IIID DSI (M) V / INNOVACION / CABREJOS CESAR - 11 DE SEPTIEMBRE

Introduction and Course Overview

Welcome and Initial Setup

• The instructor greets the students, confirming audio and attendance before starting the session.

• The course is introduced as a new didactic unit relevant to students' professional careers in system development and personal growth.

Instructor Background

• César Cabrejos Aricoché introduces himself as an administrator with over 15 years of experience in quality management systems, operations, and project management.

• He emphasizes his role in ensuring that all business processes are aligned and provide necessary data for analysis.

Understanding Business Metrics

Performance Measurement

• The instructor discusses setting realistic, optimistic, and pessimistic performance targets for production metrics.

• He explains the importance of analyzing underperformance against these targets to identify issues such as equipment failure or supply chain delays.

Key Performance Indicators (KPIs)

• KPIs are introduced as essential tools for measuring various aspects of business performance, including sales data and employee attendance.

• Students are reminded that their role will involve developing systems to collect this data effectively.

Process Management in Organizations

Types of Processes

• The instructor outlines three types of processes: strategic, mission-critical, and support processes within organizations.

• A diagnostic approach is suggested to categorize areas into these process types for effective KPI development.

Research Focus

• Emphasis is placed on conducting research to solve problems or improve processes within organizations through innovation.

Course Structure

Practical vs. Theoretical Learning

• The course will consist of 70% practical work and 30% theoretical instruction, with weekly progress checks on student projects.

Project Guidelines

• Students will focus on research aligned with their professional fields rather than traditional business plans or projects.

Syllabus Overview

Project Expectations

• An overview of the syllabus indicates a 16-week timeline where students will present a research project aimed at solving real-world problems or creating new applications.

Team Formation

• Students are instructed to form teams of three for collaborative project work throughout the course duration.

Research Methodology

Qualitative vs. Quantitative Research

• Differences between qualitative (descriptive analysis of problems like inventory control issues) and quantitative research methods are discussed.

Variable Identification

• Examples illustrate how to define independent (X variable - implementation of a system/software solution), dependent (Y variable - improvement outcomes), and their relationship in research projects.

Academic Integrity

Plagiarism Concerns

• Importance is placed on originality in student submissions; similarity thresholds for academic integrity checks using software like Turnitin are explained.

Structuring Research Projects

Idea Development

• Students must generate original ideas based on personal interests within their field rather than copying existing concepts from online sources.

Objectives & Justification

• Each project should have clear objectives focused on problem-solving or introducing innovations while justifying its significance both technically and economically.

System Design and Theoretical Foundations

Importance of Theoretical Support

• A storage system utilizes programs X and YZ, with advantages and disadvantages for each. It's crucial to provide theoretical backing when defending a thesis.

• When questioned about the effectiveness of a storage system, one should reference established theories or models to substantiate claims.

• Gathering substantial information is essential for addressing research problems effectively.

Limitations in Research

• Every project faces limitations such as time constraints, scheduling conflicts, or financial issues that hinder implementation.

• Technological limitations can cause delays; lack of necessary equipment may impede progress on projects.

Formulating Hypotheses

Crafting Hypotheses

• Hypotheses should propose potential outcomes, such as whether implementing a storage system will improve logistics management or reduce costs.

• Distinguishing between qualitative (descriptive problem analysis without hypotheses) and quantitative (influential research requiring statistical methods).

Data Collection Methods

Quantitative vs. Qualitative Approaches

• Quantitative research involves descriptive statistics and inferential statistics to analyze data collected through surveys or experiments.

• Understanding the difference between universe (total population) and sample (representative subset), which is critical for effective data analysis.

Data Processing Techniques

Collecting and Analyzing Data

• Data collection methods depend on whether the study is descriptive or quantitative; perceptions are key in descriptive studies.

• Utilizing samples from larger populations allows researchers to draw conclusions without needing to survey every individual.

Finalizing Research Projects

Conclusion Development

• After gathering data, researchers must compile findings into reports that include conclusions and recommendations based on their analyses.

