People Analytics for Decision Making Flashcards
In which countries HR analytics is a growing trend?
Australia, Italy, India & Netherlands.
What is the state of the art of HR analytics?
- Use data to measure HR’s impact on business (Little or no extent)
- Rigorous data-based decisions (Little or no extent)
- HR data to support change management (Little or no extent)
- Analytical support to business decision making Little or no extent)
- Data-based talent strategy (Little or no extent)
What is the context of HR analytics?
- Data generated from start of recorded history until c. 2015.
- Data generated in the last 2 years.
What is Big Data?
Because of big data, managers can measure, and hence know, radically more about their business, and directly translate knowledge into improved decision making and performance. But what’s new is data is generated a lot faster with high
- Volume
- Velocity
- Variety.
Thus, big data doesn’t make HR analytics better unless it is used strategically. Thus, it is not the size, it is what you do with it that counts.
What is ‘People Analytics’?
Focus on evidence-based management.
Rethinking the question:
→ What do we need to succeed?
→ How do people actually contribute to organizational success?
- Rethinking how people data are used in organizations
- People analytics requires a specific set of skills…and not only data skills.
Why is evidence based decision making important?
The complexity and fast pace of today’s organizations often lead to knee-jerk business decisions, fad chasing and guesswork regarding ‘what works’..Blind faith has no place in professional practice.” (Rousseau & Barends, 2011). Thus we need evidence management for many reasons.
What are the reasons behind using evidence based decision making important?
If we don’t think critically about information, we will rely on:
1. Obsolete knowledge
→ The risks of outdated knowledge: Half of what you learn will be shown to be either dead wrong or out-of-date within 7 years of your graduation; the trouble is that nobody can tell you which half.
2. Personal experience without reflection
→ Relying on experience
→ “Integrity tests” that try to predict whether someone will steal, be absent, or otherwise take advantage of an employer are valid predictors of counterproductive work behaviour and absenteeism. (True) [32% of managers answer correctly]
→ Being very intelligent is actually a disadvantage for performing well on a low-skilled job. (False) [42% of managers answer correctly]
→ Most employees prefer variable pay systems (e.g., incentive schemes, gain sharing, stock options) to fixed pay systems. (False) [40% of managers answer correctly]
- Specialist skills
- Hype and dogma
- Mindless mimicry
Is EMB same as people analytics?
No, it is not the same.
→ The analytics itself is only one source of evidence.
→ Multiple sources of evidence should be used, together.
→They should be used critically.
What is an evidence based mindset?
→Valuing the importance of evidence. → Challenging self-held assumptions and intuitions →Being open to scrutiny →Not being precious about knowledge →Open minded about answers
What is the changing role of HR? (Huselid & Becker, 2005)
“The development of HR’s strategic role has been an evolution…The next step in the evolution is for HR professionals, and particularly senior HR professionals, to develop what we call analytic literacy”.
How do we develop analytical literacy?
→Understanding of business logic to drive measurement.
→Thinking in terms of causal relationships.
→Appropriate modes of analysis.
→Communication skills.
Why do we need collaboration for people analytics? (Barbour, Treem & Kolar, 2017)
Increased need for collaboration across business units…multidisciplinary knowledge management. Three aspects of collaboration are:
- Access
- Trust
- Connections
How to have better people analytics?
- Ask the right questions (Is it focused? Is it strategic?)
- Build a theory of the business
- Collect evidence
- Analyze
- Visualize and tell a story
- Implement and evaluate
Where does the complexity of analytics depend on?
It depends on the question.
1. Simple (descriptive):
- How many graduate trainees in our engineering division voluntarily leave within the first year?
- What is the difference in mean salary between men and women within the same job grade and division?
(Analysis method: descriptive statistics, t-tests, ANOVA, (describing or comparing)
2. Complex (predictive)
- HR Management Dashboard
- Investing in the development of which teams will produce the biggest improvement in productivity (measured by units produced)?
- In which department are we likely to face recruitment problems within the next 12 months?
What is the problem with headcount?
The problem with headcount:
HEADCOUNT
- The number of people working in the organization, right now.
- Do we include people not directly employed by the organization?
FULL-TIME EQUIVALENT (FTE)
- The actual number of contracted people employed by the organization, right now (e.g. working half time = 0.5)
- Is this ‘point in time’ or across a period of time?
The lesson: Even the basis stats are difficult if you have not defined the question properly.
