Blog Post
At its most basic, automation is the implementation of a streamlined system – whether that’s technology or software, robotic tools or processes – to produce the desired outcome with as little human supervision or control as possible.
Whatever shape it takes, automation presents a powerful area of opportunity for forward-thinking companies in a variety of industries, in that it can massively increase business efficiency and productivity. Often, the time and resources saved by freeing a human workforce from repetitive, laborious, or mundane tasks, which can be time-consuming and error-prone, can be more effectively allocated to higher-value activities requiring a human touch: dealing with customer inquiries, or enhancing supply networks, for instance.
Automation’s Potential in Manufacturing
One such industry with significant automation potential is manufacturing. In a profoundly incisive report from 2017, McKinsey found that in 80% of the global manufacturing workforce, 64% of working hours were being underutilized on tasks that could be automated with current technology; representing 236 million out of 372 million employees, or $2.7 trillion out of $5.1 trillion labor.
Businesses in the distribution and supply sectors, too, can make dramatic gains by implementing automation. Business Wire forecasts that the warehouse automation market will exceed 37.6 billion dollars by 2030, yet 80% of the 150,000+ warehouses worldwide currently use no automation.
While a large part of that market value comprises robotic solutions for moving and managing goods, warehouse automation includes introducing software-based solutions to manual tasks, such as order fulfillment or data entry.
With software automation representing just one segment in the horizon of possibilities waiting to be explored, business leaders can position themselves to tap into those massive opportunities by grasping a nuanced awareness of the various types and subtleties of automation, how they may be implemented in practice, and the potential payoffs they may yield.
Types of Automation
‘Automation’ is a broad umbrella, and it can manifest in several distinct ways. Read on to explore the various types of automation.
Basic automation
Basic automation is automation at its most basic level. It is applied to repetitive, relatively simple tasks – typically the activities which a human employee would find unengaging or unstimulating and therefore be more likely to perform erroneously – and digitizes the work involved.
It does this through tools that centralize data and increase efficiency: for example, the use of an interconnected internal communications system that branches throughout the organization.
Robotic Process Automation (RPA)
RPA, sometimes called software robotics, allows a business to set up and configure several bots (or scripts) to perform a specific function at a particular time, depending on the information it presents. RPA bots can essentially copy the tasks a human would otherwise be required to perform, such as rekeying data from one spreadsheet to another or click-and-dragging files between folders.
This occurs through the combination of APIs (Application Programming Interface) and UI (User Interface), using rule-based software to execute tasks between enterprise and productivity at a high turnover rate with increased accuracy.
Business Process Management (BPM)
BPM identifies, analyzes, and optimizes business strategies and processes. Where task management focuses on individual tasks in isolation and project management involves a one-off body of work, BPM is far wider-reaching in its scope, focusing on repeatable end-to-end processes. Via process reengineering, companies can continually refine and improve their workflows.
A business process involves the specific arrangement of human resources, systems, information or data, and objects to achieve a particular outcome as part of a business strategy; BPM looks to streamline and optimize the process.
Business Process Automation (BPA)
Following the above definition of a business process – a task that follows a sequence of predefined steps to perform it effectively – BPA aims to hone and optimize those tasks where possible through technology or software-based solutions. In many cases, it’s possible to remove human employees from the workflow entirely, with the double-edged outcome of increasing efficiency and allowing the human workforce to focus on more value-adding activities.
In practical terms, this might be applied to a database. While any company will likely work with an informationally complex database, it is often time-consuming, laborious, inefficient, and error-prone for administrators to manually handle relevant tasks: data rekeying or cross-departmental collaboration, for instance. Database automation accelerates and refines those tasks with little human intervention.
The same BPA principles may be applied to network servers, which can be unwieldy for IT staff to oversee manually but have automatable steps involved in their management, yielding quick and accurate updates, provisioning, inventory management, and compliance regulation. There is also the possibility of automating the workflow of department-specific or specialized processes, where custom software can be engineered to streamline nuanced tasks.
Integration Automation
Integration automation occurs when a machine has a particular set of rules programmed by a human and can then emulate and repeat the desired task based on those rules.
This is borne out in the concept of ‘the digital worker.’ These are specially-designed types of software robots that are ‘trained’ to execute given activities or tasks alongside the human workforce. A ‘digital worker’ can specialize in one or more specific skillset and may be ‘hired,’ improving the working experience of their human counterparts and affording them increased working potential.
Artificial Intelligence (AI) Automation
AI automation involves implementing decision-making machines capable of observing and analyzing the situations they encounter and learning the most effective way to respond based on experience.
To many, ‘automation’ means ‘manufacturing automation’ and, within the manufacturing industry, there are three main ways of applying automation technology.
