Is cloud computing and big data out of date? No, it’s because of them that RPA has become popular
Standing on the shoulders of cloud computing, big data and artificial intelligence, RPA can go further
By Wang Jiwei**
Recently I saw such a view: cloud computing and big data are out of date, and software robot RPA is very popular.
RPA is popular, but cloud computing and big data technology are not and will not be out of date.
On the one hand, in the IOT era, cloud computing and big data are indispensable infrastructure for all kinds of applications; on the other hand, if RPA wants to develop better, it needs to integrate cloud computing, big data, AI and other technologies; in addition, only when cloud computing, big data, artificial intelligence and RPA are developing in an integrated way, can the future era of super automation that everyone can use be realized.
This view shows that there are still some misunderstandings about RPA. RPA is not to subvert the existing technology. On the contrary, it is the development and application of cloud computing, big data and other technologies that make RPA come to the current outbreak period. If you think that RPA is popular, cloud computing and big data will be out of date, it is certainly wrong.
Similar statements are also misleading, which will make people feel that with RPA, enterprises will no longer need other enterprise management software. RPA is a connector, a ferry car, and a super plug-in. Its existence is to enable more software systems to better connect and collaborate, so as to maximize the realization of business process automation.
In view of the fact that many people are still not familiar with RPA, about the relationship between cloud computing, big data, AI and RPA, Wang Jiwei channel is here to sort out, so that we can have a better understanding of RPA.
RPA is on the cloud, SaaS cannot do without cloud computing
At present, there are three main ways to provide RPA: development type, local deployment type and SaaS type (cloud type).
The development type RPA is designed separately from the stage of defining the necessary conditions, which is suitable for large enterprises to customize; the local deployment type RPA is to install and use RPA software on the company’s servers and computers, which is generally purchased by enterprises; the SaaS type RPA allows users to log on to the cloud service platform, deploy software robots in the cloud environment, and automatically perform tasks on the web browser .
Among the three RPAS, the development cost is the highest, the local deployment cost is the second, and the SaaS cost is the lowest. SaaS RPA is most suitable for companies that want to realize business process automation through cloud services.
There are many advantages of cloud based RPA, which can help enterprises to deploy RPA across domains, as well as more convenient and efficient deployment. Enterprises can online RPA robot on demand, so as to better save costs. Even though some SaaS RPAS still need local deployment services, SaaS has almost all the advantages of RPAS, so it is more popular with enterprises.
In particular, SaaS can make RPA manufacturers expand rapidly, so it will get more recognition in the capital market.
For RPA cloud, Wang Jiwei channel《Where is the future of SaaS based RPA after going to the cloud》This article has done a more detailed exposition, interested friends can click the link to read.
In terms of trend, most RPAS have to follow the SaaS or PAAS route, which is a necessary path for platform level RPA. Therefore, many manufacturers attach great importance to RPA cloud. Laiye technology even released a “RPA cloud white paper” to tell you what is the real enterprise cloud.
SaaS is one of the three service modes of cloud computing, so SaaS RPA cannot do without the support of cloud computing. The initial RPA platform will mostly choose public cloud or hybrid cloud in terms of construction. After all, RPA is just SaaS or PAAS, and the business focus is to solve the business process automation, rather than the lower level IAAs.
In fact, as far as SaaS RPA product architecture is concerned, the popularity of RPA at the top level of the architecture is also the popularity of SaaS services, so there is no saying that cloud computing is out of date. At the same time, the majority of cloud computing companies are also launching RPA business, RPA and cloud computing are entering a new stage of integration.
RPA can make data flow smoothly, and data analysis is inseparable from big data
Similarly, the relationship between RPA and big data is not a substitute. Compared with the data collection of big data technology, RPA can move data between different software systems more conveniently and quickly, and help enterprises get through the data island in another way. RPA helps the operation of enterprises to realize data flow through automation technology. After the data flow between different systems, it still needs big data technology for analysis and mining in order to further purify valuable data and assist various decisions in enterprise operation.
For the data analysis and application process using RPA tools, the first step is to automate the business process to the greatest extent through RPA, the second step is to separate, summarize and integrate various data with RPA, and the third step is to analyze, mine and apply big data technology. It can be seen that RPA plays an important role in the collection and summary of data. If this part is realized by manpower, the workload is not large, not to mention, there is a certain probability of error.
So, can big data technology realize the part of data collection and summary? Of course, it can, but you need to build a big data platform based on public cloud or private cloud, integrate all business management software, realize automatic data extraction based on business process automation, and ensure that all data have a unified export.
It is very difficult for enterprises with many kinds of business management software in information construction for many years to realize, with large investment, long construction period, difficult maintenance and low effectiveness.
Compared with a variety of tools and platforms, RPA is the best solution. As a non-invasive “plug-in” existence, RPA is a connector connecting various systems, which can enable the majority of small and medium-sized enterprises without self built big data platform to quickly get through various platforms, and realize the business guidance of enterprises with data as soon as possible.
RPA integrated with AI makes application scenarios more diversified
RPA is process automation, which can automatically complete repeated business processes according to rules, and focuses on using robots instead of human to automatically execute various process businesses. AI is to enable machines to make judgments like human beings. The main research is to enable machines to perform complex tasks that require human intelligence.
After the integration of RPA and AI, RPA robots can not only perform automatic tasks, but also have simple decision-making ability. At the same time, this ability can be upgraded with continuous in-depth learning, which can be applied to more complex business processes.
