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Commercial Analytics:  Delivering the Best in Strategically Designed Analytics Packages  for Business Solutions

According to International Data Corp., or IDC, Global spending on business analytics services is projected to rise from $51.6 billion in 2014 to $89.6 billion in 2018 at a compound annual growth rate (CAGR) of 14.7 percent.

 

More and more business leaders are aggressively driving the companies to tap into the data that they have accumulated over the years to generate insights not only for product growth, revenue, margin and profitability but also for process improvement, design and stability. Business leaders that are savvy analytics users are positioning the availability of analytical technologies as competitive edge in their industries.

 

Interaction with the Clients

In leading a company that sell analytics products and solutions, irrespective of the Statement of Works (SOWs) and the content of the SOWs, there are certain basic requirements of how best to develop or package the Data, Analytics, Modeling and Business Intelligence (BI) deliverables to meet the clients’ expectations. These include:

Part I: Identification and Assessment Stage

  • Strategic Needs: Understanding the clients’ strategic needs, alignment and prioritization for analytics deliverables

  • Current State: Assessment of the current state of Data, Analytics, Modeling and Business Intelligence (BI) Capabilities or what the clients may consider as Data, Analytics, Modeling and Business Intelligence (BI) Capabilities that include:

    • Key Data, Analytics, Modeling and Business Intelligence (BI) Capabilities in terms of people, processes and technologies

    • Key Performance Measurement in terms of

      • Workforce Performance Management and Measurements

      • Process Work Flows especially with the identification of the basic or primary processes

      • Operational data, metrics, reports and decision support process capabilities

      • Inventory and usage of relevant technologies, software, tools and applications

  • Gap Analysis: This includes:

    • Assessment of the trend in the industry and related industries

    • Trends and the focus of the competitors and how the competitors are leveraging or plan to leverage analytics today and in future

    • Assessment of regulatory environments

  •  Comparison: Comparing the client’s current state Data, Analytics, Modeling and Business Intelligence (BI) Capabilities:

    • With the trend in the industry and related industries

    • With the trends and the focus of the competitors and how the competitors are leveraging or plan to leverage analytics today and in future

    • Within the context of regulatory environments

  • Identification of Opportunities: Identify the opportunities for the clients in leveraging Data, Analytics, Modeling and Business Intelligence (BI) Capabilities

Part II: Stage for Designing Blueprint for Data, Analytics, Modeling and Business Intelligence (BI) Capabilities

  • Map out the Current State through Transitional State to the Future Strategic Needs: Understanding the clients’ strategic needs, alignment and prioritization for Data, Analytics, Modeling and Business Intelligence (BI) Capabilities deliverables

  • Design and Develop Conceptual Capabilities Models in terms of Target:

    • Enterprise Data Infrastructure: Sources of Data, Data Integration that includes connectivity layers for integration platform, application adapters, database connectors; application integration layers that include data integrity, data standardization among others and Data Workflow Capabilities Models with input to Data Management Platforms

      • Data Stream Capabilities

      • Data Governance

      • Master Data Management (MDM)

      • Enterprise Data Marshalling Domain

      • Enterprise Data Acquisition Domain

      • Enterprise Data Processing Domain

    • Process Workflow Capabilities Models

      • Business Process Management

      • Quality Management

      • Requirements Management

      • Document Management

    • Workforce and Performance Management Capabilities Models

    • Modeling and Decision Support Capabilities

      • Descriptive Modeling

      • Operations Research and Decision Support Modeling

        • Management Science Modeling

      • Predictive Modeling

        • Predictive Process Modelers

        • Predictive Process Stimulators

        • Predictive Model Markup Language (PMML)

      • Prescriptive analytics

        • Business Rules Engines Capabilities

    • Performance Metrics Catalog Capabilities including Key Performance Indicators (KPI),

    • Reporting Dashboards for Operations, Workflow, Management and Executive Dashboards

    • Real-time Monitoring Reporting for Operations, Operations Command Center, Command Center War Rooms, Executives and other Decision Makers

Part III: Stage for Tools, Software ad Technologies including Platforms to Support the Above Capabilities

Identification, Testing, and Acceptance of Relevant Tools, Software and Technologies including Platforms to Support the Above Capabilities

  • Software and Technologies to Enhance Enterprise Data Infrastructure: Sources of Data including Data Migration from the old legacy systems and  Enterprise Data Management Platform, or EDMP

    • Data Stream Capabilities

    • Data Governance

    • Master Data Management (MDM)

