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APPLICATIONSOF BUSINESS
INTELLIGENCEIN HUMAN
RESOURCES
By:
Vikramadithya T
Venkateswarlu D
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INTRODUCTION
Business Intelligence (BI) plays a crucial role to achievecompetitive edge over competitors in the challengingeconomy.
BI is rated as the most wanted technology by businessesacross the world. Even in current times of economicdownturn, when IT budgets are being cut, BI is still among thetop of executives priorities.
BI technologies and applications include data management
methods for planning, collecting, storing, and structuring datainto data warehouses and data marts as well as analytical tasksfor querying, reporting, visualizing, generating online activereports, and running advanced analytical techniques forclustering, classification, segmentation, and prediction.
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INTRODUCTION ( CONTD)
Due to advances in technologies and regulatory changesbusinesses are collecting and storing data at an alarming rate.
Companies collect large volumes of data on their employees,
such as salary information, performance reviews, andeducation level. As a result, most organizations face an
information overload. By 2020, the amount of data generated
each year is projected to reach 35 zettabytes (1 zettabyte = 1
billion terabytes, 1 terabyte = 1000 gigabytes).
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INTRODUCTION (CONTD)
Business Intelligence systems are designed to be able to
collect data from various sources, convert the raw data into
useful actionable information or knowledge. Employee data is
generally housed in separate HR systems based on vertical HR
functions, such as benefits, payroll and compensation, leave,training and surveys and/or horizontally across functional
areas. Companies need to identify all internal and external
data sources and then consolidate the data into a HR data
mart. Globilization challenges organizations HR department to
manage workforce diverse in cultures, time zones, expertise,
benefits, and compensations.
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COMPONENTSOFA BUSINESS
INTELLIGENCESYSTEM
BI system consists of a number of component systems that are
interdependent. For the system to function effectively the
components must work in an integrated and coordinated way.
BI components may be broadly classified into the following
four sub-systems :1. Data Management
2. Advanced Analytics
3. Business Performance Management
4. Information Delivery
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DATA MANAGEMENT SUB-SYSTEM
Includes components, relating to Data warehouses, Data
marts, and Online Analytical Processing (OLAP).
Deals with all aspects of managing the development,
implementation and operations of a data warehouse or data
mart including extraction, transformation, cleaning, andloading of data from different sources. The subsystem also
includes meta-data management, security management,
backup and recovery, and data distribution.
OLAP is implemented in a multiuser environment and offers
consistent, quick response, regardless of database size and
complexity.
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ADVANCED ANALYTICS SUB-SYSTEM
Includes analytic functions based on statistics, data mining,
forecasting, predictive modeling, predictive analytics, and
optimization .
Large BI vendors have incorporated comprehensive statistics
packages within their BI software system. IBM has incorporated the SPSS with their BI Cognos system,
and SAS Inc. has developed their BI software with a core
consisting of their celebrated statistical packaged software.
Microsoft has developed XLSTAT, an add-on to Excel for
Statistics and multivariate data analysis.
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BUSINESS PERFORMANCE
MANAGEMENT SUB-SYSTEM
Consists of processes for strategic goals and objectives,performance measurement and mentoring, analyzingperformance and making decisions to improve businessperformance .
Its objectives:1. Ensure supervisors/managers acquire, implement, and applyprinciples necessary to foster high performance in theworkplace.
2. Ensure supervisors/managers conduct meaningful timely
performance appraisals :a. Performance Measurement and Monitoring
b. Analyzing Performance
c. Decision Making and Performance Feedback
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INFORMATION DELIVERY SUB-SYSTEM
Gives the business users the ability to access reports and
continuously monitor organizational performance at enterprise
and lower levels.
According to his or her role as a technocrat, super user,
middle manager, executive manager, or operational user, he orshe will be given role-based rights to access relevant reports
in summary and/or detailed formats.
Depending on an individual's role and responsibility, he or she
is presented with the trends, metrics, at appropriate aggregate
levels with security to block non-privileged items .
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BUSINESS INTELLIGENCE ADOPTIONIN
INDUSTRYAND HUMAN RESOURCES
BI is gaining rapidly in popularity, faster than most
anticipated.
