NTT DATA created an analytics methodology called BICLAVIS by leveraging the expertise acquired from 200 business intelligence (BI) consulting cases.
BICLAVIS defines 4 types of business intelligence and 9 scenario patterns:
1) Proactive-type BI: Understand and predict users’ behavior to proactively provide targeted services or functions.
Scenarios:
Context Awareness: Recommend the service through the analysis of users’ behavior and preference.
Portent Detection: Detect the portent of changes by monitoring users’ behavior and status.
Anomaly Detection
Outlier Detection: Detect the outliers in a dataset that satisfy defined rules.
Incorrect Detection: Detect the deviation by matching the rule defined in the normal situation.
Examples of applications: Recommendation systems, anomaly detection.
2) What-if-type BI: Design new business logics and evaluate them by numerical simulation.
Scenarios:
Prediction and Control
Risk Simulation: Assess risks by business modeling and uncertainties.
Income Simulation: Estimate the profits by work restructuring.
Risk Hedge: Support the decisions by business modeling and optimization procedure.
Optimization: Support the risk reduction by business modeling and the method of diversification of risk.
Merchandising: Rank and allocate products to stores.
Examples of applications: Supply chain optimization, resource planning.
3) Aggregate-type BI: Aggregate and visualize accumulated data in various dimensions.
Scenarios:
Prediction and Control
Evaluation and Important Factor Analysis: Weigh up the various objects and identify their factors.
Process Trace: Extract the process of growth and development, and identify the accelerator or inhibitory.
Merchandising: Rank and allocate products to stores.
Examples of applications: Planning task, supply-demand adjustment.
4) Discovery-type BI: Discover the correlation and rules among accumulated mass data by using data mining techniques.
Scenarios:
Prediction and Control
Targeting: Extract information to target specific entities, e.g. potential customers.
Credit (Risk) Management: Determine the default risk of individuals or the bankruptcy risk of companies.
Merchandising: Rank and allocate products to stores.
Examples of applications: Customer scoring, risk quantification.