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.
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
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
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
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
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
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
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
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
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
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
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
Big Data Paradigm Adoption and Data Flows at Lufthansa
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
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
BITAM-SOA Service Engineering Framework
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