Three ways you can leverage AI to get results from process discovery

https://delivery-p141552-e1488202.adobeaemcloud.com/adobe/assets/urn:aaid:aem:b829b82a-dade-4516-a581-a9c7243a658c/as/Hero_image_Forrester_Wave_1920x1280-v1.png

For enterprises to make the most of the exciting AI tools that are continually emerging, they need those technologies to fully understand their business processes. In other words, they need AI to speak the language of their business.

But getting those business processes to an optimal state where they can effectively feed AI technologies? That requires process management techniques like process discovery, process mining, and process optimization, which can all be made significantly more effective through the use of AI.

So, with AI able to both improve and be improved by processes, here are three ways to leverage AI to realize business value from process discovery tools.

1 - Create your own Process Intelligence Graph

Process discovery is a vital step in process optimization. After all, if you don’t have visibility into your business processes, and understand how they actually run, how will you ever achieve process improvement?

But on its own, process discovery doesn’t achieve very much. Even when you use automated business process discovery as part of process mining tools (rather than manual process discovery techniques), the data it produces needs to be used alongside other technologies to make it actionable and drive continuous improvement. This is where creating your own Process Intelligence Graph, or process digital twin, makes all the difference.

Creating a Process Intelligence Graph means taking the process data from automated process discovery, standardizing it, and then layering in Celonis’ own process knowledge, which draws on more than a decade of pioneering process mining experience in partnership with clients across industries. Our proprietary AI is then added to the mix, resulting in a unique graph that connects every part of your business, provides a holistic, contextualized foundation for other (often AI-based) capabilities, uncovers vital value opportunities, and helps you make more informed, strategic choices.

Case study: STADA combines process discovery with Process Intelligence

Pharma powerhouse STADA needs to continuously adapt its processes to the requirements of the industry. But that’s a challenge when departments and systems operate in isolation and there is a limited view of each business process.

STADA uses Process Intelligence to understand how the business truly runs and to see where value is hiding. The power of the platform goes far beyond automated process discovery and transparency – it allows STADA to unlock value, fast. Combining deep process insights with process knowledge and AI, Celonis delivers a treasure map of STADA’s business, and empowers its people with easy-to-action insights.

The result (so far) is millions unlocked in Accounts Payable, stronger supplier relationships, and streamlined material replenishment. Read more about STADA’s Process Intelligence journey.

2 - Use a generative AI-based digital assistant

One of the key benefits of AI in general, and generative artificial intelligence (GenAI) in particular, is its ability to process vast volumes of information and quickly come up with answers or recommendations.

European retailer Carrefour experienced the power of GenAI when it ran a proof of concept to compare procurement quotes. Manually comparing quotes previously took a buyer 30 minutes, but the GenAI assistant was able to do it in 10 minutes, delivering considerable productivity gains for the department.

Using this type of GenAI-based assistant to analyze the insight generated by a process mining tool has a number of benefits. These include making the process mining solution more accessible to non-technical teams, and rapidly identifying opportunities to improve process performance – speeding up the time to value.

AI process discovery tools: Celonis Process Copilot

Process Copilot enables a type of AI-powered process analysis that simplifies and accelerates the identification of value opportunities. This is achieved through its natural language processing (NLP) interface that makes interacting with the Celonis platform as intuitive as chatting with a colleague. Users can ask questions to help them to understand their complex processes, explore various ways to improve performance, and ultimately take action.

The Process Copilot is fully integrated with the Process Explorer process discovery tool, and is a cornerstone of Celonis’ goal to make AI work for enterprises by feeding it with Process Intelligence.

3 - Embrace AI-powered intelligent automation

Until recently, business automation largely meant automating routine, repetitive tasks, using technologies such as robotic process automation (RPA), to save time and reduce errors. Then business process automation (BPA) moved automation forward by orchestrating and automating entire workflows.

Now, with AI able to analyze and interpret unstructured data, the business applications of process automation can be expanded even further. AI-powered automation can be used to automate complex, interconnected processes and meet broader goals such as reducing operational costs, increasing productivity, and driving real business value.

But jumping into this type of AI-driven automation effort without first optimizing underlying business processes comes with a variety of risks. You could magnify inefficiencies by automating sub-optimal processes, or negatively impact other areas of the business where processes intersect.

For truly intelligent automation, AI technologies like machine learning and computer vision need to be combined with Process Intelligence. AI and machine learning can use the Process Intelligence gained from the process model, or digital twin, to identify automation opportunities, understand what’s happened in the past, predict what will happen in the future, and make decisions based on that information.

AI can then trigger automations to activate those decisions. Celonis customers benefit from easy-to-build Action Flows that are used to create intelligent alerts and process execution automations based on insight from the Process Intelligence Graph.

Case study: PepsiCo uses intelligent automation in AR and AP

PepsiCo, one of the world’s largest food and beverage companies, uses Process Intelligence and intelligent automation across a variety of functions – including Accounts Receivable (AR) and Accounts Payable (AP) – to drive better outcomes with less effort.

In AR, PepsiCo uses Action Flows to automate the creation and sending of dunning notes to collect on overdue receivables, which saves the team valuable time. In AP, the company uses Celonis’ fuzzy matching capabilities to automatically identify invoices that are split to circumvent internal approval limits. This helps with compliance but also saves at least 1,000 hours per year in manual work.

AI and Process Intelligence are better together

AI is a game changer. As our Co-Founder, Alexander Rinke, says, “It offers us the power to delight customers. Provide seamless experiences. Reduce costs. Improve satisfaction. And enable our teams with the means to make it happen.”

But making the most of AI requires optimal business processes. The latest version of our Process Optimization Report reveals 58% of business leaders are concerned the current state of their operational processes may limit what they can do with AI.

As Process Intelligence is both an enabler for, and enabled by AI, the two are most effective when used side by side. Take a look at these resources to learn more about AI process discovery, process mining and Process Intelligence: