What a clear pain-revealing question from a client this week!
Everyone near me knows how I love a great question. Questions set the stage for learning, for digging deeply into the art of the possible, and most importantly, for creating tangible value.
The short answer: Absolutely
Earnings calls are critical to publicly traded companies’ success. They also eat time like a foraging boar, consuming everything in its path. Over and over again. Every quarter.
Imagine a better way to do this - using AI.
This savvy CEO is envisioning all of the time he’d recover throughout the year.
💡What he’s likely not realizing is the 40% quality improvements he’ll also get!
Here’s a breakdown of the process, typical time spent every quarter, and how AI helps at each step:
1️⃣ Data Collection and Analysis: 2-4 weeks.
AI automates the gathering and preliminary analysis of financial and operational data, significantly reducing time and improving accuracy.
2️⃣ Drafting the Report: 2 weeks to 1 month.
AI, particularly large language model tools like ChatGPT, draft version one of the narrative sections of the report, streamlining the process.
🔦Here’s the BIG opportunity for quality improvement. With the first version heavy lifting done by AI, the highly paid experts are able to analyze what’s been created. They now have the data, visualized into a report, and the TIME to really look at what it’s saying. This leads to the addition of their own identified deep insights.
This human+AI formula creates superior results. 🏋️♂️
3️⃣ Review and Compliance Checks: 2-3 weeks.
AI supports compliance checks by identifying potential issues against regulatory standards, though human oversight remains crucial.
4️⃣ Finalization and Distribution: About 1 week.
AI helps in the final formatting and distribution, ensuring consistency, with less manual effort.
🪓I commonly use AI tools to create gorgeous visuals based off of completely unformatted text docs in under 5 minutes.
🎬Start Small NOW
Each piece of this process can benefit from AI, but holds varied levels of difficulty. So start simply!
Don’t try to do the entire process all at once. Instead, here’s the recommended order to tackle the steps from simplest to most complex (difficulty scale of 1-5)
1️⃣ Finalization and Distribution
With Copilot: Difficulty Rating - 1
Automating the finalization and distribution phase is comparatively less complex, focusing on formatting and consistency checks.
Success relies on clearly defined templates and standardized distribution channels.
2️⃣ Drafting the Report
With Copilot: Difficulty Rating - 2
AI can aid in drafting narrative sections, with complexity arising in accurately interpreting and contextualizing financial data.
The process depends heavily on the integrity of input data and AI’s industry-specific knowledge.
🚨Remember-this step has huge QUALITY improvement potential, so this is definitely worth investment!
3️⃣ Data Collection and Analysis
With Copilot: Difficulty Rating - 3
The integration of AI is notably challenging due to the fragmented nature of corporate data landscapes.
The task involves ensuring data quality across diverse sources and formats, requiring sophisticated data integration strategies.
4️⃣ Review and Compliance Checks
With Copilot: Difficulty Rating - 3
Utilizing AI for compliance checks involves understanding regulatory nuances and the dynamic nature of legal standards.
This step requires a combination of AI automation and expert human review to ensure thorough compliance.
Conclusion
Tackling this process one piece at a time, in this order, ensures that you get quick results while also not exposing yourselves to data inaccuracies.
And please - embrace the philosophy that humans+AI create the best results! I see this play out over and over everyday.
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If you're mulling over one of these great questions, let my team help. Our approach gets you to tangible business value with a working enterprise solution in days/weeks. Not months or years!