Data-Driven Decision Making and Innovation

Name: Data-Driven Decision Making and Innovation
Rating: 4.2 (70 reviews)

A course on how to effectively implement data-driven decision making in any size or type of organization

Created byJef Jacobs

Last updated 9/2021

English

English [Auto],

What you'll learn

A deep understanding of the data-driven decision making process; so that you become the go-to subject matter expert in your organization
How to develop a clear data-use vision and strategy; so that investments and activities lead to real business benefits
Which human characteristics, mindsets and behaviors to practice to be more data-driven; so that you become a better 21st century leader or manager
How to identify and correct weaknesses within your organisation's decision making process; to ensure efficiencies and effectiveness of all activities
The key ingredients (beyond technology and skills) required to be data-driven; increased chances of investments leading to real organisational benefits

Course content

5 sections • 41 lectures • 3h 12m total length

Making Decisions in the 21st Century ...is all about data4:25
Make data-driven decisions to improve outcomes and growth by balancing expert insight, research, and accessible data, reducing the risk of poor decisions in the 21st century.
The Truth About Data-Driven Decision Making ...is that most people get it wrong6:10
Discover how data driven decision making can boost profit, revenue, and customer growth, and why inertia, risky overhype of analytics, and vague direction hinder turning insights into action.
The Secret to Being Data-Driven...is you2:35
What You Will Learn - Outline Of The Entire Course3:18
Explore the data to wisdom hierarchy and data use maturity frameworks. Learn the data driven decision making process and how insights, strategy, technology, and people drive organizational success.

Lecture 1: Introduction To The DIKW-D Model0:51
Explore the DIKW-D model and its role in framing data driven decision making, preparing your mind for reflection while acknowledging its high level, theoretical nature.
Lecture 1: The DIKW-D Model6:25
Lecture 1: Final Thoughts and Remarks1:09
Lecture 2: Introduction To Data-Use Maturity Frameworks2:13
Define a north star vision for data-driven evolution using data-use maturity frameworks, align resources, and guide decisions from gut feel to autopilot data-driven decision making.
Lecture 2: Data Use Maturity Frameworks11:53
Lecture 2: Final Thoughts and Remarks5:10
Lecture 3: Introduction To the Data-Driven Decision Making Process1:21
Lecture 3: The Data-Driven Decision Making Process12:31
Chapter 1: Final Thoughts And Remarks1:51

Chapter 2 Introduction4:37
Lecture 4: Introduction - The Right Data-Use Strategy3:07
Lecture 4: Introduction To The Business Model Canvas1:53
Explore crafting a clear data use strategy and a relevant problem statement, using the business model canvas to view the nine building blocks and align data plans with business strategy.
Lecture 4: Using the Business Model Canvas To Create Focus14:15
Lecture 4: Concluding Remarks About The Business Model Canvas3:32
The business model canvas starts data-use strategies but requires what and why; align teams, set clear objectives with smart goals, create multiple strategies, and secure senior leadership buy-in.
Lecture 4: Introduction To The 10 Types of Innovation1:50
Lecture 4: Using the Ten Types of Innovation Framework To Foster Creativity13:03
Lecture 4: Final Thoughts and Remarks4:46
Explore how to craft clear data use strategies aligned with existing objectives, validated by gap analyses and stakeholder interviews, and supported by executive buy-in and the data driven decision making process.
Lecture 5: Introduction - The Right Technology1:49
Explore how technology supports data-driven decision making by transforming raw data into information and insights, and learn to engage technical experts to optimize data use strategies.
Lecture 5: The Right Technology11:03
Lecture 6: Introduction - The Right People1:14
Identify the technical and non-technical roles responsible for delivering outcomes across the nine steps of data-driven decision making, from raw data to actionable insights.
Lecture 6: The Right People (skills)16:39
Lecture 6: The Right People (structure)6:54
Chapter 2: Final Thoughts And Remarks5:07

Chapter 3: Introduction2:06
Explore the data driven mindset of individuals and leaders, and the beliefs and behaviors that cultivate a data driven decision making culture.
Lecture 7: Data-Driven Mindset #12:48
Lecture 7: Data-Driven Mindset #23:58
Lecture 7: Data-Driven Mindset #32:22
Lecture 7: Data-Driven Mindset #45:05
Adopt a customer-first data-driven mindset by acting as a service provider to internal and external customers, democratizing data access, and delivering self-service solutions that address context and needs.
Lecture 7: Data-Driven Mindset #54:17
Lecture 7: Final Thoughts and Remarks2:20
Lecture 8: Data-Driven Behavior #12:11
Lecture 8: Data-Driven Behavior #23:21
Apply data-driven behavior by asking probing questions about data quality, data warehouses, data transformations, algorithms and modelling techniques, while assessing probabilities, biases, and encouraging further exploration.
Lecture 8: Data-Driven Behavior #32:48
Lecture 8: Data-Driven Behavior #41:54
Lecture 8: Data-Driven Behavior #53:30
Lecture 9: Course Conclusion2:01
Celebrate completing this data-driven decision making and innovation course, built on research and interviews. Reflect, critique, and apply insights with peers and your organization.

Links4:17
This document contains the free weblinks I used to construct this course. I have also included all the academic articles used in my broader research on the topic. Some articles may require you to access them via Journals for which you have to pay - in most cases you can find free versions. I do not have any business relationships with any of the sites, companies or research journals I used and list here.

Requirements

No coding, analytics or computer science skills or experience is required
Some work experience or exposure to business decision making would be advantageous

Description

Making strategic decisions, which is the act of allocating limited time and money towards specific objectives, is a fundamental component of business and personal management. Good decisions lead to success while poor decisions lead to loss or failure.

A data-driven organization is one that leverages information technology to collect, manage and transform data into relevant insights for strategic decision making. Research has shown that data-derived insights can reduce the time and the costs associated with an organization's research and development process. In fact, research has shown that data itself can become or define a new product, and that data-driven firms innovate more frequently and more intensely than other firms.

The overall objective of this course is to make you a more effective 21st century decision maker. This will aid you in becoming a more effective leader or role model in your current organization, and potentially a more attractive candidate for future leadership roles.

The course aims to achieve this by equipping you with a deep insight and understanding of the following two themes:

1. How to effectively implement data-driven decision making within an organization

2. What mindsets and behaviors you need to develop or practice in order to become an effective data-driven leader

This course is not technical in nature at all. No background experience in data analysis or data technology is required. Exposure to business decision making, in any type or size of organization, is advantageous.

(All slides are provided in the first and last lecture of each chapter)

Who this course is for:

Anyone who is interested in making better decisions using data
Anyone who works in data intensive industries such as manufacturing, finance, technology, sales, education, retail, etc.
Anyone who works within a technical field - but wants to graduate to a management or leadership role

Data-Driven Decision Making and Innovation

What you'll learn

Explore related topics

Course content

Introductions4 lectures • 16min

Chapter 1: Key Terms, Frameworks And The Data-Driven Decision Making Process9 lectures • 43min

Preparing for Success: The Right Strategy, Technology and People14 lectures • 1hr 30min

Ensuring Success: The Mindsets and Behaviors of Data-Driven Leaders and Managers13 lectures • 39min

Links to articles and websites used1 lecture • 4min

Requirements

Description

Who this course is for: