Engineering business 6
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LW06BuildingaPeopleAnalyticsStrategypart1.pptxMA in People Management and Development
Building a People Analytics Strategy and constructing a Framework of Measures – Part One
HRM 4412
Learning Week 06
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LEARNING REVIEW of Week 5
What is the difference between “analysis” of data and “Visualisation”?
What do you understand by “GESTALT” psychology?
What are some ways we can mislead people by the way we present data and
its analysis?
What is the difference between “a dashboard” and “storytelling”?
What make a “successful story” in presenting a set of data?
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The Job Description of the HR Analytics Manager
The core purpose of this role is likely to be:
Prepare a HR Analytics Strategy for the department which will:
provide a regular monthly, quarterly and annual reporting schedule
of metrics and analysis, chosen to add value to stakeholder groups in helping
them be more effective
define and publicise a process for conducting investigatory projects
define a roadmap for the department to develop its expertise and contribution
over time
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INPUTS:
Business and HR Strategies/Plans/Goals
Daily updated data from HRIS
Inputs from HR “Centres of Excellence”
Survey and External benchmark data
Data from Other Departments
Awareness of Problems in the organisation
THE HR ANALYTICS TEAM
OUTPUTS:
Annual Strategic Direction Plan
Regular Reports and analysis
Stakeholder communications
Results of Investigations
“Prescriptive and Predictive Data”
The work of the HR Analytics Team
HR Reporting and HR Analytics
REPORTING
Preparing reports and presenting data
on a regular basis of the metrics we have
chosen, against targets where they exist
ANALYTICS
Turning data into information and knowledge;
i.e analysing the data in the report and summarising
what we learn from it
b) Conducting specific evidence-based projects on
an HR issue or business issue that is dependent on
people
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“ROME was not built in a day”
It takes time and experience
to grow expertise in HR
Analytics.
Stages of Maturity of an HR Analytics Group
Descriptive
2
Operational
1
Predictive
4
Prescriptive
5
Diagnostic
3
People Analytics > Adding Value through Insight
Workforce Reporting > Providing Information
(this expands the first stage in the previous slide into two stages)
Copyright | Source: Workforce Dimensions Limited
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Descriptive
2
Operational
1
Predictive
4
Prescriptive
5
“This is What Happened”
Diagnostic
3
“Sets of numbers”
Level
Characteristics
Stages of Maturity for HR Metrics and Analytics – Stage 1
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Reactive to ad hoc requests from colleagues
Data often presented in raw form with analysis left to the person requesting
Hard data only – mostly taken from HRIS with minimum summarisation
Data sources not coordinated or linked
Adapted from,| Source: Workforce Dimensions Limited
Descriptive
2
Operational
1
Predictive
4
Prescriptive
5
“This is What Happened”
Diagnostic
3
“Sets of numbers”
Level
Characteristics
Stages of Maturity for HR Metrics and Analytics – Stage 2
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Regular and Structured reports, adapted for different stakeholders
Summaries and Trends; intelligent analysis
Metrics chosen by deliberate strategy; hard and soft; combinations as appropriate
Responsibility and ownership for data sources is clear
Reactive to ad hoc requests from colleagues
Data often presented in raw form with analysis left to the person requesting
Hard data only – mostly taken from HRIS with minimum summarisation
Data sources not coordinated or linked
Adapted from | Source: Workforce Dimensions Limited
Descriptive
2
Operational
1
Predictive
4
Prescriptive
5
“This is What Happened”
Diagnostic
3
“Sets of numbers”
Level
Characteristics
Stages of Maturity for HR Metrics and Analytics – Stage 3
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Regular and Structured reports, adapted for different stakeholders
Summaries and Trends; intelligent analysis
Metrics chosen by deliberate strategy; hard and soft
Responsibility and ownership for data sources is clear
Reactive to ad hoc requests from colleagues
Data often presented in raw form with analysis left to the person requesting
Hard data only – mostly taken from HRIS with minimum summarisation
Data sources not coordinated or linked
“This is Why it Happened”
Connections are made between metrics, both within and beyond HR
Proactive initiatives, e.g Measuring and monitoring the Effectiveness of HR Processes
Regular discussions with line managers lead to diagnostic projects
Ability to design diagnostic instruments
Expertise in root cause analysis
Adapted from | Source: Workforce Dimensions Limited
Descriptive
2
Operational
1
Predictive
4
Prescriptive
5
“This is What Happened”
Diagnostic
3
“Sets of numbers”
Level
Characteristics
Stages of Maturity for HR Metrics and Analytics – Stage 4
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Regular and Structured reports, adapted for different stakeholders
Summaries and Trends; intelligent analysis
Metrics chosen by deliberate strategy; hard and soft
Responsibility and ownership for data sources is clear
Reactive to ad hoc requests from colleagues
Data often presented in raw form with analysis left to the person requesting
Hard data only – mostly taken from HRIS with minimum summarisation
Data sources not coordinated or linked
“This is Why it Happened”
Connections are made between metrics, both within and beyond HR
Proactive initiatives, e.g Measuring and monitoring the Effectiveness of HR Processes
