Data Analytics and the Future of Finance
Note: This Live Virtual course is presented in collaboration with CPA Western Provinces. The content is applicable to all participants. If you have questions regarding this course, please contact pdregistration@cpaalberta.ca
Overview:
We are entering a fourth industrial revolution based on machine learning, intelligent automation and Artificial Intelligence. The nature of work and the expectations of what we can do will change significantly. Those who are prepared and plan ahead have the opportunity to transform their role, their finance team and their organization.
This course covers the ways finance is changing due to automation (and increasingly machine intelligence automation), the greater expectations for actionable information and the potential wider role for finance to play as change/ transformation partner.
It introduces key analytics processes, techniques, tools and application - using examples and case studies. Including core analytics skills all finance professionals should develop and also introduces more advanced techniques that should be understood by those who want to develop more advanced skills or who want to work on/ lead more advanced analytics projects with technical specialists who will carry out the detailed work.
The final section will guide you to develop an action plan to improve both your personal and your organization’s capability in analytics.
Course Content:
In this course, you will gain knowledge about the following topics:
Section 1: Context and big picture
The fourth industrial revolution and the growth of analytics. The different types of analytics and how these relate to the changing role of finance. What past finance transformation tells us about the future, the shift to Robotic Process Automation (RPA), to Intelligent Automation and what that means for the finance function. What is ‘actionable information’, how it differs from typical reporting and how to create it. How actionable information is critical for finance to add value and how visualization helps in achieving this. Digital transformation and finance’s potential role as change partner/ performance manager. The gap from traditional finance and what is needed in skills and development, key roles finance can play. Predictions for the future finance function – proactive case vs complacent case.
Section 2: Core tools and techniques
Creating a solid data foundation – the need for reliable and timely data for analytics and different approaches; including data warehousing, Business Intelligence (BI) tools and automation in Excel. Changing expectations on skills – even for Excel. The power of data visualization, why doing it well is more than just adding charts, the need to understand how the mind and eye process information and different ways visualization can be used. Introduction to more advanced analytics process and techniques, including machine learning, AI, big data and key advanced techniques. More accessible ways to access advanced analytics tools and techniques.
Section 3: Data analytic thinking, skills development and implementation
Introduction and exercise in data analytic thinking – breaking down business problems and considering which analytics techniques you would apply to them. Developing organizational capability in analytics, what do you need to be ready, how to start, inhouse vs external resources, risks, data and other considerations. Your personal analytics journey, what role do you want to take, what you will need to develop – skills, tools, techniques, knowledge. Analytics projects and building a portfolio of experience.
There is no formal post course project – but you are encouraged to use the provided organizational maturity questions and skills concepts discussed to help plan and develop their organizations and their personal analytics skills after the course.
Who Will Benefit:
This course is for business and finance professionals who want to understand and prepare for the changing role of finance due to the growth of intelligent automation, the need for added value ‘actionable information’ and the ability to understand and support business change (such as digital transformation) through supporting advanced analytics projects.