Day 1: Fundamentals of Innovation and Data-Driven Decision Making

Objectives:

  1. Understand the concept of innovation and its role in organizational decision-making.
  2. Learn the importance of data in supporting innovation and decision-making.
  3. Explore modern data analysis techniques and tools.

Topics:

  • Concept of Innovation and Importance of Data-Driven Decisions
    • Defining innovation and its types (product, service, process innovation).
    • The relationship between innovation and organizational decision-making.
    • How data can support making innovative decisions.
  • Types of Data and Their Uses in Decision Making
    • Difference between descriptive, diagnostic, and predictive data.
    • How to collect and analyze data to derive valuable insights.
    • Using data to enhance innovation strategies.
  • Modern Data Analysis Techniques
    • Descriptive, diagnostic, and predictive analytics techniques.
    • Modern data analysis tools: artificial intelligence, machine learning, big data analytics.
    • How to integrate these tools in making strategic innovative decisions.

 

Day 2: Using Data and Modern Technologies to Enhance Innovation

Objectives:

  1. Learn how to use data and modern technologies to foster innovation.
  2. Explore how to leverage AI and data analytics to develop innovative solutions.
  3. Apply predictive analysis techniques to forecast future trends.

Topics:

  • Role of Artificial Intelligence in Innovation and Decision Making
    • How AI contributes to discovering new solutions and improving processes.
    • Examples of AI applications across various sectors.
    • Strategies for using AI to drive innovation in business.
  • Big Data Analytics to Support Innovation
    • Definition of big data and how to manage it.
    • Strategies for using big data in research and development.
    • How to turn big data into strategic, innovative insights.
  • Forecasting Future Trends Using Data
    • Predictive techniques using data: statistical analysis, machine learning.
    • How forecasting future trends can enhance innovation and improve decision-making.
    • Tools for trend forecasting and analysis.

 

Day 3: Applying Innovation and Data-Driven Decision Making in Practice

Objectives:

  1. Learn how to apply innovation and data-driven decision making in everyday work.
  2. Develop innovative data-driven strategies to improve organizational performance.
  3. Use modern data tools to evaluate the results of innovation and decision-making.

Topics:

  • Applying Data-Driven Innovation in Organizations
    • How to integrate innovation into the organizational culture.
    • Strategies to create an environment that supports innovative decision-making.
    • Techniques for applying innovation in different organizational functions (finance, marketing, operations).
  • Developing Innovative Solutions Using Data
    • How to use data analytics to improve operational performance and decision-making.
    • Applying data analysis tools to develop new, sustainable solutions.
    • How to build data-driven decision-making models.
  • Measuring the Impact of Innovation and Data-Driven Decisions
    • How to measure the success of data-supported innovation.
    • Using Key Performance Indicators (KPIs) to assess innovation outcomes.
    • Analyzing the impact of innovation and data-driven decisions on organizational results.