Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Workforce Analytics: How to Measure
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Workforce Data > Workforce Analytics: How to Measure
Big DataWorkforce Data

Workforce Analytics: How to Measure

Melanie Aizer
Melanie Aizer
6 Min Read
Image
SHARE

ImageHaving made your first important decision about what to measure in part one of this blog series, HR ’s next key decision is how to deliver the reporting and analy

ImageHaving made your first important decision about what to measure in part one of this blog series, HR ’s next key decision is how to deliver the reporting and analytics related to the goals you have chosen. This decision is complex, as it involves the technical aspects of IT and data management, as well as, the human elements of decision-making and HR ’s role to support business leaders throughout the organization.

From the technical perspective HR leaders need to:

A. Determine which data they need and what source they will use.

B. Decide how to extract, organize and store all of their data so it is available for reporting.

C. Choose an analytics solution to generate reports, dashboards and run ad-hoc queries.

More Read

Decision Management: Business Intelligence’s Missing Piece
How Big Data And Education Can Work Together To Help Students Thrive
Essential Branding Guidelines For Aspiring Data Scientists
Do you believe in Magic (Quadrants)?
“In the following Edge original essay, Taleb continues his examination of Black Swans, the highly…”

D. Create a process that allows the right business leaders to view the information they need to make better people decisions.

All of the four components listed depend upon each other and it is the interaction between these components that creates the overall value of the final solution.

In order to create the right type of interaction between the four components, HR needs to focus on component C; choose an analytic solution to generate reports, dashboards and run ad-hoc queries. Traditional analytic technologies require a single source of data, such as a data warehouse, and staff specifically trained to use the software, in order to produce reports, etc. Modern workforce analytics applications have been designed to remove this barrier, allowing organizations to gain insight from their data quickly, and without needing to invest in additional learning or headcount to build the reports, dashboards, etc. The additional advantage of this type of application is that these solutions will import data from many sources, including sources outside of the organization. This removes the need to go through a complex and costly data integration project prior to generating workforce analytics.

The analytics solution you choose should also handle the sharing and security of your HR reporting. Although spreadsheets may seem an attractive tool, as they are low cost, this solution quickly becomes a roadblock to delivering value. Spreadsheets are not designed for collaborative decision-making and the value of the insights they generate, quickly get locked into the tool, and/or your costs start to increase as you need to hire more people to keep up with the demand for output.

The 2013 Visier Survey of Employers highlighted that those HR organizations who use spreadsheets as their workforce analytics tool are four times more dissatisfied, than those who are using a purpose-built tool.

The experience of organizations over the past few years have helped to definitively answer the question about which workforce analytics solution to use.

So many workforce analytics projects have become bogged down in the data management process that selecting a tool, which avoids the need for a central data repository, has become the best way to go. The high rate of satisfaction from dedicated workforce analytics solutions indicates that these are the types of tools that best serve the needs of executive and HR leaders. This is especially true when you include the fact that purposebuilt solutions reduce HR ’s reliance on IT support and, therefore, remove another common barrier to accessing HR data.

As the field of workforce analytics has matured, it has moved from a process whereby existing technologies are co-opted to serve new needs and become an area where the big barriers to success have been identified.

Through this process, new solutions have been created, which remove these barriers making it quicker, cheaper, and easier for HR organizations to be successful. When it comes to making the important decision of which workforce analytics solution to use, HR organizations need to meet the following criteria:

1. The solution should not need a central repository and complex extract, transfer and load (ETL ) process.

2. The solution should handle data that is internal to the organization AND data from sources external to the organization.

3. The solution should handle all types of reporting including dashboards, standard reports and ad-hoc reporting.

4. The solution should both produce and share the reporting, maintaining data security across the whole process.

5. The solution should be owned and run by HR with limited or no requirement for IT support.

The choice of technology for your workforce analytics program will be the single largest investment you make in this area. It is not a decision you can afford to get wrong. Making your decision to meet the criteria listed above is a sure way to achieve the highest levels of satisfaction demonstrated by those who are working with a dedicated workforce analytics application.

image: workforce/shutterstock

 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai and satelite technology
How Machine Learning Improves Satellite Object Tracking
Exclusive Machine Learning
Diverse Research Datasets
The 5 Best Platforms Offering the Most Diverse Research Datasets in 2026
Big Data Exclusive
macro intelligence and ai
How Permutable AI is Advancing Macro Intelligence for Complex Global Markets
Artificial Intelligence Exclusive
warehouse accidents
Data Analytics and the Future of Warehouse Safety
Analytics Commentary Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Image
AnalyticsBest PracticesBig DataCloud ComputingCollaborative DataCRMData ManagementData MiningData VisualizationExclusiveITSocial DataSocial Media AnalyticsSoftwareWorkforce Analytics

B2B Software Startups: The SaaS Platform Dilemma

8 Min Read
Image
AnalyticsCloud ComputingCommentaryData WarehousingExclusiveRisk Management

Building Information Technology Liquidity

4 Min Read

Big Social Data Can Unlock the Power of Engaged Viewers

9 Min Read
big data and AI
Big Data

What’s Happening with AI & Big Data in August 2022

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?