Process 

Processes are an integral part of how we get things done, whether it's in our personal or professional lives. They help us to be efficient and organised, breaking down complex tasks into smaller, manageable steps.  Robotic Process Automation (RPA) is a technology that allows us to automate these processes, using software bots to handle repetitive tasks. This can significantly increase efficiency and accuracy, freeing up humans to focus on more complex and value-added work. By automating processes, we can also reduce the risk of errors and improve the speed at which tasks are completed. This can be especially valuable in industries where there is a high volume of repetitive work, such as finance or insurance.

 

Overall, the use of RPA can help businesses to streamline their operations, improve efficiency, and increase productivity. It's important to carefully consider which processes are suitable for automation, and how it can be implemented in a way that maximizes the benefits while minimizing disruption.

 

Automation 

The term "automation" refers to the use of technology to perform tasks without the need for human intervention. It can involve the use of machines, software, or a combination of both. Automation can be applied to a wide range of processes and can be used to improve efficiency, accuracy, and speed.

​

An example of automation is the use of robotic process automation (RPA) software to perform tasks such as data entry, processing invoices, or generating reports. With RPA, a digital worker can be programmed to carry out a specific set of tasks, following a set of rules and instructions. This can free up human workers to focus on more complex and value-added tasks.

​

Robotic Process Automation 

Robotic Process Automation (RPA) is a type of technology that allows organisations to automate repetitive, routine tasks by using software bots (aka Digital Workers/Digital Workforce). These bots are usually designed high-volume, rules-based processes that are performed automatically, with minimal human intervention. RPA can work around the clock, requiring only minimal supervision to function effectively. It can greatly improve efficiency and reduce the burden on human employees by taking on time-consuming tasks, allowing them to focus on more complex and value-added work. RPA is suitable for a wide range of industries and can be customised to fit the specific needs of an organisation.

​

Automation at work

Automation has been a part of human work for centuries, starting with simple tools like pottery wheels and windmills. The goal has always been the same: to streamline processes and reduce the need for manual labour. Today, digital technologies are helping us reach new heights of efficiency and cost-saving through automation. By reducing the number of steps and hands involved in a process, we can improve its smoothness and reliability. Automation is an important part of modern business, and it will continue to play a vital role as we move into the future. 

 

Process Discovery 

Process discovery is the first step in identifying opportunities for automation in the workplace. There are several approaches to discovering processes, including forming a team to map and analyse them or using process discovery software to review and report on linkages and blockages. Regardless of the method chosen, process discovery is a crucial step in identifying areas for improvement and making informed decisions about automation. By understanding the current state of your processes, you can determine where automation can be most effectively implemented to streamline workflows and increase efficiency. Ultimately, the decision of how to approach process discovery is up to you, but it is an important consideration in any automation strategy. 

 

Application

Applications, often referred to as "apps," are software programs that enable users to perform specific tasks or access specific information. They can include productivity tools like Microsoft Word and Google Sheets, email clients like Outlook, and design software like Adobe. Applications can also refer to systems used by businesses to manage operations, such as SAP, Oracle, Dynamics, and Sage. It's important to note that applications refer to the software itself, not the devices on which the software runs. Applications can be accessed on various types of devices, including computers, smartphones, and tablets.

​

Error Rates

Error rate is a measure of the frequency of errors in a process. It is calculated by dividing the number of errors that occur in a process by the total number of times the process is run. For example, if a process is run 100 times per month and errors occur on 5 of those runs, the error rate would be 5%. It is important to track and monitor error rates in order to identify areas for improvement and reduce the occurrence of errors in a process.

​

Screens

Screens refer to the various interfaces or pages within an application that allow users to view and input information. They are an essential part of many processes, as they provide the means for users to interact with a system and complete tasks. In the context of a finance system, for example, screens may be used to input supplier information, issue payments, and view financial reports.

 

High-level Steps

High-level steps refer to the major stages or milestones that make up a process. They provide a broad overview of the process and help to break it down into manageable chunks. In the context of an invoice process, for example, high-level steps might include receiving the invoice, reviewing and validating it, entering it into the system, and seeking approval. It is important to clearly define and document the high-level steps of a process in order to ensure that it is carried out consistently and efficiently. This can also help to indicate early on where a process can be improved.

 

Scanned Documents

Scanned documents are digital copies of physical documents. They can be created by scanning a physical document with a scanner or by converting an electronic document to a format such a PDF. Scanned documents are often used to support processes within a business, such as invoicing, and may contain important data and information related to a specific job, customer, or supplier. They are a convenient and efficient way to store and access documents electronically, as they can be easily shared and accessed from multiple devices. It is important to ensure that scanned documents are of high quality and legible, as this can help to minimize errors and improve the efficiency of processes that rely on them.

​

OCR (Optical Character Recognition)

Optical Character Recognition (OCR) is a technology that enables computers to read and interpret text and numbers from images or scanned documents. It works by analysing the pixels in an image and identifying the shapes and patterns that correspond to specific characters. OCR technology is commonly used to digitise paper documents and convert them into editable electronic formats, such as Word or Excel. In recent years, advances in artificial intelligence (AI) have led to the development of OCR systems that are more accurate and efficient, as they can use machine learning algorithms to improve their performance over time. OCR technology can be useful for automating data entry tasks and reducing the time and effort required to manually transcribe information from images.

