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Creating a Masterpiece from Financial and Nonfinancial Data

Data Quality
Management Reporting
SEC Reporting
David surrounded by numbers
6 min read
Published: June 4, 2020
Last Updated: April 25, 2023

With over 1 million visitors each year, Michelangelo’s statue of David is perhaps the most adored sculpture in the world. 

Cut from a single slab of marble and standing over 17 feet tall, the statue had a rocky start (pun certainly intended). It began as a rough outline of legs, feet, and a torso and switched between a handful of artists for nearly half a century before the exceptionally clever Renaissance artist Michelangelo was commissioned to finish the project. 

What does one of history's greatest works of art have to do with your data, you ask? Well, creating something beautiful out of all the data, systems, and collaborators may also seem like a daunting task, but there are lessons to be learned from Michelangelo's journey from raw materials to masterpiece. Let's take a look. 

Don't let distractions or detractors hold you back

As you can imagine, a project the scale of the statue of David is tremendously difficult. One wrong chisel mark could have ruined years of work. On top of that, the previous attempts at crafting the piece forced Michelangelo to inherit constraints over his vision. 

Yet, he remained undeterred. When asked about the challenges he encountered while sculpting his marble masterpiece, his response was simple:

“It is easy. You just chip away the stone that doesn’t look like David.”

No one knows whether that was actually what Michelangelo said, but the results of his work remain. The statue overcame its own challenges, just like its subject—David was meant to symbolize the strength of the Republic of Florence, which was surrounded by more powerful rival states.

In short—don't give up hope on transforming your big data project just because things look intimidating now.  

A data renaissance requires a plan

To create your own masterpiece out of a mishmash of data requires the same two things: a strong foundation and solid vision. 

Whether you’re starting with a clean canvas or picking up where others left off, achieving a lean data analytics structure likely requires you to start refining HOW you provide that team with better data, resources, and structure (especially if you want to keep your new Chief Data Officer happy). 

At Workiva, we’ve found that it sometimes requires our customers to also simply cut away what doesn’t belong. Make those hard decisions in the early stage, and then you can enjoy a more fruitful and fulfilling working environment.

Assess the situation 

Any IT organization that truly desires continuing success needs to stay on mission with a clear focus and lean thinking. Although IT has faced this issue for more than 20 years, the need is ever greater. 

You can point to a variety of factors why, but one of the main reasons is that all of the systems IT operates for the business are becoming more complex. And, it doesn’t help that business line users threaten to make their decisions many times without IT, leading to ownership issues and maintenance of tools that are cumbersome, expensive, and sometimes just plain clunky. 

This is your inventory. These systems represent the marble, canvas, and tools you have to begin carving your vision. You need to make sure they are right for the job at hand.

Think lean when creating your vision

This concept of "lean" is intended to clear away wastes from work processes—just like carving away the excess marble to form your final statue. And, finding ways to create more value for customers using fewer or less resources is something every CFO wants to hear. 

When you are taking an inventory of your tools, you have to start cutting away like you are standing in front of your own statue of David.

Intelligence, by definition, is the "ability to acquire and apply knowledge and skills." Many organizations are good at getting the block of stone (massive amounts of financial and nonfinancial data), but not everyone can get what they want out of it (actionable insights). Unfortunately, that's because they allow the chaos of process and people to get in the way of generating rock-solid business intelligence. 

Start carving away at reporting waste

At this stage, it’s important to follow Six Sigma best practices. Whether you have a Six Sigma background or not, the key tenets are relatively straightforward. 

Here’s a quick primer to help you to categorize things in the Six Sigma framework and how they relate to office operations and reporting "waste" within analytics: 

  • Defects – Unused reports, defective results, systems that don’t work but should. (You know, those things that make you want to throw a server out the third-story window.) 
  • Overproduction – Excess of product or service is produced without regard for demand—examples include reports users don’t access, data generated with no clear value or purpose.
  • Waiting – Simple things like processing security requests, not enough processing time or people, bogged systems, waiting in line for a data feed project. 
  • Neglecting or not utilizing talent – Misuse of significant resources, such as investing in data scientists, but relegating them to a reporting role or data entry.
  • Transportation – Unnecessarily moving data from edge devices to permanent storage, or using tools like email and inefficient processes for moving reports and facts. For example: How many people are still using Excel® and emailing results?
  • Inventory excess – Too many reports, tools, data projects, conversion projects, applications, or maintaining data stores in obscure locations that are not registered or traceable.
  • Motion waste – Too many clicks, saves, API movement between systems, refreshes, run times. Anything that requires motion, but then starts stealing time, or perhaps data transfer costs.
  • Excess processing - When a task involves more work than necessary, or a process produces a higher quality deliverable than required by the end user.

How Workiva can help 

To solve for all this, Workiva practices what we call “starting with the end in mind”—or rather, picking out what you want—or more importantly, need—your David to look like. Then, we help you carve away the excess in your process. 

If you have spent a ton of time in your analytics and data office solely for difficult data reporting, trust us—your CAO or CDO will love you for it.

At Workiva, we've built technology with very specific end results in mind. As a result, we've helped thousands of organizations tackle problems where the report styles were extremely fixed, such as SOX compliance, SEC reporting, and so on. We've had to make documents dance like nobody ever had before. 

One thing we are really good at is pinpointing the exact report that your team says “WE MUST HAVE.” (You know the one: the report that your boss shares with their boss, and for some reason it HAS to be in PowerPoint®.)

Then, with that exact report in mind, our technology allows you to start chipping away at the waste processes you don’t need, keeping only what you do. (Surprise, you may not need PowerPoint after all!)

For example, do you have users who still like cutting and pasting? Workiva offers up a solution where cutting and pasting DOESN’T cause you revision issues, because everything is connected. Literally. Sure, your users can still cut and paste, but when that number changes at the source, it updates automatically everywhere else. Plus, you always know exactly where, when, and what source it came from originally. 

All in all, the Workiva platform allows you to create beautiful reports from a bedrock of data. So, when you want to start carving your next data analytics project with the CDO, based on a lean model and tools that perform, give us a call. We're ready to help you build that masterpiece.

Excel and PowerPoint are registered trademarks of Microsoft Corporation in the United States and/or other countries.

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