Part 1: Data Analysis Delivering 100% accurate orders to customers is at the cor

Part 1: Data Analysis
Delivering 100% accurate orders to customers is at the core of our operation. One key metric we use to track our success in this promise at DashMart is INF, shorthand for Item Not Found. This metric is defined as: % of orders that include at least 1 item that our team could not find during the picking process.
Associates pick orders using a Shopper App on phones, and scan items to verify that they’ve picked the right items. If they can’t find an item, they press an “Item Not Found” button in the app, which triggers an INF incident and allows the associate to refund the customer for that item or contact them to determine a suitable replacement item.
Please review this spreadsheet with 1 week of data from one of our warehouses, and respond to the following questions:
Which product category has the most INF instances? How many instances were there?
Which associate (aka “shopper”) had the most INF instances? How many did they have?
Which individual product had the most INF instances?
How did you find the answers for questions 1-3?
What are some reasons that products might be marked INF?
Part 2: Project Planning
Imagine that you are the DashMart Site Manager for the site whose data you just analyzed. Your overall site INF was 7.41% for last week, and our current target for this metric is 1.8%. Your manager asks you to put together a project plan to tackle this metric and bring it to goal over the next 4 weeks.
Please outline a detailed plan to address this metric over the next 4 weeks.
Your plan should include the following:
What questions would you have for your manager before kicking off this project?
How would you communicate this plan with your team and inspire them to work toward reducing INF?
How would you track progress and measure success?
What would you do if you noticed two weeks in that you weren’t improving?

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