Article | 23.11.2020
RPA's role in Mining Industry - Sisua Digital interview in Gerencia Magazine
Robotic Process Automation (RPA) is becoming a key element of digital transformation efforts around the world. A technology that, particularly in the mining sector, takes center stage for its contribution to productivity and also for more efficient decision making.
Mining, to the surprise of many, is an industry that has always sought safe, high-productivity processes at competitive costs. The processes of continuous improvement, formal research and innovation have been sources where this sector has managed to find answers to these challenges. In this sense, one of the new technologies and innovation in the traditional way of managing business processes is RPA or Robotic Process Automation, an area in which the European company Sisua Global – with its subsidiary for Latam , Sisua Chile- has specialized in the technology and processes necessary to deploy this type in any industry of projects.
According to Alan Berstein, CEO of Sisua Digital Latam, the role of RPA in mining is:
- Leverage productivity, allowing to obtain fewer resources and higher quality.
- Allow a more efficient analysis of the information, in less time and with greater analysis complexity if necessary.
- Reduce or eliminate management errors, in addition to ensuring results on time and within the committed budget.
- Data for decision-making faster, more frequently and without errors.
Better decisions at the optimal time
In a highly competitive market such as mining, with global players and a series of important challenges, the leaders of this type of company, saturated with information and overwhelmed by the large number of variables, their interrelationships and the urgency of decisions that they must take to maintain the rhythm of the business, they pose a set of key questions such as: What do we do with all this information that the different business processes give us? What impact does it have in my company, how do I quantify it? Why do we generate so much data, if in the end we cannot analyze it? Why haven’t the decisions we’ve made had all the expected impact?
Answering these questions is a function of the resources to manage the information, the time, the capacity and intelligence of the analysis, as well as the efficiency to understand and manage the results, which are ultimately transformed into decisions aimed at adding value.