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Cases

Ohjelma
Bike Lease Finland

Bike Lease Finland

Leasing and maintenance of employee bicycles, digital services.

Ohjelma
Excelence Solutions

Excelence Solutions

Consulting and data analytics, expert services and consulting.

Ohjelma
Finnish Timber Oy

Finnish Timber Oy

Ecological log buildings and construction site processes, project business.

Ohjelma
Green Scape

Green Scape

Customized green wall services for B2B clients, service business.

Ohjelma
Marine Craft

Marine Craft

Customized motorboats, project delivery, manufacturing industry.

Ohjelma
Scandinavian Design

Scandinavian Design

Leasing and maintenance of company bicycles, digital services.

Task

Data Quality Challenges



In this task, the student examines the quality of financial data from the perspective of different systems and processes in a case company. They identify typical data quality challenges, such as missing information, errors, and inconsistencies between systems, and consider their impact on reporting and decision-making. The student also prepares a list of improvement actions, a concise action plan, and suggests a way to monitor the development of data quality. This task strengthens the ability to assess and improve the reliability of financial data in practical work.

Learning objectives

After completing the task, the student:
1. Understands what kind of data quality issues may arise in the financial management information of the case company.
2. Is able to assess the impact of data quality on reporting and business decision-making.
3. Can suggest concrete process, system, and operational changes to improve data quality.
4. Understands the importance of continuous monitoring of data quality in the collaboration between financial management and data analytics.

Step by step

  1. Data quality challenges

    Objective:
    The objective of the assignment is that the student understands what kinds of data quality issues may occur in the case company's financial information (e.g. missing values, errors, inconsistencies between different systems) and is able to propose concrete ways to improve data quality.

    Materials:

    • The case description of the selected case company from the learning material.

    • Possible example material on financial reports provided in the course (if needed, you may imagine typical reports and systems, such as invoicing, accounting, sales system).

    • The assignment is based on the case description and well-grounded assumptions about how the company’s financial data is collected and used.

    Assignment steps (instructions for the student):

    1. Describe the financial data sources of the case company
      Write 5–8 sentences about which different systems and processes likely generate financial data in the case company (e.g. invoicing, accounting, payroll, sales system, online store).
      Name at least 3 key data sources and briefly describe what information they process.

    2. Identify data quality challenges
      Create a list of at least five possible data quality problems that could occur in the case company.
      Pay special attention to:

      • missing data (e.g. missing cost centres, customer identifiers)

      • errors and inconsistencies (e.g. incorrect amounts, duplicate transactions)

      • conflicting information between systems (e.g. sales figures not matching accounting records).
        Write 2–3 sentences for each challenge: where it might arise and what consequences it has for reporting.

    3. Assess the impact of data quality on decision-making
      Select 2–3 of the most significant challenges you identified and describe in 1–2 paragraphs:

      • how they can distort financial reports

      • what types of erroneous decisions or delays they may cause for management.
        Try to use examples that describe the operations of the case company (e.g. incorrect information about the most profitable products, unreliable cash flow forecast).

    4. Propose ways to improve data quality
      Create a list of at least 5 concrete improvement actions that could help the case company.
      You may include, for example:

      • consistent recording guidelines and training for finance and sales staff

      • automatic checks and error notifications in systems

      • regular reconciliation between different systems

      • clarifying responsibilities (who owns and verifies the data)

      • small user interface improvements or mandatory fields that reduce missing data.
        Write a short justification for each suggestion: how it concretely improves data quality.

    5. Create a concise action plan
      Select the 3 most important actions from your improvement list and create a half-page concise action plan:

      • which challenge each action addresses

      • who in the company would be the natural responsible party

      • what first practical steps could be taken in the next 3–6 months.

    6. Reflect on future data quality monitoring
      Finally, write 5–7 sentences about how the case company could monitor data quality in the future (e.g. number of errors, reconciliation discrepancies, report correction rounds).
      Propose one simple metric or practice that would allow management to see whether data quality is improving.

    Submission and evaluation:
    Submit a text of about 1–2 pages showing:

    • the key financial data sources of the case company

    • the identified data quality challenges and their impact on decision-making

    • the proposed improvement actions and a short action plan

    • a proposal for monitoring data quality.

    Evaluation focuses on how well you:

    • identify realistic data quality problems from the case company's perspective

    • are able to assess the impact of the problems on financial reporting and decision-making

    • propose concrete and feasible improvement measures

    • write in a clearly structured way with logical reasoning.

    Recommended working time: approximately 45–60 minutes, individually or in pairs.

Tasks by audience and theme

University of applied sciences

Polytechnics and higher education studies.

68 tasks