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Interactive Dashboards

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  • Interactive Dashboards

    February 2016

    Dr Rupert Booth, FIET FRICS FCMA PMP CEngChief Economist

  • Agenda

    Interactive dashboards: what & why

    Business Intelligence basics

    Case study

    Work done

    Lessons learned

    Choosing a platform

    Other applications:


    Asset/Facilities management

    Smart Cities


    Operational and Analysis Dashboards

    Summary for RICS Members

  • Definition of Interactive Dashboards

    Simple dashboard is adequate for:

    Limited information

    Readers with similar skills and information needs

    Typically delivered in an Excel workbook with up to a

    dozen sheets

    User-interaction adds:



    Threshold control for exception reporting

    Filter control (e.g. sliders)

    Choice of display formats for nave or expert users

    Excel offers limited interaction but database solution

    offers more potential

  • Potential of Data Visualisation

    Use of a database increases potential of visualisation:

    Handles large volumes of data

    Increased productivity

    Gain new insights that were not obvious before

    Common vision do you see what I see?

    Increased user interaction:

  • Need for Automation

    Hand-crated executive scorecards impractical with large data


    Essential to design data flow.

    Data source, usually Line-of-Business systems

    Staging area, for receipt and cleansing of data

    Data warehouse for storage

    Data extraction to answer queries

    Data visualizing for user, often by the user, i.e. self-service

    Data flow is typically web-enabled, and independent of the


  • Initial Scoping

    Demand-side: Who are the stakeholders and what

    do they want?

    Organisational goals and objectives

    Personal wins

    Supply side: What data is available?

    Inventory of systems, applications and data

    What technical infrastructure is available?

    Communication and storage options

    Gap analysis

    Initial dashboards

    Key performance indicators

  • First step: Identify & Classify the stakeholders

  • What are the other ingredients for success?

  • Dashboard & System Design

    Base around Use Cases (Story-boards)

    Who are the user groups

    What type of dashboard: Operational, Strategic, Analytical

    Group data logically

    Make data relevant to users

    Avoid data overload rely on navigation

    Avoid visual clutter

    Consider reporting cycle and decision-making cycle

  • Case Study: Monitoring the National Porfolio

    Developing a national level Programs/Projects Monitoring Dashboards

    on a recent project was a true challenge for Malomatias Analytics team,

    from standardising the data structure through Service Level Agreement

    governed data feeds, to having a User Interface that is intuitive,

    interactive and easy to use. Developing a business-oriented dashboard

    & story-board, and aligning it with a highly creative User Interface,

    allowed us to report very sophisticated project data in fast and user-

    friendly ways, catering for the needs of country leaders, agency heads,

    project and budget analysts, and project managers.

    Khalil Khalil, Head of Analytics, Malomatia.

  • Program level screen shot

  • Project level screen shot

  • Choosing a Platform: Range of Features (Gartner)


    Business User Data Mashup & Modelling

    Internal Platform integration

    BI Platform Administration

    Meta-data management

    Cloud Deployment

    Development and Integration



    Collaboration and Social Integration

    Embedded BI


    Free-form Interactive Exploration

    Analytics Dashboards and Content

    IT-Developed Reporting and Dashboards

    Traditional styles of analysis

  • Gartner Magic Quadrant

    Described as Gold Standard by Gartner

    Two products, QlikSense & QlikView

    Traditional Business Intelligence tools

  • Beware: Not Big Data

    Large volume of data does not equate to big data

    Most dashboards based upon:

    Relational data based management system

    Structured data and Structured Query Language

    Record all past transactions

    In contrast, Big Data:

    Typically based on Hadoop

    Not based upon data schemas

    Flexible mapping

    Pass-through data

    However this traditional contrast is beginning to blur

  • Olympic Delivery Dashboard

  • Facility Management Dashboards


    Typical graphical output: Inter site

    comparisons (left) Service cost trends


    Typical choice of metrics:http://dashboardspy.com/dashboards-for-facility-managers/

  • Smart City Engagement http://data.london.gov.uk/

  • Geographic Applications

  • Operational Dashboard Real Estate


  • Analysis Dashboard Transport Planning

  • Possibilities for RICS members?

    Improve the usability of a construction dashboard

    Design a dashboard from scratch

    Manage a dashboard implementation

    Corporate performance measurement

    Web-enabled lifecycle management

  • The End

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