Newsletter

MASTER DATA SOLUTIONS FOR MECHANICAL ENGINEERING, SPECIAL MECHANICAL ENGINEERING AND PLANT ENGINEERING

D&TS offers various IT solutions, including multicad-capable ones, to make data and information usable across different systems.

SAP
SAP S/4HANA
SOLID EGDE
SOLIDWORKS
CATIA
AUTODESK INVENTOR
Microsoft Dynamics
Infor
ERP
PLM
PIM
Winshuttle
CATALOGcreator
PARTsolutions

The challenge of data quality in mechanical and plant engineering

Data quality often only comes into focus when acute problems arise. Whether it’s a loss of competitiveness, a bottleneck at an important key supplier, or revenue losses from spare parts sales – these kinds of scenarios require quick decisions based on reliable data. As a plant and mechanical engineering company, you need high-quality material master data because it forms the basis for digitalization and all Industry 4.0 projects. Without complete up-to-date data sets, industrial networking of machines and machine-operated processes cannot take place. If this project is to succeed, so that components ultimately communicate independently with the production plant, the most important basis must be accurate: your data.

Poor data quality costs a lot of money! Where are the biggest sources of error?

The average revenue lost by companies due to erroneous data is up to $15 million (Gartner’s Studie). In other words: The cost of poor data quality is 15% to 25% of revenue (MITSloan). Moreover, poor data quality has even more far-reaching consequences than financial losses. They start with effects on employee confidence in decisions or on customer satisfaction and range from productivity losses to compliance problems.

The sources of poor data quality can be very diverse. However, the data entry process, whether by employees or customers, usually comes first. We humans can create much, but not one-to-one master data. Therefore, it is even more important to establish automated processes for building and maintaining good data quality in the company.

The right solution for every problem

Many mechanical and plant engineering companies face the same challenges when optimizing their data quality. Which ones are you facing? With our customized and field-tested solutions, you can achieve high and sustainable data quality in your material master data.

Challenge 1:

Unstructured data storage, duplicates and data silos

Material master data is created and maintained at different locations and in local systems. This has created data silos that reduce the quality and reliability of your data. Sources of error arise in the business processes, which may lead to wrong strategic decisions.

Solution 1:

Data harmonization, duplicate cleansing and migration to a single point of truth

D&TS creates a common database so that high-quality, cleansed, harmonized and standardized master data is available throughout the company. This increases data transparency, provides greater flexibility and reduces complexity.

Challenge 2:

Too much variety of parts and variances

A search for parts is unsuccessful and components are redesigned rather than reused. Thus, thousands of hours are spent each year on work that does not make a positive contribution to added value. In addition, each newly introduced component generates enormous additional costs. Systems are full of duplicates and outdated parts.

Solution 2:

Increasing the reuse of components through strategic parts management

Parts that have already been used can be quickly and easily found and can be reused. No additional costs occur for recreating or reconstructing them. Not only will you minimize the variety of your parts but also accelerate your operating processes.

Challenge 3:

Complicated spare parts sales

Poor quality, inconsistency and an unstructured spare parts portfolio complicate your after-sales processes. Customer satisfaction decreases because required spare parts cannot be found. In addition, the ordering process is too complex and outdated because the process is not innovatively supported, and interfaces to the ERP system are missing.

Solution 3:

After-sales success with e-catalogs and master data management

You can generate more sales, reduce incorrect orders and streamline ordering processes with electronic spare parts catalogs. You will increase customer satisfaction with intelligent search capabilities including AI search. Furthermore, you will achieve more transparency in spare parts through professional master data management.

Challenge 4:

Manual processes of material creation and maintenance

Your master data management has no clear rules or workflows. Duplicates, incorrect and outdated master data slow down your processes. You still manage and maintain your master data using many individual Excel spreadsheets.

 

Solution 4:

Automated processes for material creation and maintenance

With IT solutions from D&TS and selected partner solutions, you can maintain your material master data throughout the company and with maximum data quality. These integrated systems support the traceability of your materials and the ongoing digitalization in your company.