Regular discussions with line managers lead to diagnostic projects
Ability to design diagnostic instruments
Expertise in root cause analysis
“This Will Happen Next”
Focused Investigation of Correlations and Interdependencies
Hypothesis Testing
Building a library of projects completed
Connecting regular trends and projects to forecast what is likely to happen next
Ability to do accurate predictions re financial effects of forecasts
Adapted from, | Source: Workforce Dimensions Limited
Descriptive
2
Operational
1
Predictive
4
Prescriptive
5
“This is What Happened”
Diagnostic
3
“Sets of numbers”
Level
Characteristics
Stages of Maturity for HR Metrics and Analytics – Stage 5
12
Adapted from, | Source: Workforce Dimensions Limited
Regular and Structured reports, adapted for different stakeholders
Summaries and Trends; intelligent analysis
Metrics chosen by deliberate strategy; hard and soft
Responsibility and ownership for data sources is clear
Reactive to ad hoc requests from colleagues
Data often presented in raw form with analysis left to the person requesting
Hard data only – mostly taken from HRIS with minimum summarisation
Data sources not coordinated or linked
“This is Why it Happened”
Connections are made between metrics, both within and beyond HR
Proactive initiatives, e.g Measuring and monitoring the Effectiveness of HR Processes
Regular discussions with line managers lead to diagnostic projects
Ability to design diagnostic instruments
Expertise in root cause analysis
“This Will Happen Next”
Focused Investigation of Correlations and Interdependencies
Hypothesis Testing
Building a library of projects completed
Connecting regular trends and projects to forecast what is likely to happen next
Ability to do accurate predictions re financial effects of forecasts
“This is What we
Should Do”
Practical Intervention Strategies
Action Planning in Partnership with Business Managers
Business Impact and ROI Assessments leading to continuation/cancellation of initiatives
Enablement Technology for Scenario Testing, What If Analysis, and Artificial Intelligence
Stages of Maturity - progression
Descriptive
2
Operational
1
Predictive
4
Prescriptive
5
Diagnostic
3
In practice we start by progressing from Stage 1 to 2.
We may start on Stage 3 simultaneously with Stage 2.
After building up experience we can progress to Predictive and Prescriptive
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Adapted from, | Source: Workforce Dimensions Limited
What do we mean by a
“People Analytics Strategy”?
The word “Strategy” is greatly overused!
A STRATEGY is about making choices in order to focus
on those that will bring the most benefit or
help the organisation take the right actions
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In practice it is a document that guides what an HR Analytics
department will do and explains that to others
– see the last slide for the contents of the document
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How Do We Build a “Strategy”?
We have to ask a lot of questions! ( Remember – a core skill..)
What kinds of questions do we need to ask and of whom?
We need to check out the foundations on which we are building. Where are we NOW?
What questions do we need to ask about the organisation before we even start?
We answer this one in Slides 18/19
What specialised knowledge and skills does the unit need?
See LW02 Slides 10-17. We do not expect ALL skills in ALL team members – need to be sure
We have them all IN THE UNIT
If we have a specialised department do we need to train other HR professionals?
Yes! They need to understand what the specialist group is capable of and how they
can use the expertise in HR Analytics to help them in their own job
Some Questions to Ask (1)
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HR is constantly being told “to link to the Business”. How will we do that?
We will discuss this choice in Part Two next week
There are hundreds of metrics that we could report on. How will we choose the right ones?
We will discuss this also in Part Two next week
How will we report and communicate to different stakeholders, and how frequently?
We looked at this in LW 05 - see later slides this week also.
What process will we use to set up a specific Analytics project?
We will devote a whole lecture to this subject
Some Questions to Ask (2)
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Should we belong to any benchmarking groups? What kinds of metrics would we like to
benchmark?
As per our comments on LW04, we need to take care that we will get good value for spending
time and money on metrics that are usefully comparable
Should the leader of our HR Analytics be put forward to belong to cross organisational
groups such as IT strategy, business planning, or business performance management?
It will be of great advantage to the Analytics Group to belong to these in terms of
connection to the business priorities
Do we need any specialised software of our own?
We will be able to use excel for most things. We may benefit from some additional
‘presentational tools” and also some “Artificial Intelligence” tools.
Some Questions to Ask (3)
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The Foundation on which we build – from what
base do we build?
What we should check find out before we start building an Analytics Strategy
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What kind of HR Information System(s) exist? How comprehensive are they? How old are they?
What data do they hold? What is the typical lag time in updating a record?
What other specialised Software is used and who owns the data from it?
What kind of soft data is collected? How often? How is it analysed and by whom? Where is it kept? Which outsourced firms do we use and what are their contracts?
