WorkBuddy can be used for table analysis and Kanban board organization, but the premise is that your Excel must at least be understandable by AI: clear table headers, clear field meanings, complete time ranges, and consistent metrics. Simply throwing in a file with multiple worksheets, lots of merged cells, and notes floating everywhere usually doesn't work well.
Tencent's Technology Public Welfare Digital Toolbox has already listed "Excel instantly into a visual Kanban" as an example of WorkBuddy application, indicating its suitability for office data organization, chart planning, and Kanban drafts. What truly affects the outcome is not whether it generates a graph, but whether it correctly understands your data columns and business scope.
There are three things to do before uploading
First, change the table header to a name that is instantly understandable, such as "Order Date," "Channel," "Actual Amount Received," "Refund Amount," and don't just write A, B, or Amount 1. Second, remove irrelevant notes, blank lines, merged cells, and temporary notes. Third, clearly state the metrics you want to see: sales, average transaction value, conversion rate, gross profit, or inventory turnover.
If multiple tables are involved, it's best to explain how they relate to each other. For example, use the order number for the order form, the customer ID for the customer table, and the SKU for the product list. WorkBuddy can help you organize relationships, but it shouldn't guess the primary key in your business system for you.
How to make it produce more like a Kanban board?
Don't just say, "Help me analyze," but have it output according to role: show the boss key conclusions, abnormal causes, and action suggestions; For operations, you need to break down channels, timing, products, and regions; For finance, you need the caliber, missing items, and list of outliers.
A more reliable instruction is: first check the quality of the fields and data in this Excel file, then suggest four charts suitable for Kanban, explaining each chart's horizontal and vertical axes, filtering criteria, and business meanings. This way, it won't rush to generate a beautiful image right away, but will first help you judge whether the data supports your conclusion.
Don't rush to draw conclusions about these situations with AI
If the table contains a lot of manual rewriting, cross-month variations in caliber, refunds and revenue mixed together, or if certain fields are seriously missing, the Kanban generated by WorkBuddy can only serve as a draft. You need to have it list the data issues first, then decide whether to supplement the data, split the caliber, or just do trend observation.
The key to the Kanban table isn't letting AI create the chart, but rather avoiding packaging erroneous data as sophisticated. First, organize the header and caliber, then let WorkBuddy analyze it, and the result will be closer to a deliverable office board.
