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Robots on the Loose: Avoiding the Chaos of the Unmanaged Digital Workforce
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March 5, 2021 Blog

 

Authored by: Zakir Ahmed, Senior Vice President & GM – Asia Pacific & Japan at Kofax

Many companies are well in the throes of scoping out their robotic process automation (RPA) projects. Some have even designed their software robots and are ready to deploy.  Even after your army of super-productive software robots is up and running, it still needs guidance, management and maintenance. And that requires a strong governance and version control programme.

When a robot breaks down, if you don’t have governance, it’s almost impossible to track which one among hundreds or thousands is causing an issue or where one may have crashed into another and stopped a process in its tracks.

As EY points out in its report, “Getting Ready for Robots,” it’s not easy getting RPA right. “We have seen as many as 30 per cent to 50 per cent of initial RPA projects fail. This isn’t a reflection of the technology; there are many successful deployments,” the consulting company says, “But there are some common mistakes that will often prevent an organisation from delivering on the promise of RPA.”

From a technical point of view, governance is easy to accomplish when RPA tools include management and oversight capabilities like version control, or more sophisticated capabilities such as Robot Lifecycle Management. Getting governance right also requires organisations to first define guidelines and rules. In fact, according to Forrester Research, the top reasons organisations struggle to deploy RPA are performance and scalability, followed by managing rules of robot behaviour and controlling and operating RPA robots in a mature fashion.

To maximise RPA benefits, chief operating officers (COOs) and chief information officers (CIOs) should collaborate to lay the governance groundwork for how RPA robots will interact, access and disseminate data and content.

A best practice is to put a guiding framework in place. While operations will naturally take the lead in designing such a model, they must work closely with IT on strategic initiatives to avoid duplicating automation efforts.

An effective framework requires three elements:

 

  1. An enterprise robotics council to define scope, spearhead the program and set targets for tracking execution efficiency and outcomes
  2. A business unit governance council that will prioritise RPA projects across departments and business units
  3. An RPA technical council – also known as the Centre of Excellence (CoE) – that designs standards, formulates working principles and guidelines and compiles best practices

 

To accomplish the first and third elements, the governance team needs certain tools embedded in the RPA platform, including robot analytics, performance tools, version controls and security. For example, a platform that integrates Robot Lifecycle Management helps teams manage enterprise RPA robot deployments from hundreds to thousands of RPA robots. With it, teams can more easily keep track of changes, compare files and explore changes made. It also makes it easy to store backup files so that if companies must revert to a previous working version, they can do so easily.

Meanwhile, the CoE plays a critical role as it acts as “single source of truth” and keeps the organisation focused on the long-term goals. It represents a group of core resources and people that guide all things related to automation, including maintaining and overseeing standards across the business; training; management of vendors; establishing best practices and so much more.

Members of this team come from across the organisation. IT is a core member, but stakeholders from each business unit bring subject matter expertise. With this collection of intelligence, the team is better equipped not only to make decisions on the right RPA tools to deploy but also which processes are prime candidates for automation. Organisations also have flexibility in terms of how such a programme can be structured. There are three main models, each differing in how responsibilities are shared across the enterprise.

Centralised operating model: A single team is responsible for running and controlling all aspects of the programme.

Decentralised operating model: The responsibilities for running the automation programme are replicated across separate business units within the organisation.

Hybrid operating model: Some aspects of the automation programme are run by a single, centralised team, while others are replicated across business units.

Of course, there’s no ‘right’ or ‘wrong’ answer. Organisations and financial teams should start with the model that makes the most sense given where they are today and adjust down the road as needed. By leveraging a Centre of Excellence along with sophisticated tools like Robot Lifecycle Management, organisations can take a more business-centric approach to RPA that goes far beyond simple task automation.

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