Moving Beyond Data Visualization to Predictive Analytics...Data Visualization and Analytics Strategy...
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Contact: [email protected] © ResultWorks, LLC Moving Beyond Data Visualization to Predictive Analytics ResultWorks, LLC – Strategic Innovation, Integrated Business Analysis, Information Transformation and Data Management Consulting for Life Sciences Business Analysis Approach Business Challenges Background www.resultworksllc.com Current State Assessment • Engage with cross-functional team to align to data visualization definition and how visualization will be used within the organization • Analyze gaps and opportunities mapped to pain points in current data visualization strategy Future State Vision and Strategy Development • Reach consensus on future state vision, describing how the organization will operate in the future— culturally, operationally, and technically • Develop an Agile approach to define and align to future state use cases that describes how technology will support the business Strategic Roadmap • Develop direction-setting roadmap reflective of business priorities and work needed to achieve vision Tools and Technology Assessment • Define the technology capabilities and architecture needed to support the use cases • Investigate viable commercial technology solutions and approaches Breakthrough Thinking Transforms Data Quality Strategy to Leverage Advanced Predictive Analytical Techniques Use Case and User Story Development Provides the Foundation for the Future State Using advanced tools and improved business processes, decision making becomes proactive, timely, and data-driven Teams operate with analytical curiosity , using tools to help derive insights from what the data is telling them Intelligent Agents scour data to identify and track trends, anomalies, and resolutions, providing end-to-end traceability Leverage approaches that are risk-based and favor error prevention over remediation and tools ensure the right people are looking at the right data at the right time On-demand visualizations clearly communicate insights to teams, highlighting key information that may otherwise be overlooked Agile approach to use case development aids implementation of solutions in response to evolving business needs Data Visualization and Analytics Strategy Roadmap Teams are focused on the operational, transactional activities, rather than data-driven decision making Need to evolve from incremental approach to radically transformative change There are many tools available; some tools are better than others for certain situations Organizations need to think strategically about how to use the data they have and to select tools for automating analyses and decision making Layering transformative vision with cross -cutting elements and business value solutions on a strategic roadmap enables projects areas to be prioritized and sequenced Conclusions Companies have historically focused on checking individual data points using data edit checks, line listing reports, and—to a lesser extent—basic graphs predicated on checking against known business rules Few companies have any ability to quantitatively measure overall quality of study data, nor predict when sufficient data will be available for analysis; any predictions are made qualitatively on instinct and experience The volume of studies, data, and the need for rapid interim analyses in support of adaptive programs makes the manual approaches to visualization and analysis unsustainable A variety of data visualization tools including Excel, Spotfire, Tableau, and JReview are already in use, but without a clear strategy and supporting business use cases these tools are selected and applied inconsistently Acknowledgements: Bob O’Hara, Managing Partner • Susan Butler, Managing Partner • Karen Hiser, Senior Consultant • Dan Joyce, Consultant Look beyond basic charts and graphs to more sophisticated analysis techniques with prescriptive decision making and machine learning Persona Oversees study data progression to monitor for key study milestones Needs to know if milestones like interim analysis are at risk and what corrective actions can be taken Manually runs reports to identify study progression issues with variety of tools Needs automated monitoring of study, patient, enrollment data without managing different tools Clinical Data Associate Clinical Data Manager Persona Process Incoming data is monitored Generate and analyze reports Issues are flagged based on risk - profile Track and escalate data issues Clinical Data Associates, Clinical Operations, Statisticians Clinical Monitors, IT Data Managers, Statisticians Actors Consumers Inputs Outputs Data / Systems Tools: Intelligent Agents Dashboards and Visualizations Risk-based rule definitions Issue tracking and outcome Reports
Transcript of Moving Beyond Data Visualization to Predictive Analytics...Data Visualization and Analytics Strategy...
Contact: [email protected] © ResultWorks, LLC
Moving Beyond Data Visualization to Predictive AnalyticsResultWorks, LLC – Strategic Innovation, Integrated Business Analysis, Information Transformation and Data Management Consulting for Life Sciences
Business Analysis ApproachBusiness Challenges
Background
www.resultworksllc.com
Current State Assessment• Engage with cross-functional team to align to data
visualization definition and how visualization will be used within the organization
• Analyze gaps and opportunities mapped to pain points in current data visualization strategy
Future State Vision and Strategy Development• Reach consensus on future state vision, describing
how the organization will operate in the future—culturally, operationally, and technically
• Develop an Agile approach to define and align to future state use cases that describes how technology will support the business
Strategic Roadmap • Develop direction-setting roadmap reflective of
business priorities and work needed to achieve vision
Tools and Technology Assessment• Define the technology capabilities and architecture
needed to support the use cases• Investigate viable commercial technology solutions
and approaches
Breakthrough Thinking Transforms Data Quality Strategy to Leverage Advanced Predictive Analytical Techniques
Use Case and User Story Development Provides the Foundation for the Future State
Using advanced tools and improved business processes, decision making
becomes proactive, timely, and data-driven
Teams operate with analytical curiosity, using tools to help derive
insights from what the data is telling them
Intelligent Agents scour data to identify and track trends,
anomalies, and resolutions, providing end-to-end traceability
Leverage approaches that are risk-basedand favor error prevention over remediation
and tools ensure the right people are looking at the right data at the right time
On-demand visualizations clearly communicate insights to teams, highlighting key information that may otherwise be overlooked
Agile approach to use case development aids implementation of
solutions in response to evolving business needs
Data Visualization and Analytics Strategy Roadmap
Teams are focused on the operational, transactional activities, rather than data-driven decision makingNeed to evolve from incremental approach to radically transformative changeThere are many tools available; some tools are better than others for certain situationsOrganizations need to think strategically about how to use the data they have and to select tools for automating analyses and decision makingLayering transformative vision with cross-cutting elements and business value solutions on a strategic roadmap enables projects areas to be prioritized and sequenced
Conclusions
Companies have historically focused on checking individualdata points using data edit checks, line listing reports, and—toa lesser extent—basic graphs predicated on checking againstknown business rules
Few companies have any ability to quantitatively measureoverall quality of study data, nor predict when sufficient datawill be available for analysis; any predictions are madequalitatively on instinct and experience
The volume of studies, data, and the need for rapid interimanalyses in support of adaptive programs makes the manualapproaches to visualization and analysis unsustainable
A variety of data visualization tools including Excel, Spotfire,Tableau, and JReview are already in use, but without a clearstrategy and supporting business use cases these tools areselected and applied inconsistently
Acknowledgements: Bob O’Hara, Managing Partner • Susan Butler, Managing Partner • Karen Hiser, Senior Consultant • Dan Joyce, Consultant
Look beyond basic charts and graphs to more sophisticated
analysis techniques with prescriptive decision making
and machine learning
Persona
Oversees study data progression to monitor for
key study milestones
Needs to know if milestones like interim analysis are at
risk and what corrective actions can be taken
Manually runs reports to identify study progression issues with variety of tools
Needs automated monitoring of study, patient, enrollment
data without managing different tools
Clinical Data Associate
Clinical Data Manager
Persona
Process
Incoming data is monitored
Generate and analyze reports
Issues are flagged based on risk-profile
Track and escalate data
issues
Clinical Data Associates, Clinical Operations, Statisticians Clinical
Monitors, IT
Data Managers, Statisticians
Actors Consumers
Inputs Outputs
Data / Systems Tools:Intelligent Agents
Dashboards and VisualizationsRisk-based rule definitions
Issue tracking and outcome Reports
