HRM ASIA 2016 May 11.0
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Transcript of HRM ASIA 2016 May 11.0
HR SUMMIT 2016 DHEERAJ SHASTRI
The Evolution of
Analytics
Analytics Framework
Taking Leadership
Along
Reporting to
Forecasting
Art Or Science
Bringing different
functions together
SESSION FLOW
JUST THINK AND THIS TRAIN RUNS IN
OPPOSITE DIRECTION
YOUR BRAIN HAS POWER TO CHANGE THE
DIRECTION OF THIS TRAIN
MY CAR IS ALLERGIC TO VANILLA ICECREAM!!
CAR MECHANIC
BACK TO ICECREAM PARLOUR
PUZZLED
COLLECT DATA
CORRELATION
FAILED TO START
Wai
ting
Tim
e Day of Week
CAUSATION SOLUTION
MYSTERY SOLVED
The “moral” of this story is that buying
vanilla ice cream and the car failing to start
are correlated events however; this story
demonstrates that correlation does not
mean causation.
This often is the case in work environment.
HR Analytics Maturity Scale
Initial Chaotic,
adhoc,
individual
heroics
Repeatable Documented,
simple process
Defined Quality Assured,
owned,
operational
Managed Standard
Metrics,
strategic
Optimizing Process /
improvement
What’s my
Headcount?
How do I collect
the data?
Where’s my Headcount
and how is it changing?
Which Spreadsheet do I
use?
What is the quality of
the data?
Who owns the
process?
Is our HR Strategy
working?
How do we compare to
other organizations?
How do we recruit higher
quality talent?
Which processes are driving
employee engagement?
??
COOKING PROCESS
What to cook?
Understanding
Project Scope
PREPARING INGREDIENTS
DATA CLEANING
GETTING THE RIGHT TOOLS
RIGHT ANALYTICAL TOOLS
ADDING THE RIGHT SPICES
RELEVANT INDUSTRY BENCHMARK
INDICATORS: MACROECONOMIC & REGULATORY
REFERENCES : EXTERNAL & INTERNAL
COOKING
CORELATION, REGRESSIONS
IDENTIFY MISSING LINKS
DISH DECORATION
SLIDES, PICTURES, GRAPHS,
COLOR, FONT
SERVING DISH
PRESENTATION : STORY TELLING,
MESSAGE
The Art The Art The
Science
Using data to drive talent decisions requires both art and science:
The ability to ask the right questions, shape the analysis and deliver the findings (the
“art”), in addition to having access to metrics based on high-quality data drawn from
a range of sources (the “science”).
ANALYTICS FRAMEWORK
Reference: Successfactors Webinar
Identify
the Issue
Analyze
the Data
Deliver
the
Findings
STEP 1: ART
Identifying Business Issues for Analytics
• Start With Strategy, Not With Data
• Treat Requestor as “Customers”
• Understand Business & Market
Reference: Successfactors Webinar
STEP 2: SCIENCE
Analyzing Data With “Actionability” in Mind
• Elements of Data Analysis
• Understand What the Metric Tells Us and
What’s Missing
• What level of confidence in the analysis/
data will be acceptable?
Reference: Successfactors Webinar
STEP 3: ART
Delivering the Findings to Drive Action
• Create a Compelling Message
• Less Data, More Story
Reference: Successfactors Webinar
Data Facts Information Appears in
the Report
Provide
Insights to
make
decisions
Research findings
is what managers
already know
DATA RESEARCH TREND OBSERVED
What’s missing? How can we improve?
Analytics Influences across Human Capital
Reference: McKinsey & Company and The Conference Board report
CORRELATION DOES NOT MEAN CAUSUATION
Summary
DATA REPORTING IS NOT ANALYTICS
START WITH AN INTENT AND KNOW END CUSTOMER
CONNECT THE DOTS TO PRESENT A COMPLETE AND COMPELLING STORY
BRINGING DIFFERENT FUNCTONS TOGETHER
Thank you !