“Bots create acceptance for digitisation”

Acceptance reason 1: You can watch how the bot works

Each bot at ERGO not only has a personnel number created in the HR department - because only registered employees are allowed to access sensitive customer data. In some teams, the robots also have names. They are called Roberta, Probotti, Manuel Bü or T-Rex. This is one of the most important reasons for acceptance: A bot works like a clerk, merely mimicking the clerk's activities. You can literally watch it perform its work.

Imagine looking at your computer screen and watching a movie in fast-forward mode: an Excel spreadsheet is opened, data is copied, spreadsheet is closed again, another spreadsheet is opened, then a Word document, data is copied from left to right. 30 process steps that run before your eyes at breakneck speed. At the end, you see the letter to the customer being pushed into the outbox.

Afterwards, your eyes may hurt, but you were able to watch how the digital works. With a classic AI, it's different. You don't see (and understand) how image recognition fishes photos that include, say, railroad trains out of millions of photos. You don't know how the AI recognizes that that's a train in the photo and not a wall or a candy bar in the landscape. And, frankly, Data Scientists often really don't know much more, either.

That's a clear victory for the robots against machine learning! This kind of traceability creates trust. You know what the machines are doing. The mystique that often surrounds the digital is thus lost.

Acceptance reason 2: Annoying typing work is eliminated

Typically, what makes your life easier grows on you. To me, that's the case with my insurance scanning app for submitting medical bills, and it's the same in my case with Google Maps. Even with the bots, colleagues quickly realized that the digital helpers provide real assistance with daily routine work. Effects such as "less overtime" were directly noticeable.

The robots take over tedious, monotonous, low-value-added tasks with high transaction volumes. Typing tasks that nobody likes to do. Open one system, copy, open the other system, and so on. With large insurance groups that have merged several insurers under one roof over the years - each bringing its own technical system landscape - this is not uncommon. That's why there's such a need for bots to link the systems together and do the mindless copy/paste.

For employees, this simultaneously means they can (and must) devote more attention to the more complex activities of customer and claims service. This realization also increases the acceptance that the robot relieves employees of repetitive processes in order to bring in their strengths such as creativity and emotionality in the sense of customer orientation.

This realization led to a fundamental rethinking in the specialist teams: With the prospect of remedial action, the willingness to critically scrutinize and automate other processes grew as well.

Acceptance reason 3: fast, inexpensive, customer-centric

The approach to building the bots differs from classic large-scale IT projects: At RPA, we make products, not projects. Producing tangible results in a short time without changing existing system landscapes - that's what it's all about.

As a result, only a few weeks, rather than months, pass from the start of the project to the day a bot goes live. Some people talk about “no code - low code” here - in other words, a manageable programming effort. We work with Blue Prism, by the way. There are few technologies where such a short time elapses between plan and finished product. Two robots go live at ERGO Germany every month.

For our colleagues in those departments the bots are meant for, this is crucial. They have to pursue their actual job in customer service. There, capacities for projects are severely limited. The short sprint instead of a long project marathon raises motivation, leads to a better product and more acceptance for the technology right from the start.

The beauty is: RPA is capable of increasing employee satisfaction as well as improving the service experience of our customers and working more cost-efficiently. The technology has also been tried and tested for a long time and is therefore mature.

Acceptance reason 4: cross-functional working

The teams work agilely according to DevOps principles: The classic separation between “one writes software (Dev), the other runs it (Ops)” is eliminated. Four to six colleagues form a team, composed in the roles of Process Owner, Subject Matter Expert, Process Analyst and Developer. They work in close coordination with the IT infrastructure.

The RPA team does not see itself as a full-service provider: Although it supplies complete solutions from a single source - from potential and process analysis to development, testing, coordination with the works councils and operation - the departments for which a robot is being built are deeply involved in the project.

This cross-functional work is another principle we promote at ERGO: don't just digitize and put it in front of the target department. Instead, involve those specialist colleagues and develop things together with them. Make the bot their bot!