{"id":7349,"date":"2022-03-28T03:35:05","date_gmt":"2022-03-28T03:35:05","guid":{"rendered":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/?post_type=article&#038;p=7349"},"modified":"2024-10-18T10:59:50","modified_gmt":"2024-10-18T10:59:50","slug":"throughput","status":"publish","type":"article","link":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/article\/throughput\/","title":{"rendered":"Throughput"},"content":{"rendered":"<p>Start with the video first to get a better grasp of the topic!<br \/>\n<iframe loading=\"lazy\" title=\"Learn to Plot Throughput Widget using Nimble Analytics\" src=\"https:\/\/player.vimeo.com\/video\/956929625?dnt=1&amp;app_id=122963\" width=\"500\" height=\"281\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write\"><\/iframe><\/p>\n<table style=\"line-height: 10px; height: 77px; width: 99.2704%; border-collapse: collapse; background-color: #f7f7f7;\">\n<tbody>\n<tr style=\"height: 108px;\">\n<td style=\"width: 100%; height: 77px;\">\n<p style=\"text-align: left;\"><strong>Skip Ahead to:<\/strong><\/p>\n<p style=\"line-height: 10px; text-align: left;\"><a href=\"#Overview\">Overview<\/a><\/p>\n<p style=\"text-align: left;\"><a href=\"#Configuration\">Configuration<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2><a id=\"Overview\"><\/a>Overview<\/h2>\n<p class=\"whs1\">Throughput, which is quite similar to Agile Velocity metric, indicates the amount of work being done in a given period. The unit of work can be interpreted in terms of user stories, story points or others. Throughput can be a useful indicator in understanding how well the team or the organization is performing against the lead time and the target delivery date and turning stories into working features.<\/p>\n<p class=\"whs1\">You can measure throughput in terms of the number of cards delivered for a specified period. You can also track the break-up of the cards delivered, based on a specific attribute such as priority, class of service, size and so on. A SCRUM team can effectively plan a Release or Sprint by measure throughput in terms of card estimates or points delivered in a Release or Sprint.<\/p>\n<p class=\"whs1\">So, you can drive following key information from this Throughput chart:<\/p>\n<p class=\"whs2\">\u2022 Track how much effort your team has reported as complete for each release or time period.<\/p>\n<p class=\"whs2\">\u2022 Estimate how much backlog effort your team can handle in future releases\/time periods if your team composition and duration stay constant.<\/p>\n<h3><a id=\"Configuration\"><\/a>Configuration<\/h3>\n<p class=\"whs1\"><span style=\"color: black;\">To configure a CFD chart, perform the following steps &#8211;<\/span><\/p>\n<p class=\"whs1\">1. Click the\u00a0<b>Add Widget<\/b> icon on the Analytics page. The Analytics Builder appears.<\/p>\n<p class=\"whs1\">2. Click the\u00a0<b>SKIP<\/b> button at the bottom right of the Analytics Builder to see the <b>Standard Widgets<\/b>\u00a0screen.<\/p>\n<p class=\"whs1\">3. From the\u00a0<b>Lean Analytics<\/b>\u00a0section, click the\u00a0<b>Throughput<\/b>\u00a0chart. The\u00a0<b>Settings<\/b>\u00a0page appears.<\/p>\n<p><a href=\"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-content\/uploads\/2022\/03\/settings_throughput.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-9534\" src=\"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-content\/uploads\/2022\/03\/settings_throughput.jpg\" alt=\"\" width=\"900\" height=\"490\" srcset=\"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-content\/uploads\/2022\/03\/settings_throughput.jpg 900w, https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-content\/uploads\/2022\/03\/settings_throughput-300x163.jpg 300w, https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-content\/uploads\/2022\/03\/settings_throughput-768x418.jpg 768w\" sizes=\"(max-width: 900px) 100vw, 900px\" \/><\/a><\/p>\n<p class=\"whs1\"><span style=\"color: black;\">To plot the Throughput widget, \u00a0specify the following information:<\/span><\/p>\n<p class=\"whs1\"><b>Data Criteria<\/b><\/p>\n<ul class=\"whs5\" type=\"disc\">\n<li class=\"p\">\n<p class=\"whs6\">Workitem type:\u00a0Select the workitem type based on your requirement.<\/p>\n<\/li>\n<li class=\"p\">\n<p class=\"whs7\"><b>Start Date and End Date<\/b>:\u00a0Select a specific period, i.e. the Start Date and End Date from the calendar to limit the scope of chart data. View charts by selecting appropriate dates to analyze the recent performance of the team against the previous duration or the outcome of any process change. The chart considers cards that are lying in the chosen lanes\/stages during that date range.