Team player - process automation
The recipe for success today lies in intelligent process automation supported by robotics, which allows resources to be used efficiently, time and costs to be saved, and complex business processes to be mastered.
Robot automation is not new: It has been used in production for a long time to increase speed and efficiency. What will change, however, are the areas of application, which are increasingly software-based.
Robotic Process Automation (RPA) is expected to be in pilot or full operation at 72 percent of companies by 2019, according to a study by Information Services Group (ISG).
What current studies also prove: The ROI of RPA depends heavily on which business processes are automated. When selecting and optimizing the processes that promise the greatest ROI, Big Data technology Process Mining can make a decisive, success-promoting contribution.
RPA: Exploit existing opportunities
Repetitive, time-consuming tasks characterize the daily work of many employees and discourage productive activities. RPA can provide a remedy here: Daily routine tasks such as creating invoices or maintaining master data are then taken over by virtual robots.
The cost and time savings potential inherent in the fully automated handling of business processes and the relief of employees is enormous - as confirmed by the ISG study: By using RPA, business processes can be carried out up to ten times faster.
Another advantage of virtual robots is their reliability: they adhere to the specified workflow at all times. This increases both process reliability and compliance.
However, companies can only fully benefit from the advantages of an RPA implementation if the preparation is right. The first step is to identify the business areas and processes that will benefit most from automation - and the second is to define the rules behind them.
Using the example of a service center where many employees post invoices, the amount of time it usually takes to prepare for an RPA implementation becomes apparent: Repetitive activities that are best suited for automation can only be identified here by searching through thousands of processes.
With process mining, this manual effort can be avoided: The technology is able to make internal business processes transparent at the click of a mouse and uncover bottlenecks and loops.
Companies can thus filter out the repetitive processes associated with high process costs and exploit the full optimization potential of RPA.
Process Mining and RPA
Process mining not only supports companies in identifying the processes whose automation promises the greatest ROI. Through process mining, selected processes can be optimized in advance and errors in the RPA implementation can be avoided in advance.
Because RPA makes processes faster, but not better. So if a company automates a faulty process, this does not increase efficiency - faulty processes only run faster. Process mining makes use of company data to automatically reconstruct actual processes and can thus uncover and eliminate inefficiencies even before a process is automated.
With this newfound visualization capability, process mining enables companies to fully realize the improvement potential of RPA.
However, it must also be mentioned at this point that RPA is far from being able to solve all problems in connection with process flows.
The human factor is also important when it comes to transforming processes or systems in companies - keyword change management. However, process mining helps to find the right tool in each case to optimize a faulty process.
More process efficiency
RPA initiatives offer the advantage over other automation solutions that they can be easily implemented without requiring changes to the existing enterprise IT environment - promising a quick ROI.
Once configured, processes become highly scalable through intelligent automation. Thus, a single software robot is able to do what several employees would otherwise have to do.
The telecommunications company Vodafone demonstrates how process mining and RPA can be successfully implemented in parallel. Vodafone has a widely ramified supplier network - the situation is correspondingly complex in purchasing, where numerous transactions and orders are processed in parallel.
The use of process mining makes it possible to visually map these highly complex processes and identify both optimization and automation potential.
In addition, current benchmarks make it possible to predict both the time and cost savings of the individual RPA initiatives. Continuous monitoring of the software robots ensures that the ROI from the RPA initiatives is guaranteed at all times.
