Robotics process automation (RPA) is a fast-growing field, with new solutions arising every month. For businesses starting new initiatives, it can be hard to decide which RPA tool has the biggest potential for the future. But it is even harder if your company already has a tool running with several automations, and it turns out that it simply is not the right one.
RPA vendors are in a constant race to introduce the newest features, streamline operations, and enhance user experience. We already see some effects of this race. Compared to where the capabilities of RPA tools are now to where they were five years ago, there has been a great deal of advancement, but for companies have seen mixed results in implementation.
There is no simple answer about which tool to use: As with most technologies, there is no one-size-fits-all solution. But if you take these considerations into account before making a single decision, your business will be much more likely to choose the most appropriate RPA tool without going over-budget.
The mother of most challenges when it comes to RPA implementation is scalability. Sure, most RPA projects start off as a small proof of concept (PoC). But this happens to be where the first mistakes occur that can have dire financial circumstances in the long term.
The problem for many teams is that most PoCs are built quickly with little foresight and even less methodology in mind. These bots become a painful burden whenever maintenance or adjustments are needed. But fortunately, this can be avoided by paying attention to the proper documentation and development comprehensive standards from the start.
Another aspect of scalability that needs to be planned from the very beginning is how full-time employee (FTE) savings will be calculated. At intive, we offer a number of great solutions that can be implemented at the design level to make the calculations accurate and easy to gather. We achieve this by understanding that with complex processes there is no single path that cases take, which allows us to create simple and elegant solutions.
The next key consideration is long-term maintenance. There's a crucial challenge that comes with each new bot that is put into production: You must spend time monitoring it, troubleshooting any issues, and updating bots in case any of the applications they use get updated.
With this in mind, it's worth checking how often different systems get their updates, how much they usually affect the user interface and if there are any APIs available – all before even starting to build the bots.
Having this information will help create more accurate ROI calculations as the cost of control and maintenance is easy to miss during initial estimations. This is a cost that you can not avoid – but if you prepare well, it's easy to minimize. At intive, we accomplish this by using bots to monitor other bots and perform the role of first-level support. This ensures we don’t have to do manual work to keep things going, as well as minimizing downtime.
While we are on the subject of finance, it's important to recognize the costs that can quickly add up. It is not advised to run some bots at all times; there are usually critical processes that should run only during standard office hours (which save on the cost of FTEs) and fewer that can work only during the night (which improve process quality).
From my experience, bots will work for up to 17 hours per day, hence you will probably have to buy a couple more licenses in the long term than you might initially expect. This will affect the actual ROI, which is why it is important to find a tool with a financial model that fits your company's needs.
Deploying an RPA initiative also creates a new dependency: Bot licenses have to be paid for each year. This means that if the prices go up – and they will – your project runs the risk of become unsustainable from an economics perspective. That is why at intive, we prioritize gathering as much information as possible to understand how a long-term cooperation with different vendors will look financially.
And finally, RPA tools each handle scaling demands differently. I have worked with tools that were hard to use past 100 bots, and others that could easily handle bots numbered in the thousands. It is worth getting different perspectives – even on RPA projects that are already running, because the earlier you check, the easier it will be to steer the ship onto the right course. For this, there's no better partner for implementing RPA tools than intive.