Fixed Automation
Sometimes called ‘hard automation,’ fixed automation is the name given to a center of production where the step-by-step operations are subject to the configuration of the equipment. Each machine contains predefined commands depending on the task it is built to perform. It is designed to perform that task repeatedly; adapting it to a variant style is challenging. Fixed automation is mainly used for high-volume production lines.
Programmable Automation
This style of automation is intended to produce batch quantities of a product. After each batch, the machines and equipment must be reconfigured and adapted to align with the new product specifications. The productivity rate in programmable automated equipment tends to be lower, as the machine is designed with an element of flexibility at the expense of optimal production figures.
Flexible Automation
Flexible automation may be seen as an upgrade or refinement of programmable automation, where the time taken to reconfigure machines between products equates to lost productivity and revenue. Flexible automated machines are limited in the scope of products they are tailored to; therefore, reconfiguration between specifications is much faster and more efficient. Often, that reconfiguration can be performed digitally without the need to alter the machine physically.
Applying Software Automation
Application of automation, specifically in an IT environment, through software, offers the potential to streamline repeatable processes, boost efficiency and productivity, eliminate human errors and realign employees to more valuable activities. Below are some ways software automation may be applied within a business.
Content Management
Enterprise Content Management (ECM) is the overall management of an organization’s content, including all kinds of documents, spreadsheets, legal contracts, and other resources. This gives the opportunity to fully leverage the information contained within that content, adding value to information that may otherwise be inefficiently stored or invisible.
Document Processing
Through a combination of AI and deep learning (a type of machine learning which aims to simulate the behavior of the human brain), document processing refines and increases efficiency in how business documents, such as invoices or POs, are extracted into a system of records.
Document Management
A document management system receives, keeps track of, and effectively files digitally-encoded documents, for example, PDFs or images of documents. Typically, document management software can record and update versions in real-time based on modifications.
Workflow Automation
Workflow automation creates a ‘hands-off’ or touchless workflow by using rules and customizable business logic to streamline processes through the reduction of inefficiency and wasted time. It can be applied to unique or non-repeatable tasks.
Decision Management
Sometimes referred to as business or enterprise decision management, this solution involves the automation of decision-making systems within a process through machine learning, which a company employs to determine the most suitable course of action in a given situation.
Process Mapping
Process mapping is typically the first step in an organization’s automation strategy: it gives a bird’s eye view of an entire process so that inefficiencies, bottlenecks, unnecessary complexities, and other costly pain points can be identified and addressed.
Improving Customer Experience with Software Automation
Of all the potential business benefits of automation software, an improved CX (Customer Experience) can be among the most rewarding. IBM found that 75% of companies when evaluating the payoffs of a digital transformation journey, indicate that CX is their most value-delivering area.
This is mainly due to the effort and resources reclaimed from low-value activities, for example, a CSR manually copying data from a PO into a system of records and realigning with more effective and profitable tasks: investing energy into developing customer relationships or servicing clients in a more timely, personalized manner.
Below are five specific use cases of automation software that may be implemented to yield directly beneficial outcomes.
Updating customer information
If a CSR or office employee spends too much time manually inputting new customer data into a company’s system, which is a time-costly process with an inherent risk of errors, RPA may be implemented. The RPA bots will quickly and accurately identify updated customer information, validate it, and store it, heading off any customer data discrepancies and the negative impact that might have on their backend experience.
Routing customer requests
Often, an employee is required to review and route customer communications as part of their job. While it’s necessary to make sure customers are directed to the correct place, this manual process is time-consuming; moreover, customer communications may contain new and potentially valuable information, for example, the opportunity to upsell or recommend a relevant product, which is an opportunity missed if the employee has no time to action that insight.
Intelligent automation can optimize the customer routing process by efficiently categorizing and extracting data, determining a priority queue, and creating individualized customer request cases that can be filled out with the extracted data.
Approving refunds
Even the most efficient human employees may struggle to keep up with refund requests in the event of a higher-than-normal volume if they are required to painstakingly and manually navigate each proposal according to its merits. This manual processing style means that customers often have to wait for a long time or may face repeated inconveniences.
A decision service automated system would have refund requests routed to it and reliably arrive at approval or denial based on multiple data input streams. From there, an automated workflow would authorize the system to issue a refund automatically, send a notification to the customer and update the company records accordingly.
Verifying customer information
It’s sometimes necessary for a company rep to pick up the phone with customers, or engage them in an email back-and-forth, to check and ensure that their record information is correct. With automated remote data uploads implemented, customers can utilize documents on a mobile device, and AI-based mobile capture could identify and extract relevant information from those documents. That data would be automatically verified, with the customer having the opportunity of a final review before it is uploaded to the company system.
