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:
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Context Awareness: Recommend the service through the analysis of users’ behavior and preference.
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Portent Detection: Detect the portent of changes by monitoring users’ behavior and status.
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Anomaly Detection
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Outlier Detection: Detect the outliers in a dataset that satisfy defined rules.
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Incorrect Detection: Detect the deviation by matching the rule defined in the normal situation.
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Examples of applications: Recommendation systems, anomaly detection.
2) What-if-type BI: Design new business logics and evaluate them by numerical simulation.
Scenarios:
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Prediction and Control
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Risk Simulation: Assess risks by business modeling and uncertainties.
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Income Simulation: Estimate the profits by work restructuring.
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Risk Hedge: Support the decisions by business modeling and optimization procedure.
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Optimization: Support the risk reduction by business modeling and the method of diversification of risk.
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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:
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Prediction and Control
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Evaluation and Important Factor Analysis: Weigh up the various objects and identify their factors.
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Process Trace: Extract the process of growth and development, and identify the accelerator or inhibitory.
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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:
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Prediction and Control
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Targeting: Extract information to target specific entities, e.g. potential customers.
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Credit (Risk) Management: Determine the default risk of individuals or the bankruptcy risk of companies.
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Merchandising: Rank and allocate products to stores.
Examples of applications: Customer scoring, risk quantification.
