roje Nae Name of Daa Recaser Lasaon D Colecten Dee Defect Types Evert Occumeroe We y Monday Ty Thursday frday OTAL y8ablens PN wong ade Nof Dt Recde L es Clecion Da wong phone arorg ten Dc Tye Evet Oenen dever Menday Tday Wey Thsdey Frdey TOTAL van rate dawn w n or los 11 ww mic not home TOTAL www.hoe NO 1 wong t 35 d p h n TN1 ne dnver vee bke doe ww. 29 A Questions from Pareto Exercise 1. What was the most significant delivery problem? 2. The histogram shows problems according to days of the week. Although the data was collected and presented this way, is this chart useful? Why? 3. If a quality improvement team decides to focus on correcting only the top three problems, what percentage of total problems could they solve? (hint: this is the 80/20 rule; in many cases 20% of problems account for 80% of all errors) 4. If the delivery quality improvement team decided to work on the van breaking down (because one of the team members likes to work on vans), as the manager of this team, what advice or direction would you have for them? Project Name: Name of Data Recorder: Location: Data Collection Dates: Defect Types/ Event Occurrence Monday Tuesday Wednesday Thursday Friday TOTAL wrong qty wrong address not home wrong phone wrong item missed app-late no driver van broke down order lost misc TOTAL elivey ReablenS Project Name Name of Data Recorder Location Data Collection Dates month perioel Defect Types/ Event Occurrence Monday Tuesday Wednesday Thursday Friday TOTAL Wrong gty 24 wrong address not home N Wrong phone |1 wrong item N missed app-late HI N N 35 HLI11 11 1 no driver IN van broke down 3 77 order lost 20 misc TOTAL