Whether it is RPA + AI or AI + RPA, the two combinations can “communicate” with robot through monitoring engine, decision engine, operational research engine, control engine, etc. Robot can better execute operation commands through AI (OCR, NLP, voice interaction, etc.).
At the same time, the robot work data is fed back to AI + RPA (intelligent brain), after algorithm training and machine learning, a better process route is selected to run.
At present, most RPA have introduced OCR, chat robot, natural language processing, speech recognition, intelligent decision-making and other related AI technologies. RPA integrated with AI can process a large number of unstructured data quickly and accurately, so it can be competent for many business scenarios and help enterprises reduce costs and increase efficiency quickly.
You can feel the change of business process efficiency brought by the integration of RPA and AI through the following business scenarios.
- By using RPAI, we can save up to 100% of the audit process in one hour.
- A city commercial bank adopts a smart international business order checking robot with the data set RPA + OCR + NLP + kg, which shortens the remittance business process from 30 minutes to 5 minutes, improves the efficiency by 500%, and significantly reduces the error rate.
- After the adoption of cloud expansion intelligent RPA in an insurance company, the original cumbersome process of vehicle insurance recording only requires the business personnel to upload a photo, and the whole process is automatically executed by RPA robot, which greatly improves the efficiency.
There are many similar RPA application scenarios, each RPA product can effectively and quickly help enterprises achieve cost reduction and efficiency.
It should be noted that improving the efficiency of RPA application through OCR, NLP and other technologies is only one of the benefits of integrating RPA with AI. More importantly, AI technology enables RPA to understand the decision-making within the organization, and apply statistical analysis to formulate corresponding decision rules, so as to complete intelligent decision-making for complex problems in large-scale business processes.
This means that if the feeding data is enough, the time of deep learning is long enough, and the algorithm model for RPA application is strong enough, in theory, enterprises only need RPA in the future, which is enough to dig out most of the processes that need to be optimized and realize automation, which is not to mention the efficiency and cost reduction of enterprises.
Postscript: cloud computing and big data will not be out of date, RPA will be popular because of them
As the infrastructure of IOT era, cloud computing will never be out of date. It is also because of the continuous development of cloud computing, such as 5g, AI and other technologies can be more quickly integrated with various industries. Cloud computing has three main functions, namely network, storage and computing. Network is oriented to data transmission, storage is the foothold space of data, while computing is used to process all kinds of data.
Cloud computing provides the necessary technical architecture platform for big data applications. Big data must adopt distributed computing architecture. Data mining must rely on the distributed database, cloud storage and virtualization technology of cloud computing. Cloud computing and big data complement each other. Only based on big data can cloud computing be carried out, and their interaction can be managed and simulated in the current Internet world.
As long as cloud computing exists, big data technology is indispensable, and there is no saying that cloud computing and big data are out of date.
At present, the overall trend of RPA industry is that artificial intelligence, big data and other platforms are exploring and landing with the help of RPA, RPA platform has stepped into SaaS, and cloud business management software is also integrating RPA. While RPA integrates multiple technologies, integrates with multiple platforms, moves towards cloud computing and is accepted by more enterprises, cloud computing, big data, artificial intelligence, business management software and other platforms are also actively integrating RPA.
For example, Alibaba cloud, Huawei cloud, UFIDA and Kingdee have launched RPA. At the same time, many domestic general RPA manufacturers originally do cloud services, big data and artificial intelligence platforms. With the increasing maturity of RPA technology and more diverse application scenarios, RPA is becoming a new force of automation solutions and an important carrier of various digital transformation solutions. These, you can read Wang Jiwei channel before the article, here will not repeat.
I believe most people know about RPA because they have seen more and more media reports. The news of a number of RPA financing has constantly touched the public’s attention. RPA is really in fashion, but it’s not yet in the stage of pandemic.
Cloud computing, big data, artificial intelligence, low code, workflow, OA and other platform products launched by various manufacturers can also help enterprises realize business process automation. But for those enterprises with poor information foundation, it needs more investment to achieve business process automation with the help of this kind of platform.
Digital transformation needs to be different from demand. When the business volume is not so large, there is no need to invest a lot of money to build big data and other platforms. At this time, RPA is a better choice. This is one of the reasons why RPA is popular.
RPA can bring enterprise ROI is very direct, because all enterprises have the need of business process optimization. In particular, traditional enterprises still have a lot of human resources to process data tables, such as financial and human resources departments. These departments usually need more than one person to complete the work after the application of RPA, so the cost reduction and efficiency increase are very obvious.
From the perspective of transformation and upgrading, compared with the practice of big data platform, we can cut into digital transformation from business process automation, and enjoy benefits while doing practice, which belongs to the transformation strategy of killing two birds with one stone.
This is what channel Wang Jiwei is doing《Small and medium-sized enterprises digital transformation is difficult, might as well start from the business process automation》In this paper, we recommend the main reasons why enterprises should first try business process automation in digital transformation.
If you still don’t know how to carry out the digital transformation, you might as well start with business process automation, because all enterprises will have the need of business process optimization. When enterprises start from automation to solve the problem of data flow, the later transformation path will be upgraded due to demand, which is much simpler.
In a word, RPA is one of the most simple and effective tools for digital transformation, and the majority of small and medium-sized enterprises can try it.
[Wang Jiwei channel, focusing on TMT and IOT, focusing on digital transformation and process automation. 】