      • Metadata

      • Data quality

      • Data Architecture

      • Transactional Data Architecture

      • BI Data Architecture

      • Metadata Server

    • Enterprise Data Marshalling Domain

      • Enterprise Data Storage

      • Enterprise Data Warehouse

        • Cloud-Based Enterprise Data Warehouse

        • Data Store and Data Mart Consolidation

      • Data Content Management

    • Enterprise Data Processing Domain

  • Software and Technologies to Enhance Process Workflow Capabilities Models

    • Business Process Management

      • Configurable Workflow Dashboard

      • Resource Management

      • Process Activity Monitoring

      • Approval Process Control

      • Event-Based Notifications

      • Asset Management

    • Quality Management

      • Corrective Actions based on new design, redesign or improvements

      • Defect Tracking

      • Customer Complaint Tracking

      • Action Item Tracking

      • Compliance Management

      • Calibration Management

      • Incident Management

      • ISO 9001 Management

      • Internal Audit Management

      • Supplier Quality Control

      • Document Management

    •  Requirements Management

      • User Defined Attributes

      • Multiple Projects

      • Traceability

      • History Tracking

      • Status Reporting

    • Document Management

      • Compliance Management

      • Access Controls

      • Archiving & Retention

      • Document Assembly and Conversion

      • Document Delivery

      • Document Indexing

      • Security & Encryption

      • Version Control

  • Software and Technologies to Enhance Workforce Force Capabilities Models

    • Associate/Agent Management System

      • Human Resource Integration

      • Scheduling

      • Labor Projection

      • Skills Tracking

      • Productivity Reporting

      • Employee Location Tracking

      • Forecasting

      • Budgeting

  • Software and Technologies to Enhance Modeling and Decision Support Capabilities

    • Descriptive Modeling

    • Operations Research and Decision Support Modeling

      • Management Science Modeling

        • Mathematical optimization

        • Simulation

        • Queueing theory

        • Stochastic process models

        • Markov decision processes

        • Econometric methods

        • Data envelopment analysis

        • Neural networks

        • Expert systems

        • Decision analysis

        • Social Network

        • Analytic hierarchy process

      • Predictive Modeling

        • Predictive Process Modelers

        • Predictive Process Stimulators

        • Predictive Model Markup Language (PMML)

      • Prescriptive analytics

        • Business Rules Engines Capabilities

  • Technologies Designed to Support Performance Metrics Catalog Capabilities including Key Performance Indicators (KPI)

  • Business Intelligence (BI) Technologies to Provide Reporting Dashboards for Operations, Workflow, Management and Executive Dashboards

  • Technologies to Support Real-time Monitoring Reporting for Operations, Operations Command Center, Command Center War Rooms, Executives and other Decision Makers

  • Technologies Designed to Support On Demand Capabilities for Analytics in terms of Performance Metrics, Predictive and Prescriptive Scenarios

Part IV: Identification Stage for the Structural and Process Models to Deliver Services

  • Governance Model that can best integrate Data, Analytics, Modeling and Business Intelligence (BI) Capabilities in:

    • Data Governance Model

    • Analytics Governance Model

    • Modeler Governance Model

    • Business Intelligence (BI) Governance Model

  • These governance models by default include:

    • Governance framework, structure, principles, architecture, processes and procedures

    • Quality tracking

    • Governance deployment

  • Operating Model which maps out the processes and activities that enable the company to direct and drive the transformation of Data, Analytics, Modeling and Business Intelligence (BI) Capabilities in:

    • Data Management Team Operating Model

    • Analytics Team Operating Model

    • Modeler Team Operating Model

    • Business Intelligence (BI) Team Operating Model

  • Organization Model which maps out the mission, vision, objectives, structure, roles, responsibilities and skills of the key strategic players that enable the company to direct and drive the transformation of Data, Analytics, Modeling and Business Intelligence (BI) Capabilities  in:

    • Data Management Team Organization Model

    • Analytics Team Organization Model

    • Modeler Team Organization Model

    • Business Intelligence (BI) Team Organization Model

  • These organization models by default include:

    • Mission, vision and objectives that are linked to the company strategic goals, priorities, fulfillments and culture

    • Roles, responsibilities and skills

    • Training requirements

    • Organization model deployment

Part V: Execution Plan Stage - Towards the Transformation in Client’s Business

  • Phased Implementation Plan (Task, Timeline, Dependencies, etc. aligned to the client’s project prioritization/approval format)

  • Roadmap

  • Pilot Plan

  • Adoption Plan recommends ‘adoption plan’ required to progress the evolution of the transformation. The document focuses on the timeline, players and major activities that will facilitate the phased introduction through planned schedule and tasks associated with its ongoing deployment in:

    • Data Management Space

    • Analytics Space

    • Modeler Space

    • Business Intelligence (BI) Space

  • Communication Plan

  • Technology Statement of Direction

  • Training and Development Plan

  • Employee Buy-In and Culture Change Management Plan

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