What is the mindset and current level of knowledge/skills in the HR department on the use of metrics?
What kinds of existing reports are produced and how are they communicated?
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The Foundation on which we build – from what
base do we build? (2)
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Are there any specialist software for reporting/analytics in use?
What is the strength of buy-in to HR analytics from senior management? Do they
see it as an important contribution to better business decisions?
What is the attitude of the IT department? Cooperative or competitive?
What is the culture of the organisation in respect of “evidence-based” decisions? Or do managers typically take an “intuitive” approach?
What kinds of connections does the HR department make to “the business”: its strategies, problems, and challenges?
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28/10/2021
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HR ANALYTICS
DEPARTMENT
SENIOR
MANAGEMENT
EXTERNAL
PEOPLE
“What stakeholders need...”
LINE (Operational)
MANAGERS
HR
DEPARTMENT
EMPLOYEES
(investors, shareholders,
government, industry bodies)
Confidence in good management
So (most) focus on “good numbers” only
And on “headlines”
We do not show trends if they work against us
Mode: written annual report
We are selectiv,e choosing those which are
Important for various reasons, such as KPI’s
We tell the truth as clearly as possible
We enable Internal benchmarking
We convert data as far “up the pyramid” as we can
Mode: regular reports; maybe monthly/quarterly
presentations
Feedback on surveys usually summarised
Mode: internal publication; team meetings
Regular monitoring and trend
analysis of chosen metrics
Mode – monthly meetings looking
at relevant data and planning actions
Detailed discussions with the owners of
the data measurement
Regular reporting on key metrics
Mode: reports and meetings
Workforce Issues
Ongoing
Ongoing
Stakeholders in the People Analytics Strategy
Ongoing
HR Process Effectiveness
Ongoing
SHAREHOLDERS/OWNERS/PARENT COMPANIES - have their own interests. They are concerned we are acting legally and are interested in anything that might affect reputation. Normally we communicate to shareholders through an annual report and there is no legal requirement to include any people related data.. For this group we focus on “good news” by choice. And any metrics we publish are usually consolidated for the whole organisation. Note if our “owner” is the public sector there may be data required for compliance or comparisons and “parent companies” may demand more detailed data.
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TYPICAL METRICS OF INTEREST TO THIS GROUP
Gender and Diversity data
Reputational data such as # employees doing community work; # apprentices
Positive data and trends
Big Numbers
Workforce Issues
Ongoing
Ongoing
Stakeholders in the People Analytics Strategy
Ongoing
HR Process Effectiveness
Ongoing
SENIOR MANAGEMENT - need good and bad news. They are interested in the overview, in top level issues like succession planning; in metrics applied to business strategies and goals; in problem areas while they are problems; in reputational areas such as court cases. They like to see “internal benchmark” tables
on metrics of particular interest
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TYPICAL METRICS OF INTEREST TO THIS GROUP
inter departmental comparisons for eg labour turnover, engagement
talent management data (see later lecture)
KPI data
Employment Court cases
Costed metrics and trends (see later lecture)
Selected external benchmarks (eg pay levels)
Workforce Issues
Ongoing
Ongoing
Stakeholders in the People Analytics Strategy
Ongoing
HR Process Effectiveness
Ongoing
OPERATIONAL MANAGERS – are only interested in their own
department. They want data on labour turnover, absenteeism,
skills gaps, training, engagement, vacancy progress, bonus schemes. HR BUSINESS PARTNERS working with them would want the same sets of information
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TYPICAL METRICS OF INTEREST TO THIS GROUP
departmental data as above
Workforce Issues
Ongoing
Ongoing
Stakeholders in the People Analytics Strategy
Ongoing
HR Process Effectiveness
Ongoing
HR EXECUTIVE - would have access to all the metrics. Specifically they want metrics relating to the HR Strategy/Plans and Process improvement projects.
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TYPICAL METRICS OF INTEREST TO THIS GROUP
all are of interest, including diagnostic projects
uniquely metrics relating to HR processes, such as appraisals, grievances,
specific training, recruitment
Workforce Issues
Ongoing
Ongoing
Stakeholders in the People Analytics Strategy
Ongoing
HR Process Effectiveness
Ongoing
EMPLOYEES - we use our HR metrics for occasional feedback on surveys, either on the intranet or through meetings. The organisation may share other business data through strategic briefings.
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TYPICAL METRICS OF INTEREST TO THIS GROUP
Opinion surveys
Culture surveys
Engagement surveys
Selected benchmark data
Take up of employee benefits
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People Analytics Effectiveness
People Analytics Effectiveness
From: People Analytics Effectiveness, Peeters T, Paauwe, J, Van de Voorde, K, Journal of
Organizational Effectiveness: People and Performance Vol. 7 No. 2, 2020 pp. 203-219
ENABLERS
DELIVERIES
GOVERNANCE
(Management)
STAKEHOLDER
MANAGEMENT
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Thank You – see you tomorrow!
