Imagine a central control room where, with just a few clicks, ‘bots’ are deployed at scale to handle different business processes automatically. This is no longer theoretical: financial services institutions are already using this kind of technology to manage key processes.

The transformation – part of what has been labelled the fourth industrial revolution or ‘Industry 4.0’, driven by waves of automation and connectivity – has been picking up speed in the last couple of years in the financial industries as new technologies and the expertise to implement them become more readily available.

Even in this futuristic-sounding scenario, humans still do most of the work. This approach, known as a hybrid workforce, integrates automation capabilities (or bots) provided by robotic process automation (RPA) and artificial intelligence platforms to handle part of the workload.

In the first two articles in this series, I touched on how to begin an efficient process optimization program that can take advantage of this shift towards hybrid work forces. Let’s now dig deeper into how to get started from an organizational perspective.

Organizational setup

An enterprise process optimization program is best driven by a central team, or Centre of Excellence (CoE), who share a lot of the characteristics of an enterprise data team – a more established part of financial institutions. In my view, three key roles drive the central team’s success:

1) Commercialization lead

Process mining platforms, which use process data to help identify process inefficiencies and how to mend them, can help generate a pipeline of ‘to-be-optimized’ processes. However, they are only one way to identify potential areas of improvement.

A program should also be in place to encourage and collect feedback from staff, especially those who are themselves operating processes. This should be managed centrally by a ‘commercialization lead’ who not only organizes the collection of such ideas but, more importantly, calculates their ROI and prioritizes the improvement pipeline.

This role represents the business side of the program.

2) Automation expert

The industry lacks a standardized automation platform. It is therefore very important for an automation expert to showcase the optimal way to deliver automation, either by leveraging existing IT infrastructure, or by working in conjunction with external vendors and platforms. This person will be deeply familiar with the strengths and limitations of the technologies available in the market and will work closely with the commercialization lead to prioritize improvements.

Not all processes in need of improvement are worthy candidates for automation and it is important to look at potential improvements from other angles. Digitalizing the process, e.g. adopting an optical character recognition (OCR) solution at the beginning of a loan application process, can banish physical documents from the entire process and remove both the manual inputting step and the checking step.

This role represents the technology side of the program.

3) Change management lead

Whatever the strategy for automation – bots, digitalization or a combination of both – there will be changes to existing processes. An efficient and good communicator is therefore required to manage the change. This person should work closely with the HR department to re-skill and, in some cases, re-deploy staff. It is of course best to plan and communicate early with the staff that may be affected.

These three roles form the foundation of any process optimization CoE, however, there are other important roles to consider, such as the overall CoE lead who looks after aspects such as performance management of the CoE and reports to the COO.

With the CoE set up, it’s mission should be to fiercely consolidate operations by looking for ways to radically improve the efficiency of existing processes.

Preparing for future operations

As the hybrid workforce becomes no longer a question of if, but when, financial industry leaders need to put teams in place to help them embrace it sooner rather than later.

While the pace of industry transformation is quickening, this is still a time of first-mover advantage. We expect to see more financial institutions stepping into this space and then executing more and more systematically – with the help of a well-organized central team.

You can read the first two articles in this series - using the links below - on how to fulfill the promise of operations optimization and how data mining can improve process discovery.