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Building Strategic Digital Analytics Organization for the Best in Deliverables for Efficiency,  Revenue and Profitability

Designing and Building Strategic Digital Analytics Organization As Part of Strategic Digital Transformation:
To effectively, efficiently and proactively build Digital Analytics Organization within a company or for a client as an enabler for productivity, efficiency, customer acquisition, customer retention, market share increase, revenue and profit, there is the need for the Chief Digital Analytics Officer/SVP of Digital Analytics to understand the Strategic Digital Direction of the company or the client in terms of where the company or the client is heading next.
Strategy
The inital engagements of the Chief Digital Analytics Officer/SVP of Digital Analytics include working closely with the Executive and Leadership Teams and of course, with the Board of the company/client, to understand the strategic plan and the strategic digital transformation of the entire company/client as the company/client moves into a new level of excellence in meeting the shareholders’ values

The Chief Digital Analytics Officer(CDAO)/SVP of Digital Analytics has the responsibility to align the Digital Analytics Strategic Roadmap with the strategic needs of the company or the client. 

The detailed Data, Analytics, Modeling and Business Intelligence (BI) strategic roadmap or frameworks will have to follow a very good understanding of the strategic digital direction of the company.

Therefore, the CDAO will need to have:

  • Clear understanding of what capabilities the company/client or the leadership is trying to develop as the company/client leadership tries to leverage Data, Analytics, Modeling and Business Intelligence (BI) structures, organization, systems and processes. Essentially the focus on Data, Analytics, Modeling and Business Intelligence (BI) structures, organization, systems and processes is not an end in itself.

    • The focus is to:

      • Use Data, Analytics, Modeling and Business Intelligence (BI) structures, organization, systems and processes to drive the company/client's results to the next level of higher performance. 

      • Be able to sustain the new level of performance. So it very important that there is a very good understanding of what the Board and the Senior Leadership Team (SLT) really wanted after discussions and consensus with the Board, SLT and other relevant Stakeholders on how best to achieve the greatest benefits and impacts from Data, Analytics, Modeling and Business Intelligence (BI) programs.

  • Open and active communication with the Board, SLT and all stakeholders of the company/client: For Data, Analytics, Modeling and Business Intelligence (BI) structures, organization, systems and processes to be designed, developed, built or/ and sustain, there is the need for active involvement of all the Senior Leadership Team members as partners and stakeholders.

The Deliverables from the CDAO/SVP of Digital Analytics are broken into parts below:

Part I: Identification and Assessment Stage

  • Strategic Digital Needs: Understand the strategic digital needs, alignment and prioritization for Digital Analytics deliverables

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

    • Key Digital Data, Digital 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 Digital Data, metrics, reports and decision support process capabilities

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

Part I: Identification and Assessment Stage

  • 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 Digital Analytics today and in future

    • Assessment of regulatory environments

    • Comparison: Comparing the client’s current state of Digital Data, Digital 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 Digital Analytics today and in future

      • Within the context of regulatory environments

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

Part II: Designing and Development Stage for Digital Analytics Blueprints

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

  • Design and Develop Conceptual Capabilities Models in terms of:

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

      • Big Data Governance

      • Big  Data Acquisition Domain

      • Big Data Marshalling Domain

      • Big  Data Processing Domain

      • Big Data Stream Capabilities

    • Process Workflow Capabilities Models

      • Business Process Management

      • Quality Management

      • Requirements Management

      • Document Management

    • Workforce and Performance Management Capabilities Models

    • Modeling and Decision Supports 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 Digital Analytics

        • Business Rules Engines Capabilities

Part II: Designing and Development Stage for Digital Analytics Blueprint

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

    • 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 and Technologies including Platforms to Support Digital Capabilities.

These include Identification, Testing, and Acceptance of Relevant Tools, Software and Technologies including Platforms to Support Digital Capabilities

  • Assessment of Software,  Technologies and Providers to Enhance Big Data Infrastructure: Sources of Digital Data including Digital Data Migration from the old legacy systems and  Big Data Management Platforms

    • Big Data Governance

      • Enterprise Digital Data Processing Domain

      • Master Digital Data Management (MDM)

      • Big Data Stream Capabilities

      • Enterprise Digital Data Marshalling Domain

        • Technology providers that include main technologies and vendors are Amazon, Cassandra, Cloudera CouchDB, Google, Hadoop, Microsoft, MongoDB, Oracle, Splunk and Teradata among others

      • Enterprise Digital Data Acquisition Domain

        • Technology providers that include IBM Informatica, Kalido, Microsoft, Numenta, Oracle, SAP, SAS, Splunk, Syncsort and Talend among others

Part III: Stage for Tools, Software and Technologies including Platforms to Support Digital Capabilities