Challenge 5:

Differences in terminology and material short texts

Unlimited terms/designations are entered via your CAD, PLM, and ERP systems, including new creations, incorrect entries, or arbitrary changes in designation. In addition, purchase order texts and material short texts are still created manually and are therefore inconsistent and contradictory

Solution 5:

Generating standardized texts automatically

The “Material short text generation” tool allows you to automatically derive the material short text and the order text in the material master based on defined classification properties. Manual input is unnecessary and material descriptions can be harmoniously built up automatically in all relevant languages.

Challenge 6:

Missing/insufficient product group keys in purchasing

Your purchasing department struggles with the lack of a suitable basis for strategic initiatives and/or for negotiations. The prerequisite for this is the possibility of a clean and company-wide standardized spend analysis. However, the material master data is unstructured making the current situation non-transparent.

Solution 6:

Standardized product group structure

Thanks to AI and D&TS’ IT solutions, you can obtain a uniform structure for your data by deriving an industry standard such as ECLASS based on process techniques or by identifying geometric similarities. You thus achieve maximum data transparency which enables you to perform a clean spend analysis and thus act strategically.

D&TS recognizes and understands your challenges!

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Data with class

Classifications are used to capture knowledge about product data in a comprehensive and unambiguous way. Products are thus uniquely identifiable, which helps significantly in interdepartmental and cross-company communication. The meaning of a product becomes consistent through classification.

Classifications (such as ECLASS, ETIM, UNSPSC) are also the basis for optimization in the areas of master data management, PIM systems, electronic catalogs, electronic marketplaces, online stores, electronic procurement and ERP systems.

Classification of standard and purchased parts

Classification systems and ECLASS

D&TS advises you on the most suitable standard classification system for your company or support you in building your classification system. We classify your standard and purchased parts and enrich your data with valuable information from our knowledge database. Using classification, you increase reuse in “C-parts” and reduce the administrative effort for management, approval and processing. In the long term, this will reduce the need of creating new parts in your systems and, by bundling suppliers, your procurement costs. D&TS has successfully classified material master data according to ECLASS standard in numerous projects with renowned mechanical engineering companies.

Learn more about ECLASS

Classification of your drawing/individual construction parts

Self-classification according to ECLASS, geometric similarities or process techniques

In addition to standard and catalog parts, the classification of drawing parts is becoming increasingly important. The most proven classification standards, such as ECLASS, have limited use for drawing parts. For purely drawing-based parts, company-specific classes and properties (attributes) are to be developed based on different methods (extension of ECLASS, according to geometric similarities or according to process technologies).

In design, development times can be significantly reduced thanks to classification because search times in CAD systems are avoided. Parts that have already been used can be quickly and easily found and can be reused. No additional costs occur for recreating or reconstructing them. Not only will you minimize the variety of your parts but also accelerate your operating processes – and you will save significant costs.

We will calculate the return on investment (ROI) of your project. This will also convince your management!

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Open data silos and leverage digitalization potential

A prerequisite for a functioning Information Supply Chain (ISC) is that data silos are broken down to make data and information usable across different systems (ERP, PDM, PIM, CAD, etc.). Data that is tied to an application creates significant additional work for data maintenance and interrupts the data flow. They cannot be used across systems because interfaces are missing. To successfully implement digitalization and thus the shift from manual to automated processes, you need to open existing data silos, make the information holistically usable and thus drive standardization.

The IT solutions of D&TS are specialized systems that support you in data acquisition, processing and distribution

Our solutions

OUR TIP

Only with a clear route, can you handle your master data project and create sustainable, high data quality!

Master data management software is not a panacea, but merely an important component on the path to high data quality. Organization, processes and the integration of the software into the existing IT landscape must also be considered. Prepare carefully: Because without clear goals, without a vision, there is no clear route for your master data management journey.

Do you already know our Workshop?

You need assistance in optimizing your product master data and digitalizing your processes?

Please feel free to call us or simply send us your request by mail.

Sebastian Böttjer

Head of Sales & Project Management