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When an enterprise is examining its technology landscape, there are often long-forgotten applications and data that enterprise architects (EAs) unearth, complicating a transition or adding to the timeline. And time is money. 

To help find those applications and create better documentation, André Christ and Jorg Beyer created LeanIX in 2012, later selling to SAP in 2023. 

“Multiple consultants would spend months researching and interviewing IT and business colleagues to create an accurate and complete inventory of applications and IT infrastructure in use, only to find that by the time this information was to be used for decision making, it was already outdated,” wrote René de Daniel, Principal EA at SAP, and Marianne Dahmen, Strategic Product Success Principal Consultant, Product & Engineering at SAP LeanIX, in their latest SAP PRESS publication, SAP LeanIX: The Practical Guide. 

Dahmen and de Daniel shared their insights with ASUG on how organizations can benefit from using LeanIX, how it is changing the role of EA, and what they recommend for using LeanIX in the future. 

This inter­view, con­duct­ed over email, has been edit­ed and con­densed for length and clarity.

What is your intended audience for this book, and at what point in their exploration or implementation of LeanIX do you recommend they read this?

The book targets primarily EAs and admins alike; aimed at senior EAs yet accessible from student to seasoned expert. The book supports readers from the beginning of setting up the LeanIX workspace to implementing advanced use cases and can be read as a journey or as a look-up resource.

In a nutshell, how does LeanIX enable business leaders to create the best enterprise architecture they can?

The transparency and connected data ecosystem that LeanIX creates helps business leaders find the right data in the right format and aggregation level to make relevant strategic decisions on which technology to use and roll out and what to decommission and sunset to prepare the organization for long-term success. 

Do you have any examples of how you’ve seen LeanIX help organizations uncover information about their data or technology landscape they otherwise might not know? 

A classic example is turning on, for instance, SAP Landscape discovery and finding legacy systems that nobody in the organization was aware were still up and running. The discovery functionality in particular can help identify shadow IT or unknown legacy that is still up and running and poses a security threat.

How is LeanIX poised to change the role of the EA? 

For 20 years, a big share of EA effort went into producing and maintaining documentation. In the near future, AI handles the assembly so EAs can focus on judgment. That is the design principle behind LeanIX’s AI capabilities. The architects who embrace that shift will move from the back office to the boardroom. The ones who don’t will find their role increasingly difficult to justify.

You describe waves one through three of enterprise architecture. What do you think wave four will look like? 

That is the question we deliberately left open at the end of the book; intentionally so, because we believe wave four is still being written in real time. Let us focus first on autonomy — (end of wave three). Specifically, this means the enterprise that can sense, decide, and act on its own behalf, with EAs governing the boundaries of that autonomy rather than the day-to-day execution of it.

A founder of LeanIX, Andre Christ, wrote the intro for this publication; what was the process like for collaborating with him? 

Working for and with André Christ was one of those experiences that permanently shaped how you think about leadership. André was a visionary who listened. He valued every voice in the room regardless of title or seniority, and he heard things others missed. Yet he also brought a quality of thought-leadership the EA industry had simply not encountered before: deep enthusiasm for the discipline, paired with razor-sharp clarity that cut through noise before others had even noticed the noise was there. That is part of why having him write the foreword means something to us. André embodies exactly what we tried to put into this book: a genuine passion for EA, zero tolerance for distraction, and an instinct for where the field needs to go next.

How does the acquisition of LeanIX in 2023 fit into the future vision of SAP and enabling SAP customers? 

The acquisition was not simply SAP adding another tool to the portfolio. It was SAP closing the loop between strategy, process, architecture, and execution, and positioning itself to govern what comes next. For SAP customers, that means the transformation journey now has a beginning, a middle, and a continuous operating model, with LeanIX as the architectural thread running through all of it. The part we find most interesting is the content rather than the plumbing. SAP reference architectures, industry capability models, and SAP EAF become things you pull into your workspace instead of rebuilding from scratch.

Why is measuring the effectiveness of governance important, and how do you recommend users track this? 

Ungoverned governance becomes theater, and theater is expensive. Every review board I’ve watched decay kept meeting, produced minutes, stopped changing outcomes; and nobody noticed for months because nobody measured anything except attendance. What Architecture Review Boards often cannot tell you is whether any of its decisions are actually working. Are decisions being made faster because governance exists, or despite it? Is the architecture inventory getting more trustworthy over time, or quietly drifting? Are standards being applied, or quietly bypassed? Without measurement, you are managing by assumption. 

Track coverage first. What share of changes enter the process before build starts? Then cycle time, then exceptions granted versus closed. Underneath it all sits data quality. Your governance is only as trustworthy as your inventory. Track, for instance, fact sheet completion scores, the percentage of applications with a named responsible owner, and whether lifecycle and business criticality fields are populated. 

If you are just beginning, do not try to measure everything at once. Start with one question per layer: Is our data trustworthy? Are our decisions timely? Is our landscape improving? Define a baseline today, review it quarterly. The act of measuring changes the conversation from ​“we have governance” to ​“our governance is working.” That shift is what earns EA a permanent seat at the table.

While writing this publication, what were you most excited to share with readers?

The demo workspace. Readers get a curated environment and a running case study (EA7) carried through the whole book. Too many EA books explain something beautifully and leave you nothing to do on Monday. We wanted the reader to be able to read a chapter, open the workspace, and explore hands-on in the product.

What do you see for the future of LeanIX, and is there anything that organizations should do to prepare to take better advantage of the technology? 

LeanIX is moving fast: more inventory maintained automatically, more analysis done conversationally, agents shifting from proposing changes to making them. The platform is becoming the governance backbone for every AI agent in your landscape no matter the source (SAP, Microsoft, custom-built, third-party). 

To prepare, three things matter: 

1. Fix data quality and ownership first. Move from manual maintenance to integrations. The repository cannot stay current at AI speed by hand. An AI layer on a 60%-complete inventory just gets you wrong answers faster.
2. Get EA into AI governance before it becomes urgent. 63% see EA as best positioned to lead agent governance, yet two-thirds are not currently involved.
3. Use what already exists. Architecture guidance, the EA assistant, the agent hub, etc., and become an expert in the new feature releases to speed up contribution to the broader AI strategy at your organization.

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