A systematic analysis of Talent Analytics position descriptions aimed at revealing the backgrounds, skills, competencies and responsibilities most central to the role and how some requisitions stand apart from the crowd.
Predictive Analytics for HR: A Primer to Get Started on your HR Analytics Jou...Dr Susan Entwisle
Traditionally, HR teams have made decisions on hiring, retaining, assigning and developing employees using intuition, experience, and basic descriptive statistical reports. Predictive analytics complements and extends on these approaches by enabling HR teams to make proactive ‘forward-looking’ data-driven decisions on its people across the employee lifecycle. Examples of this include gaining insights into the drivers and predicting who are our top performers, what employees are at risk of leaving, is our training program effective, and more. This capability can support HR teams to better align HR programs with strategic business goals.
This presentation outlines the limitations with current approaches and explain what predictive analytics is so business users can understand the business opportunity and problems it can be applied to. A number of case studies on its use across the employee lifecycle are described and guidance given on how to get started on your HR predictive analytics journey.
Diving into the space of HR automation and understanding the role of Analytics and Bots in prioritizing and streamlining HR functions with efficiency to the uplift and upkeep the Business Profitability as a whole.
HR Analytics and its Impact on Organizational Excellenceijtsrd
The aim of this paper was to find out what HR analytics holds the promise of both elevating the status of the HR profession and serving as a source of competitive advantage for many organizations that have put it to good use for industry that can go a long way to make India for organizational excellence. The realization of this promise hinges on our individual and collective ability to master the art and the science of HR analytics. That, in turn, will happen much more quickly if we can achieve clarity even consensus on a number of issues where neither clarity nor consensus currently exists. The increasing globalization of the job market combined with an ever increasing shortage of skillful staffs and advances in technology have resulted in large scale changes to the recruitment practices throughout the world through the use of HR Analytics. This paper aims to find out the benefits, importance and impacts of HR analytics and this study of the current state of HR analytics depends heavily on data integration which emphases on overarching business disciplines and centralizing data. Ms. Anjali T V "HR Analytics and its Impact on Organizational Excellence" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd19076.pdf Direct URL: http://www.ijtsrd.com/management/hrm-and-retail-business/19076/hr-analytics-and-its-impact-on-organizational-excellence/ms-anjali-t-v
Predictive Analytics for HR: A Primer to Get Started on your HR Analytics Jou...Dr Susan Entwisle
Traditionally, HR teams have made decisions on hiring, retaining, assigning and developing employees using intuition, experience, and basic descriptive statistical reports. Predictive analytics complements and extends on these approaches by enabling HR teams to make proactive ‘forward-looking’ data-driven decisions on its people across the employee lifecycle. Examples of this include gaining insights into the drivers and predicting who are our top performers, what employees are at risk of leaving, is our training program effective, and more. This capability can support HR teams to better align HR programs with strategic business goals.
This presentation outlines the limitations with current approaches and explain what predictive analytics is so business users can understand the business opportunity and problems it can be applied to. A number of case studies on its use across the employee lifecycle are described and guidance given on how to get started on your HR predictive analytics journey.
Diving into the space of HR automation and understanding the role of Analytics and Bots in prioritizing and streamlining HR functions with efficiency to the uplift and upkeep the Business Profitability as a whole.
HR Analytics and its Impact on Organizational Excellenceijtsrd
The aim of this paper was to find out what HR analytics holds the promise of both elevating the status of the HR profession and serving as a source of competitive advantage for many organizations that have put it to good use for industry that can go a long way to make India for organizational excellence. The realization of this promise hinges on our individual and collective ability to master the art and the science of HR analytics. That, in turn, will happen much more quickly if we can achieve clarity even consensus on a number of issues where neither clarity nor consensus currently exists. The increasing globalization of the job market combined with an ever increasing shortage of skillful staffs and advances in technology have resulted in large scale changes to the recruitment practices throughout the world through the use of HR Analytics. This paper aims to find out the benefits, importance and impacts of HR analytics and this study of the current state of HR analytics depends heavily on data integration which emphases on overarching business disciplines and centralizing data. Ms. Anjali T V "HR Analytics and its Impact on Organizational Excellence" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-1 , December 2018, URL: http://www.ijtsrd.com/papers/ijtsrd19076.pdf Direct URL: http://www.ijtsrd.com/management/hrm-and-retail-business/19076/hr-analytics-and-its-impact-on-organizational-excellence/ms-anjali-t-v
Power Up Your HR Data - Part 5: Using Predictive AnalyticsCeridian MarComm
Take your HR data to the next level with Ceridian’s five-part SlideShare training series. You’ll learn today’s top data challenges and discover tools for HR data success. In Level 5, we bring everything together and focus on how HR professionals can use predictive analytics to help their organization make smart business decisions.