According to a report done in April 2010, it was found that the
BI platforms, analytic applications and performance
management (PM) software revenue surpassed $9.3 billion in2009, a 4.2 percent increase from the 2008 revenue of $8.9
billion .
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WORLDWIDE BI, ANALYTICSAND PERFORMANCE MANAGEMENT REVENUE
ESTIMATESFOR 2009 BY SUB-SEGMENT (MILLIONSOF U.S. DOLLARS)
Sub-system Revenue Estimate Market Share %
BI Platform 5982.4 64.2
CPM Suites 1937.1 20.8
Analytic Applications &
PerformanceManagement
1402.4 15.0
Total 9321.9 100
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MAJOR SOFTWARE ACQUISITIONSINTHERECENTPASTAND PRICE PAID
Vendor Select BI
Acquisitions
Price Paid
SAP Sybase (2010) $ 5.8 BBusiness Objects (2007) $ 6.8 B
Outlook soft (2007) $ 200 M
Pilot Software (2007) NA
SAS Institute Teragram (2008) NAOracle Sun Microsystems
(2009)
$ 7.4 B
Hyperion (2007) $ 3.3 B
Siebel Systems (2006) $ 5.85 B
Sigma Dynamics (2006) $ 10.3 B
PeopleSoft (2005)
IBM SPSS (2009) $ 1.2 B
Cognos (2007) $ 5.0 B
Telelogic AB (2007) $ 845 M
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HR MODULESAND BI & DATA ANALYTICS SOFTWAREFOR GIANT
VENDORS
Vendor HR Module BI & Data Analytics
SAP SAP ERP Human
Capital Management
Workforce Analytics
SAS Institute SAS Human Capital
Intelligence
Human capital
Predictive Analytics and
Retention Modeling
Oracle Oracle Human Capital
Management
Oracle Human
Resources Analytics
IBM IBM CognosHuman
Resources
Business Intelligence
and Human Resource
Performance
Management
BUSINESS INTELLIGENCE AND DATA
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BUSINESS INTELLIGENCEAND DATA
ANALYTICS FEATURESIN HUMAN
RESOURCES
Software joints offer many BI products, including HR
embedded with business intelligence and data analytics
capabilities . They are :
1. SAP ERP Workforce Analytics
2. SAS Human Capital Predictive Analytics and RetentionModeling
3. Oracle Human Resources Analytics
4. IBM Cognos Business Intelligence and Human Resource
Performance Management
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SAP ERP WORKFORCE ANALYTICS
Product includes features and functions that support these
business activities:
1. Workforce Planning
2. Workforce Cost Planning and Simulation
3. Workforce Benchmarking
4. Workforce Process Analytics and Measurement
5. Talent Management and Analytics and Measurement
6. Strategic Alignment
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SAS HUMAN CAPITAL PREDICTIVE
ANALYTICSAND RETENTION MODELING
Product includes the following features :
1. Predicted Turnover Percentage
2. Causes of Voluntary Termination
3. Organization Exposure
4. High Risk by Job Category
5. Top 50 Employees at High Risk
6. Top Performer
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ORACLE HUMAN RESOURCES ANALYTICS
Product includes the following features :
1. Workforce Insight
2. Targeted Workforce Development
3. Improved Compensation
4. Leave and Absence5. Better Understanding of HR Performance
6. US Statutory Compliance
7. Workforce Planning
8. Workforce Cost Planning and Simulation9. Workforce Benchmarking
10. Workforce Process Analytics and Measurement
11. Talent Management Analytics and Measurement
IBM COGNOS BUSINESS INTELLIGENCE
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IBM COGNOS BUSINESS INTELLIGENCE
AND HUMAN RESOURCE PERFORMANCE
MANAGEMENT
Product includes the following features pertaining to the
following five HR core areas :
1. Organization and Staffing
2. Compensation
3. Talent and Succession
4. Training and Development
5. Benefits
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By taking advantage of the rich business intelligence features
in these and other similar products, Human Resources can
position itself as essential value-adding department of the
organization.
THANK YOU