Welcome to the
BIG DATA READINESS ASSESSMENT
for the PAPER
INDUSTRY
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
✔ How many 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 on basis of your with your data in
the future.
✔ Calculation formula for the potential 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 therefore 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" for Supllier - means that all (relevant) data
about the supplier or the supplying elements of a process are captured and
stored.
"I" for Input - means that all (relevant)
characteristics and quantities of the input to a process are captured and
stored.
"P" for Process - means that all data of the
process, i.e. the process and the machine data, are captured and stored.
"O" for Output - means that the output of the
process is accurately recorded and stored according to quantity and quality.
"C" for Constumer - 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.
ADD-ON: CALCULATION OF THE POTENZIAL ECONOMIC
VALUE OF YOUR DATE
As ADD-ON, you get a calculation of the potential economic value your data
contains and how it can increase it.
➨ Start assessment now
(free registration required)
You would like to know more, have further questions
or would like to give us your feedback on the Readiness Assessment? Then please
feel free to contact us!
Your contact person at M Consult GmbH is Ms Bianca Karl:
[email protected]
+49 8709 9150-55
www.mconsult.de
In addition to this simplified free online version,
our partner atlan-tec Systems GmbH offers 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, atlan-tec Systems is there to help you!
[email protected]
+49 2161 2775250
www.atlan-tec.com