Managing Job Creep in the CFO Role
If you are a CFO, it’s not an illusion. You are doing more. Your job is expanding.
The result of doing good work is more responsibility with all the benefits and trials that go with it.
If you are a CFO, it’s not an illusion. You are doing more. Your job is expanding.
The result of doing good work is more responsibility with all the benefits and trials that go with it.
In recent months, particularly following the release of ChatGPT, there has been an unprecedented surge in interest surrounding artificial intelligence (AI). This heightened attention spans across a multitude of sectors, including business enterprises, technology companies, venture capital firms, universities, governments, media outlets, and more. As the interest in AI is intensifying, some companies have even rebranded their existing software solutions as “AI” products, a phenomenon often referred to as “AI washing.” Furthermore, there is also a growing sense of “FOMO” (Fear of Missing Out) among corporations regarding AI adoption.
Delivering successful data analytics solutions that have a strong business impact is dependent on numerous factors such as culture, literacy, governance, technology, quality data, leadership and more. However, one key component that acts as a lynchpin in data analytics — i.e., the pivotal element that is the coherent source of support and stability is the key performance indicator (KPI). What is a KPI? Why does it hold such a significant position in data analytics? Finally, what can organizations do to design and build a robust KPI framework and deliver improved business performance from data analytics?
On Rapid Fire Prashanth responds to these questions:
I have been this question asked many times - Is JupyterLab recommended data analytics for FP&A (Financial Planning and Analysis) professionals? Should, a FP&A professional invest his or her time and resources in learning JupyterLab over Microsoft Excel for data analytics needs? This blog answers some critical questions the FP&A professionals have regarding JupyterLab. Let’s start with the fundamental concepts.