<\/p>\n<\/li>\n<li class=\"p\">\n<p class=\"whs7\"><b>Select Filter:<\/b>\u00a0Select or create a filter to apply on the specified data.<\/p>\n<\/li>\n<li class=\"p\">\n<p class=\"whs1\"><b>Lane<\/b>: \u00a0Select the lane from the list box for which you want to plot the chart.<\/p>\n<\/li>\n<li class=\"p\">\n<p class=\"whs1\"><b>From<\/b>\u00a0and<b>To Column:<\/b>\u00a0Select the exact stages for which you want to generate by defining the Start Column and End Column. The charts consider all cards that exited the last column or have moved to or beyond Done column type and may or may not have entered the Start Column during the selected date range.<\/p>\n<\/li>\n<\/ul>\n<p class=\"whs1\"><b>Dimensions and Settings<\/b><\/p>\n<ul class=\"whs5\" type=\"disc\">\n<li class=\"p\">\n<p class=\"whs1\"><b>X Axis (Date Range):<\/b>\u00a0Snapshot of time (Daily, Weekly, Monthly, and Quarterly) for Analytics to be rolled up or unrolled on the X-axis of the chart. If you select the time unit as Weekly, then please remember that the week is considered from Sunday to Saturday.<\/p>\n<\/li>\n<li class=\"p\">\n<p class=\"whs1\"><b>Y Axis (Card Data):<\/b>\u00a0You can choose to plot the chart by \u2018Card Count\u2019 or \u2018Story Points\u2019 (provided you have Story Points entered for cards). Estimate entered for a Card can be interpreted as days\/hours\/story points (as selected by the enterprise).<\/p>\n<\/li>\n<li class=\"p\">\n<p class=\"whs1\"><span style=\"color: black;\">\u00a0<\/span><span style=\"color: black;\"><b>Stacked By: <\/b><\/span><span style=\"color: black;\">Select the option (Priority, Class of Service, Card Type and so on) based on which you want to stack the chart bar.<\/span><\/p>\n<\/li>\n<\/ul>\n<p class=\"whs1\"><b>Note<\/b>: The chart considers the cards that have exited the End Column or moved to or beyond the Done column type in the date range and also cards that may have skipped the Start Column through the End Column. Throughput is calculated based on the time the card entered any column in between the Start column and the End column to the time it was moved out of the End column. But, if the End column is tagged as Done column type, then the throughput is calculated till the card\u2019s entry into the End column, not based on its exit from the End column.<\/p>\n<p class=\"whs1\">If you select all or multiple columns for plotting the chart, then the throughput is calculated based on the archived cards and any cards that enter into the Done column type or move beyond Done column type.<\/p>\n<p class=\"whs1\">On the Throughput chart, hover over a bar to view the attribute and the throughput number. The drill-down capability on the <a id=\"VideoReference\"><\/a>Throughput chart helps you analyze the completed cards that contributed to the Throughput number. Click the bar to see the list of completed cards in a pop-up. You can go to the card details by clicking on a card on the list.<\/p>\n<div class=\"helpful-block-content wth-theme-thumbs\" data-title=\"\" >\n<ul>\n<li><span class=\"wth-title\">Was this helpful?<\/span><\/li>\n<li><a data-post=\"7349\" data-post-url=\"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/article\/throughput\/\" data-post-title=\"Throughput\" data-response=\"1\" href=\"#\" class=\"wth-green-btn icon-thumbsup\">Yes<\/a>&nbsp; &nbsp;<a data-response=\"0\" data-post=\"7349\" data-post-url=\"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/article\/throughput\/\" data-post-title=\"Throughput\" href=\"#\" class=\"wth-red-btn icon-thumbsdown\">No<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"author":1,"featured_media":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","format":"standard","multi-rating":{"mr_rating_results":[]},"_links":{"self":[{"href":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-json\/wp\/v2\/article\/7349"}],"collection":[{"href":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-json\/wp\/v2\/types\/article"}],"author":[{"embeddable":true,"href":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-json\/wp\/v2\/comments?post=7349"}],"version-history":[{"count":10,"href":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-json\/wp\/v2\/article\/7349\/revisions"}],"predecessor-version":[{"id":19807,"href":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-json\/wp\/v2\/article\/7349\/revisions\/19807"}],"wp:attachment":[{"href":"https:\/\/www.nimblework.com\/knowledge-base\/nimble\/wp-json\/wp\/v2\/media?parent=7349"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}