How to use data and predictive analytics to attract, retain and develop top talent
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Join Qualtrics and guest speaker David Munro from Effective HR Consulting as we talk through how businesses can use data and predictive analytics to attract, retain and develop top talent
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How to use data and predictive analytics to attract, retain and develop top talent
- 1. How to use data and predictive analytics to attract, retain and develop top talent By David Munro Guest speaker from Effectus HR Consulting
- 2. Taking Employee Experience to the next level: How to retain, attract and develop talent How to use data and predictive analytics to retain, attract and develop talent Date: 17th of May 2017 The bottom line impact of employee recognition 30th of May 2017 Developing an Employee Value Proposition that recruits and engages today’s top talent 19th of June 2017
- 3. Housekeeping 3 The recording and slides for today’s presentation will be made available within 24 hours. Please use the question window to submit questions throughout the webinar. We have time designated at the end for Q&A.
- 4. 4 David Munro Director & Head of Customer Experience – Effectus HR Consulting David is a psychologist and veteran of the talent analytics field, having worked across product, suppliers and consulting. For more than 15 years David has pioneered the use of people data to inform business decisions. More recently, David has become renown for helping organisations move from ‘insight to foresight’ with the emerging field of predictive analytics. David is a Director and Head of Customer Experience at Effectus HR Consulting – who are the business partners of choice for organisations seeking to optimise performance from their people.
- 5. How to use data and predictive analytics to attract, retain and develop top talent
- 6. Agenda • The transformation currently underway with data led-decision making • Some examples and ‘quick wins’ • Where to start 6
- 7. Data Analytics Maturity 7 Information Insight Foresight Predictive Analytics: Evolution of HR Data
- 11. Employee Lifecycle Examples 11 Attraction, Recruitment, Onboarding CVs Psychometric information Number of applicants compared with number of positions Time to hire Time to productivity ↓safety incidents ↑sales Development & Engagement Engagement data Training and capability data Performance and productivity data ↑ L&D ROI ↑ efficiency & objectivity of talent identification ↑ leadership self-awareness Retention & Separation Turnover rates Exit interview data Tenure data Customer experience data ↓turnover costs including recruitment ↑ customer experience Information & Insight Foresight
- 12. Where do I start? 12 Analytical CapabilityInformation • Collect data • Organise and cleanse data • Gaining an understanding of where you are at Data-led Decision MakingInsights • Key business drivers and Stakeholders • Identify patterns and use calculations to make predictions • Providing greater explanation to the data (e.g. year-on-year improvement) Commercial Acumen and Data ScienceForesights • Return on Investment • Machine learning • Understanding capability and reporting on impact
- 13. Q&A
- 14. Thank you! David Munro Email: david.munro@effectushrc.com LinkedIn: linkedin.com/in/davidmunroeffectushrc
Editor's Notes
- Information Currently lots of unorganised “Big Data” “What was their experience?” Focus on the past (historical information) 56% of organisations do this Looking at data in isolation is retrospective – tells you what happened in the past or at a key point in time. It provides no explanation to the ‘why’ or the relationships with other business variables and as a result, is open to misinterpretation. Insights This step provides greater explanation to the data or information. Key trends and insights from HR Analytics “What is their experience?” Focus on current, real-time data 40% of organisations do this Foresights This represents predictive analytics – taking the step beyond reporting and metrics. “What will their experience be and how could it be better?” Focus on future Currently 4% of organisations to this, but will be about 50% by 2020 (Bersin) The role of HR in the Information stage is Personnel, moving to Business Partners in the Insights stage, and Business Optimisers in the Foresights stage. This transitions HR to being a strategic part of the organisation and moving from simply HR analytics to business analytics. Predictive analytics uses HR data to predict organisational performance (i.e. Return on Investment vs. Cost) through defining success criteria, identifying the relevant data and using the most appropriate methods to address the criteria.
- What are Predictive Analytics Predictive analytics is the branch of the advanced analytics which is used to make predictions about unknown future events. Predictive analytics uses many techniques to analyse current data to make predictions about future. Using existing data to predict future performance. For example, using employee engagement data in 2017 to predict employee productivity in 2018
- “Predicting the future….without being psychic” “Big data is nothing without the ability to draw insights and predict future performance”
- Data and metrics are gathered across the employee cycle through a variety of different methods. Consider the information gathered by: Attracting, Recruiting and Onboarding: CVs Psychometric information Number of applicants compared with number of positions Time to hire Time to productivity Development and Engagement: Engagement surveys Pulse surveys Training and capability data Performance and productivity – effectiveness, individual, team, group And Retention/Separation: Turnover rates Exit interview data Tenure
- Tips on starting: Acquire or partner in analytical capability Choose a metric or project that matters to your business. Appreciative enquiry Outline the results in $ dollar figures on 1 page.