strategic management in marketing

1. DISCOVER . LEARN . EMPOWER
Unit 3.1- Organizational development and change
INSTITUTE- University School of
Business
DEPARTMENT- Management
MBA
Organizational Change and Development
22BAT740

2. Organizational development and
change
CO
No
Statement Performance
Indicator
Knowledge
Level (BT
Level, Highest)
CO1 To demonstrate an understanding of the organization
development and identify the need for change and
renewal
1.2, 2.2 1
CO2 To describe the reasons for the resistance to change in
organizations.
1.3, 2.5 2
CO3 To analyze the linkage of power and politics with OD
interventions
2.3, 3.2, 5.1 3
CO4 To predict the future trends of OD to build
transformative organizations.
3.5, 3.6, 4.2,
4.3
4
Course Outcome
2

3. Strategic Change Intervention
A strategic change intervention in human resource
analytics refers to a deliberate and purposeful approach
taken by an organization to implement significant
alterations or improvements in its HR processes,
practices, and systems. This intervention is based on a
thorough analysis of data and metrics related to the
workforce, aiming to achieve specific organizational
objectives.

4. Key components of a strategic change
intervention in human resource analytics
include:
1.Data-Driven Decision Making :The intervention relies
heavily on data and analytics to inform decision-making.
This may involve using various HR metrics, such as
turnover rates, performance indicators, employee
satisfaction scores, and other relevant data points.

5. 2.Alignment with Organizational Goals:The
intervention is closely aligned with the broader strategic goals
and objectives of the organization. It seeks to ensure that HR
practices are in sync with the overall direction of the company.
3. Proactive Approach: It is a proactive rather than reactive
approach to managing human resources. The organization
anticipates and plans for changes in the workforce based on
predictive analytics and trends.
4.Change Management Principles: It involves the application
of change management principles and techniques to facilitate a
smooth transition. This may include communication plans,
stakeholder engagement, training programs, and other strategies to
support employees through the change process.

6. 5.Customization and Personalization: The intervention is
tailored to the specific needs and challenges faced by the
organization. It takes into account the unique characteristics of the
workforce, industry, and organizational culture.
6.Technology Integration: Utilizes advanced HR technologies
and analytics tools to gather, process, and analyze data. This could
involve the use of HR information systems (HRIS), predictive
modeling, machine learning algorithms, and other technology-
driven solutions.
7.Continuous Monitoring and Evaluation: The intervention
involves ongoing monitoring of key performance indicators (KPIs)
and metrics to assess the effectiveness of the changes
implemented. This allows for adjustments and refinements as

7. 8.Cross-Functional Collaboration: It often requires
collaboration across different departments and functions within the
organization. This could involve HR, IT, finance, operations, and
other areas to ensure a holistic approach to change.
9.Employee Involvement and Engagement: Engages
employees in the change process, seeking their input and feedback
to enhance acceptance and commitment to the new initiatives.
10.Measurable Outcomes: The success of the intervention
is measured based on predefined metrics and benchmarks.
This could include improvements in productivity, employee
satisfaction, retention rates, or other relevant KPIs.

8. TYPES
OF
STRATEGIC
CHANGE
INTERVENTION

9. 1.Talent Acquisition Optimization:
1.Using predictive analytics to improve recruitment strategies.
2.Implementing algorithms to screen and shortlist candidates
efficiently.
3.Analyzing data to identify the most effective sourcing channels.
2.Employee Retention Strategies:
1.Conducting predictive analysis to identify flight risk factors.
2.Designing and implementing targeted retention programs
based on data insights.
3.Utilizing sentiment analysis to understand employee
engagement levels.

10. 3.Skills Development and Training:
1.Analyzing skill gaps through competency mapping and
assessments.
2.Using learning analytics to optimize training programs.
3.Personalizing learning paths based on individual employee
data.
4.Performance Management Enhancement:
1.Implementing continuous performance feedback mechanisms.
2.Utilizing data to identify top performers and areas for
improvement.
3.Leveraging analytics to set and adjust performance
benchmarks.
5.Workforce Planning and Optimization:
1.Forecasting future workforce needs based on business goals and
trends.
2.Using analytics to optimize workforce distribution across teams
and departments.
3.Scenario planning to prepare for various business contingencies.

11. 6.Diversity, Equity, and Inclusion (DEI) Initiatives:
1.Analyzing demographic data to identify areas for improvement
in diversity and inclusion efforts.
2.Utilizing data to track progress towards DEI goals and
benchmarks.
3.Implementing targeted initiatives to address specific disparities.
7.Employee Engagement and Well-being Programs:
1.Using surveys and sentiment analysis to gauge employee
satisfaction and well-being.
2.Analyzing data to identify factors affecting engagement levels.
3.Designing and implementing well-being programs based on
data-driven insights.

12. 8.Succession Planning and Leadership Development:
1.Identifying high-potential employees through data analysis.
2.Creating tailored development plans for potential leaders.
3.Ensuring a smooth transition for key roles based on succession
plans.
9.Compensation and Benefits Optimization:
1.Conducting market analysis to ensure competitive compensation
packages.
2.Using analytics to design performance-based incentive programs.
3.Evaluating benefits offerings based on employee preferences and
needs.

13. 10.HR Technology Adoption and Optimization:
•Analyzing data to identify gaps in HR technology utilization.
•Implementing and integrating new HR systems based on data-driven
insights.
•Optimizing existing technology platforms for efficiency and
effectiveness.

14. EXAMPLES

15. 1.Implementing Predictive Analytics:
1.Utilizing advanced statistical models and machine learning
algorithms to forecast future HR trends such as turnover,
performance, and talent acquisition needs.
2.Creating a Culture of Data-Driven Decision Making:
1.Fostering a workplace culture that encourages HR and business
leaders to rely on data for making key HR decisions, rather than
solely relying on intuition or past practices.
3.Integrating HR Data with Business Objectives:
1.Aligning HR analytics efforts with the overall business strategy to
ensure that HR initiatives and activities directly contribute to
achieving organizational goals.

16. 4.Developing HR Scorecards and Dashboards:
1.Creating visual representations of HR metrics and KPIs that
provide a quick overview of HR performance and help in
identifying areas that need attention.
5.Implementing Employee Engagement Surveys:
1.Conducting regular surveys to gauge employee satisfaction,
identify areas of improvement, and track changes in engagement
levels over time.
6.Utilizing Social Network Analysis:
1.Analyzing the social connections and interactions within an
organization to identify key influencers, communication patterns,
and potential areas for collaboration.

17. REFERENCES
Change Management and Organizational Development, Raina,
R., 2019, 1st edition.
Organizational Development And Change, Cummings And
Worley, 2019 11th Edition.
Organizational Change, Pathak, H., 2010, Pearson Publication.
Cases and Exercises in Organization Development and Change,
Anderson, D.L., 2017, 2nd edition.
Organizational Development, Ramnarayan, S., Rao, T.V.,
2011,SAGE Publications.

18. THANK YOU
For queries
Email:
Vijesh.e14801@cumail.in