Our economy is now truly global, meaning companies grow, change, and become increasingly complex. More people are involved in day-to-day business, more data is locked in disparate systems, and there is more unpredictability – thanks to political developments or global epidemics.
Therefore, business processes become very complex, variable and difficult to control, creating additional costs or even risks for any business. The current COVID-19 situation with most employees suddenly working remotely shows the challenge for businesses to stay transparent in their processes and communicate to keep up the good work.
But all is not lost. To continue growth and increase profit margins, technologies are available that can help to analyze and optimize these processes, making everything run more smoothly.
Artificial intelligence (AI) and machine learning (ML) have gained significant momentum in recent years. As businesses from all industries continue to invest in innovative technologies at a fast pace, adoption will only increase further. Greater numbers of companies are beginning to see the positive impacts this technology can bring – and Gartner predicts that by the year-end, 85 percent of all customer interactions will be managed without a human.
Traditional business intelligence (BI) tools have helped provide high-level ‘overview’ analytics, which lets process leaders make more informed decisions from the massive amounts of data they have by collecting it to display key performance indicators (KPIs). Using BI, companies can analyze big data and view summaries of the data in real-time.
However, like many other technologies, it has limitations. While BI software can shed some insight into business operations, it has always required a hypothesis on which to shine the light. Only then can you see where things work well or don’t. That means users need to understand the process and be able to ask the right questions, and without those questions, traditional BI analytics cannot uncover anything. In addition, processes tend to be rather complex, which means it is difficult to gain a detailed explanation of what is going on. While BI can display the operational metrics, they still need to be interpreted by humans – but different people will look at the same metrics and see different meanings.
The Secret Weapon
This is where process intelligence (PI), a new type of big data analytics for business processes, comes in. PI leverages a suite of different technologies to change and enhance the way business users understand processes: process mining, industry best practice analysis tools, real-time monitoring through text messaging, e-mail, and webhooks, and predictive AI capabilities.
Why is this technology a secret weapon? Process intelligence does everything that traditional BI can’t. It offers 100 percent transparency into how processes are working in real life, enabling them to detect business process inefficiencies. There’s just not any other software solution available today that enables such a deep understanding and real-time monitoring of business processes. With today’s process intelligence solutions, you see the “as-is” state, including all the advanced analytics, and have the ability to drill down into the granular details of processes. Process intelligence can explain why processes are broken and how to fix them by giving the data you already have a ‘full body scan’ – this scan presents you with unbiased analytics to solve problems you didn’t even know you had.
The future for BPM and AI is bright! With AI, processes are being transformed on an entirely new level, and many businesses are continuing to implement AI in new ways to bring new improvements. AI is empowering human intelligence to continually improve user interactions and process execution.
This is a marked change, as until recently, consultants were the best solution to improve business processes. The main issue here was the plethora of manual tasks involved in understanding and analyzing processes, meaning consultants come at a high price and with their own biases and preconceptions alongside them. For businesses using advanced process analytics, the benefits of objective analysis quickly become clear: no more biases and no more guessing games. You can now analyze processes from the data you already have.
The objective, all-seeing view of processes and process flow that is now being presented to businesses provides them with the opportunity to introduce Robotic Process Automation (RPA) into their processes. With AI and RPA in one package, bots can continuously learn new paths that improve performance and reduce time constraints. This ultimately leads to truly intelligent automation.
Powering the Future by Intelligent Automation
Intelligent automation uses advanced process analytics to observe historical patterns and flag future constraints that are not easily perceived by a human. Advanced decision automation capabilities can be based on both process-mining algorithms and machine learning techniques. This then allows for the ability to analyze business process execution and predict certain behaviors that may result from specific steps within the process. Intelligent automation can be used in this way to make real-time recommendations for automated or human decision-making, creating a more streamlined and efficient process flow.
True intelligent automation, if applied correctly, can predict constraints that may happen and align them with the available resources. This means that instead of being reactive to issues you may encounter, you can become proactive about them, avoiding potential bottlenecks, backslides and delays. This is achieved by combining advanced process mining, process-flow pattern detection, and machine learning, all of which are then able to guide corrective actions and update bots in real-time – closing the loop on automation.
Without intelligent automation, organizations can only be reactive, learning about problems – no matter how big or small – when it’s already too late. When monthly or quarterly reports are due, employees will be consistently checking to try and find issues that have already happened, and which cannot be changed. In this day and age, the concept of not acting before problems occur when the technology to be ahead of the game seems like living in the Stone Age.
So why wait to begin using this technology? Why miss out on gaining a huge competitive advantage, and saving time and money? We know that early adopters are experiencing better process execution and are continuing to benefit from process excellence, time and time again. We also know that this technology enables higher-skilled workers to focus on the more difficult and time-consuming work that would otherwise be left behind, to the detriment of the business.
AI and machine learning are now mainstream business tools being used in myriad technologies, including process intelligence. With all the benefits this could bring, it should no longer be a question mark for any business that wants to secure its future. Put simply, not investing in intelligent automation is a step in the wrong direction.
Susanne Richter-Wills is Head of Sales DACH at ABBYY.