For decades, industries and companies around the world have known talent can serve as one of the best competitive advantages. It is also clear identifying the right talent for your business is vital because not everyone is going to be a perfect fit.
Ibm smarter workforce Unlock the people equation using workforce analytics to...Pauline Mura
Enabling the workforce to drive the business
IBM Talent and Change services and Smarter Workforce
solutions combine market-leading talent management
and social collaboration tools with the power of workforce
science and advanced analytics. They enable
organizations to attract, engage and grow topperforming
talent, create an engaging social and
collaborative culture, and connect the right people to get
work done. We help organizations build an impassioned
and engaged workforce and deeper client relationships
leading to measurable business outcomes.
HR ca not operate in traditional ways any more
The technology driven data management is a necessity .
HR analytic is pretty useful in driving crucial decisions.about work force
especially in IT sector.
Here are few tips.If you liked least you could do is to share
also read my latest book in Amazon
Everyone is a data scientist today, but that is impossible. How do you spot the real data scientist from the fake? Some people just lie. Don't be fooled this presentation will help find the fools
Case Study: Building a Culture of Analytics in HR at MicronHuman Capital Media
Supporting 30,000 employees worldwide, the Workforce Information team at Micron Technology Inc. has a clear vision: When someone thinks of analytics at Micron, they want that person to think of HR. For most companies today, that seems a tall order to fulfill. And with Micron’s highly technical staff of more than 10,000 engineers, it was a particularly bold aspiration. Over the past two years Micron’s Workforce Information team, working within the HR department, has made significant progress in achieving that goal.
Since implementing Visier Workforce Analytics in late 2013, Micron’s Workforce Information team has rolled out self-service analytics to more than 150 HR leaders and business partners and more than 800 business-area managers globally. As a result, Micron is uncovering new workforce insights that can be used to make decisions that are closely linked to business performance.
For more than 30 years, Micron’s teams of dreamers, visionaries and scientists have redefined innovation — designing and building some of the world’s most advanced memory and semiconductor technologies.
Join 2014 Brandon Hall Excellence in Technology award-winner Tim Long, director of Workforce Information at Micron, as he discusses his team’s journey in enabling HR to “demand evidence and think critically.”
Long will share his team’s experience:
Developing global standards for workforce data.
Implementing a highly scalable solution for workforce analytics on demand.
Fostering a data-driven culture within HR.
Leveraging workforce analytics in HR processes, such as compensation reviews..
Speaker:
Tim Long - Director of Workforce Information Micron Technology INC.
As the director of Workforce Information at Micron Technology Inc., Tim Long leads a team of business intelligence engineers, analysts and data scientists to create insight from workforce data. Long’s team supports Micron’s strategic commitment to data-driven decision making helping to inform people decisions with sound analytics. Long holds a bachelor’s degree in mechanical engineering from the University of Wyoming and a master’s degree in business analytics from New York University’s Stern School of Business
A presentation on Talent Analytics or HR Analytics. This presentation gives various tools and parameters involved in HR Analytics and their Application.
Hr analytics, insights and implementation forum apac 2016Jayesh Menon
How to break resistance, and get HR to embrace meaningful data analytics. Removing the phobia of data and making HR business partners true champions of translating data into insights. How visualizations help in storytelling.
Human Capital Management's Employee Disconnect. A Global SnapshotADP Marketing
Gain insight into the wide disparity in perceptions among employees, HR leaders and senior management on vital HCM issues and how it may impact employers’ ability to deliver on corporate strategies.
Power Up Your HR Data - Part 5: Using Predictive AnalyticsCeridian MarComm
Take your HR data to the next level with Ceridian’s five-part SlideShare training series. You’ll learn today’s top data challenges and discover tools for HR data success. In Level 5, we bring everything together and focus on how HR professionals can use predictive analytics to help their organization make smart business decisions.
For decades, industries and companies around the world have known talent can serve as one of the best competitive advantages. It is also clear identifying the right talent for your business is vital because not everyone is going to be a perfect fit.