  • Assessment of  Software and Technologies to Enhance Digital Process Workflow Capabilities Models

    • Business Process Management

      • Asset Management

      • Event-Based Notification

      • Approval Process Control

      • Process Activity Monitoring

      • Resource Management

      • Configurable Workflow Dashboard

    • Quality Management

      • Document Management

      • Supplier Quality Control

      • Internal Audit Management

      • ISO 9001 Management

      • Incident Management

      • Calibration Management

      • Compliance Management

      • Action Item Tracking

      • Customer Complaint Tracking

      • Defect Tracking

      • Corrective Actions based on new design, redesign or improvement

    • Requirements Management

      • Status Reporting

      • History Tracking

      • Traceability

      • Multiple Projects

      • User Defined Attributes

    • Document Management

      •  Version Control

      • Security & Encryption

      •  Document Indexing

      •  Document Delivery

      •  Document Assembly and Conversion

      •  Archiving & Retention

      • Access Controls

      • Compliance Management

 

  • Assessment of  Software and Technologies to Enhance Digital Workforce Force Capabilities Models

    • Associate/Agent Management System

      • Budgeting

      • Forecasting

      • Employee Location Tracking

      • Productivity Reporting

      • Skills Tracking

      • Labor Projection

      • Scheduling

      • Human Resource Integration

  • Assessment of  Software and Technologies to Enhance Digital Modeling and Decision Supports Capabilities

    • Descriptive Modeling

    • Operations Research and Decision Support Modeling

      • Management Science Modeling

        • Analytic hierarchy process

        • Social Network

        • Decision analysis

        • Expert systems

        • Neural networks

        • Digital data envelopment analysis

        • Econometric methods

        • Markov decision processes

        • Stochastic process models

        • Queueing theory

        • Simulation

        • Mathematical optimization

      • Predictive Modeling

        • Predictive Process Modelers

        • Predictive Process Stimulators

        • Predictive Model Markup Language (PMML)

      • Prescriptive Digital Analytics

        • Business Rules Engines Capabilities

Part III: Stage for Tools, Software and Technologies including Platforms to Support Digital 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 Digital Analytics in terms of Performance Metrics, Predictive and Prescriptive Scenarios

Part IV: Identification Stage for the Digital Analytics Models As Enabler to Deliver Digital Products and Services.

  • Design, Develop and Adopt Governance Models that can best integrate Digital Data, Digital Analytics, Modeling and Business Intelligence (BI) Capabilities in:

    • Digital Data Governance Model

    • Digital Analytics Governance Model

    • Modeler Governance Model

    • Business Intelligence (BI) Governance Model

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

    • Digital Data Management Operating Model

    • Digital Analytics  Operating Model

    • Modeler Operating Model

    • Business Intelligence (BI)  Operating Model

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

    • Digital Data Management Team Organization Model

    • Digital Analytics Team Organization Model

    • Modeler Team Organization Model

    • Business Intelligence (BI) Team Organization Model

Part V: Execution Plan Stage - Implementation: Towards the Transformation in Digital Analytics for Digital Products and Services

  • Implement Governance Models that include:

    • Data Governance Model

    • Information Governance Framework Model

    • Analytics Governance Model

    • Reporting Governance Model

  • Implement Operating Models that include

    • Digital Analytics Strategy, Services and Solutions

      • Data Management Services & Solutions

        • Data Strategy Focus

      • Performance Metrics Strategy

      • Advanced Business Analytics Services

      • Campaign Management & Marketing Analytics Services

      • Business Intelligence Data Reporting Solutions

        • Dashboard and Office Mobile

        • Operations Command Center

      • Cloud  Services (DaaS, AaaS, MaaS & RaaS) to Deliver Real Time Analytics and Reporting to the Business

  • Implement Organization Models that include

    • Foundational

      • Current and the Future States

    • Roles and Responsibilities

    • Functions

    • Alignment with Digital Products and Services Deliverables

      • Business

      • Operational

      • Process

      • Technical

    • Training Requirements

    • Matrix Relationships

    • Performance Measurements

  • Deployment

    • 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:

      • Digital Data Management Space

      • Digital Analytics Space

      • Modeler Space

      • Business Intelligence (BI) Space

    • Scope, Objectives and Constraints

    • Communication Plan

    • Timeline, Major Activities and Actors

    • Deployment Approach and Schedule

    • Technology Statement of Direction

    • Training and Development Plan

    • Project Schedule and  Management

      • Establishing the Transitional

        • Implementing the recommended Organization Model

        • Deployment of the Governance Model

        • Executing the Operating Model

    • Risk Management and Mitigation

    • Employee Buy-In and Culture - Change Management Plan

    • Issue Management

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