Why Tax Needs a ‘Front-of-the-Line’ Technology Mindset
Tax leaders who want to optimize their supporting technology can get started by addressing a pervasive tail-end challenge.
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When companies let loose artificial intelligence (AI) algorithms to sniff out hidden treasures within vast collections of data, the results can be astounding, and highly profitable.
Data analytics is a straightforward concept—the process of extracting meaning from raw data—that has achieved enormous technological sophistication in recent years. When companies let loose artificial intelligence (AI) algorithms to sniff out hidden treasures within vast collections of data, the results can be astounding, and highly profitable.
However, companies cannot capitalize on data analytics’ findings unless that meaning is clearly communicated to the folks in the business who act on those insights. Sometimes, analytics teams communicate less than effectively, according to a CIO article by John Edwards that examines “sure-fire ways to sour the business on analytics.”
Recognizing when something is done incorrectly, of course, represents a helpful way to learn how to do something better. On that count, the article is packed with instructive suggestions on how to get key decision-makers excited about analytics.
John was kind enough to include some of my thoughts in his discussion on the importance of understanding your audience when you’re telling your analytics story. It’s a simple yet important point, and worth bearing in mind as the tax data analytics mindset takes hold in more corporate tax departments. Like anyone else who gets excited about the power of numbers and what you can do with them, tax executives should understand their audiences when promoting their ideas.
I’ll rephrase John’s key points here while recommending that you take a look at the article for more details and context:
Done right, tax analytics can help tax functions make smarter, real-time decisions to improve business performance and drive strategy.
A tax-specific solution for the data validation, analysis, and transformation steps that are required to properly support the indirect tax compliance process.
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