Robotic Process Automation (RPA) involves automating simple transactions for speed, accuracy, and efficiency, at a fraction of the human-labor cost. Organizations are fast turning to RPA to streamline mundane operations to drive efficiency and effectiveness in business operations. Seeing this trend, Forrester has predicted that the RPA market is expected to grow 41% per year up till 2020, reaching $2.9 billion in 2021. This is thanks to the fact that RPA is quick and easy to implement, and presents very tangible business benefits. However, there is a caveat here. A thoughtless and impulsive approach to administering RPA, without an in depth understanding of the concept and its implications, is sure to pose problems. Today we see a race for RPA, with every organization aiming for it, without proper planning and needs analysis. This is a sure recipe for failure; it can lead to corporate risk due to too many bots not doing the right things in the right way. Companies must therefore resist the temptation for ad hoc RPA implementations are have a centralized, meaningful RPA strategy in place.
First and foremost, RPA presents a challenge in how to balance speed versus control. While many bots performing different tasks give the advantage of speed, overpopulating a function with bots could entail them going out of control. The answer to this is to centralize RPA, and here are the three models you can choose from to make this happen:
These three models will help centralize digital labor, bringing about a modicum of control and direction to the RPA process. Each has its pros and cons, and organizations must evaluate which suits the business model and RPA objectives. A centralized model is the way ahead if organizations expect to realize the benefits such as quality, consistency, risk management, market intelligence, flexibility and scalability. Whatever model they choose, leaders must make sure their plans are flexible and adapt to the changing times as RPA standards evolve.
Source: Read IT Quik