Along with artificial intelligence, any conversation involving digital transformation and productivity gains is likely to feature business automation and automated workflows. The potential of automation software to accelerate and enhance business processes, while improving data processing integrity, is an enticing prospect for any CFO or CTO.
Automation is becoming an integral part of workflows across virtually every industry, across every business function. And at the heart of many automated processes is automation software, which (depending on scope and sophistication) can be either digital workhorse, transformation general or a bit of both – orchestrating and completing everything from routine, repeatable tasks through to complex workflows – most of which would have been previously carried out manually.
In this post, we’ll explore what exactly automation software is, its different types and levels, some common use cases, plus important considerations to getting maximum value from your automation software.
So what is automation software? In essence, the term refers to a set of tools or technologies designed to perform tasks without human intervention. These tasks can range from simple, repetitive actions to complex, rules-based processes.
The overarching goal of automation software is to enhance efficiency, accuracy and speed, thereby allowing human resources to focus on more strategic, creative and value-adding activities.
Since computers first entered the workspace, software developers have been testing new ways to drive productivity through organization and automation of menial, manual tasks. As we enter the era of generative AI, the sophistication and capability of automation software is growing at an exponential rate. An automated workflow across teams and technologies is now a business reality.
New use cases, applications and enhancements are being added to the canon of automation software all the time. This gives businesses a dizzying array of choice as to scale, scope and specificity of tasks or processes they want to automate. Starting with the most basic, however, the broad types and levels of automation software include:
Macros / scripting: At the most basic level, automation software includes scripting and macros. These are sets of predefined instructions that automate specific actions within software applications. They are commonly used, for example, in spreadsheet software, where macros can be created to automatically format data or perform common calculations.
Task automation: Still relatively basic, task automation involves automating specific tasks or processes within a workflow. This level of automation is often applied in scenarios where repetitive tasks can be standardized. Email automation, data entry and file manipulation are common examples of task automation.
Robotic Process Automation (RPA): RPA is a popular form of task automation that uses software robots or ‘bots’ to mimic human interactions with digital systems. These bots can interact with various applications, extract and manipulate data and perform rule-based tasks. RPA is particularly useful for enabling organizations to link and automate tasks across diverse systems without need to conduct complex integrations.
Business Process Automation (BPA): BPA takes automation to a higher level by orchestrating and automating entire business processes or workflows. This can involve multiple tasks and applications, creating a seamless end-to-end workflow – often utilizing elements of task automation such as RPA. Human Resources, finance and Customer Relationship Management (CRM) systems often benefit from BPA. You’ll find a great example in Celonis’ automation and digital transformation work with PepsiCo that saved the global giant millions of dollars and thousands of hours across accounts payable and receivable.
Advanced / intelligent automation: This type of software fuses automation with artificial intelligence and machine learning, using ongoing operational data to train and improve the impact of automations. This is the realm of the self-learning digital worker. This type of automation software enables evolving solutions and better decision making through real time data insights. Current high profile examples include organizations using AI-powered predictive analytics to enhance their online customer experience. Increasingly sophisticated chatbots, virtual assistants and search interfaces learn from user interaction to deliver more personalized experiences while also driving down customer services costs.
So there’s a spectrum of sophistication, from old-school to borderline science fiction. And almost every industry or internal business function will have automation software tested and tailored to their needs. It’s important to note that many automation software solutions will incorporate multiple types of automation, depending on business requirements and desired benefits.
There’s a reason so many businesses are looking to put automation software to work. But they each boil down to the same thing: delivery of business benefits and competitive advantage. Key benefits to successful implementation of automation software include:
Increased efficiency: Automating repetitive, rules-based tasks allows companies to improve productivity and speed. Software bots can process high volumes of transactions faster than human counterparts.
Cost savings: Reducing manual labor through automation significantly cuts costs associated with hiring, training and managing full-time employees.
Delivers scalability: Automation software (particularly where introduced to automate whole business processes or workflows) equips a company to seamlessly scale up. Typically these systems have the flexibility to cope with the demands of business expansion such as increased transactions, new markets or product lines. It effortlessly accommodates the challenges arising as a business grows, simplifying the process of fulfilling larger volumes and broader scope.
Strategic workforce deployment and happier teams: With mundane tasks managed by automation software, human employees can devote their talents to more meaningful responsibilities that have tangible impacts on organizations. That is, those tasks that require cognitive judgment and experience. Greater utility to the business, greater job satisfaction: win-win.
Enhanced data quality: As automation software doesn’t get bored or distracted during mundane, repetitive tasks it eliminates the human error that’s commonplace with manual data entry, calculations and recordings. As a result, businesses benefit from greater transactional accuracy and enhanced data quality.
