Events & Media
Three Facets of a Successful Data-Driven CFO
Is data still important? In reality, this is a catch-22 question. On one hand, we need data to drive the decision-making process. However, on the other hand, if the data is siloed, bad, outdated, or incomplete, this creates the perfect storm of unrealistic goals and horrendous decisions.
The benefits of finance automation are manifold and include improved efficiency, accelerated productivity, reduced costs and increased profits, improved scalability, increased employee value, higher employee satisfaction and better data. But there is another benefit that goes beyond the income statement and direct to your company’s balance sheet: automation can increase the value of your business.
NASHVILLE, Tenn., Nov. 1, 2021 /PRNewswire/ — Algorithms rule the world … or, at least, the world is headed that way. How can you prepare your company and its financial underpinnings not only to survive but also thrive under this new big data paradigm? In his new book, Deep Finance: Corporate Finance in the Information Age, author Glenn Hopper provides a clear guide for finance professionals and non-technologists who aspire to digitally transform their companies into modern, data-driven organizations streamlined for success and profitability.
In a time where tech companies are struggling to keep up with their workflows and processes, it’s surprising that one of the most important roles in a company (CFO) is not being utilised as much as they could be.
All of the great endeavors in human history started with a decision. From early voyages across vast and unknown oceans to the discovery of the double helix structure of DNA, our choices have defined not only the world in which we live, but our humanity itself.
Glenn Hopper has spent the past two decades helping startups transition to going concerns, operate at scale, and prepare for funding and/or acquisition. He is the author of Deep Finance: Corporate Finance in the Information Age, which serves as a strategic guide for finance departments to lead digital transformation of their companies.
Data Science is the process of applying scientific methods, algorithms, and systems to extract information from data. For the unfamiliar it can seem like inexplicable magic that happens inside a black box. But when we peel back the lid and peer inside, we see that many of the tools used by data scientists and business analysts are pretty straightforward. By breaking down these processes and how they work, we – as business managers – can better understand what data science is and how it can benefit our organizations.