Business planning and performance analysis

Master 2024/2025

Type: Compulsory course (International Business in the Asia-Pacific Region)

Area of studies: Management

Delivered by: Department of Finance

Where: St.Petersburg School of Economics and Management

When: 2 year, 1, 2 module

Mode of studies: offline

Open to: students of one campus

Instructors: Olga Makarova

Master’s programme: International Business in the Asia-Pacific Region

Language: English

ECTS credits: 6

Full Syllabus Ask Question

Abstract

The course covers aspects of business-planning in an enterprise and performance management in financial perspective. Starting with foundamental strategic and architecrural concepts and questions on linking strategy with operations, students then deep dive into profitability and cost analysis accompanied with revenue planning, will study business modelling, planning and budgeting instruments that support decision-making process in an organization. Students will work with financial models and will analyse in practice strategy-operations linkage and operational financial performance management

Learning Objectives

This course equips students with basic analytical! frameworks and tools for strategic and operational decision-making in managing enterprise based on financial data analysis and data modelling

Expected Learning Outcomes

Able to choose statistical methods appropriate to their data and substantive research problem
Able to conduct descriptive statistics on quantitative data, apply basic statistical methods and interpret results of analysis
Application of basic tools (plots, graphs, summary statistics) to carry out exploratory data analysis.
Ability to analyse and decompose organization structural elements to create an analytical model for performance management
Able to choose calculative methods appropriate to the type of decision-making aspect and substantive research problem
Able to conduct quantitative evaluation in decision-making, apply basic accounting and forecasting methods and interpret results of analysis
Application of basic tools (plots, graphs, tables) to carry out exploratory data analysis.
Construct a financial model for planning and decision-making

Course Contents

Introduction to Business Analysis
Operational Performance and Marginal Profitablity
Cost management techniques and decision-making
Constructing the enterprise analytical system
Financial Structure of Organization
Introduction to data analysis
5. Management Control Systems and Budgeting
Analytical models and tools of perfromance and management
Using data for decision-making
Project budgeting

Assessment Elements

Hometask
Hometask on using data and financial modelling for decision-making
Project
Group project, field research on practical implementation of business analysis tools, interviewing business practitioners.
in-class activity
attendance and activity at lessons, in-class tasks & hometasks completion and presentations, initiating contentive knowledge-based discussions
Exam
Exam in written form, consists of multiple choice questions, calculative tasks and open questions tasks.

Interim Assessment

2024/2025 2nd module
0.3 * Exam + 0.15 * Hometask + 0.15 * Project + 0.2 * in-class activity + 0.2 * in-class activity

Bibliography

Recommended Core Bibliography

Aguinis, H. (2014). Performance Management: Pearson New International Edition (Vol. 3rd ed). [N.p.]: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1418135
Boris Mirkin. (2011). Core Concepts in Data Analysis: Summarization, Correlation and Visualization (Vol. 2011). Springer.
Cardy, R. L., & Leonard, B. (2011). Performance Management: Concepts, Skills and Exercises : Concepts, Skills and Exercises (Vol. 2nd ed). Armonk, N.Y.: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=929342
Enterprise architecture at work : modelling, communication and analysis, Lankhorst, M., 2013
Nicola Terracciano. (2017). Performance Management at the Organizational Level. Annals of Spiru Haret University Economic Series, 2, 19.
Rohatgi, V. K., & Saleh, A. K. M. E. (2015). An Introduction to Probability and Statistics (Vol. 3rd edition). Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1050364
S. Christian Albright, & Wayne L. Winston. (2019). Business Analytics: Data Analysis & Decision Making, Edition 7. Cengage Learning.

Recommended Additional Bibliography

Fraser C. Business statistics for competitive advantage with Excel 2016: basics, model building, simulation and cases. New York, NY: Springer Science+Business Media, 2016. 475 с.
Business Analysis & Valuation: IFRS Edition. (2007). Thomson Learning. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsnar&AN=edsnar.oai.cris.maastrichtuniversity.nl.publications.9a0d36f2.def1.42ca.8628.dc936372947e
Clark, D. (2017). Beginning Power BI : A Practical Guide to Self-Service Data Analytics with Excel 2016 and Power BI Desktop (Vol. Second edition). Camp Hill, Pennsylvania: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1478775
Cokins, G. (2009). Performance Management : Integrating Strategy Execution, Methodologies, Risk, and Analytics. Hoboken, N.J.: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=317048
Danielle Stein Fairhurst (2015). Using Excel for Business Analysis
Enterprise architecture as strategy : creating a foundation for business execution, Ross, J. W., 2006
Groebner, David, et al. Business Statistics, EBook, Global Edition, Pearson Education, Limited, 2018. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=5186156.
Mohanty, M., & Shankar, R. (2019). A hierarchical analytical model for performance management of integrated logistics. Journal of Management Analytics, 6(2), 173–208. https://doi.org/10.1080/23270012.2019.1608326
Pernille Christensen. (2011). An Introduction to Statistical Methods and Data Analysis (6th ed., international ed.). Journal of Property Investment & Finance, (2), 227. https://doi.org/10.1108/jpif.2011.29.2.227.1?utm_campaign=RePEc&WT.mc_id=RePEc
Rasch, D., Verdooren, L. R., & Pilz, J. (2019). Applied Statistics : Theory and Problem Solutions with R. Hoboken, NJ: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2218318
Strategic enterprise architecture management : challenges, best practices, and future developments, , 2012
Zelterman, D. (2015). Applied Multivariate Statistics with R. Springer.

Authors

MAKAROVA OLGA VSEVOLODOVNA
SOLOVEVA EKATERINA EVGENEVNA

Course Syllabus