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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/scientific-approach-innovation-management
课程评论：没有评论
课程名称：科学创新管理方法 课程概述：本课程旨在帮助创新者判断其想法是否值得开发与追求。我们提供了一种系统的流程，用于对创新产品或服务进行战略决策，帮助企业家、管理者和创新者避免常见的误区。课程教授学员通过问题框架技术和严谨的数据分析，评估创新想法的可行性，以“科学方法”为主导。课程互动性强，包含练习和现实案例应用，借助多种例子和案例研究展示科学方法在创新管理中的重要性。 课程大纲： 1. 创新决策：讨论创新如何作为问题解决的方式，介绍科学创新决策的基础知识，包括问题的界定、假设和理论的构建及其测试，应用于具体的管理问题和工具。 2. 创新管理的理论与数据：深入讲解科学方法，介绍概率理论，帮助理解不同决策如何导致不同结果，如何有效制定和测试假设，以及如何设计和实施实验。 3. 数据分析：讲解数据分析基础，包括相关性与因果关系的区别，以及如何使用回归分析进行预测，并结合实际案例展示企业如何利用数据进行创新决策。 4. 创新管理决策的高级工具：讨论因果关系，并介绍大数据和机器学习在管理决策中的应用，课程最后总结科学方法的适用性和局限性，帮助学员识别何时适用科学方法或依赖直觉。 5. 最终项目：参与者将应用所学知识完成一项实际项目。 本课程适合所有希望提升创新管理决策能力的学员。
Name:THE INNOVATION DECISION
Description:We provide a general discussion of innovation as problem-solving and we link the discuss the building blocks of the scientific approach to innovation decisions – from how to formulate the problem, to how to formulate the hypotheses and the theory, and how to test them. The whole discussion will be framed and applied to concrete managerial problems, including a discussion of the specific managerial tools that facilitate the application of a scientific approach to innovation management.
Name:THEORY AND DATA FOR INNOVATION MANAGEMENT
Description:We provide more details about the scientific approach and we introduce probabilities to understand how and why certain decisions lead to some outcomes instead of others and how to make better decisions. We also focus on how to formulate and test hypotheses in practice, and how to interpret these tests. We finally discuss how to design and run experiments. NB: some videos may contain a downloadable database; please, download it and follow the in-video instructions
Name:DATA ANALYSIS
Description:We cover the basics of data analysis, beginning with the distinction between correlation and causality in the analysis of data. We also teach how to make predictions using regression analysis and link these methods to the scientific approach, showing what role these analyses play, how they help to make scientific decisions and why. We complement this with real examples of companies using data to make innovation decisions. We close by discussing how to interpret these analyses and results critically to make sure we understand what we really learn from the analyses and when, how and why we should interpret our results cautiously and critically.
Name:ADVANCED TOOLS FOR INNOVATION MANAGEMENT DECISIONS
Description:This is s a more advanced part in which we discuss causality and provide the students with some broad exposure to big data and machine learning, and we discuss what they can do for managerial decisions.We provide a general wrap-up and conclusion of the course, including a discussion of when the scientific approach is most appropriate or has limitations. This helps to see when to apply it, or when to apply other approaches, including our own gut feelings. NB: some videos may contain a downloadable database; please, download it and follow the in-video instructions
Name:FINAL PROJECT
Description:
How can innovators understand if their idea is worth developing and pursuing? In this course, we lay out a systematic process to make strategic decisions about innovative product or services that will help entrepreneurs, managers and innovators to avoid common pitfalls. We teach students to assess the feasibility of an innovative idea through problem-framing techniques and rigorous data analysis labelled ‘a scientific approach’. The course is highly interactive and includes exercises and real-world applications. We will also show the implications of a scientific approach to innovation management through a wide range of examples and case studies.
