data analytics advisory services - abeam consulting · data analytics system deployment abeam bi...
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Business Challenges of DataThe evolution of AI, ML, IoT technologies is magnifying how data is created and used by businesses.Data-driven decision making has many challenges across business roles from the executive to middle management staff.
ABeam’s BI ApproachABeam BI proprietary approach is based on “Improvement of Analytical Skills” and “Data Analytics System Deployment” to achieve results.Traditional consulting approaches, in most cases, focus on either the improvement of analytic skills or data analytics system deployment, not both.
ABeam's approach supports improvement of data analytics by promoting both sides; improvement of analytic skills and the data analytics system deployment.
Stages of Project ProcessABeam’ s BI approach considers each business problem and takes a phased approach.
Data Analytics Advisory Services
Improvement of Analytical Skills
Data AnalyticsSystem Deployment
ABeam BIApproach
AnalyticalConsultingServices
IT Vendor
TechnicalSupport
Test AnalyticsApproach
Introduction&
Training
Strategy Human &Organization SystemBusiness
Process
Improvement of
Data Analytics
Improvement of
Data Analytics
Strategy ConsultingServices
As-Is analytics
Define HR
Goal/Strategy Setting Define analytics Roadmap
Data AnalyticsSystem
Development
Improvement of Analytic Skills
Define Organization Maintenance Training/Evaluation System
Define Data Define Analytics System Define Analytics Strategy
Introduction & Training Test Analytics Approach Technical Support
Define Business Process Maintain Analytic Processes and Interaction
Phase 1 Phase 2 Phase 3Find business issues and define To-Be state
Find business issues and define To-Be state
Define goals and determine overall To-Be concept
Define goals and determine overall To-Be concept
Perform independent analytics operations and continuously
improve analytical skills
Perform independent analytics operations and continuously
improve analytical skills
Example of Common Issues
Executive
ProjectManager
Staff
Don’t know where to start ; positioning data analytics, setting goals, identifying themes, etc.
Visibility and access to data across enterprise systems.Limited experience in executing data analytics.
Availability of skills to execute data analytics.Understanding the business impact of data analytics.
Role for Business
Deployment of Organizational Structure based on Data AnalyticsABeam BI improves strategic feasibility and data analytics by creating an organizational structure that centrally manages data analytics executed by each division.
AI / ML Application (not using “Black Box”)Generally with continuous usage of AI(Artificial Intelligence) / ML(Machine Learning) the businesses data will become harder to understand.
ABeam provides “white box” approach that integrates lifecycle of products, services, business and also the intelligence cycle.
It is important to control AI / ML technology depending on the characteristics of issues in a business setting. ABeam BI offers an approach using AI / ML more effectively based on the understanding that AI / ML technology should be managed as one component of the whole system.
Example of Problem Solving Approach using AI / ML
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Example Approach of Slot Car Optimization Case
Management Strategy
Analytics Department
Business Strategy
Business Department Analytics for improving profitability
CorporatePlanning HR Accounting
Analytics to support the business
Centrally manage data analytics executed by each divisionPromote improvement of data analytics and strategy feasibility
Enterprise Strategy
Enterprise Department
Data Analytics Level
Management Strategy
Analytical Results(Each department)
Knowledge Management
Issues
Input OutputProcess
Centrally ManageData
SCM Marketing/Sales Services
Strategy
Feasibility
データの構造化
Improve analytics cycle by embedding analytics results into the business operation and system.
Expansion As-Is Analytics / Hypothesis Building
Extract results by combining multiple algorithms and adjust based on experience.
Data Mining / Prediction Analytics
Clean data structure based on international regulations such as ISO and business insight.
Data analytics based on the field workers insight and build hypothesis.
Clean Data Structure
Select Business Problem Pilot Testing
Define possible problems that can be resolved using AI / ML.
Verify whether the problem can be solved as expected in a small test environment.
Based on the results from pilot testing modify the initial assumptions to select the right tool for problem solving.
Deploy AI / ML technology system to solve the problems in accordance with discussion results.
Select AI / ML Tool
System Deployment
Optimize Car ControlBased on data: • What is “good control”? • How to display and reproduce “good control”?
Method Verification• Can we display control status by voltage?
• Optimize voltage equal to control optimization?
Slot Car Case selected “SAP Predictive Analytics®” because...• Quick processing speed• Easy understanding of results
Deploy system to display voltage control and find trend to optimize car control based on experience.