People Analytics: Transforming HR Strategy with Data Science

Achieving Operational Excellence with Data: How do you organise and leverage what already exists within your organisation?

• Identify and manage key stakeholders
• Develop a pragmatic approach to people analytics projects
• Find opportunities from data and vice versa
• Identify where relevant data resides within organisations
• Recognise the key benefits of data warehouses
• Conceptualise the role of data warehousing in strategy

 Transforming the Workplace - What is your vision for the future of work?

• Analyse inherent limitations of people analytics techniques within ethical scenarios
• Develop strategies for mitigating the diverse array of risks that arise when applying machine learning to organisational challenges
• Define a personal vision of how people analytics technologies should follow the principles of ethical leadership, corporate social responsibility, and values-oriented algorithm design
• Examine how people analytics can transform society and the workplace for the better

Root Cause Analysis and Project Tactics - How do you ensure you solve the right problem within the appropriate timeframe?

• Create project management plans for people analytics
• Explore counter-intuitive hypotheses
• Break down symptoms of people-related challenges into their constituent parts
• Uncover the root causes and tackle them intelligently

Designing Successful Experiments - How can you best achieve scientific rigour and quality within complex and dynamic organisational settings?

• Design experiments and formulate scientific hypotheses
• Compare underlying measurement principles behind experimental designs
• Draw conclusions from data analysis and communicate results to senior leadership
• Apply scientific methods to resolve practical organisational challenges

Psychometrics - What role do latent traits have in governing workplace behaviour and how can psychological data augment people analytics efforts?

• Assess the influence of latent psychological traits on workplace behaviour
• Define criteria against which to evaluate psychometric tests
• Present opportunities and limitations of psychometric data in strategic decision-making

Organisational Data  

• Translate an organisational problem into a data question
• Address corporate challenges using both structured interviews and unstructured text analytics
• Become fluent in statistical and data science terms on a high level, to effectively lead data scientists
• Understand the process of moving from description to prediction to prescription
• Appreciate the differences between machine learning, AI and other predictive models
• Analyse prepared code and simulated organisational data, including internal news boards, managerial reviews, employee surveys, emails, and unstructured text data
• Deliver written and oral communications to keep stakeholders engaged and invested in the success of the people analytics function