Checking compliance in retail sales
When a company trades in regulated products, for example, chemical-based goods, CSRs are required to support transactions by manually verifying compliance with the necessary regulations for each sale. This may take a significant amount of time, and the situation may quickly become unmanageable in the event of a high volume of orders. Based on decision services, the automated verification process would quickly check the eligibility of purchased items against a set register of rules before confirmation, massively decreasing the time customers are required to wait.
Forces & Trends in Automation
IBM traces the inception of modern workflow automation to 2005, with the advent of BPM. Since Apple released Siri in 2011, automation has trended more towards automation software, away from tangible equipment and machinery. Today, several forces are dictating the future direction of automation developments.
Machine learning further optimizes workflows.
Machine learning aims to allow computers to learn based on their information. As this technology develops, it paves the way for new business processes or a redrawing of existing ones.
Hyperautomation
Hyperautomation aims for far-reaching, full-scale automation of as many processes as possible. It involves nuanced coordination of the capabilities afforded by machine learning, AI, and other automation technologies.
Intelligent automation
Intelligent process automation, or cognitive automation, merges AI, BPM, and RPA to optimize decision-making across operations at a scalable level. It does this by streamlining processes, realigning resources, and increasing operational efficiency.
Intelligent industrial robots
The vision for the future of complex machinery and robotics is for them to execute various functions, select a course of action, and troubleshoot and maintain themselves autonomously.
Low-code workflows
Software that requires minimal coding – or even no coding – will enable automation across an organization’s operations by making it as accessible as possible.
What is Automation Testing?
Whether intended for use by consumers or in a business context, any new piece of software must be rigorously tested before it can be deemed ready for release. The software testing process is open to automation; manual testing, much like manual processing, is inefficient and time-consuming.
Automation testing allows businesses to capitalize on harmony in their testing setup, where all aspects of new software can be tested within an automation framework with optimal levels of efficiency.
Rather than a single tool, an automation framework integrates several devices, which collaborate to perform automated software testing. It offers several distinct benefits, including:
- Reusability of testing code
- Standardization of testing formats
- Honing in on a clear strategy
- Acquisition of low-maintenance code
- Optimally accurate testing of software
- Ongoing testing with minimum turnaround time
Below, we examine 6 of the most common test automation frameworks.
Linear Automation
Also called the ‘record and playback’ model, this framework is popular for testing smaller applications or software packages. While the data comes built into the test script, meaning the test cannot be rerun using different data sets, custom code is unnecessary – so linear automation can be applied relatively quickly.
Modular Driven
The test coordinator builds test scripts in modules based on the breaking down of the overall software into component sections. Dividing the test into sections is easier to maintain and may be scaled; the tester can customize test scripts depending on the module. However, it is a more time-consuming framework to engineer and analyze.
Behavior Driven Development
The principle here is to create a platform where all relevant employees – developers, end users, analysts, executives, and the tester(s) – can participate. This yields a more holistic view and increases collaboration but requires knowledge from all parties involved.
Data-Driven Testing
In most scenarios, the tested data is extracted from files (such as Excel, CSV, ODBC, etc.), which are input into the testing script. The data-driven framework allows the tester to create testing scripts compatible with multiple file types. This increases practicality in that fewer scripts can test more data – however, it is more challenging to engineer.
Keyword-Driven Testing
Another framework best suited for smaller software, testing scripts are executed based on keywords contained within the source data set. Again, keyword-driven testing can be complex and time-consuming to set up, though it does result in reusable code. This framework is sometimes referred to as table-driven testing.
Hybrid Automation
Hybrid automation testing effectively combines keyword-driven and data-driven frameworks and yields the benefits of both with fully-scripted tests.
The Value of Automation Software
Ultimately, many processes occur within a business operation – whether in the manufacturing, distribution, supply sectors, or another industry – that unfold in a repeatable, sequential manner. It is possible to have your human resources perform these sequential steps, one after another, though time has shown that this is far from the most effective way of reaching the desired outcome, as it is laden with the risk of errors and time-consuming.
Software automation can deliver a business from those operational pain points. Well-placed and purpose-built technological solutions perform the same steps, in less time, with more accuracy – along with the knock-on benefits that yield, such as harmony within the system of records or an improved CX.
Rather than replacing the human workforce, software automation should be viewed as a constructive tool that makes employees’ work lives more fulfilling and valuable. Closing this automation gap positions an organization to reap the highest potential rewards of this expanding area of opportunity.
In today’s business world and as we move into the next generation, the automation of trade documents is a significant area of opportunity. Various unstructured trade documents – such as PDFs, POs, AP invoices, or shipping notices, to name a few – can be instantly extracted, transformed, and delivered into your system of records in a matter of minutes, with 100% data accuracy.
Get in touch with us to book a free demo of our touchless trade document automation solution.