Explore how data, the new center of gravity in today’s digital world, is redefining business models and disrupting markets. Hear how SAP Data Network monetizes unique insights from data to offer CEOs new growth opportunities and to enable superior customer experiences. Learn how Schindler has reimagined its business by putting data at the core. (Source: SAP/ASUG)
Source: ASUG/SAP
I am thrilled to have the CDO of Schindler, Michael Nilles, presenting along SAP’s Former Member , President of the SAP Data Network.
Abstract of the webcast:
SAP Leonardo Data Intelligence
Data is the most underestimated asset of our time. Traditionally it drove operational excellence, today it drives differentiation and growth. Therefore data, in today’s world is a strategic competitive advantage.
SAP Data Intelligence operates as a team of experts that is laser-focused on delivering customer value within short time-to-market, realizing business value in 4 months through a standardized process that is built on SAP’s design thinking methodology. It harnesses all of SAP’s leading-edge cloud technology and services to deliver ready-to-consume data monetization cloud services.
You will get
• an overview of SAP’s take on Data Monetization
• an overview of available products
• insights from data driven customer projects
Source: SAP User Group
SAP Data Network team is focusing on data monetization. SAP Leonardo focus is “innovation” – a portfolio of technologies and offers technology bundles, and methodologies with “Faster innovation, less risk” (source: SAP)
Source: SAP
Data intelligence is a big word; data volumes are growing
Data is “the new asset”
Today focuses on Live Customer Cloud; right ecosystem, connections, and “unleash” data
Source: SAP
New revenue streams for customers with the data
Connect your data sources with the right combination of external data sources
Discover value
Source: SAP
What does data monetization mean?
Above shows three directions
Schindler (Elevator company) – they have installation data, they have the data, but not predict the future of the elevator
They took the installation data and combined it with the weather data
They were able to predict which sites needed more attention
Business efficiency includes predictive maintenance
Not sell raw data; sell insights to other
Source: SAP
This is a turnkey solution
Insert customer data, social data, weather data
Based on use case, enrich customer data, data lake for your use case
Cautious about GDPR; anonymize data at customer site
Data ingestion “wrangles” data
Data scientists start writing models or use machine learning, to solve business use case with your data
Comes with nice visualization; uses SAP Analytics Cloud as UI
Hybris billing so you can meter/monetize based on data consumption and packages
Source: SAP
Speed matters; so packaged solutions are available
Behind the scenes, uses Data Hub for pipelines and data orchestration
Data science uses machine learning layer
Source: SAP
All the tools in the previous slide can be accessed with Live Customer Cloud
Source: SAP
Industries such as retailers, and all different industries have data monetization use cases
Insurance risk profiling includes external data
Examples are shown above
Source: SAP
Combine your internal data with the data sources shown above
Data sources are on the SAP platform and can be immediately be used; if you did it yourself it would take a long time
Source: SAP
For retailers, saw patterns – find the next retail site, market basket
Source: SAP
Data ingestion, enrichment, is repetitive
Source: SAP
It is a cloud solution; goal is to be fast and “less risk”
Methodology is 3-4-3 – 3 days of ideation, including design thinking
Source: SAP
Ideation – goal to find a business use case to bring value to your company
Require an NDA for workshop
“no charge” for workshop
Exploration – customer cloud solution – take your company’s data and bring in with your solution, building models, visualizing, and build model
Source: SAP
What is your contribution? 2 day workshop at an SAP location, and 1 at your location
Day 3 focuses on data sources
Day 1 & Day 2 – business process specialists, stakeholders
Exploration phase – extract data from your systems, start modeling (happens remotely, weekly meetings)
Source: SAP
You do not need a data monetization use case in mind
Every workshop is different
Personas, user journeys, sketch the flow to understand, using wireframes
Source: SAP
Set up your own data monetization strategic market
SAP Data Hub is behind customer cloud
Source: SAP
Above is a summary slide
Why do it in cloud? It is turnkey solution; SAP says it can scale
Source: SAP
Data center is located in Germany, GDPR compliant
Source: SAP
SAP references
SAP Site: SAP Data Network | SAP
