1) The document discusses building master data factories to capture value from advanced planning and scheduling (APS) implementations. It covers 7 guiding principles for setting up a data factory, including having an end-to-end focus in master data management, finding a "golden record", investing in analytical skills, and building a data organization.
2) Embedding quality from the start and challenging periodic reviews is important for high quality data. Defining data quality involves generating and maintaining quality data on an ongoing basis through analytical checks and business rules.
3) When implementing an APS solution, organizations should seize the opportunity to make a comprehensive business case for a data factory and create a dedicated data workstream equal to other transformation workstreams.
8. A DIGITAL WAVE IS GOING ON…
Thinking POC Decision Time Implementation CI phase
#OnAJourney
APS
Lots of companies are on the way to fundamentally revise their landscape –
implementing APS solutions replacing APO, moving to S/4, …
AI capability S/4
11. CASE FOR CHANGE
Let’s create the
foundation!
ECC
Implementations
Let’s plan our
supply chain!
APO
Implementations
The valley of disillusion
Xls Wave
APO retirement
The APS Wave
Let’s simplify
The S/4 Wave
Let’s increase value
The AI Wave
1980-2005
1995-2010
2000-2015
>2010
>2018
>2017
Let’s increase efficiency
The RPA Wave
>2018
13. CASE FOR CHANGE
Let’s create the
foundation!
ECC
Implementations
Let’s plan our
supply chain!
APO
Implementations
The valley of disillusion
Xls Wave
APO retirement
The APS Wave
Let’s simplify
The S/4 Wave
Let’s increase value
The AI Wave
1980-2005
1995-2010
2000-2015
>2010
>2018
>2018
Let’s avoid the valley of
disillusion and learn from
the past:
1. Process drives: Technical →
business steered
2. Integrate your people all
along your journey
3. Make your data explicitly part
of it: Build your master data
factory
14. DO YOU RECOGNIZE
My plan
doesn’t
match reality
The system
is not
working
Your data is
not correct
or complete
The data
should just
be there
We don’t know
anymore
which data is
doing what Master data is
not sexy
#Let’sNotGoThereAgain
15. CREATE YOUR DATA FACTORY ALL ALONG
Triggers
Data
On Time,
In full
Business Drivers Business Goals
Data Strategy
Data Governance
Toolset
Metrics
Security
ComplianceData Quality BI / Analytics Architecture
Enablers
Maturity Assessment
Project & Process Management
MountK Change Management
Business Data Stewards
IT Data Management
Stakeholders
16. 2 7 guiding principles to
setup your data factory
17. MASTER DATA
FACTORIES
A cornerstone for all digital
transformations, in planning &
beyond
Shaping your organisation, capabilities
and mindset to capatilise on digital
opportunities
Shaping the level of informed decision making
to match your speed of information and
leverage the vast amount of information
becoming available through digital capabilities
Understanding the decisions you are
driving and finding the right solution fit
within your (planning) technology
approach
DIGITAL-READY PEOPLE
& ORGANISATIONS
NEXT GENERATION OF
PLANNING ‘PROCESSES’
TECHNOLOGY STACK
STRATEGY
4 KEY
BUSINESS
ENALBERS
CAPTURE VALUE FROM YOUR APS IMPLEMENTATION
18. DATA FACTORY – A SET OF 7 GUIDING PRINCIPLES
E2E focus in
MDM
Find that golden
record
20. DATA FACTORY – A SET OF 7 GUIDING PRINCIPLES
Invest in analytical
skills
Build a data
organization
E2E focus in
MDM
Find that golden
record
21. THE DATA ORGANIZATION &
DECENTRALIZED
Master data activities happen
within the business functions
Close to business reality.
Not core focus of the role.
FUNCTIONAL
Introduction of dedicated master
data steward roles to support/
facilitate data maintenance
activities
Data steward role focus on
tech. data activities
Functional approach
HYBRID
Introduction of SC data
configuration role to build
analytical capabilities in E2E plan
constraints.
Further build analytical
skills to increase data Q.
More complex governance
models.
CENTRALIZED
Data configuration happens in a
cross-functional set-up, taking into
account E2E constraints.
Leverage analytical
capabilities cross-functional.
Data configuration becomes
a pivotal role – aligning with
many stakeholders
SC
Fctn 1 Fctn 2
Make
Fctn 1
..
..
SC
Fctn 1 Fctn 2
Make
Fctn 1
..
..
Data
Stew.
Data
Stew.
Data
Stew.
Data
Stew.
SC
Fctn 1 Fctn 2
..
..
Data config.
Data Stew.
Make
Fctn 1
SC
Fctn 1 Fctn 2
..
..
Data config.
Data Stew.
Make
Fctn 1
&
22. DATA FACTORY – A SET OF 7 GUIDING PRINCIPLES
Embed quality
Challenge the
periodic reviews
Invest in analytical
skills
Build a data
organization
E2E focus in
MDM
Find that golden
record
23. DEFINE DATA QUALITY? &
QUALITY
DATA
Generating quality data as
of day 1
Maintaining quality data all
the time
Analytical
checks
Changing
environment
Workflow
management
Business rules
24. DATA FACTORY – A SET OF 7 GUIDING PRINCIPLES
Enable best-of-breed
solutions
Embed quality
Challenge the
periodic reviews
Invest in analytical
skills
Build a data
organization
E2E focus in
MDM
Find that golden
record
25. ALIGN DATA CAPABILITIES TO YOUR IT LANDSCAPE
Importance of data
strategy & governance
capabilities.
Useofbest-of-breed
solutions
Integrated
model
Core-satellite
model
Honeycomb
model
Layered stack
model
27. APS IMPLEMENTATION TAKE-AWAYS
SEIZE THE
OPPORTUNITY
Make a comprehensive business case,
include the different elements of a data
factory in your journey.
Create a data workstream on equal footing
with your business transformation
workstreams.
Your data factory is an area of investment to
enable other business benefits.
28. Thank you!
Anneleen Tronquo
Partner consulting
Cédric Van Helleputte
Head of Planning
Life Science
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