bot team with the right skillsets, set up project management teams, have functional support, bot stakeholder ownership, and identify outsourcing requirements and setup.
Process management skills
Key activities include opportunity identification and prioritization, bot development and support, creating design methodologies for the optimum build based on best operating standards, templates and guidelines, and setting up managed services.
At HGS, we design for automation in three ways – blended, reengineered for automation, and fully automated. It is imperative to select the right automation tools that suit the varying business needs and processes.
A quick-fix to embrace automation
Process discovery tools are a great way to determine the scope of automation required for any business that is looking to take the automation leap. These tools help to capture the processes as they stand without any bias, then determine the automation strategy that works best for the business. This reduces the time-to-market and dependencies on SMEs for process evaluation.
Factors determining automation strategy
To arrive at an optimum automation model, it is important to look at factors that can determine the success of outcome.
Scale of operations
While all businesses wish to embrace automation, depending on the scale and complexity of operations — large, medium, or small — the automation strategy and business model offered will vary.
Sometimes businesses can automate specific corporate functions (e.g., HR, finance, procurement) to improve efficiencies. These impact stories will create a conducive environment for better acceptance of automation in core operations.
Types of processes
Depending on the volumes involved in a particular process and the complexity of processes, organizations will have to choose between a simple RPA solution and an intelligent automation solution. It is important to know what and how much to automate.
Intelligent automation at the helm of change
The scope and strategy for automation may vary depending on the type of company, size, and the process design. With experience in automating across verticals, processes, and scale of operations, we partner with you to find solutions that will yield significant ROI.
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.
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