Mar 13, 2018 | Elizabeth Kaydanovsky
Is Your Team Spending Too Much Time Reporting?
How much time do people spend on data reporting? The answer is A LOT! In fact, almost two thirds of analysts surveyed in our recent State of BI Reporting research report said that more than half of their weekly activities are dedicated to manual reporting tasks. Operational performance reporting has become increasingly more vital, governed, and (everyone’s favorite) time-consuming.
The problem? We still have the same 24-hour day and 40-hour workweek. While data reporting requirements are mounting, we have two options: delegate or automate.
Chart Source: State of Business Intelligence Reporting Report by Narrative Science
Delegating tasks means more headcount. More headcount means more cost. To keep up with required compliance monthly, quarterly, semi-annual, and annual reporting, you need to build out a team to spread out that work.
Then there is a learning curve. As you build out your team, it takes time for report authors to fully get on board. This takes chunks of time and resources, particularly from other team members. As new rules and standards develop, the team must constantly be trained to ensure consistency and standardization in its reporting practices. This makes the work demanding and can be stressful to meet deadlines.
Lastly, delegating tasks means more room for error. Human error is unavoidable. Even with multiple sets of eyes reviewing the report, the opportunity to miss something or get a calculation or fact wrong looms. Per PwC, more than 90% of spreadsheets contain serious errors, while more than 90% of spreadsheet users firmly believe that their models are error-free. Reporting mistakes happen all the time in financial reporting; if they are minor and without intent, the worst that can happen is fines. But if data is purposely and grossly manipulated, the penalties can be hefty and punitive in nature.
Automation may take more time up front to set up, but it is your best friend in the long run. And it’s also cheaper, as you don’t need to continually hire and train staff to keep things going.
Here’s my motto: if you can automate something in your life, do it! For example, something as simple as setting up recurring monthly payments to pay down a credit card is a lifesaver for me. I do monitor it, but I don’t have to think about it. If I don’t have to think about it, I don’t have to worry about it. I know that my credit card will be paid off in a timely and effective manner, thanks to automation, and I can spend my time focusing on more interesting things. What if I said you could automate long, time-intensive monthly and quarterly data reporting?
For example, one company I worked with increased its touch-points with clients by going from manually producing 300 reports for only top clients to automatically creating smart, insightful reports for 6,000 clients. This way, the company now treats all of its clients with the same level of service.
And the best part? Automating reporting with natural language generation (NLG) not only automates manual data analysis and reporting tasks, but it transforms the data at machine speed (we’re talking immediately) into natural, easy-to-understand narratives that sound like a human wrote it. Quill can handle complex data sets and has the power to run accurate reports at large scale and high frequency. And Quill learns the context of your business, meaning it’s applicable for use cases outside of financial data reporting (marketing, operations, consulting, etc.)
By automating reporting with NLG, those who report can get ahead of deadlines and have a higher touch-point with all their clients. They can produce valuable, digestible insights for more people than they were ever able to before, with fewer resources.