1. Enterprises have begun to derive value from big data, but many challenges remain. This article reports how Lufthansa successfully discovered big data value and addressed the technical complexities, and used big data as the basis for renovating its traditional business model to one that embraces customers as value co-creators. From Lufthansa’s experience, we identify the challenges and critical success factors for innovating with big data and navigating through uncharted waters.

2. Agenda Big Data Deployment Gap
Lufthansa’s Competitive Environment and Business Model
Enabling a Service-Dominant Business Model through Big Data
Discovering Big Data Value
The Big Data Paradigm is Enabling Lufthansa's AIA Business Model
Critical Success Factors for Innovating with Big Data

3. The Big Data Deployment Gap
Big Data – data sets that are so large or complex that traditional data processing applications are inadequate to deal with them
Offers unprecedented opportunities for enterprises to use analytics for achieving competitive advantage
Big data “Deployment Gap”
Exploiting big data and gaining value from it requires large amounts of up-front investment and involves high risk
Enterprises indicated intention to adopt big data but actual deployments are still scarce resulting in the “Deployment Gap”
Key reason for gap: an enterprise’s inability to discover innovative uses, or value, from big data
Lufthansa successful in discovering value in big data and deploying big data initiatives

4. Agenda Big Data Deployment Gap
Lufthansa’s Competitive Environment and Business Model
Enabling a Service-Dominant Business Model through Big Data
Discovering Big Data Value
The Big Data Paradigm is Enabling Lufthansa's AIA Business Model
Critical Success Factors for Innovating with Big Data

5. Lufthansa’s Competitive Environment and Business Model
Lufthansa’s business environment
Lufthansa is largest airline in Europe
Airline industry is characterized by low profit margins which underscores the need for business innovation
Lufthansa’s goal is to reduce costs and increase revenue
Airline CIO’s moving to customer centricity, ancillary revenues, and mobility solutions
Given the highly competitive and volatile nature of airline industry Lufthansa decided to renovate its business model

6. Agenda Big Data Deployment Gap
Lufthansa’s Competitive Environment and Business Model
Enabling a Service-Dominant Business Model through Big Data
Discovering Big Data Value
The Big Data Paradigm is Enabling Lufthansa's AIA Business Model
Critical Success Factors for Innovating with Big Data

7. Enabling a Service-Dominant Business Model through Big Data
Lufthansa identified big data as enabler of desired innovations
Strategic imperative to leverage IT innovations to provide best personalized travel experience for its customers
Big data is being mined to discover innovative service offerings and operational efficiencies Lufthansa’s renovated business model is referred to as Amazon in the Air (AIA)
AIA business model
Likens airline industry to Amazon
Customers seen as co-creators of value
Fundamental shift from goods-dominated to service-dominated logic

8. Agenda Big Data Deployment Gap
Lufthansa’s Competitive Environment and Business Model
Enabling a Service-Dominant Business Model through Big Data
Discovering Big Data Value
The Big Data Paradigm is Enabling Lufthansa's AIA Business Model
Critical Success Factors for Innovating with Big Data

9. Discovering Big Data Value
To discover big data value, Lufthansa used Value Discovery, a top-down innovation process
3 phases: innovation process, use case development, strategic development planning
Use case development – scenario based technique used to solicit innovative uses for big data
Big data use cases
Lufthansa identified hundreds of use cases
Selection process identified four primary cases that show how big data can strategic and operational value

10. Four Primary Use Cases Case 1: Personalizing Customer Experiences
Case 2: Handling Irregular (IRREG) Situations
Case 3: Predicting Departure Delays and Proactive IRREG Recovery
Case 4: Predictive and Preventive Aircraft Maintenance

11. Agenda Big Data Deployment Gap
Lufthansa’s Competitive Environment and Business Model
Enabling a Service-Dominant Business Model through Big Data
Discovering Big Data Value
The Big Data Paradigm is Enabling Lufthansa's AIA Business Model
Critical Success Factors for Innovating with Big Data

12. The Big Data Paradigm is Enabling Lufthansa’s AIA Business Model
Collecting data from everywhere (weblogs, social media, mobile apps, etc. )
Requires integration of internal, external, real-time and batch-processed data of structured and unstructured data
Lufthansa adopted big data analytics
Prior to big data paradigm, Lufthansa stored only structured and transaction oriented data
Can provide insights to reduce costs and identify innovative services

13. Big Data Paradigm Adoption and Data Flows at Lufthansa

14. Agenda Big Data Deployment Gap
Lufthansa’s Competitive Environment and Business Model
Enabling a Service-Dominant Business Model through Big Data
Discovering Big Data Value
The Big Data Paradigm is Enabling Lufthansa's AIA Business Model
Critical Success Factors for Innovating with Big Data

15. Critical Success Factors With Big Data
Lufthansa’s success in innovating with big data to renovate its business model is predicated on seven critical success factors (CSFs)
CSFs consistent with the BITMAN-SOA (Business-IT Alignment Model-Service Oriented Architecture)
Success of big data adoption rests on Lufthansa’s business-IT alignment capabilities

16. BITAM-SOA Service Engineering Framework

17. Critical Success Factors With Big Data
CSF 1: A Formal Top-Down Value Discovery Process
CSF 2: Direct Involvement by the CEO
CSF 3: Service-Dominant Guidelines for Deploying Big Data
CSF 4: Business-Case-Driven Decision Making with Creativity
CSF 5: An IT Architectural Foundation for Growth and Integration
CSF 6: Effective Outsourcing and Vendor Management
CSF 7: Data Governance and Talent Planning Process