While the process of changing people can be more difficult because it involves deeper aspects, we also have the improvement of business processes. Automation and RPA have been attracting the attention of many companies recently. This is because it involves the development of robots, also known as bots, which can carry out processes using a pre-defined decision matrix or even be associated with Artificial Intelligence and data processing in order to learn and simulate digital operational processes carried out by people.
One of them is that people with skills, knowledge and expertise in analysis and strategy (such as data wranglers, for example) will be able to leave repetitive and operational tasks to dedicate themselves to actually carrying out the analysis or even leading their teams, guiding them towards better results for the business. This allows for more strategic management, with significant results, increasing the effectiveness of deliveries on all fronts, as it increases speed and precision, as well as reducing costs.
The results, however, can vary according to the parameters analyzed, as many variables can be taken into account, such as the type of processes, complexities, integrations, processing and delivery times, volumes and repetitions. For example, if we take into account the performance variable, the return on investment could be as much as 2000%, but if we consider the financials, the return would be 110% in this example.
But, in this task, many managers end up making a serious mistake, which is not considering the cultural level of the company in relation to significant changes. Without this knowledge and alignment, the bots that would serve to generate more results end up generating internal noise in the team, causing a lot of wear and tear and frustration. Another point that is often overlooked is the company's level of maturity. Not all of them are prepared or used to technological processes or even don't have well-defined manual processes and, depending on the level they are at, the way in which RPA, or the automation chosen, should be introduced changes.
And that's what we're going to delve into in this article, covering the basics of Process Mining and also its real value within organizations.
Process Mining is a methodology used to survey business processes in order to achieve substantially positive results.
Ton Weijters and Wil Van Der Aalst created the methodology in 1999. The purpose of the concept is precisely to extract as much data as possible from each process, thus providing a comprehensive view of what is happening in the business, empowering managers with the amount of input provided for decision-making, in other words, the famous "extract, transform, load".
Thus, based on the results obtained when exploring the three pillars, we can discover flaws and deviations in the processes, thus proposing an action plan for correction. It is worth remembering that once corrections have been made, they must continue to be monitored.
The methodology uses three main types of data, usually obtained by connecting to the database of the systems involved.
These are:
An important point to note is that this data mining methodology allows us to take a snapshot of the process before the correction, for comparison purposes after the corrections have been applied. This panorama ends up showing the real value of process improvements. This is data science in its purest form!
It's also worth pointing out that the data above allows us to make a quick and simple analysis of what is happening in the business. However, there is nothing to stop us from adding more data to this analysis, since this data will undoubtedly be available in databases.
In this way, we can have a detailed view of bottlenecks and rework that can occur in processes. Thus, the more data involved in the analysis, the more assertive and accurate the Process Mining response will be.
The day-to-day life of functional analysts working on RPA (Robotic Process Automation) projects necessarily involves analyzing the processes that are candidates for robotization.
It's therefore quite common to come across situations in which the client presents us with a process that we can tell from the first meeting that it won't present the RoI or, even worse, that it isn't ready for automation.
First of all, you need to keep in mind what a robot (RPA) is capable of performing effectively. Some activities could be
And these are just some of the activities that an RPA can perform.
According to McKinsey, 30% of the tasks currently performed in organizations are operational and could therefore be automated.
Accordingly, Gartner points out that by 2021 (we're already in the second half of the year, eh?!) 90% of medium and large companies will have at least one process supported by RPAs.
In this sense, it is worth applying Process Mining before proposing an RPA project. In this way, we guarantee the client's success, highlighting process improvement and delivering robots that can return the investment to the client.
Here at AMcom, the customer's challenge is our product. In this way, their challenges are at the heart of every interaction, from start to delivery.The results we have generated for our clients are proof of this: from optimizing costs, increasing productivity and revenues and improving the experience of internal or external users, to generating a significant contribution to continuous innovation.
And of course we do this by helping our clients define and plan technological solutions for their business, creating and implementing customized, integrated and multi-technology applications. After all, we know that this is how you gain scale to accelerate and generate rapid gains in the most strategic projects, maintaining and evolving essential systems, with a focus on the user experience.
And we don't stop there! We are a strategic consultancy in RPA, specializing in scaling operations, with experience in implementation, support and governance. Check out some of what we can do for businesses seeking digitalization through automation:
What did you think? Leave your opinion in the comments and let's talk!
Blog comments