Deutsche Version


Welcome to the

 This online version for self-diagnosis is free of charge and provides you in just a few minutes with information about:

• Your current data quality
• Your current SIPOC score
• Your current analysis and modelling skills
• What percentage of your data potential you are already using
• How you can (further) increase your Big Data Readiness Score and achieve (even) more added value with your data in the future.
• Calculation formula for the economic value of your data




To determine the Big Data Readiness Score, three central quality criteria are examined:
• Your data quality
• Your SIPOC score
• Your analytical and modelling competence

These three quality criteria determine your Big Data Readiness and thus the degree of value creation that can be achieved.


Quality criterion 1: Data quality

The following individual criteria are important for data quality:
• Accuracy
• completeness
• relevance
• consistency
• reliability
• Accessibility


Quality criterion 2: SIPOC method according to DIN ISO 13053-2

The SIPOC method is known from Lean Six Sigma and is defined as an international standard in DIN ISO 13053-2. SIPOC means Supplier, Input, Process, Output, Customer, and describes the elements of a production chain.

According to DIN ISO13053-2, value creation through Big Data Analytics can only be created sustainably if complete and correct data are collected and evaluated across ALL elements of a production chain.

"S" means that all (relevant) data about the supplier or the supplying elements of a process are captured and stored.
"I"   means that all (relevant) characteristics and quantities of the input to a process are captured and stored.
"P" means that all data of the process, i.e. the process and the machine data, are captured and stored.
"O" means that the output of the process is accurately recorded and stored according to quantity, purity and quality.
"C" means that the target or customer of the output of a process is known as well as its product evaluation.

The Big Data Readiness Assessment determines your data quality in each of these areas.


Quality criterion 3: Analysis and modelling competence

In addition, we look at your current analysis and modelling competence, i.e. which analysis and modelling methods you currently use and how advanced and efficient they are. We base our assessment on the (German) VDI guideline VDI3714: "Implementation and operation of Big Data applications in the manufacturing industry; implementation of Big Data projects".

According to this, modern AI-based methods are far superior to classical statistics and thus increase the Big Data Readiness Score.


Start assessment now
(free registration required)


In addition to this simplified free online version, we also offer a detailed Big Data Readiness Assessment including expert advice and a detailed report. If you would like to delve deeper or need support with the implementation of Big Data projects, OPEX 4.0 and Industry 4.0, we are there to help you!

[email protected]
  +49 2161 2775250