IT teams face the formidable, two-headed challenge of keeping the business running and driving transformation. With migration deadlines looming, tech evolving, budgets shrinking, and AI awaiting proper use, the job isn’t getting easier. Especially when you have to increase efficiency, minimize risk, and make new and existing tech play well together (take a breath).
To pull it all off, you need to understand how, when, and where the tech in your stack is actually being used across departments and systems.
And how to do that? By focusing on processes — with the help of Process Intelligence. Read on to learn why, what, and how this new class of technology is helping IT departments rise to the complex challenges they’re facing.
In recent years, a great disconnect has emerged at the heart of most enterprises.
Let’s start with the disconnect in the tech stack. As enterprises have grown, the legacy systems in their increasingly-complex tech landscapes bump up against new, fit-for-purpose apps. The gap between legacy and modern systems makes it difficult to migrate systems, integrate applications, and implement emerging tech. And because tech stacks are so multilayered, interconnected and ever-changing, it can be difficult to understand how things really happen across them. In many cases, this complexity means neither IT teams nor colleagues in other departments have a real-time, complete understanding of how, where, and for what reason tech is being used — causing big problems.
There’s also a disconnect between IT and the rest of the business, making it even harder for IT teams to understand how tech’s being used. Siloed departments are becoming more common, and as tech becomes more complex and difficult to understand, colleagues in the rest of the business can feel increasingly distant from their peers in IT.
Without shared understandings of how and why tech is being used, shared measures of performance, and shared ways to observe and discuss tech, it can be difficult for IT to get the information they need from other teams. Sometimes, non-IT teams themselves don’t even know how or why some of their own tech is used. Efforts to optimize can end up being based on anecdotal knowledge, rather than on real data — and when issues inevitably arise, IT is left holding the figurative bag.
To gain visibility into how their layers of systems, apps, and programs work together, many companies use unified data warehouses to consolidate and manage their data, along with applied analytics tools to gather relevant insights.
But these tools aren’t providing the full picture, and don’t give the context, analytics, and improvement insights needed to make decisions about how best to optimize tech and support the business. Many existing observability and analytics tools don’t know how any of IT or the business’s processes run, which systems processes run on for which steps, why delays emerge, or why errors crop up.
Without an understanding of how processes run across the business — from individual steps taken by people to sequential events that happen within the stack itself — it’s very hard to find meaning in your data, or use it to drive improvements.
In the same way that IT teams employ specialist software to provide system observability, IT departments can use the Celonis Process Intelligence platform to leverage process observability. This can help IT understand exactly how the business operates without needing to rely on subjective anecdotes, outdated process maps, or incomplete business requirements documents.
Without knowing how, where, or why business and IT processes actually run, it’s almost impossible to effectively put artificial intelligence to work and reap its full potential — which can be a thorn in IT’s side as IT is expected to lead the AI charge.
To be useful, AI needs to be given proper business context. It needs to be trained on how and where things are happening, and be given a complete framework for how things should run, end-to-end. But without an understanding of business processes, it’s very difficult for enterprises to provide this context, and, consequently, very difficult to make AI work to its full potential.
IT leaders agree: In the Process Optimization Report, IT edition, 68% said process shortcomings may hold back further implementation of AI within the next few years.
AI tools like LLMs that lack true, actionable insights into the business are able to provide little more value than standard business intelligence solutions, as they’re both pulling from the same data in the same transactional systems — without any deeper context. This can even lead to challenges like hallucinations. The last thing most IT teams need is a much-hyped tool handing out inaccurate answers due to insufficient context.
In a 2023 survey of IT leaders about process optimization, 84% said processes are their greatest lever for value and their fastest lever for change. 86% also said process optimization grows in importance during times of economic instability.
If the opinions of a few hundred IT leaders aren’t enough to convince you, consider this: IT teams often think about their projects in terms of systems they work with, or people they work with, rather than thinking in terms of the processes they work with. This point of view overlooks processes’ potential power.
Enterprises run on hundreds of millions of processes interconnecting across departments, systems, apps, and programs. Those processes can provide valuable knowledge to propel IT and the business’s projects. On the flipside, processes can cause issues if they’re not understood, or not able to be changed and improved.