Improved customer experience: Greater process efficiency and reduction in process errors throughout an organization can lead to faster completion of customer requests or enquiries. What’s more, automated responses via chatbots and self-serve options – particularly those powered by AI predictive analytics and machine learning – give users 24/7 instant access to more personalized services and support.
Any one of the benefits can represent the difference between surviving and thriving, or even between surviving and…not.
The reason automation software plays such an important role in so many organizations’ digital transformation strategies is how widely task, process or workflow automation can be applied across sectors and business functions. While in no way exhaustive, here are some indicative use cases that highlight the kind of impact automation software can have.
Manufacturing: Automation software can play a pivotal role in manufacturing, where it is often utilized for process control, quality assurance, inventory management or finance. For example, automated systems can streamline production lines and reduce margins of error or process bottlenecks. Case study: Take a look at how Celonis worked with global manufacturer Mars Group to apply automation to its processes more intelligently and drive down unwanted, unexplained deductions across its accounts function.
IT and software development: Within IT and software development, automation software is frequently used for code deployment, testing, and infrastructure management. Prime examples include continuous integration and continuous deployment (CI/CD) pipeline processes and tools that allow developers to frequently and reliably build, test and deploy code changes. Case study: Working with one of the biggest names in tech, Cisco, Celonis enabled 17 critical steps in its two-hour service delivery process to be automated, reaching 54% automation overall.
Retail and consumer products: Common automation software deployments within the retail and consumer products industries include the facilitation of inventory management, order processing and customer support. Case studies: In the case of global consumer health, hygiene and nutrition company Reckitt, the Celonis system used automation software to transform a range of processes from procurement to financials to order management. Meanwhile, with Conrad Electronics, Celonis used intelligent automation to deliver a slew of benefits to its order management function including: increased the automation rate from 51% to 79%, cut one hour in rework, reduced blocked orders by 30% and lowered the order rejection rate from 2.5% to 1.8%.
Telecommunications: When it comes to telecommunication companies, automation software is frequently leveraged for network management, provisioning and troubleshooting. This helps ensure the seamless operation of complex communication networks. Case study: However, when it came to Deutsche Telekom, Celonis helped the telecoms giant save over €66M by maximizing the execution capacity of its procure-to-pay process to tackle duplicate payments and cash discount losses. Of this, €12M was saved by increasing automation which drove up their ‘no-touch’ rate significantly, freeing up capacity for tactical sourcing.
Whatever use case or automation tool under consideration, the only real way to ensure a return on investment (of time and money), is to make sure that you’ve done your due diligence. Not just on the specifics of the workflow automation tool itself, but more fundamentally on the tasks, processes and workflows you’re potentially looking to automate.
It’s vital to understand how each task actually works (not just how they were designed to work) and how they interact with connected processes across the business. Similarly, you need to be clear as to the specific benefits you’re looking to generate through automation, how they will be measured and how automation impact will be monitored on an ongoing basis. Automating a process without understanding it is a risky and potentially very expensive proposition. And by understanding, we’re talking data driven insight not gut feel.
Deploying automation software to the wrong processes or to automate inefficient processes – even if the automation tool itself is excellent – is unlikely to deliver the financial or productivity gains you’re targeting. In the worst case scenario, the automation could actually amplify any inefficiencies or anomalies in the process.
That’s why many businesses use techniques such as process mining to provide the necessary data-derived insights for a successful introduction of automation software – pre-implementation, during implementation and post-implementation.
Process mining extracts information from real-time event logs generated by organizations’ systems to build up a hyper-accurate picture of business processes in all their variations. This sort of visualization provides the ideal foundation for planning business automations with confidence, with any execution gaps highlighted clearly.
Celonis has advanced process mining with the introduction of innovations such as object-centric process mining (OCPM) and our Process Sphere. These provide end-to-end maps of complex business processes, enabling you to see how they interact with each other, and even to test automation potential long before committing too much time or budget to it.
The bottom line is that implementing automation software from a position of knowledge drastically improves your chances of realizing full value on your investment.
As we navigate the evolving landscape of technology and digital transformation, the integration of automation software is set to become an ever-more pressing strategic imperative. Organizations that embrace automation position themselves to thrive – just so long as those automations are rooted in hard data, in business intelligence.
Because whatever wonders AI and ML are set to conjure up in the automation software space in the coming years, a deep and detailed understanding of business processes will remain the key catalyst and criterion for success.
Only automate what you understand. Stick with that and you’ll do just fine.