Project Scoping
S/4HANA
About Qorelo
We are building Qorelo as a Berlin-based team with a clear mission: change how ERP transformations work by giving consultants an AI colleague that helps turn discovery into structured, execution-ready deliverables faster, more consistently, and with traceability from the start. Not as a generic assistant. As a practical sparring partner embedded in the way transformation teams actually operate.
This is our story.
For Louis, the origin moment came during an SAP S/4HANA transformation at a Fortune 500 company. It was a serious program with serious people: senior SAP expertise, large teams, and a relentless schedule. And yet the number that stuck wasn't a milestone, a launch date, or a business outcome.
It was 800 workshops.
Hundreds of sessions to collect requirements, align stakeholders, capture decisions, and translate business needs into something implementable. The calendar filled up. The documentation grew. The program consumed attention. But progress toward something tangible—something that could finally be tested—moved painfully slowly. That was the moment the question shifted from "How do we run a better project?" to "Why is the operating model of transformation built like this?"
When you look closely, the bottleneck was not the lack of SAP expertise. It was the lack of a system that turns collective knowledge into reusable, traceable outputs.
Too many parties were involved, and the work fragmented. The same patterns repeated:
Senior experts brought crucial insight, but the machine around them turned that insight into paperwork slowly—and often inconsistently. In practice, transformation became a high-cost process of continuous re-collection.
And once you see that dynamic up close, it becomes hard to accept as "just how it is."
Nicholas experienced the same failure mode from the client side. In theory, a transformation is meant to enable the business. In practice, it can temporarily disable it.
At one point, the program forced a painful trade-off: the business effectively stopped or slowed operations just to keep the transformation moving. Internal team members were pulled away from day-to-day responsibilities. Time that should have gone into running the business went into workshops, follow-ups, and re-explaining context.
What made it worse was that the consulting support did not feel "fulfilling" in the way it needed to be. The process took too long, created too much overhead for the client team, and left people feeling like they were constantly behind—not only on the project timeline, but on their actual jobs.
That is the kind of cost that doesn't show up cleanly in a project report, but it is exactly what organizations remember afterward.
When we compared our experiences, we realized something simple and uncomfortable:
Many transformations are compromised before implementation even begins. Not because nobody is working. But because the earliest phase—Prepare & Explore—generates massive amounts of raw input, and teams lack a reliable way to convert it into:
When that conversion is manual, everything downstream becomes slower, riskier, and more political. Workshops repeat. Decisions drift. Documents become versions of memory. Teams spend their best talent on synthesis instead of outcomes.
This is where we chose our wedge.
We did not start by trying to optimize the end of the transformation. We started at the point where the disaster quietly begins: requirements and discovery.
Because if requirements are not captured correctly and mapped properly from the start, the program is already on unstable ground. No amount of perfect execution can fully compensate for a foundation that is inconsistent, untraceable, or constantly rewritten.
So the thesis of Qorelo became:
"Make Discovery Operational"
Turn scattered inputs into execution-ready deliverables that teams can trust.
We did not jump from pain to product in a straight line. We validated the problem relentlessly through hundreds of customer conversations.
That process confirmed what we suspected: the pain was widely felt, but rarely solved in a systematic way. People did not need to be convinced that the work was inefficient—they needed a believable path to outputs they could trust. That validation became the fuel to build.
Three principles define our approach:
In transformation, trust depends on being able to answer: where did this requirement come from, who said it, what was decided, and what changed?
A tool that creates yet another place to duplicate work is not progress. Qorelo is built to fit into real workflows so that the experience is smooth for users, not another layer of overhead.
We build as close as possible to how consultants actually work: in workshops, follow-ups, handovers, and iterative alignment cycles. The goal is to move quickly from discovery to execution by leveraging technology where it adds real leverage—reducing manual synthesis, compressing turnaround times, and helping teams maintain momentum without sacrificing rigor.
Qorelo stands for Core, Relevance & Logic. Because transformations don't fail due to a lack of information. They fail because organizations can't reliably preserve the relevant core and connect it to the logic that drives execution. That is what we aim to provide: a system that makes clarity durable.
For Louis, it was frustration—watching effort multiply while outcomes lagged, and seeing talented people spend time on work that should not be so manual.
For Nicholas, it was loss of momentum—feeling the organization fall behind because the transformation demanded so much attention that day-to-day work suffered.
And for all of us, it was the same underlying experience: always being behind the timeline, not because nobody cared, but because the operating model of transformation creates drag by default.
Qorelo exists because we believe that drag is not inevitable. We are here to change the system—starting at the beginning.