Ibm smarter workforce Unlock the people equation using workforce analytics to...Pauline Mura
Enabling the workforce to drive the business
IBM Talent and Change services and Smarter Workforce
solutions combine market-leading talent management
and social collaboration tools with the power of workforce
science and advanced analytics. They enable
organizations to attract, engage and grow topperforming
talent, create an engaging social and
collaborative culture, and connect the right people to get
work done. We help organizations build an impassioned
and engaged workforce and deeper client relationships
leading to measurable business outcomes.
HR ca not operate in traditional ways any more
The technology driven data management is a necessity .
HR analytic is pretty useful in driving crucial decisions.about work force
especially in IT sector.
Here are few tips.If you liked least you could do is to share
also read my latest book in Amazon
Everyone is a data scientist today, but that is impossible. How do you spot the real data scientist from the fake? Some people just lie. Don't be fooled this presentation will help find the fools
Case Study: Building a Culture of Analytics in HR at MicronHuman Capital Media
Supporting 30,000 employees worldwide, the Workforce Information team at Micron Technology Inc. has a clear vision: When someone thinks of analytics at Micron, they want that person to think of HR. For most companies today, that seems a tall order to fulfill. And with Micron’s highly technical staff of more than 10,000 engineers, it was a particularly bold aspiration. Over the past two years Micron’s Workforce Information team, working within the HR department, has made significant progress in achieving that goal.
Since implementing Visier Workforce Analytics in late 2013, Micron’s Workforce Information team has rolled out self-service analytics to more than 150 HR leaders and business partners and more than 800 business-area managers globally. As a result, Micron is uncovering new workforce insights that can be used to make decisions that are closely linked to business performance.
For more than 30 years, Micron’s teams of dreamers, visionaries and scientists have redefined innovation — designing and building some of the world’s most advanced memory and semiconductor technologies.
Join 2014 Brandon Hall Excellence in Technology award-winner Tim Long, director of Workforce Information at Micron, as he discusses his team’s journey in enabling HR to “demand evidence and think critically.”
Long will share his team’s experience:
Developing global standards for workforce data.
Implementing a highly scalable solution for workforce analytics on demand.
Fostering a data-driven culture within HR.
Leveraging workforce analytics in HR processes, such as compensation reviews..
Speaker:
Tim Long - Director of Workforce Information Micron Technology INC.
As the director of Workforce Information at Micron Technology Inc., Tim Long leads a team of business intelligence engineers, analysts and data scientists to create insight from workforce data. Long’s team supports Micron’s strategic commitment to data-driven decision making helping to inform people decisions with sound analytics. Long holds a bachelor’s degree in mechanical engineering from the University of Wyoming and a master’s degree in business analytics from New York University’s Stern School of Business
A presentation on Talent Analytics or HR Analytics. This presentation gives various tools and parameters involved in HR Analytics and their Application.
Hr analytics, insights and implementation forum apac 2016Jayesh Menon
How to break resistance, and get HR to embrace meaningful data analytics. Removing the phobia of data and making HR business partners true champions of translating data into insights. How visualizations help in storytelling.
Human Capital Management's Employee Disconnect. A Global SnapshotADP Marketing
Gain insight into the wide disparity in perceptions among employees, HR leaders and senior management on vital HCM issues and how it may impact employers’ ability to deliver on corporate strategies.
Analytics is the discovery, interpretation & communication of meaningful patterns in data.
HR analytics is a methodology for creating insights on how investments in human capital assets contribute to the success of four principal outcomes.
HR analytics focuses primarily on the HR function and is not – as is largely believed.
The terms HR Analytics, People Analytics, Workforce Analytics are often used interchangeably.
#HR #HRAnalytics #TypesofHR #Analytics #Sourcing #Workforce #PeopleAnalytics #SocialNetworkAnalytics #TimetoHire
Navigating the Data Analyst Job Market in 2023- A Comprehensive GuideOptnation
In 2023, the job market for data analysts is experiencing unprecedented growth, fueled by the increasing reliance on data-driven decision-making across various industries. Data analysts play a crucial role in extracting valuable insights from vast amounts of data, aiding businesses in making informed choices. If you're considering a career as a data analyst or looking for entry-level opportunities.Visit at: https://www.optnation.com/blog/navigating-the-data-analyst-job-market-in-2023-a-comprehensive-guide/
A profession in data analysis could provide you with significant influence over an organization's expansion and success. A data analysis role involves much more than just crunching numbers. Analysts examine data to find ways to use it to address issues, get important understanding of a company's clientele, and increase revenue.
