For fresh-starters, RPA may seem another ordinary development, requiring the right set of frameworks to be implemented. But this is just a look on the surface; RPA is a new phenomenon in software development and should be approached with new considerations in mind.
Today, we collected the most frequent mistakes companies make when releasing an RPA solution for the first time. These mistakes are made for lack of experience and understanding of how to handle automation technologies. Yet, even at that point, you can avoid them — by knowing these mistakes and the reasons for them firsthand.
Lack of Oversight
You may deliver a fast and scalable RPA solution that arguably meets market demands… and find yourself struggling with losses due to the low ROI. Why did that happen? Well, most likely, you missed something. You might get lost amidst all the hype around RPA, getting carried away by its novelty and promises.
No doubt, RPA embraces a robust set of technologies, but a couple of RPA training for sales specialists aren’t enough to master these. Rather, you need to have everyone on board, and, first, your IT staff, submitting them to extensive RPA training programs. Make sure you built up a strong automation department to minimize the chances of failure in this new, undiscovered area.
Wrong Automation Candidate
Another reason why your ROI may lack the desired attention is the wrong choice of tasks to automate. Will automating these bring you the value, eventually? Maybe you should go to the heart of the problem and consider automating more complex procedures instead of the basic ones? Better, don’t automate discrete procedures, think holistically instead, and choose a broader spectrum of tasks to change.
Once you build, say, a chatbot, don’t expect it to run everything smoothly, without any control from your part. As humans, AI-powered chatbots learn through mistakes, and the time should pass before they can perform tasks impeccably.
What should you do to avoid disastrous mistakes while the system is learning? Run a maintenance program along the way to check chatbot capacity at peak performance times. Ongoing tests will exclude unpleasant surprises as you will always know what the system is capable of now and calculate the value the implemented automations deliver and their overall impact on your business.
Limitations of Scaling
Bots are great at performing various tasks, thus streamlining operations. Yet, when it comes to scaling, they face many restrictions. Take a provident approach here, keeping in mind possible integrations you may need in the future. Are your chatbots capable of it? Based on that insight, you may build up your development strategy accordingly.
Concerns with Third-party Tools
There are complications when RPA tools are used for retrieving data from third-party interfaces since those aren’t uniform. For instance, truckers usually operate independently and provide paper documents to confirm delivery instead of their digital analogs.
Automating these retrieval procedures with RPA would ensure the increased efficiency of the process. On the other hand, these documents are dispersed across sources, have different layouts, and are placed in different orders.
At this point, automation software isn’t responsible to the extent you want it to be. Bots don’t make a difference among specific document structures and work according to predetermined algorithms. Hence, you need to cover as many scenarios as possible beforehand to anticipate these changes and variations by writing them down in automation algorithms.
Often, RPA projects fail because not all people involved are on the same page in the planning process. Some of them, particularly “nontechnical” marketers, may be unintentionally left out of the picture and not understand how the resulting project should operate.
To prevent the disaster, conduct practices on upskilling your marketing employees who work on the project’s promotion. After all, these people find ways to align the developed solution with your company’s business goals.
Another tip is to engage a focus group in the development process, at least several people that match your target audience. With their help, you will have invaluable insight into what features to deliver and which ones to reject.
From the managerial perspective, nontechnical specialists help you rationalize recruiting budgets since you understand what engineers to hire to deliver the demanded functionality. And, of course, stakeholders should be a part of the process; who can know what the product should look like better than they?
Wrong Success Metrics
Understanding the outcome of your venture from the start helps to define the entire journey ahead of you. Instead, companies often embark on the development with the sole purpose of doing it quickly and with the least investments possible. The goal is important, but it’s too narrow as you miss such aspects as deployment quality, productivity gains, and, finally, what value it will bring to people.
Take time to identify a goal and think about how to evaluate its achievement. The information you get will help you create an overarching vision of your future product and work out the appropriate plan on choosing candidates for automation.
Each of the described failures may have a tremendous impact on your ROI, if neglected. However, if you take care of these in due time, you may prevent adverse effects of launching your RPA software.