How Pedlar's 1-creditor model improves data quality, simplifies ERP processes and makes indirect procurement more efficient
Many companies invest heavily in modern ERP systems, automate processes and digitalise their procurement. Yet despite significant investment, efficiency gains often fall short of expectations. The reason frequently lies not in the software itself, but in the quality of the underlying data. ERP manufacturer Planat has highlighted this clearly: poor master data slows processes, causes errors and jeopardises transparency across the entire value chain.
This is particularly critical in the area of indirect needs. Here, thousands of decentralised orders, varying supplier relationships and a large number of small procurement transactions arise every day.
While direct materials typically follow clearly defined procurement and production processes, the procurement of indirect needs is considerably more complex. Office supplies, IT accessories, tools, services or consumables are frequently ordered by different departments — with their own suppliers, individual item names and inconsistent data structures. As a result, master data grows in an uncontrolled manner.
Duplicate supplier profiles, varying item descriptions or outdated creditor data mean that ERP systems lose their core strengths: transparency and process reliability.
For indirect needs specifically, this gives rise to typical problems:
What initially appears to be minor data errors quickly develops into a structural efficiency problem.
When supplier data is incomplete or inconsistent, this directly impacts operational processes. Invoices cannot be processed automatically, orders run through incorrect creditors and analyses lose their validity.
Indirect procurement affects almost every department in the company. Erroneous data therefore multiplies across numerous processes simultaneously — from procurement and accounting through to controlling.
ERP systems are intended to simplify processes. Without clean master data, however, the exact opposite occurs: more manual work, more coordination effort and lower process automation.
As data volumes increase, the situation intensifies further. Companies today manage significantly more suppliers, orders and invoices than just a few years ago. At the same time, they expect real-time transparency, automated approvals and reliable analyses. This only works with a consistent data foundation.
Particularly in indirect procurement, it becomes clear that data quality is not a purely technical task. Companies need clear responsibilities, standardised processes and systems that reduce complexity rather than creating new data silos.
A central lever for improving data quality in indirect procurement is the reduction of supplier and creditor complexity. This is exactly where Pedlar's 1-creditor model comes in.
Instead of creating and maintaining numerous individual creditors for different suppliers in the ERP system, Pedlar consolidates all indirect needs through a single central creditor. Companies benefit from a significantly simplified master data structure, reduced maintenance effort and more consistent procurement data.
This not only reduces administrative complexity in procurement and accounting, but also improves the foundation for automation, reporting and controlling. Invoice processes become leaner, ERP data cleaner and expenditure more transparent. Particularly for heavily fragmented indirect procurement processes, the 1-creditor model creates significantly higher process stability.
Discussion around ERP systems often focuses on features, automation or AI. Yet the actual success factor frequently lies deeper: in the quality of the data foundation.
Especially for indirect needs, a clean master data structure determines whether processes scale efficiently or grow increasingly complex. Companies that consolidate their procurement data and actively reduce complexity create the foundation for sustainable digitalisation.
Because an ERP system can only work as efficiently as the data on which it is based.