Data science and data analytics professionals enable organizations to utilize the potential of predictive analytics to make informed decisions & help in transforming analytics maturity model of the organization.
Get your Insider’s Guide to Workforce Analytics. Learn the definitions of key terms, see examples of metrics and analytics, and discover how to measure your company’s workforce analytics maturity. Plus, learn about common approaches to workforce analytics and hear case studies of analytics in action.
Chapter 3: Data Analysis or Interpretation of DataEmilyDagami
This is for Inquiries, Investigation, and Immersion Senior High School grade 12 learners and teachers: Chapter 3: Data Analysis or Interpretation of Data. Data analysis is the process of cleaning, analyzing, interpreting, and visualizing data using various techniques and business intelligence tools. Data analysis tools help you discover relevant insights that lead to smarter and more effective decision-making. "It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts," Sherlock Holme's proclaims in Sir Arthur Conan Doyle's A Scandal in Bohemia.
This idea lies at the root of data analysis. When we can extract meaning from data, it empowers us to make better decisions. And we’re living in a time when we have more data than ever at our fingertips.
An Example Of Job Analysis Report On Apple, Inc.
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An efficient data science team is crucial for deriving value from the humongous data a business collect. Learn how the data science team can help in this regard.
Workforce Analytics in India - A state-of-evolution report 2018Nitin Dheer
This study is based on a survey conducted by Inqubex Consulting (www.inqubex.com) where we asked HR leaders on their perception of importance of Workforce Analytics as well as the current state of deployment of measurement/ analytics in their HR functions
Workforce Insight And Change Making Comms V4 AaAladam
These slides provide an overview of how to do Workforce Planning & Analytics so leaders can make better, more informed decisions. Hope you like it!
Similar to Making the Cut: A Review of Open Talent Analytics Job Postings (20)
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Show drafts
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
2. Q2 2018 7
What educational and work experience do talent
analytics professionals have?
The roles we examined are typically midcareer roles requiring
at least three to eight years of relevant experience. Since the
entire field of talent analytics is barely as old, requiring this
amount of experience in the field would mean competing
for the small number of self-taught people who got in on
the ground floor and played a role in developing it. And
while organizations may want to fill a program management
position with one of these premium pioneers, those that
need rank-and-file analytics doers must think more flexibly
about other experiences relevant enough to serve as good
career precursors.
Most position descriptions we reviewed show an open-
mindedness toward other experiences (see Figure 1) but
failed to list specific positions that would make relevant
precursors. Adding these career precursors helps people
searching for those other positions by name discover your
position, immediately see themselves in the role and know
their applications are welcome (see Figure 2).
Source: CEB analysis.
Figure 2: Example of Listing Experiences
to Attract More Applicants
Original Text
Suggested Addition
Five or more years working
in an analytics, research or data
science environment; two or more
years leading a team of analytics
professionals; experience working
with progressive analytics
(e.g., R, Python, JMP) and data
visualization (e.g., Tableau)
tools to drive actionable
business insights
Data engineers, business
intelligence engineers, Python
developers and data scientists
working in R, Python or Julia in
marketing, sales, finance, supply
chain or IT are encouraged
to apply.
Figure 1: Terms Used in Required
Qualifications Section of Talent Analytics
Job Postings
Source: CEB analysis.
Educational qualifications are even more intriguing than
prior experience because they reveal hiring managers’
beliefs about the relative importance of formal training in
4. Q2 2018 9
Source: CEB analysis.
Figure 3: Terms Used in
Responsibilities Section of Talent
Analytics Job Postings
What are talent analytics professionals'
responsibilities?
The responsibilities associated with talent analytics positions
span the full spectrum of the analytics value chain from
data acquisition and data wrangling to visualization and
oral presentation to stakeholders (see Figure 3). Too
often, the complete value chain is part of a single position
description. Organizations large enough to have a people
analytics team rather than a people analytics person should
look to specialize roles within the team. Finding people who
excel at the full pipeline is a rarity, and using them prevents
the organization from developing scalable processes
run by teams.
We also caution organizations against equating analytics
with reporting or technology. This confusion stems from the
newness of the people analytics and talent analytics fields.
