Human Resources 2021-22 (LM IMaST - Olbia) - Syllabus

Lessons by Francesco Virili

1-2: Introduction

01 Mon 11/15. Introduction; program, objectives, content, teaching and learning aspects.

02 Tue 11/16. Definition and examples of business intelligence systems application

3-5: Pivot tables

03 Wed 11/17. Data analysis with pivot tables. Introduction

  • From operational to analytical systems . From relational databases to data warehouses. Source: Kimball & Ross, The data warehouse toolkit, Wiley 2002, II ed., ch. 1, download link

  • Two types of corporate databases

    1. database for operational systems (numerous day by day transactions, frequent updates by many users: e.g. orders, invoices, etc.)

    2. database for analytical systems: data warehouse (quick and simple queries on large amounts of data with aggregated results: e.g. sales analysis)

  • Business analysis example: sales by agent and region. Basic questions:

    1. area of ​​interest of the analysis (sales or for example logistics, or human resources, or production etc.)

    2. how do we measure the facts we observe? (turnover, number of transactions, number of products, costs, margin, etc.)

    3. what kind of breakdown do we want to obtain by dimension? (e.g. by agent, by region rather than for example by month / year; by classes and products; by classes and customers; by sales channels, etc.)

    4. how do we aggregate facts? (sum, count, max, min, variance, etc.)

    5. what is the elementary level of aggregation / granularity of the phenomena we are analyzing? (e.g. a row in the sales table, what does it correspond to? to a single sales transaction? to a monthly total? to a quarterly total?

  • Key elements to know in order to carry out a business analysis:

    1. the chosen measurements of facts (KPI = Key Performance Indicator)

    2. the aggregation dimensions (object: what was sold? (products: series, version, model, brand, etc.) subject: who sold? (agents); time: when? (days / months / quarters / years); where ? (municipality, province, region, nation, continent ...) how? (sales channels; payment conditions or other);

  • The typical analysis answers this question: aggregate (KPI) by dimension1, dimension2, etc .. ex. sum the quantities sold (KPI) by agent (analysis dimension)

  • Reference book for pivot tables: www.pdfdrive.com/excel-data-analysis-your-visual-blueprint-for-creating-and-analyzing-data-charts-and-pivottables-d175111364.html

  • Pivot tables files for exercises: HR03 PivotTables04 .ods and HR04 PivotTables08.ods (see bottom file list to download)

04 Thu 11/18. Building pivot tables

  • file HR03 PivotTables04 .ods

5-8: HR analytics using pivot tables and Power BI

05 Mon 11/22. Building pivot tables. Assignment for Tuesday: what is turnover? Why is it important in HR? What are the main causes of turnover? Sources: cfr. textbook chapter 5 and compare with this Open Access HRM textbook. Please prepare a short presentation with your answers for discussion

  • file HR04 PivotTables08 .xlsx

06 Tue 11/23. Building pivot tables with HR data sets. Intro

  • file HR06 turnover 2015-16 .xlsx

07 Wed 11/24. Building pivot tables with HR data sets. Discussion

  • file HR06 turnover 2015-16 .xlsx

08 Thu 11/25. Analysis with Microsoft Power BI. Introduction. Individual assignment for next week. Explore the HR datasets and identify one dataset figuring out what type of analysis you might perform. Check in the textbooks the related chapter(s) to motivate and justify the analysis.

9-11: Project work setting

09 Mon 11/29. Selected data set: discussion and design of the HR analysis

10 Tue 11/30. Building the business case and designing pivot tables

11 Wed 12/01 - 12 PM-1:30PM. Project work setting

  • Project work: powerpoint slides + HR analytics model (pivot tables)

    1. Business problem description: what is the HR challenge to be solved?. Model description: dataset used, dimensions, KPIs; analysis description; Pivot tables (first set): results and interpretation with problem solutions.

    2. Same as 1), second set of pivot tables

    3. Theory behind your results. Eg: what is turnover? Why is it important to detect it? What are its causes? Are your results in line with theory? (use also textbooks). Comparison with a similar business case (see for example https://www.humanresourcestoday.com/analytics/case-study/). Plus: your answers to challenges and feedback given in part 1) and 2).

12-14: Project work presentations

12 Thu 12/02 - Project work presentation 1 of 3: Pivot

13 Mon12/06 - Project work presentation 2 of 3: Power BI

14 Tue 12/07 - Project work presentation 3 of 3: Theory behind results and presentation of a similar business case for comparison


Further material: