1. HR Analytics – Adopting an Agile Framework for Enhanced Adoption & Effectiveness
Brad Markis
MBA Candidate - Ryerson University
INTRODUCTION
Literature Review & Primary Research
CONCLUSIONS
Proposed Model Moving ForwardRESULTS
Figure3. Talent Analytics Maturity Model Figure4. RADAR Model (Agile Analytics)
ABSTRACT
CONTACT
Figure 1. Fitz-Enz Value Ladder Figure 2. Business Partner Model
Brad Markis
Ryerson University
Email: Bmarkis@Ryerson.ca
Phone: 647 710 2268
The purpose of this report was to
explore the current state of analytics
adoption, and the overall paradigm
around it. This paper did an in-depth
literature review, as well as some
primary research with a diverse array
of organizations. This paper focused
on the models used, and on a variety
of organizational sizes.
This paper found that the majority of
firms reviewed, struggled to effective
adopt and maintain effective HR
analytics. Furthermore, the models
proposed by various groups and
individuals, were contradictory, static
in nature, and often defied case
studies from various organizations.
This paper proposed an agile HR
analytics framework, that took into
account the needs of organizations,
as well as the dynamic and rapidly
changing factors that are changing
the ability for organizations to deploy
HR analytics.
The majority of the trouble revolving around the adoption
and effective execution of HR analytics revolves around
technology, path-dependence, and analytical skill
shortages.
Even Fortune 500 firms, known for being innovative,
and leading edge, often had trouble deploying
sophisticated analytical solutions.
The available models and frameworks for HR Analytics
were scarce. Furthermore, the providers of these models,
as well as the models themselves, often conflicted on the
basic premises they used to build out their HR analytics
paradigms.
One disturbing trend, was cases of organizations
deploying analytics, with low effort, and high reward,
while directly contradicting the basic tenants of the
models currently promoted on the market, including
the Business Partner Model, and the Talent Analytics
Maturity Model.
Another trend throughout the research, and interviews
was that HR was often able to set a strategy, but failed to
have a framework or method of tactical execution.
Organizations were actively seeking support on how setup
a blueprint for execution on their HR analytics strategies.
Specifically, what data to collect, what systems to use,
what questions should be pursued, and how to effectively
translate analyzed data into business insights.
Many organizations showed the capability to deploy
analytics, in a swift and low effort model, based on
available data stored in current systems such as the
HRIS and Payroll.
Furthermore, many organizations have propped up to
provided analytics as a service, and help fill gaps in
available data, and analytical talent.
The current models available fail to be dynamic
enough to respond to the emerging analytics as a
service model, as well technology limiting the
amount of analytical talent on the HR team
necessary to deploy HR analytics.
The proposed model in this research was an agile
analytics framework that threw out complex planning,
unnecessary steps, and data hoarding, and instead
focused on swiftly solving business problems with
precise, based on current technology and talent, to
quickly test various hypothesizes.
By incrementally building out analytics quickly,
to solve one business problem at a time,
organizations can ensure that the business
alignment, and an ROI, are built into the
foundation of the analytics program.
Over 50 research pieces were reviewed, and over 20
organizations were interviewed.
The research pieces spanned across academia,
private sector research, and established research
companies.
The interviews were predominately with HR
executives from Fortune 500 firms, though multiple
smaller firms were interviewed to see how solutions,
traditionally targeted at large HR departments, were
being scaled down.
These interviews were performed in my role as
Product Manager at McLean & Company, an HR
Research & Advisory firm.
Three predominate models were identified in the
research review, all of which came from competing
sources. These models showed limited overlap in
terms of content, or paradigm.
HR analytics, for most organizations, compared
to other departmental analytics, are relatively
basic
Even large and innovative organizations are
failing to effectively adopt sophisticated HR
analytics, that align to business goals.
The Current HR analytical models are flawed
Talent and technology gaps are significant
impediments to HR analytics adoption
Agile processes, typically found in IT, but
becoming prevalent in performance management
and succession planning, can also be used in HR
analytics
Agile HR analytics drive results that have impact
at every step, and that are aligned to the business
Analytics have been adopted by many departments,
at many organizations, but HR has been slow to
adopt analytics at the same pace. Organizations that
have HR departments that actively use analytics
have been shown to have higher stock returns,
increased retention, and higher productivity, amongst
many other benefits.
Furthermore, the technology and skills that allow for
analytics to be adopted are becoming to cheaper to
acquire every year, and more abundantly available
from various service providers.
The growing supply of options available drastically
conflict with the current maturity of analytics adopting
and use by organizations globally, and especially
Fortune 500 firms, which should have the bandwidth
and wallet to take on analytics projects.
This paper's primary purpose is to explore the
current state of HR analytics adoption, as well as
the benefits, costs, barriers, and models used to
guide organizations around analytics usage.