Presentation by Tomi Bergman at Luxus NEXT 2016 event.

1. Value of data in Digital Transformation
19.8.2016
Tomi Bergman, CEO / Partner
Talent Base Oy

2. Topics
• How is data connected to Digital
Transformation?
• Data as a key enabler for new innovations
• What does it take to benefit from data?

3. HELLO! WE ARE TALENT BASE.
WE DO BUSINESS-DRIVEN IT CONSULTING.
WWW.TALENTBASE.FI

4. Fast facts
• 40 experienced professionals working in demanding,
business critical digitalization projects
• Focus on solutions design – specialized in
information management, CRM and digital services
• Founded in 2007

5. How is data connected to
Digital Transformation?
Value of data in Digital Transformation

6. Why is it important to focus on
the most important data?
Focus on data
which
a) has a meaning
and
b)can be reused

7. Data is fuel for digitalization
• Data is fuel for any digital processes
• Disruption is the name of the game – data is
used heavily in a different, creative manner
• Digitalization makes data more and more
visible – and data quality issues, too

8. Familiar feeling?

9. How to understand data?
BIG DATA
TRANSACTION DATA
MASTERDATA
REFERENCE DATA
METADATA
AMOUNT OF DATA
SEMANTICS AND REUSE
STRUCTURED
UNSTRUCTURED
The biggest challenge currently is to combine unstructured data and
metadata driven digital content (e.g. documents, videos, blogs)
with structured data in order to bring business value

10. Seamless processes and systems require
good quality data
• An underlying common denominator is seamless data that runs
across processes, across systems
• For this to happen, there needs to be a common understanding
on key entities, such as "products" and "customers”, and tight rules
and discipline in maintaining the common part of the data
• Supporting technologies and organizational capabilities need to
be in place, and overall data architecture needs to be flexible
• Effective digital process change and customer’s expected quality of
services relies on secure information and platforms where
information privacy and security is well taken care of

11. Typical challenges for process digitalization
Question: What are the biggest challenges associated with your efforts to digitize processes?
Source: Cognizant Center for the Future of Work

12. Data as a key enabler for new
innovations
Value of data in Digital Transformation

13. Innovation model
Solutions use data in
order to fulfill processes
Well-functioning
processes enable
solutions
Available and reliable
data across the
organization from
different channels

14. Advanced analytics as a tool for innovation
• Nowadays, advanced analytics and use of machine learning
algorithms are key methods for developing data-driven innovations
• The goal is to understand and describe potentially massive
amounts of structured and unstructured data, and derive valuable
insights from them
– E.g. new services/offers, cost cutting, risk reduction, automation
• Data scientists working together with business and product
development starts to be de facto – however, finding data talents is
not easy
• Innovation doesn’t always mean creating new products
– Process innovations via digitalization and automation (e.g. robotics) can
yield significant business value, too

15. Case Castrén & Snellman: global business
partner map
Improved core master data maintenance enabled data visualization and better communication
of Castrén’s partners, and increased brand awareness as international strong player

16. Case Facebook: artificial intelligence
+
A virtual assistant powered by artificial intelligence as well as a band of Facebook
employees, dubbed M trainers, who will make sure that every request is answered
M proposes relevant content, services and products based on users questions

17. Case DAQRI: Smart helmet for industry
Smart helmet is used to create augmented reality for the industrial worker, including
visual instructions, real time alerts, and 3D mapping
E.g. combining product data with installed base data, content and real-time sensor data
for user’s helmet

18. Case Uber and Airbnb: dynamic pricing
Both companies are using algorithms to build dynamic pricing based on regional supply
and demand

19. What does it take to benefit
from data?
Value of data in Digital Transformation

20. How to boost innovations with data?
• Understand economics and the
potential of data
• Define & organize core (master)
data within the organization
• Acquire right competences (human
+ technical) to use and connect big
data to corporate (master) data
• Consider using “Data-labs” with
access to all data

21. Data-labs for trial-and-error
• Many big companies (like British Petroleum & British Gas) have
established “data-labs” for boosting their product and offering
development
• Idea is to deep dive into data to discover innovative solutions
with the help of right people and competences
• Transferring ideas and techniques across industries –
benchmark also “unusual / non-related industries”
– What can you learn from other industries?
• Key is to access all the data (inside & outside), including
customer needs analysis
Note! Data labs are not the only option for data quality improvements
and innovations – analyze the data and potential improvement factors
and start to take coordinated steps to improve the quality.

22. Summary
• The importance of data in digitalization is increasing all the
time – data is the fuel for innovations, processes are the
engine.
• Digitalizing processes and creating new innovative solutions
makes data visible – and data quality issues, too.
• Invest first on putting core information (master data) in order,
and then start to reuse and combine it with big data.
• Acquire right competences (technical + human) to build new
innovations with data.

23. THANK YOU!
Tomi Bergman, Partner / CEO
tomi.bergman@talentbase.fi
www.talentbase.fi