Today data is no longer used for just operations and compliance; it is the driving force behind company’s strategy and performance. To leverage data for improved business performance, employees must think like a “Data Person” - a Data Scientist or a Decision scientist. But who exactly is a Data Person and how can one become a Data Person? A Data Person is someone who thinks critically, interprets data, and applies insights to drive decisions and results—whether in business, research, or everyday problem-solving. They don’t just collect or analyze data; they ask the right questions, challenge assumptions, transform data into actionable insights, and collaborate with relevant stakeholders to implement and improve business performance. In this regard, here is my 10-step process on how to become a “Data Person”.
As we enter our fourth year of running this poll, the gap between the pillars continues to widen. For the fourth consecutive year, we surveyed the global finance community to uncover whether there have been shifts in the importance of each Pillar of CFO Success. The results tell a compelling story.
The career track of CFOs often takes them through the roles of accountant and analyst; then to controller, finance manager or treasurer. They earn well-deserved reputations for being diligent expense watchdogs, budget analyzers and cash managers; but it is a significant transition moving from controller, FP&A director or treasurer to the CFO role. This is especially true today, when nearly all CFOs are expected to play a large strategic role at their company.
Many financial teams spend countless hours getting the past right, when they could make a much more significant contribution getting the future right.
Timely financial statements are the key to creating powerful forecasting tools that build a transparent map for the future. On the other hand, laggard financial statements cloud the future and deny us a clear map to get there.
In today’s AI (Artificial Intelligence) landscape, IT, data, finance and business leaders rely on data more than ever to make strategic decisions and drive business performance. While deriving insights from LLM (Large Language Model) based tools like ChatGPT (by OpenAI), Gemini (by Google), and Copilot (by GitHub) have become much easier, effective communication of the insights derived to propel action remains a challenge for most leaders. Communicating insights goes beyond simply presenting data or KPIs or insights. It encompasses collecting the right data, selecting appropriate models, deriving insights, targeted messaging, creating trust and cultural awareness, engaging with the right stakeholders, creating impactful visuals, and more. The process of deriving and communicating insights in today’s AI centric world is as shown below.