​

IDP/IDC – Intelligent Document Processing/Capture

Intelligent Document Processing (IDP) and Intelligent Document Capture (IDC) refer to advanced technologies that use artificial intelligence (AI) to extract and digitize information from documents. These technologies go beyond basic optical character recognition (OCR) by using machine learning algorithms to analyse and interpret the content of documents in greater detail. IDP and IDC systems can extract structured and unstructured data from documents, such as names, addresses, and numerical values, and convert it into a digital format that can be easily stored and processed by a computer. They are often used to automate data entry tasks and reduce the time and effort required to manually transcribe information from paper documents. IDP and IDC systems can improve the accuracy and efficiency of document-based processes, as they can handle a wide range of document types and languages and are less prone to errors than manual data entry.

 

Free Text

Free text refers to text that is not constrained by a specific format or structure. It is often unstructured and unrestricted, meaning that it can take any form and can be used to convey any type of information. Free text is commonly found in emails, reports, and other types of written communication, and can include both alphabetic and numeric characters. It is important to carefully review and interpret free text, as it can contain valuable information that may not be captured by structured data sources. However, free text can also be challenging to analyze and process, as it may be difficult to extract specific pieces of information or to compare it to other data sources. Tools and techniques such as natural language processing and machine learning can be used to help extract and interpret meaning from free text.

​

Remote Desktop/Server/Screen Reading

Remote desktop, server, and screen reading technologies allow users to access and control applications and computers remotely from a device such as a desktop, laptop, or phone. They work by establishing a secure connection between the remote device and the computer or application being accessed, and allow users to interact with the remote system as if they were physically present at the same location. Remote desktop and server technologies are often used by businesses to allow employees to access work resources from remote locations, or to provide technical support to users who may be located remotely. Remote screen reading technologies are also used to assist users with visual impairments, as they can provide audio or tactile feedback to help users navigate and interact with a remote system. These technologies can be useful for increasing productivity and enabling collaboration, as they allow users to access and work with resources from anywhere with an internet connection.

​

Artificial intelligence

Artificial intelligence (AI) refers to the ability of computers and other machines to perform tasks that typically require human-like intelligence, such as learning, problem-solving, and decision-making. It is a broad field that encompasses a variety of techniques and approaches, ranging from simple rule-based systems to more complex machine learning algorithms that can adapt and improve their performance over time. AI systems can be trained to recognize patterns and trends in data, and to make predictions or decisions based on that information. For example, a basic AI system might be trained to recognize images of cats by analysing a large dataset of cat photos and learning what features are most commonly associated with cats. It could then use this knowledge to identify cats in other images or videos. AI has the potential to revolutionize many aspects of society, from healthcare and transportation to education and entertainment. It is an active area of research and development, with significant investment and effort being put into developing new AI technologies and applications.

​

Autonomous

Autonomy refers to the ability of a system or device to operate independently, without the need for human intervention or input.  AIn the context of artificial intelligence (AI), autonomy refers to the ability of an AI system to perform tasks and make decisions on its own, without the need for human oversight or guidance. For example, a driverless car may be considered autonomous if it is able to navigate and drive without human intervention, using sensors and other technologies to perceive its environment and make decisions about how to respond. Autonomy can be thought of as existing on a spectrum, with some systems being more autonomous than others. For example, a self-driving car may be considered to have level four autonomy if it is able to drive itself in most circumstances, but still requires a human to take over in certain situations. A vehicle that is completely independent and does not require any human intervention or connection to external systems would be considered to have level five autonomy. It is important to note that the concept of sentient AI, or an AI system that is capable of self-awareness, is currently purely theoretical and has not yet been achieved.

​

Algorithms

In the context of Robotic Process Automation (RPA), algorithms play a key role in automating tasks and processes. RPA systems use algorithms to interpret instructions and execute them on a computer, just as a human worker would. These instructions may be simple, such as entering data into a spreadsheet, or more complex, such as analysing data and making decisions based on the results. Algorithms allow RPA systems to perform tasks automatically and efficiently, and can be used to handle a wide range of tasks and processes. For example, an RPA system might use algorithms to automate data entry, perform data analysis, or generate reports. RPA systems can be trained to use machine learning algorithms to improve their performance over time, making them more efficient and adaptable. By automating tasks and processes using algorithms, RPA systems can help organizations reduce errors, improve efficiency, and free up human workers to focus on more complex and value-added tasks.

​

Machine learning

Machine learning is a subset of artificial intelligence (AI) that involves the use of algorithms and statistical models to enable computers to learn and improve their performance over time. It is based on the idea that machines can learn from data, rather than being explicitly programmed to perform specific tasks. Machine learning algorithms are designed to analyse data and recognise patterns or trends that can be used to make predictions or decisions. These algorithms can be trained on large datasets and can improve their performance as they are exposed to more data. Machine learning is used in a wide range of applications, including image and speech recognition, natural language processing, and predictive analytics. It is an active area of research and development, and has the potential to transform many aspects of society by enabling machines to perform tasks that would be difficult or impossible for humans to do.

​

Intelligent Automation

Intelligent automation refers to the use of advanced technologies, such as artificial intelligence (AI) and robotic process automation (RPA), to automate tasks and processes. It involves the integration of intelligent systems and tools that are capable of learning and adapting over time, allowing them to perform tasks more efficiently and effectively. Intelligent automation can be used to automate a wide range of tasks, including data entry, analysis, and decision-making, and can be applied in a variety of industries and sectors. It has the potential to improve productivity, reduce errors, and enable organizations to focus on more complex and value-added tasks. However, it also raises questions about the potential impacts on employment and the ethical implications of using advanced technologies to automate tasks that have traditionally been performed by humans.