Data teams are contributing to a variety of value streams, as they are delivering value to a variety of stakeholders. The value streams are often not well-supported and the involved teams are facing constant challenges like Data Quality and Data Ownership. Also, data products often rely on the same data points for building the product and for measuring its success - so a lack of data quality leads to poor product quality and weak measurability at the same time. These challenges become exponentially harder, the larger the organization has grown. We propose a way of conceptualizing and visualizing the process of building data products, using the concept of the data value chain. Applying the Five Principles of Lean, especially Defining Value and Mapping out Data Value Streams, to the way build data products and operate data systems at scale, we create a framework that allows to focus on value delivery, avoids "waste" and supports ownership.

1. The Data Value Chain
Building Data Products the Lean Way
Dr. Stefan Kühn
data2day 2022

2. Outline

3. The Starting Point is Business
Know and map out your
business domain.
Align with your team.

4. The Starting Point is Business Impact
Where is Impact in this
map?
This Map is static –
Impact is dynamic –
Process view required

5. The Five Principles of Lean
1. Define Value – Value is what customers
are willing to pay for
2. Map Value Stream – Start with the end
in mind and map out all essential steps
3. Create Flow – Ensure that value-adding
activities flow smoothly
4. Establish Pull – Only deliver what is
needed, following pull avoids waste
5. Pursuit Perfection – Develop a
Continuous Improvement culture
https://theleanway.net/The-Five-Principles-of-Lean

6. Useful Terminology
Efficacy – Getting things done, capacity for
solving the problem / doing the right thing
Effectiveness – Do the right things, achieve
impact, get the things you want
Efficiency – Do the things right, use
resources carefully
Don‘t mistake activity for
achievement.
John Wooden, basketball coach
How to create an effective and efficient
organization?
We find an expensive and slow Deep-
Learning-based approach to identify fraud.
Through vertical scaling we achieve speed
up and catch fraudsters in production.
Finally, we implement a linear model that
does the same job in no time at no cost.
Start with the end in mind.
Delivering value to your customers efficiently drives sustainable business impact.
Everything else is just busy work.

7. Less is More – Minimize Output
https://miro.com/miroverse/impact-mapping/

8. Less is More – Minimize Output
Start with the end in mind –
here is the end
https://miro.com/miroverse/impact-mapping/
Jeff Patton - Output vs Outcome & Impact

9. Avoiding Waste
„Data Systems grow like a blockchain – append only.“ (Stefan Kühn, 2022)
The 8 Wastes of Lean
Inventory is considered
one of the biggest wastes
in any production system.
What about your data
inventory?

10. Why is working in Data so hard?
1. Define Value – Value is what customers
are willing to pay for
2. Map Value Stream – Start with the end
in mind and map out all essential steps
3. Create Flow – Ensure that value-adding
activities flow smoothly
4. Establish Pull – Only deliver what is
needed, following pull avoids waste
5. Pursuit Perfection – Develop a
Continuous Improvement culture
Be honest to yourself:
How many of these Lean
Principles are implemented
in your Data organization?

11. The Data System You Need?

12. The Data System You Need Have
Reference Article
Apply the
BOTTYN principle
(Stefan Kühn, 2022)
BUILD (or BUY)
ONLY
THE
THINGS
YOU
NEED

13. The Things Your Customers Need

14. The Things Your Business Needs

15. The Things You Need
A product is a set
of features and
functionalities
that solves a user
problem, and a
tool that collects
the data points
to make it better.
Every Product is
a Data Product.
Stefan Kühn, 2022

16. The Things You Need
A product is a set
of features and
functionalities
that solves a user
problem, and a
tool that collects
the data points
to make it better.
Every Product is
a Data Product.
Stefan Kühn, 2022

17. The Things You Need

18. The Data Value Chain Revisited

19. The Data Value Chain Revisited
You need to make friends to make it work.

20. The Things You Need don‘t work … but can
Make data ownership explicit.
Respect the BOTTYN principle
and keep your system lean.
Map out value streams for your
data products based on actual
business impact, not based on
internal „needs“.
Manage your inventory wisely,
avoid waste as much as possible
Do this together with your
friends – buy-in is a natural by-
product of co-creation.

21. Thanks for your attention is all you need
data2day 2022 | Karlsruhe | 2022-09-21 | Dr. Stefan Kühn | The Data Value Chain
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