Streamline & Prioritize ERP Data Cleansing

July 17, 2026

Like most manufacturers we work with, your ERP data is likely not perfect. In almost all cases, our clients face an abundance of inaccuracies in their data. Some companies think all ERP data has to be in order before they can implement a factory analytics solution like LeanDNA. But maintaining high-quality ERP data is an ongoing requirement, and LeanDNA can help you get there.

Here are the three key ways LeanDNA helps teams like yours take a simpler, more manageable approach to ERP data cleansing.

Data Validation: LeanDNA identifies and flags the most critical ERP data sets to get you up and running with inventory analysis.
Prioritization and Cleanup: LeanDNA prioritizes data issues with the greatest business impact to deliver fast time to value.
Continuous Improvement: Ongoing recommendations continue to surface data-cleansing opportunities as you operationalize usage of LeanDNA.

Focus On the Most Critical Data First, Then Continuously Cleanse Over Time

The truth is you don’t need impeccable ERP data to be successful with factory analytics. In fact, only certain data tables need to be mapped to use LeanDNA. Through our vast experience working with manufacturers of various sizes around the world that have unruly ERP data, we’ve developed a proven methodology for systematically prioritizing and cleaning the requisite data sets.

Common Inaccuracies in ERP Data

Inaccurate Demand
Wrong Item-to-Buyer Assignment
No Supplier Commit Dates
Invalid Lead Times
Wrong Lot Sizes or Order Policies

In this way, LeanDNA serves as a tool to assist your data-cleansing process. Our solution provides an ongoing, surgical approach to uncover data issues by shining a light on inventory data in your ERP, surfacing inaccuracies, and recommending prioritized actions to resolve them. This process guides and empowers your teams to cleanse the most critical ERP data day-over-day while simultaneously optimizing inventory.

The Shortages Report in particular is helping our buyers and supply chain teams understand some of the rubbish data that’s been left behind that they’re now tasking each other to clean up. It’s also helping to clean up the MRP engine side of things, like accuracy of requirement dates and policy, as well as purchase price data. - Craig Jarman, Business Intelligence Lead at Safran Seats GB

Challenges With a One-Time Blitz Approach

Many leaders believe they must undertake a massive company-wide project to address all of their data issues before they can implement an advanced analytics solution like LeanDNA. This “one-time blitz” approach presents a number of challenges. First, work is concentrated in a single employee or team, which leads to multiple opportunities for failure when time constraints inevitably arise. A large project of this type also requires significant IT hours to build out reports and surface all of the data issues. With so much on their plates already, IT departments don’t have the time or resources to dedicate the necessary man-hours.

How LeanDNA Eases the Burden With an Ongoing Approach

First, LeanDNA identifies and flags the most critical issues during the data validation process. These are brought to light via daily prioritized actions that teams use to address the most valuable next steps. After implementation is complete, LeanDNA continues providing daily prioritized actions, task assignments, and system-generated emails to encourage streamlined collaboration on addressing data-quality issues. By standardizing work processes, LeanDNA helps eliminate the dependency on tribal knowledge around data, bringing everyone onto the same page with the same current information.

Key Benefits

Address ERP data cleansing in smaller, more manageable chunks of work, rather than with a huge, expensive initiative.
Prioritize data actions based on real business value.
Distribute actions across teams, over time, rather than requiring multiple dedicated teams running reports for weeks or months.

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