Transforming Data into Strategy with Shasha Guan

Timing. While large datasets and advanced analytics have been available for years, the ongoing challenge across industries remains delivering insights at the right moment. Providing actionable data precisely when it’s needed—often on short notice or in real time—continues to be one of the greatest hurdles for finance leaders.

It would not be appropriate to simply say, “take a wild guess.” Instead, it’s essential to identify comparables among companies of similar size and circumstances to substantiate strategic decisions. In practice, major strategic choices tend to be mid- to long-term and focus primarily on generating revenue or reducing costs. Relevant data for those decisions is generally available from market research firms, and it’s crucial for a CFO to subscribe to at least one such service to ensure access to reliable comparables.

Secondary strategic decisions usually support those primary ones, often involving capital investments in equipment, fixed assets such as buildings or leases, and payroll. These are collective decisions made at the company level, not by a single individual. However, I always make sure my perspective is represented—rooted in analyzing company cash flow across monthly, quarterly, and annual periods, assessing performance against board-approved budgets, and considering available working capital for other initiatives.

Speed and efficiency. Most organizations already have clearly defined frameworks that outline which data is required for specific decisions. The real differentiator today lies in reducing the time it takes to prepare and present that data in a way that informs action. This program provided methods to tighten that process—to transform data analysis into decision-ready insights more quickly and confidently.

Given my background in auditing, the contextual analysis pillar was less of a revelation to me than precision questioning. Despite conducting countless interviews with key stakeholders and board members, engaging in precision questioning during the program gave me new perspective—particularly on how artificial intelligence can enhance my work.

AI’s potential for efficiency is undeniable, but understanding its current limitations and applications was especially enlightening. The experience raised my own performance standards and inspired me to evaluate how emerging technologies could streamline core financial processes while maintaining accuracy and control.

I wish I knew (IWIK) is a tool I greatly appreciate. I’ve often thought about how valuable it would have been to ask previous teams, “What do you wish you had known?” IWIK encourages exactly that kind of proactive reflection before finalizing plans or decisions.

It’s simple to implement yet has significant impact. It helps teams anticipate potential gaps early on and ensures that experience and intuition are fully leveraged. Senior employees may not always be as familiar with emerging technologies, but their institutional knowledge is invaluable. IWIK helps integrate that expertise with the perspectives of newer staff, creating more balanced and effective teams.

The group project was an enjoyable and valuable experience. It helped strengthen my business decision-making abilities, while also developing leadership and teamwork skills that extend beyond the workplace.

Working with participants from different backgrounds exposed me to a variety of personalities and approaches to problem-solving—each offering insights applicable to real-world scenarios. This diversity helped our team identify blind spots, reach consensus, and consider alternative methods that might not have surfaced otherwise.

What stood out most was how every team member demonstrated leadership—balancing individual goals with collaboration. I also learned that objectives can sometimes be achieved through unexpected means, such as taking a different route to reach the same goal. The experience reinforced the value of adaptability, awareness of blind spots, and the importance of maintaining an open mindset when leading teams.

Yes, I’m developing a checklist of what not to do—common pitfalls that reduce clarity and impact when presenting financial data. The goal is to keep communication concise, decision-oriented, and directly tied to organizational priorities.

Since completing the program, I’ve begun researching AI-driven financial tools to evaluate how automation can improve efficiency and accuracy across the finance function. I now approach technology investments not only as operational upgrades, but as strategic decisions that can reshape the way finance supports the broader business.

I’ve updated my criteria for identifying potential team members and refined the key discussion points I use during interviews and team meetings. I also plan to introduce new challenges in our regular meetings—designed to stretch analytical thinking, creativity, and decision-making speed. This approach helps ensure the team continues to grow and adapt in a fast-changing business environment.

Take the class if you have the time and budget for it. If not, read the book. The framework is practical, adaptable, and directly relevant to how finance leaders make decisions under pressure.

It reminded me that data can make anything seem believable if we’re not careful about its source. The lesson is to remain critical—always questioning where the data comes from, how it was gathered, and whether it truly supports the story being told.

I would recommend it to accounting and finance professionals at organizations with more than $500 million in annual revenue, especially in the manufacturing sector, where complex data and fast decisions often intersect.

Engaging, exciting, and intriguing.