Intelligent Automation As A New Era Of RPA

#Big Data & Highload
#Machine Learning
#Software Development
April 27, 2020 9 min read

I think intelligent automation can smooth certain tasks that in the past were impossible to be simplified, so not only will we have a much wealthier civilization, but the quality of work will go up very significantly and a higher fraction of people will have callings and careers relative to today.

Jeff Bezos, founder of Amazon.

Intelligent Automation as comprising technology in the field of RPA (Robotic Process Automation) and AI (Artificial Intelligence) is aimed at enabling business processes automation and digital transformation performance.

According to the global Statista survey, 39% of respondents share the opinion that intelligent automation is implemented in their enterprises to streamline operational activities. And 32% more notice it is planned to launch RPA in a year. RPA worldwide revenue is growing constantly as it’s seen in the chart below.

Robotic Process revenue

CMO of Softomotive, RPA solutions development company, Kyle Kim-Hays described the main 2020 trend of intelligent automation in such a way: “It’s specifically for 2020 that robotic process automation is moving from the field of back-office and IT-focused tasks and moved deeper into the production and day-to-day logistics and supply chain management operations”.

So, here we propose to outline the basics of the process intelligent automation, the main challenges of the industry now, to follow successful cases of RPA application in SCM and logistics as well as robotics technologies integration to enhance operational efficiency.

What Is Intelligent Process Automation

Intelligent process automation is the way artificial intelligence technologies, machine learning, cognitive automation, and computer vision are applied to benefit in operational business processes. Examples of everyday routine process automation are all around us as it’s depicted here.

RPA use cases

The process to build a bot (any RPA solution) or other digital workforce demands precise processes documentation to provide people with ‘a new set of eyes and nullify the waste in the process’ – that is a core characteristic given to robotics technologies by Tim Kulp, who is the Vice President of Innovation & Strategy at Mind Over Machines.

To create an RPA solution one must learn the operational part of the business in the tiniest details, and then design software to perform everyday human activities smoothly and efficiently.

RPA can be performed in different ways: just an automated complaint email response or a large bots network to automate job scopes in ERP (enterprise resource planning) system as well as an automated tracking system, inventory control, order processing, or shipment status smart documentation. In this article, we have a focus on intelligent automation tools, supply chain solutions, and artificial intelligence applications for automation business processes.

Before the more substantial description of intelligent automation as a new era of RPA aimed at streamlining business processes, nullifying operational errors, making business cost-effective, and boosting revenue, let’s distinguish the concepts specifying what’s the difference between intelligent automation, AI and RPA.

As it was defined above intelligent process automation is a complex technologies combination, among which RPA can be treated as a software robot application, where AI is a human intelligence simulation.

To consider all the differences between the terms, it’s worth mentioning IEEE Standard 2755 created for clarity in utilizing Software Based Intelligent Process Automation (SBIPA). In accordance with this standard RPA is defined as ‘pre-configured software using business rules to execute separate processes, activities or transactions’, whereas intelligent process automation is ‘the application of AI to robotic process automation’.

Automation is called ‘the fourth industrial revolution’ and paid much attention to during the last years. It pushes big enterprises to the decision of huge digital transformation. And intelligent automation has really powerful potential to smooth business processes and increase the profit, but at the same time, it’s quite a tricky thing to be implemented and tuned. It is analyzed by Forbes article deeply being summed up with the following conclusion: ‘RPA is not always the all-encompassing silver bullet it is sometimes perceived to be’. Let’s see the main challenges of intelligent automation before we present successful RPA cases in logistics and enumerate IA solutions on the modern market.

Main Challenges of Intelligent Automation

Statista calculated that 26% of companies responded in the survey are willing to implement intelligent automation on the enterprise level within 2 years. This fact proves the popularity and necessity of business automation, but to obtain an overall view of this issue we propose to follow the number of challenges:

  • having no sufficient strategy vision before business automation (it’s critical before RPA implementing to create a schedule of adoption, implementation scope, governance mechanisms, building inbound CoE (Center of Excellence) to monitor the progress);
  • ROI (return on investment analysis): dealing with numbers is important considering not only how many full-time employees you replace with robots, but how many customers have increased their loyalty gaining more personalized service;
  • talent acquisition (it’s crucial to have a capable team with good expertise in your company business processes, perfect matching skills, awaring AI peculiar features to support and maintain the business running under new technology usage);
  • choosing the vendor (we’ll make a brief market overview of RPA software development companies, machine learning consulting options, and the main challenge in this field is to define which processes are really needed automation and which is reasonable to be handled by people);
  • change management and corporate culture readiness (high-quality communication with the staff and deep leadership expertise will be helpful to improve the transition period as well as the user-friendly platform of any software you are implementing);

If you are on the path of atomizing your business processes, research the basics to know what exactly you need (either separate RPA solution or complex AI and machine learning technology application), clarify future perks, and avoid wrong expectations via challenges learning and preparation stage arrangement.

