Welcome to the
BIG DATA READINESS ASSESSMENT
for the CHEMICAL
INDUSTRY, PHARMACEUTICAL INDUSTRY, REFINERY
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
EXPLANATIONS TO THE QUESTIONNAIRE
THREE QUALITY CRITERIA
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.
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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
✪
www.atlan-tec.com