The reporting layer and the technology layer are being built
in parallel to analytics capabilities, but these skill sets and
ambitions are typically not found in the same person.
In analytics job descriptions, the lists of duties and
responsibilities varies widely and often strays far into other
areas of expertise. See how these responsibilities fall into
three categories: core to analytics, adjacent to analytics and
outside of analytics.
Core Analytics Responsibilities
• Translate business questions/needs into appropriate
analytical problems, do high-quality analysis and turn
outputs into concrete, actionable business insights.
• Deliver workforce analytics that answer key strategic
questions as identified by business leadership.
• Conduct both qualitative and quantitative statistical
analyses (this includes, but is not limited to,
data screening and imputation techniques, chi-
square tests, t-tests, correlations, ANOVA, simple
and multiple regression, relative weight analysis,
logistic regression, discriminant analysis, MANOVA,
exploratory and confirmatory factor analysis, cluster
analysis, path analysis, psychometric assessment, test
development and validation).
• Storyline, create and deliver visually compelling
presentations used to educate, inform and influence.
• Think innovatively, and challenge the status quo.
Responsibilities Adjacent to Analytics
• Develop and implement dashboards and reporting
solutions.
• Quickly respond to various data requests
from SVPs and HR leaders.
• Train internal clients on self-service reporting tools
and how to interpret data.
• Lead design, development and delivery of leadership
training to guide the use of people information.
• Drive data quality and influence the development
of people processes and technology to allow for
effective data collection.
• Maintain data integrity, and observe data for
inconsistencies.
• Gather qualitative data through focus groups and
interviews.
• Assist in designing, building, distributing and
analyzing ad hoc surveys to meet business needs.
Probably Someone Else’s Jobs
• Create mobile apps for company executives.
• Build robust and scalable data integration
(ETL) pipelines.
• Manage internal reporting platforms including
troubleshooting, development and access security.
• Explore and recommend emerging technologies and
techniques to support and enhance BI landscape
components.
• Compose technical documents in support of the
development, implementation and maintenance
of BI systems.
• Develop and maintain appropriate benchmarks with
other organizations to include quarterly and annual
performance reporting.
• Evaluate effectiveness of all HR and recruiting
investments and programs.
Source: CEB analysis.
Note: Responsibilities taken verbatim from job descriptions.
6. Q2 2018 11
Source: CEB analysis.
Table 2: Mentions of Software, Methods
and Platforms in Talent Analytics Job Postings
What skills do talent analytics professionals need?
Hiring organizations list a large number of hard and soft skills
in the qualifications and duties sections of analytics position
descriptions. While the verbs in that list (e.g., communicate,
change, translate) largely reveal the soft skills, mentions of
specific software, methods and platforms within the text
reveal the hard skills required.
The word frequencies (see Table 2) illustrate the crossroads
at which the field currently finds itself. A simple interpretation
of this table offers a few insights:
• The large prevalence of Excel represents the historical
norm for data analysis and visualization.
• The BI platforms and analytics software as well as the
languages are ensnared in an all-out brawl pitting the
free, open-source route for analysis and visualization
that requires original programming skills (e.g., R,
Python, JavaScript/D3) against the proprietary route
for accomplishing the same via a graphical user
interface (e.g., Tableau, SAS, Alteryx).
• The organizations looking for Hadoop and other big
data skills are the ones that have collected so much
data on their workforce that traditional storage and
query tools are no longer an option. This segment is
small but growing.
• SQL is the new lowest common denominator to replace
Excel. Getting data into your local environment in order
to do analysis and modeling generally requires a basic
knowledge of SQL.
Programming Languages
SQL 40
R 35
Python 25
Javascript, Java, JS 7
Visual Basic 5
BI Platforms and Analytics Software
Tableau 37
SPSS 13
SAS 10
Alteryx 4
Visier 4
Cognos 3
Matlab 2
Microstrategy 2
Strata 2
Big Data Storage, Access and Manipulation
Hadoop 4
AWS (Amazon Web Services) 3
Impala 2
Spark 2
Hive 2
General Purpose
Excel 50
PowerPoint 22
Outlook 3
SharePoint 2
Visio 2
Enterprise HR Systems
Workday 21
Oracle 9
PeopleSoft 9
SAP 7
Taleo 2
The right mix of hard
skills depends on your
technology infrastructure
and existing investments.
Number of Times Mentioned