7 Technologies Powering the Business Process Automation Revolution
Macroeconomic factors are pushing businesses across sectors to find ways to lower costs, improve customer satisfaction, and improve overall productivity. With the emergence of many new technologies in the past few years, BPA (business process automation) has become an increasingly attractive option for many organizations.
While technology is driving innovation in this area, it’s the implementation of that tech that is truly having an impact on business operations. Everything from customer service communication, to inventory tracking, to the underlying structure of the business processes themselves is fair game to be automated. With that said, our list today is going to be a mix of the cutting-edge technology powering these innovations and some of the ways that tech is being put to excellent use in streamlining business functions. One final note before we dive in, while technically things like Excel macros can be considered BPA, we’re going to be focusing on newer innovations that have the potential to impact business across sectors and industries.
Business Process Automation: What exactly is it?
To ensure we stay on the same page, our working definition for BPA looks like this:
a fundamental redesign or existing business processes, combined with the use of emerging technology to automate workflows.
BPA has been described as “taking the robot out of the human.” What they mean is that BPA takes the rote tasks like data entry, answering the same question over and over again, and basic data analysis off of your human workforce’s plate, and serves it to the software instead. This frees your people up to focus on the creative, intuitive, and human-centered aspects of their jobs.
BPA is most often a software-based solution, whether a suite of tools or an all-in-one offering. These solutions manage both the process redesign and the automation aspects of the overall project, from one convenient dashboard.
BPA: The Innovations
As we discussed in the introduction, our list today consists of some entries that form the foundation tech upon which modern BPA solutions are built. You will have heard of some of these in other settings, we’re going to be sticking with their impact on business processes. The rest are examples of the innovative ways companies are finding to put those foundational technologies to work in designing specific ways to streamline processes, cut costs, and free up work hours.
1) Artificial Intelligence (AI)
We know, it’s 2020 and unless you’ve been living under a rock you’ve undoubtedly heard about AI. But what do you really know about it? This is one of the most misunderstood phrases in all of emerging technology in our experience. Whenever a computer uses a set of rules (algorithms) to complete a task in a way similar to how a human would do it, that’s AI. Seriously, at its core, that’s what it’s all about. And that is an incredibly powerful concept that stands to continue making waves for years to come. There is, of course, a lot more going on, but for today, that’s what we need to know about AI.
As far as it’s use in BPA, it’s everywhere. Each of the solutions discussed below, in one way or another, counts as AI. Whether it’s a chatbot answering customer’s questions or a process mining operation determining where the bottleneck in your production facility is—that’s a computer doing work formerly done by humans.
2) Machine learning
One of the subcategories of AI, machine learning (ML) is a way of programming computers to learn new ways to do the jobs they’re doing. This learning is conducted by the computer itself, rather than by a human programmer changing the code, hence the moniker machine learning.
Many of the systems used in modern BPA either are or are on the way to becoming, ML-based. Some chatbots already create new answers on the fly, rather than selecting one from a pre-programmed database. Looking forward, there are many avenues for ML to continue making inroads into BPA, from RPA bots that can teach themselves how to pick up new tasks, to analytics that can predict future needs or actions.
3) Advanced analytics
This is a class of algorithms that are using machine learning principles to learn to predict future trends based on historical data patterns. A data set is fed into the analytics engine, and the resulting output helps guide the development of the business’s next moves. Whether an insurance company looking to improve compliance numbers or a manufacturer that needs better accuracy in its demand forecasts.
This level of analysis is in use already, often in conjunction with several of the other technologies on our list. For example, IoT sensors on a factory floor may be feeding real-time data into the engine to be analyzed for signs of impending machine downtime. Or a process mining operation may be using advanced analytics to determine which processes need to be addressed first.
4) Process mining
Before any solution, including human workers, can set about analyzing and modifying business processes, it’s crucial to know those processes inside out. Process mining is an automated way of doing this with the utmost accuracy. Process mining software essentially crawls a business network, recording every bit of information it finds related to the processes taking place. This information most often takes the form of event logs.
That data is then analyzed, looking for signs of bottlenecks, missing steps, “shadow” steps taking place outside of the established process stream, and more. The interactive process map generated is then used to begin the work of repairing damaged processes, implementing fixes and changes to make others more efficient, and documenting each action taken along the way for future reference.
5) The Internet of Things (IoT)
A blanket term, referring to any piece of equipment that has a connection to the network. IoT has been touted for several years now but is really only just beginning to make an impact. This impact is being felt primarily in industrial settings, known as the Industrial IoT. Sensors on factory floors feed real-time data into monitoring software so operators have instant data on production levels.
They also feed data into analytics engines that work to identify signs of impending machine downtime so proactive maintenance can be done, eliminating delays and disruptions. The AI component here really comes into play at that last step of feeding the data to a back-office system for analysis and action. But without the sensors, the floor would still rely on a person seeing something physically wrong with the equipment to know when repairs were needed.
6) Robotic Process Automation (RPA)
Consisting of so-called “bots,” RPA solutions are a way to automate tasks like data extraction through existing user interfaces. Bots are trained by means of configuration scripts, in a way similar to the macros of old. Once a bot has learned the steps involved, they can be turned loose to continue doing these tasks 24/7, since they’re using the same interface as a human employee would, they only need to be retrained in the event of a software update that changes some aspect of that interface.
RPA is making inroads in many sectors, being used for data entry and extraction, even repetitive copy/paste tasks between legacy software isn’t beyond these smart little bots. RPA bots have their own set of user credentials, so accessing restricted data isn’t an impediment, in fact using bots reduces the possibilities of user error when the data is mission-critical.
The last time you logged onto your banking site, did you use the chat interface? Chances are, you were conversing with a bot, not a live human. The technology that underpins these chatbots has advanced quite a bit in the last few years, to the point where it’s often difficult for people to realize that it’s a bot and not a person on the other end.
With advancements in NLU and NLP (Natural Language Understanding and Natural Language Processing), bots can now parse not only the words a person uses, but they can gauge the intent behind the words as well. When you combine that ability with APIs allowing the bot to retrieve data from internal business systems (ITSM, HRIS, CRM, etc) the power of bots to operation on an enterprise-wide scale becomes evident. This level of automation frees the workforce to focus on human-centric activities, while at the same time keeping customer satisfaction high.