Analyse the role of data, volume, quality, and timeliness, in decision making and critically evaluate, with particular reference to digital data, traditional leadership models
Data-Driven Leadership Skills Course 3: Data-Driven Leaders
This course is part of Data-Driven Leadership Skills Specialization
Instructor: Matt Offord
Sponsored by Coursera Learning Team
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What you'll learn
Analyse the role of data, volume, quality, and timeliness, in decision making
Critically evaluate, with particular reference to digital data, traditional leadership models
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6 assignments
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There are 3 modules in this course
Welcome to the third and final course in this specialisation. The course is a deeper dive into data than the previous two course, we will tie up the themes of traditional leadership and agility to describe a data landscape, how to navigate and how to lead. In this module, we will focus on that landscape with a brief history of data and how it has radically changed our environment as leaders.
What's included
1 video11 readings2 assignments2 discussion prompts
In this module we will look at the best approach to explore and navigate this new data landscape. At the heart of this approach, I introduce my SWAN model which begins any leadership venture by challenging existing beliefs and stories in the organisation. You could say that when surrounded by data, verifying those data is of paramount importance. We will then look at some recent case studies surrounding decision making in the Covid-19 crisis. Our approach here is not make leaders look silly but to highlight just how difficult it is to make a decision about something you know too much about.
What's included
1 video5 readings2 assignments2 discussion prompts
In this final module, of the final course we will put our learning together to create a framework for leadership in the age of data. This draws on the legacy of 'traditional' leadersship because it must. But we also recognise the mismatches between this form of leadership an an emerging agile workplace of hyperconnected humans and, yes, machines. This requires embrace more power to the edge, but that we also get control of our data. In short, we must be kind to humans and demand that our data work for us. In this module you will find out how.
What's included
4 videos7 readings2 assignments2 discussion prompts
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