Lena Đorđević Milutinović

Lena Đorđević Milutinović

Assistant professor

Lena Đorđević Milutinović, Ph.D. is an associate professor at University of Belgrade, Faculty of the Organizational Sciences. Her field of expertise includes operations management, production and services management, material flow management, control systems and models, spreadsheet engineering and management, enterprise information systems and business applications. So far, she has published over 100 bibliographic units, including scientific papers in journals and conference proceedings, monographs, textbooks and auxiliary literature. She has taken part in numerous scientific, research and commercial projects related to process improvement and automation, design and development of control models and applications, data-driven decision making in various business areas. She has been engaged as a trainer for the development and improvement of employees’ analytical skills and data-driven decision-making competencies in many companies. Lena Đorđević Milutinović has taken part in a few international scientific and research projects in the field of business administration. She has been a part of the mentoring team for student projects within the R&D center of the faculty and mentor or committee member for over 100 graduate and master theses, related to monitoring, modeling, and control of material and immaterial flows (materials, products, inventory, employees, transport services, etc.) and supporting business applications in different industries.

All Sessions by Lena Đorđević Milutinović

11:30 - 13:00
D300

Advanced Excel for Sales

This course is designed to equip students with some of the necessary skills to use advanced Excel features for analyzing sales data, creating powerful reports, and making data-driven decisions. The course will cover various advanced Excel techniques, such as pivot tables, conditional formatting, advanced filter, data validation, lookup formulas and more. Students will learn how to use these tools to analyze sales data, track customer behavior, and create visually appealing reports. Upon completion of this course, students will be able to:

  • Use advanced Excel features to analyze sales data.
  • Use Excel's data validation feature to ensure data accuracy.
  • Track customer behavior and preferences using Excel's advanced filtering options.
  • Create visually appealing reports to communicate sales data effectively.
Course Outline:
Module 1: Introduction to Advanced Excel (Introduction to advanced Excel features, Overview of the course content, Preparing data for analysis);
Module 2: Pivot Tables and Charts (Creating pivot tables to summarize data, Using pivot charts to visualize data, Filtering data in pivot tables);
Module 3: Conditional Formatting and Data Validation (Using conditional formatting to highlight data, Using data validation to ensure data accuracy, Creating custom data validation rules);
Module 4: Advanced Filter Techniques (Using various advanced filtering techniques to analyze data more efficiently and accurately, Filter data based on complex criteria, specific conditions and formulas, Extract unique values, filter data by multiple criteria, and copy filtered data to a new location);
Module 5: Tracking Customer Behavior (Using Excel's advanced filtering options to track customer behavior, Analyzing customer buying patterns and preferences).

11:00 - 12:30
111

Data Driven Decision Making

Business Intelligence Solutions for Banking utilize the data sources that one bank could have (or obtain) with an idea to provide the decision-makers with a different point of view on the business performance. Business intelligence solutions enable users to connect to multiple and disparate data sources and display interactive dashboards that would normally require significant data modeling and database skills. Besides reducing the need for data modeling, the tools used in this summer school allow the creation of ad-hoc interactive dashboards that can help decision-makers inspect and explain the factors that influence the performance of a bank. The course will enable students to define and design key performance indicators and dashboards, as well as propose a data-driven solution to the problem at hand. Objectives: 1) Gain expertise on how to apply business intelligence solutions in the banking industry, 2) Basic understanding of data types, data modeling, and data querying, 3) Designing and developing data visualizations, reports, and dashboards. Outcomes: 1) Identify and analyze the situations where business intelligence can lead to better decision-making, 2) Design dashboards and ad-hoc reporting systems, 3) Apply business intelligence tools for data-driven decision-making 4) Communicate results to (non-technical) business users.

14:00 - 15:30
111

Workshop: Designing Data-informed Banking Products Sales Strategies

The workshop will provide students with hands-on experience in designing dashboards and ad-hoc reporting systems by applying Microsoft Power BI, a business intelligence tool for data-driven decision-making.