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Lecture Notes HR analytics
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Lecture Notes of all four lectures of HR analytics (2020).
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HR-analyticsLecture 1 – Introduction to HR analytics (16-09-2020)
Why is HR-analytics important?
1. Using data to form decisions for the management
2. Statistical analysis and data presentation are both in the top 10 most
important skills that are globally needed
HR is about decisions (1)
So, what is HR? It is all about decisions. And that applies for organizations
as well. For instance:
• Do we use assessment centers or structured interviews in the
selection procedure for job A?
• What procedures shall we use for socializing new employees? Are
institutionalized tactics in this process really more effective than
individualized ones?
• Will the group of new employees require additional training? If so
what kind of training is more effective?
• All our competitors apply pay for performance; do we need to do that
as well?
• What’s the optimal team composition (Starbucks)?
• Are commitment HR practices really the best option for our R&D
department or shall we use a mix of the former and compliance HR
practices?
So, HR is about decisions. But how can we get the right answers?
- HR-analytics/data can disappear some of these uncertainties and will
help us to make the right decision.
- However, analysis are not always right, so you should understand
how statistics work. Otherwise, you may provide organizations with
the wrong advice.
HR and the new world of work
The 3 D’s (people function priorities):
1. Data
Data is crucial to understand. The success of practices depends on the value
you can prove that it positively influences the business. This is difficult to
prove. Also, data can clarify the alignment between practices and the
organization strategy (e.g. low-cost strategy and HR-practices).
2. Design
First, the overall design of an organization is changing (structure). But also,
the reshaping of the jobs itself (switching to robots).
3. Digital
Making HR more efficient
1
,What is HR Analytics?
HR-analytics → ‘‘the systematic application of predictive modeling using
inferential statistics to existing HR people-related data in order to inform
judgments about possible causal factors driving key HR-related
performance indicators’’
→ the results of this modelling can be used (where appropriate) to make
tangible predictions about particular results or people outcomes.
From reporting to analytics
2
,Reporting is not enough (e.g. sales versus turnover), it’s just ‘cold’
reporting. Here, you are focusing on the past and as such you are
presenting past trends. On the other hand, analytics is about higher
complexity, so you are more future-oriented.
Some of the problems of today’s HR “analytics”:
- Teams spend considerable amount of time and effort producing
descriptive reports, and they do not add any new information for the
decision-making
- Such reports only show a “snapshot” of what is happening
- Tell us a little about why things are happening (e.g., we have a high
turnover, but why is that?)
- After the descriptive reports are written there is a lot of unused data
- Usually such reports fail to test or check if data is robust or
valid (e.g., how should we measure human capital?)
- Such reports lack any “predictive” paradigm
Measuring the return on people – it is about intangible value
That is more difficult. We have more of this intangible value than before.
But, how can we measure these intangible values? It is almost impossible
because we do not have good measurements. But these intangible assets
are becoming increasingly important for organizations.
Also, it lacks credibility across the business, as organizations capture the
value in terms of costs.
Measuring the return on people – it is about intangible value
Future: ISO 30414? (=iso standard)
3
, - We are not going into deep into this number. But one day, you can
use this standard to help your organization in order to quantify human
capital.
Traditionally, HR is not been seen as a decision science profession. But then,
organizations want to measure these kind of HR aspects.
This model gives you an impression about how you can measure this
(further explained in the book). But he tells us that this is determined by 4
factors.
What is HR analytics?
Analytics present a tremendous opportunity to help organizations
understand what they do not yet know, by identifying trends and patterns,
HR professionals and management teams can make better strategies
decisions about the work force challenges that they may soon face.
HR analytics and predictive modeling
- Today HR somehow fails to ‘predict’ various important things
- So, what can we actually understand with the predictive modeling
that HR analytics is supposed to deliver?
Then, the question ‘what is predictive’ raises?
We can understand predictive HR analytics in three ways:
1. Prediction is usually related to identifying ‘predictors’ or potential
‘causal’ factors. Why?
a. Think about employee performance, how can we predict it? So,
what is leading to higher individual innovation?
2. Change the predictor. What will happen to the outcome? So, are they
really changing the vocal variable? And then in the end,
3. Predict how employees may behave in the future? (e.g. thin about
trends and patterns). So you would like to predict how people will
behave in the future.
HR analytics – benefits
With the right HR analytics, we are able to:
- Determine the impact of people on the business
- Demonstrate that HR practices produce value for money in terms, for
example, of return on investment
- Provide guidance on future HR and business strategies
- Provide diagnostic and predictive data that will inform strategies and
practices designed to improve the effectiveness of people
management in the organization
- Organizations that have adapted advance people analytics capabilities
experience on average 25% increase in productivity, huge rise in
recruitment efficacy and reduction in attrition rates.
4
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