Consider a major IT project like a system migration. A thorough understanding of all the processes that touch the system being migrated can help IT better plan the migration, estimate time and cost, and head off unexpected issues. Without thorough process knowledge, system migration planning can fail to account for all of the people and programs that will be impacted, which can have a cascading, negative effect on the entire project.
If you have a question about something happening within your department, your tech stack, or your business, processes can more than likely point you to an answer.
Here are a few of the things IT can learn from processes:
Process Intelligence is the powerful, insightful information that enterprises can derive from their processes. The Celonis Process Intelligence platform is made up of a broad array of tools, technologies and capabilities designed to help companies and organizations harness the power of their processes, concentrated primarily on:
Combining these, the Celonis Process Intelligence platform serves as the essential connective tissue between an enterprise’s people, systems, and processes. Think of it as the missing layer of the tech stack: better connecting your systems and programs to each other, and IT to the rest of the business. It provides an enterprise-wide shared understanding of how processes truly work, how they interact with each other, and how they could be optimized.
Using process mining, Celonis gathers and standardizes your process data, then combines it with standardized process knowledge (like key KPIs, improvement opportunities, and process best practices) and AI (built on thousands of process mining and process management implementations over the past decade) to create a living digital twin of your business processes, allowing you to see them as they really are across departments, systems, apps, and programs.
Celonis’ Process Intelligence platform is system agnostic and without bias. It can integrate data from any source or format, from all your underlying systems and tools — from ERPs and CRMs, to cloud applications, desktops, spreadsheets, and RPA bots.
It maximizes IT investments without disrupting or replacing systems of record and data platforms, layering on top of them to feed process insights to BI, automation, cloud applications, and AI. Celonis’ end-to-end context makes your technologies smarter, enabling you to orchestrate the right actions at the right times and generating meaningful predictions, recommendations, and solutions.
The Process Intelligence platform is a window into how things run, a lever for change, and a semantic layer, providing a common language between your systems and programs and between IT and the business.
When you can see your processes as they really are across departments, systems, apps, and programs, you can better understand complexity you have to work with, and more easily discover opportunities for change and improvement.
Keeping an ongoing eye on your IT processes can help you figure out when and where to take action to help your teams. In many cases, you can even use the Process Intelligence platform to trigger corrective action.
Among other things, Process Intelligence can help IT teams:
The business benefits can be hugely significant: Process Intelligence helped Autodesk save 4-6 weeks of project time during its system migration.
Finastra used Celonis to reduce its overall ITSM resolution times by 60%, while MOL Group was able to reduce its SLA response breaches by 60% with the help of Process Intelligence.
And one large telecom company was able to save a whopping €2 million annually by using Celonis to find and decommission underused software.
Process Intelligence’s end-to-end context increases the digital dividends that IT can deliver to the rest of the business. Beyond improved ITSM, better project management, and data-informed cost containment within the IT department itself, IT can also use the insights and capabilities gained from Process Intelligence to empower everyone else they work with and for.
For example, Process Intelligence can help IT:
One great example of this in practice: Sysmex America made company-wide, breakthrough improvements with Process Intelligence’s analytical capabilities. From streamlining its SAP S/4HANA migration, to helping Accounts Receivable recover $3.4 million in just one month and reducing past-due A/R by over 60% in less than a year, Sysmex’s IT teams used Celonis to help peers across the company investigate, optimize, monitor, and even automate processes.
Many IT departments also step into leadership roles by running process Centers of Excellence — central hubs that help bring process optimization to the rest of the company. Big names like Siemens, Bayer, Reckitt, and BMW have adopted IT-led Process CoE models to achieve incredible results.
Siemens increased its automation rate by 24% and reduced rework by 11% by optimizing its Order-to-Cash processes, resulting in 10 million fewer manual touches per year. Reckitt's IT CoE-led process optimization efforts helped accelerate digital transformation and save the firm tens of millions of dollars. And nearly every car that leaves BMW has been touched by Celonis (and that’s in the millions each year).
