HR Matrics – Defining metrics, Demographics, data sources and requirements, Types of data, tying data sets together, Difficulties in obtaining data, ethics of measurement and evaluation. Human capital analytics continuum.

1. Module - 5
Prof. Vijay K S Bapuji B-Schools, Davangere

2. Defining Metrics
“A System or a standard of Metrics”
“Simply put, Metrics are a way to quantify, measure, and track
key performance indicators”
In HR, Metrics are used to measure and track the performance
of the company’s largest investment.
Prof. Vijay K S Bapuji B-Schools, Davangere

3. Defining Metrics
Some questions need to be asked
- Why do we track metrics?
- Why are they important?
- What metrics do we track?
- What do we do with the information we track?
Prof. Vijay K S Bapuji B-Schools, Davangere

4. Defining HR Metrics
Human Resource (HR) metrics are measurements used to determine
the value and effectiveness of HR initiatives, typically including such
areas as turnover, training, return on human capital, costs of labor,
and expenses per employee.
Prof. Vijay K S Bapuji B-Schools, Davangere

5. Human Resources’ role in Metrics and Analytics
- Shift in focus from administrative to strategic
- Focus on revenue, Growth, Market share, Productivity.
- HR has direct impact on data driven decisions
- Data is the key
Prof. Vijay K S Bapuji B-Schools, Davangere

6. The connection between the organizational strategy and HR
In some way that an organization has a specific strategy, so
must HR.
To demonstrate HR’s value to the organization, metrics must
tie to what is most important to the C-Suite
In other words, HR metrics must tie directly or indirectly to the
organizational strategy
Rachel Salley
, HR Manager at Vology, Inc.
https://www.slideshare.net/rmsalley/what-are-you-worth-measuring-your-valueadd-through-hr-metrics?from_action=save
Reference:
Prof. Vijay K S Bapuji B-Schools, Davangere

7. How HR can bring value to the organization through metrics
Understand WHY you are measuring
- Don’t measure just for the sake of measurement
- What do you hope to discover, improve, increase/decrease with metrics
- Have an action plan once metrics are attained
Understand WHAT you are measuring
- Metrics must relate to business
- Metrics must be important to the leader
- Metrics should be easy to gather, analyse and disseminate
Rachel Salley
, HR Manager at Vology, Inc.
https://www.slideshare.net/rmsalley/what-are-you-worth-measuring-your-valueadd-through-hr-metrics?from_action=save
Reference:
Prof. Vijay K S Bapuji B-Schools, Davangere

8. How to define and implement HR metrics into your organization
Rachel Salley
, HR Manager at Vology, Inc.
https://www.slideshare.net/rmsalley/what-are-you-worth-measuring-your-valueadd-through-hr-metrics?from_action=save
Organizational Strategy
Defined
- Cost cutting
- Improve customer
satisfaction
- Develop new
technology to remain
competitive
HR Strategy Defined
- Decrease recruitment
cost
- Increase customer
service training
- Source and hire better
talent
HR Metrics Defined
- Reduce recruitment
cost by 20%
- Increase performance
level
- 10% of new hire
performing above the
average.
Reference:
Prof. Vijay K S Bapuji B-Schools, Davangere

9. Key Points To Remember
- Matric should give the whole picture, including the cost, quality, quantity, time,
cost and effectiveness
- Focus on key area where change is necessary
- Develop a benchmark to use for evaluating progress towards goals
- Set goals and establish metrics for measuring progress
- If possible, compare with Competitors
- Use the language of your leaders
- Hard metrics(real data) are better than soft metrics
- HR Metrics are directly related to important business issues
- Easy to understand and data should be readily available
- Don’t keep metrics as secret
- Use metrics to identify trends and head off problems on the horizon
- Don’t be afraid of metrics and measuring data
Rachel Salley
, HR Manager at Vology, Inc.
https://www.slideshare.net/rmsalley/what-are-you-worth-measuring-your-valueadd-through-hr-metrics?from_action=save
Reference:
Prof. Vijay K S Bapuji B-Schools, Davangere

10. Demographics
As you create the measurement plan, consider which
demographics have are a reasonable connection to the
investment, as well as the type of demographic data that is
available.
Prof. Vijay K S Bapuji B-Schools, Davangere

11. Demographics
Two Categories:
- Individual – Individuals personality traits, such as age,
gender, education level, ethnicity and so on.
- Organizational – derived from some unit the individual is
part of – Region, division and work unit and so on
These data come from different sources and are linked back to
individual.
Organizational demographics are more fluid than the individual
demographics
Prof. Vijay K S Bapuji B-Schools, Davangere

12. Data sources and requirements• Operations
• Compensation
• Customer service
• Human resources information systems (HRIS)
• Learning management systems (LMS)
• Social media and non-traditional learning systems
• Engagement
• Surveys
• Performance management systems
• Interviews and estimation by experts
• Public data from outside the organization
Prof. Vijay K S Bapuji B-Schools, Davangere

13. Types of Data
Operational Data:
- Tracks the business processes
- Sales commission, revenue, Call centre information, defects, safety
incidents,
- This has a advantage as it is closest to the cash flow and likely to be well
organised and closely tracked
- It doesn’t have privacy issue as it is with HR Data
- The results with the analysis of this data has got instant credibility because
the metrics align with those tracked by executives.
Prof. Vijay K S Bapuji B-Schools, Davangere

14. Types of Data
Customer service data:
- Addresses the important business processes – in particularly where there is
a high ratio of customers facing employees i.e. “Surface Area”
- It can be measured in many ways
- Reported satisfaction
- Business Results
Prof. Vijay K S Bapuji B-Schools, Davangere