Success Cases of RPA Implementation in Logistics

If the business owner decides on intelligent process automation and starts a long-term collaboration with any software development company, it can be the start of a success story like in this video about DHL delivery automation.

The key message of the video is that successful RPA application consists of ‘looking at the business processes, documenting them, thinking how to optimize, and, then, you do not train people, you configure a bot’.

DHL presents their view of intelligent automation as ‘a constant striving for zero-defect processes and boosting productivity’. And they provide successful cases of robotics solutions adoption, ‘accelerating over the next three years’ after being applied. These are the following ones:

  • Trailer and container unloading robots, robotics arms with powerful sensors and grippers to locate single parcels, analyze their size and shape, and determine the optimal unloading sequence;
  • Flexible automation in warehousing (e.g., from Rethink Robotics) and automatic guided vehicles (AGVs) are able to assist in picking, packing, and even night premises cleaning;
  • Digital logistics service agents (e.g., Amazon Alexa) as IoT representatives to help customers in tracking the parcel, rescheduling delivery, or giving service evaluation and delivery feedback rating.

Innovecs also provides delivery tracking systems or image recognition applications for intelligent automation as well as AI-based prediction tools to optimize WMS. If you are looking for an innovative responsive partner to automate your business, just drop a line.

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Intelligent process automation is applied in a variety of fields, and it’s a continuous process starting with every business activity research, completing with RPA implementation and monitoring, and then repeating again and again after controlling and matching performance with the desired outcomes.

RPA Lifecycle with process intelligence

Intelligent Automation Solutions On The Modern Market

Application of intelligent automation (as it’s depicted above) is possible in several ways: in processing textual big data (machine captures and analyses big amounts of the texts and delivers the course of action); changing the ways the business functions (research the functions performed and optimize, reduce or cancel them); simplifying the KPI benchmarks reach; checking business functioning correctness.

Here are some examples of intelligent automation:

  • in decision-making, it’s applied in the field of finance (e.g. SAP for maintenance posts, finding inconsistencies, managing reports submission);
  • in healthcare IBM’s Watson cognitive computing technology was adopted after 15 000 training hours to understand and match English prescriptions with national policies, protocols, and guidelines;
  • numerous workflow software we use every day (e.g. Windows and email applications);
  • Kiva system robots for WMS (warehouse management systems) to travel around and process, pick, dispatch the orders;
  • Nokia collaborative robots interacting with humans: they are able to perform human tasks and be re-configured via PLCs (programmable logic controllers). Their robots of the future can deliver medicines in hospitals or guide the patients;
  • driverless cars like future logistics solutions.

All these solutions are beneficial, because they increase process efficiency, and reduce human errors, cut the costs necessary for human training and knowledge update, and provide the possibility to run the business 24/7. And the new era of RPA is coming.

Innovecs CEO, Alex Lutskiy, said: We are among companies confirming the commitment to delivering remarkable customer experience and strong dedication to engineering perfection. Hence, highly innovative RPA solutions are our focus as well as the future of AI, machine learning, and robotics integration into operational business life.

What You Need To Know About RPA

To sum up, intelligent automation is capturing the market of digital solutions now and applied in many industrial fields (from healthcare to logistics, from finance to supply chain management). The main objective of any business owner to be aware of RPA implementation challenges such as precise strategic planning, ROI calculating, creating a pool of talent able to support business in transitional periods.

After the decision is made about intelligent process automation launch, it’s crucial to find a reliable software development partner to collaborate in understanding, precise documenting, and atomizing your business processes. RPA demands tailored design, proper management, and relevant scalability.

Intelligent automation results in business running cost reduction and revenue increase as well as boosting brand loyalty due to more satisfied customers having got personalized service.

Whether you plan RPA implementing or not, pioneers of the digital innovations such as Jack Ma, founder of Alibaba, forecasts: ‘In 30 years, a robot will likely be on the cover of popular magazines as the best CEO.  Machines will do what human can not to. Machines will partner and cooperate with humans, rather than become mankind’s biggest enemy’. So, be ready for remarkable robotics changes in the nearest future.


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Article, Logistics, Big Data & Highload, Software Development