Targeted Analytics, February 2014
February 4-6, 2014
two days total: starts at 1 pm on 2/4 and ends around lunchtime on 2/6
Any organization interested in HR delivering data-driven business solutions should attend this course. Dr. Levenson offers practical insight on where/how to start looking as you build the case to shift the direction of the business through people.
-Dianne Reece, Manager, Organizational Development & Training, FMC Technologies, Subsea Systems
The main objectives of this program are to improve analytical decision making, use analysis to lead change and make the right choices when deep analytics are not possible.
Participants will learn from case studies and applying systems diagnostics and models to challenges in their own organizations. Upon returning to their organizations, participants will be able to:
- recognize situations where analytical decision making and deep-dive diagnostics can be applied effectively to improve organizational performance
- better apply analytics to increase data-based insights for decision making
Specific applications will focus on identifying:
- the source of productivity problems at the role and group levels
- the factors at the heart of individual and organizational capability
- the data needed for a work design ROI analysis
- the right mix of qualitative and quantitative data for deepest insights
- Use a systems model to diagnose and set the stage for acting on your talent and team challenges
- Evaluate alignment of strategy and work design to make the business case for change
- Recognize situations where analytical decision making and deep-dive diagnostics can be applied effectively to improve organizational performance
- Set up analytics processes to monitor and act on organizational challenges
- Design and use surveys to improve organizational impact
The course will cover:
Using systems diagnosis, analysis, and decision making
- Using the Performance Model at the organization, group and role levels
- Identify alignment between strategy and work design
- Which data to employ and how to analyze it for deepest insights: qualitative vs. quantitative; what you have on hand vs. what you need to collect
- Decision making
- Knowledge bases to tap for insights without doing new analysis
- Building causal models for testing and stakeholder engagement
- Group-level productivity and role interdependencies
- Work design diagnostics: measurements at the role, process and unit levels
- What to focus on when you can't measure everything
- Competencies vs. capabilities for the organization, leadership and frontline employees
- What is measured vs. what should be measured
- How to bridge the divide
Application: Employee Engagement
- The causal link between employee engagement and business performance
- When engagement is the right thing to measure, and when it is not
- What more do you need to know to improve business performance
Incorporating measurement into change and change into measurement
- Measurement and monitoring while change takes place
- Using surveys and interviews as part of a change process
- How to structure analytics processes to engage key stakeholders
- How to efficiently cut corners in time crunch situations
- What measures does the business use to interpret and act on talent and HR programs and processes? How can we increase the use of relevant metrics?
- How and where to build analytic capabilities in the HR function
Recent Participant Comments about the Workshop
- "Definitely gives us a targeted strategy to focus in on retention issues"
- "Enjoyed this class. It was very insightful and helped me better understand how to tackle our outstanding and future issues."
- "Valuable models that I can apply and use in the everyday work that I do."
- "I will be immediately applying what I have learned - the ROI will be quickly realized."
Click here to learn more about our active research.
Center for Effective Organizations
- University of Southern California
- 3415 S. Figueroa Street
- Davidson Conference Center 200
- Los Angeles, CA 90089–0871
- usc marshall school of business