15. Types of Data
Human Resource Information System:
- Primarily they provide demographic information – education, tenure, job
title and other details
- It includes compensation data
- Provides master list of participants in the measurement of project
- Most likely source for mapping data that ties different data set together
Prof. Vijay K S Bapuji B-Schools, Davangere

16. Types of Data
Learning Management System.
- Contains information about training, which is a common focus of human
capital investment measurement.
- Training received and date on which the training received
- Online training virtually always contain ways of tracking this information
- Traditional classroom method has an issue of tracking – Logbook of
classroom booking and simple spreadsheet maintains the same is ideal
Prof. Vijay K S Bapuji B-Schools, Davangere

17. Types of Data
Social media and informal learning system.
Organizations use social media in different fashion
- Promoting and sharing information about the company with the outsider
- Recording the public sentiment about the company and its Products and
Services
- Use social media internally providing a forum for employee to browse
and post useful content.
- Mind set of social media is still a challenge as it requires relinquishing
central control and allowing free, unstructured exchange of information.
- If we collect the information about who has collected the information, it is
possible to directly measure impact on individual.
- External social media may be difficult to or impossible platform on which to
measure information.
Prof. Vijay K S Bapuji B-Schools, Davangere

18. Types of Data
Engagement Survey.
- Effective instrument for gauging sentiment by employees and are gaining
the popularity
- Includes gauging the employees satisfaction with their managers or with
their careers
- Because of its confidentiality these surveys are very difficult to map to a
particular individual or to a “Manager”
- Here the involvement of third party will make better sense
- Confidentiality is the important issue and all employees should not worry
about “Who is might read their information?’’ and the further
consequences
- There are issues with the surveys
Prof. Vijay K S Bapuji B-Schools, Davangere

19. Types of Data
Psychological Testing:
- These show promise in predicting the performance on job metrics, both
individual sense and “fit” towards the team.
- The role of “Psychological and social capital” in creating and maintaining a
dynamic, productive workplace is an area of growing importance.
- Research suggest that the concepts such as “Self efficacy, hope and
resilience are important constructs in understanding employee
performance.
-
Prof. Vijay K S Bapuji B-Schools, Davangere

20. Types of Data
Performance Management System:
- Internal rating and planning systems designed to evaluate employees or
teams or to plan for future development for those employees.
- 360 Degree evaluation system
- KPI
- These can results in proposing someone for training programmes
- Relationship between the KPI’s and Performance system can be tested
Prof. Vijay K S Bapuji B-Schools, Davangere

21. Types of Data
Expert estimation:
- This is one way of collecting data from many things
- Information such as estimation of cost of security breach, the likely wood of
success for particular projects, or the amount of revenue a new project
could generate
- This method is commonly applied to costs and risks
Prof. Vijay K S Bapuji B-Schools, Davangere

22. Types of Data
Public date from outside the organization:
- Bureau of Labour statistics
- Stock performances – Positively with compensation and negatively with
turnover
- Currency exchange, in particular to multinational organizations
- Benchmarking
Prof. Vijay K S Bapuji B-Schools, Davangere

23. Tying your data sets together
- Crucial task is to combine date from different sources
- “Unique identifiers” – Employee ID, E-mail ID, Social Security Number or
Aadhar Number.
- To make connection between data sets, your data analysts will need one or
more unique identifiers.
- With people or employees generally identifiers are the employee ID
- The numeric identifiers are clean, efficiently stored and unambiguous. And
they also protect the privacy of the individual.
- Proper names are the messy identifiers – There are multiple issues.
- IF the performance management system uses employee ID, a training
system uses proper name, and the other systems that use E-mail address, all
will not get into how mapping can be created, but good analyst will be able
to manage.
-Prof. Vijay K S Bapuji B-Schools, Davangere

24. Where the data may exist?
Human
Resources
Learning
Operations
Prof. Vijay K S Bapuji B-Schools, Davangere

25. Difficulties in Obtaining Data
- Data availability in many systems; difficulty in comparison and consolidation
- Need Approvals and conditions to get the data.
- Problem of negotiation in sharing the data; convincing that the amount of
data was of advantage to no one.
- The stakeholder’s apprehension about the results
- Some data stored externally and will require cooperation between different
companies
Prof. Vijay K S Bapuji B-Schools, Davangere

26. Difficulties in Obtaining Data Conti….
- Systems have different criteria for including and excluding employees, such
as terminated employees, summer interns, contract and temporary workers
and more
- Some systems may use a convention for identifying employees that does not
exist elsewhere
- Employees may have slightly different identifiers in different systems.
- Not all employees belong in all data sets.
- Identifiers may change over time
Prof. Vijay K S Bapuji B-Schools, Davangere

27. Ethics of Measurement and Evaluation
- Sensitive information – Confidentiality – Using employee ID can safeguard –
“hashing” of identifiers, unique and reproducible but does not give
information to prying eyes. Secure and encrypted channels to safeguard the
information.
- Justification to some decision – by knowledge and techniques, which may
affect their life.
- Presence of wisdom and kindness in your process – HR analytics should
provide toolkit to make tough decision
Prof. Vijay K S Bapuji B-Schools, Davangere

28. Ethics of Measurement and Evaluation
- Seeking the help of the stakeholders and compliance officers regarding
understanding on “What data are off limits for making decision?” Example-
Pharmaceutical companies giving continuous education on the treatment.
- Considering the race, gender and age, as they are very critical in making the
sensitive decision
Prof. Vijay K S Bapuji B-Schools, Davangere

29. Human Capital Analytics Continuum
Anecdotes / Reports
Scorecards & Dash Boards
Benchmarks
Correlations
Regression and Causation
Optimization
Prof. Vijay K S Bapuji B-Schools, Davangere

30. Thank You
Prof. Vijay K S Bapuji B-Schools, Davangere