Significance of Research Skills

Personal and Professional Growth

• Engaging in research enhances personal initiative, analytical skills, critical thinking, and professional expertise in technology fields.

Adapting to Technological Changes

Continuous Improvement in Technology

• The rapid evolution of technology necessitates ongoing learning; professionals must adapt to new software versions regularly.

Investigating Core Business Processes

Identifying Critical Areas

• Understanding core business processes helps identify areas needing improvement; strategic investigations can lead to better resource management.

Implementing Efficient Systems

Practical Applications

• Developing systems that allow real-time inventory tracking improves supply chain efficiency by ensuring optimal stock levels are maintained.

Integrating Technology in Healthcare

Innovations in Health Management

• Current healthcare initiatives focus on integrating digital records across hospitals for improved patient care through accessible medical histories.

Overview of Medical Staff Responsibilities

Effective and Non-Effective Hours

• Medical staff in hospitals are fulfilling both effective hours (direct patient care) and non-effective hours (training and related activities).

• The focus is on measuring the impact of these non-effective hours on medical departments like cardiology and nephrology.

Importance of Research

• Emphasis on the significance of research within medical practice, highlighting the need for thorough investigation.

Technological Integration in Healthcare

Process Management

• Der's management approach effectively integrates process management with technological research and system development.

• There is a strong demand for skilled technical personnel in system development and programming to support healthcare advancements.

Course Introduction

Course Structure

• The session serves as an introduction to the course, outlining its benefits and potential opportunities.

• Students are encouraged to bring ideas for research topics starting next week, focusing on at least two variables relevant to their fields.

Templates for Scientific Research

Understanding Scientific Research

• Three templates will be introduced that outline scientific research methods applicable in various fields such as administration and systems development.

Application of Methods

• Scientific research aims to apply systematic methods to enhance efficiency, productivity, and decision-making processes.

Goals of Scientific Investigation

Improvement Objectives

• The goal is to improve existing processes or create new solutions that yield significant results through scientific inquiry.

Types of Research Approaches

• Two primary approaches: descriptive (qualitative perceptions/opinions-based studies), which rely on subjective data collection methods like interviews; and quantitative (statistical analysis), which requires historical data comparison.

Quantitative vs. Descriptive Research

Complexity in Quantitative Analysis

• Quantitative research involves complex statistical analysis, including descriptive statistics for surveys followed by inferential statistics to determine result significance.

Practical Examples

• Example provided: Implementing a sales system could improve logistics management; requires historical data analysis before and after implementation.

Data Analysis Techniques

Historical Data Utilization

• To demonstrate improvements from new systems, researchers must analyze historical data pre-and post-system implementation using statistical tools.

Benefits of Conducting Research

Innovation & Leadership

• Engaging in research fosters innovation leading to competitive advantages within markets through improved business practices.

Continuous Improvement

Research promotes continuous improvement cycles based on methodologies like Deming’s Plan–Do–Check–Act (PDCA).

Decision-Making Processes

• Demonstrating problem-solving capabilities through applied tools leads to informed decision-making regarding project implementations despite limitations such as budget constraints or lack of expertise.

Resource Optimization

• Efficient resource utilization is crucial when implementing new systems or processes within organizations.

Ethical Considerations in Research

Ethical Standards

• Researchers must adhere to ethical standards while conducting investigations, ensuring proper citation practices when utilizing external data sources.

Plagiarism Prevention

• Institutions utilize plagiarism detection software like Turnitin; maintaining originality while allowing limited citations is essential for academic integrity.

Utilizing AI Tools Responsibly

AI Integration

• While artificial intelligence can assist with generating content, it should be adapted into personal work rather than directly copied due to potential rejection by academic institutions if flagged as AI-generated material.

Conclusion & Next Steps

Summary & Future Directions

• The session concludes with a summary emphasizing the importance of structured investigation methodologies while encouraging students’ active participation in future discussions about their chosen research topics.