Implement regular data routines to improve quality control

Use production indicators to target quick wins in quality

Train the best class methodology to implement the clinical approach

Define and implement the first project
to click on critical products..
So the goal is to optimize
the quality of your data.
A decrease in non-quality costs values
these costs to define priorities for improvement action.

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Your needs

To maintain a satisfactory product quality at the lowest possible cost.

Reduce the cost of scrap, rework and adjustments.

The objective is to optimize the quality of your data

This offer allows you to reduce your non-quality costs through data analysis.

An aid that helps improve your steering and management.

Reduce input costs through random assembly,
uninterrupted production and better use of labor and facilities.

Your goals


Increase the added value of the work. Improve the flow


A platform that brings together data integration and governance to deliver trusted data at your fingertips.

Soft integration

Data integration. Data integrity and governance


Search for perfection with statistical/analytical tools Designed for cloud, multi-cloud environments

Action follow-up

Automate the review of your item master settings for optimal tracking.

Quick wins

Improve service levels by reducing variability in supplies and stocks.
Review stocks and in particular safety stocks.

Our solution

Maintain satisfactory product quality at the lowest possible cost.
Reduce the cost of scrap, rework and adjustments.
Reduce input costs through random assembly, uninterrupted production and better utilization of labor and facilities.

Our products

Offer description

Our tool analyzes and determines the root causes of your problems. Thus it ensures that changes are made quickly once the cause is detected. This will give you in-depth knowledge and therefore a gain in competence.

Implementing a clinical approach allows you to answer the question of where the defects come from? Reducing variation is important because it allows performance to always meet customer requirements. So to minimize defects, waste and errors, variation must be controlled.

Bad data puts all decisions at risk. Even a small amount of bad data threatens your business. Try Data Quality Clinic TM that instantly assesses the quality of your data.


A first inventory which is perfectly suited to companies wishing to optimize their sales forecasts. Establishment of the inventory summary.

An ideal diagnostic phase for companies seeking to optimize forecasts, safety stocks, and replenishment points. Data analysis based on the economic quantity model. Classification according to financial criteria to prioritize updates
Avanced program

This is the advanced phase of the solution for companies looking to optimize a multi-local supply chain holistically. On-the-job training with the supply team on procurement models. Remote support for Part Number testing.

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Our References

We provide daily tools that will help production and supply chain teams. We are specialized in daily and weekly routines.
Our tools are packages for shopfloor teams and also technical and quality team.
We use ERP data to automate follow-up files.
First step is to establish a diagnostic on your industrial performance.
Then establish guidelines for daily and weekly routines optimization.
ERP Data is crunched to established first quick win actions.


Supply chain optimization is influenced by many key factors and indicators. An effective inventory management tool provides useful analytics for making supply chain management decisions. Good inventory management reduces costs and improves customer service at the same time. Our innovative tool ensures that you have the right amount of inventory at the right time and at the lowest cost possible. It has become an essential tool in many organizations, as inventory carrying costs can be reduced by more than 30%.

What is data quality?

Data quality refers to the ability to use a data set for its intended purpose, which requires four criteria
  • Availability

  • This is data that is ready to be used and up to date.

  • Relevance

  • implies that the data must be clear, not confusing and answer the research questions posed. Irrelevant data is of no use to a data analyst.

  • Cleanliness

  • complete datasets are free of errors and have minimal missing entries.

  • Ease of use

  • This refers to the ease with which analysis can be performed to discover useful results from the dataset. The aim is to eliminate anomalies at the root and improve the quality of and improve quality to better meet customer

    expectations. An approach that allows the company to gain in efficiency and performance. performance of the company.

    What is the importance of a data quality approach?

    The continuous quality improvement process of quality management allows to offer better services. It is a key factor of success that should not be neglected.

    Our tool is an alternative and agile method which industrializes the different correction processes, i.e. detection, diagnosis and resolution.

    Thus, it would be easy to set up and pilot a quality monitoring process thanks to Data Quality Clinic TM the reliability of the available data gives quality managers the possibility to accurately identify deficiencies, prioritise quality improvement initiatives and objectively assess whether changes and improvements have taken place.

    To ensure that data is 'fit for purpose', organisations need to adopt a systematic approach to assessing, improving and maintaining the quality of their data.

    Quality management in industry involves a specific approach to satisfying customers by providing products and services that meet their needs.

    Indeed, quality management is directly linked to internal processes, to the involvement of employees, to the optimisation of the management system...