{"id":263,"date":"2006-11-27T00:22:04","date_gmt":"2006-11-27T07:22:04","guid":{"rendered":"https:\/\/staging.opexlearning.com\/resources\/263\/littles-law-for-product-development"},"modified":"2014-10-03T15:50:40","modified_gmt":"2014-10-03T20:50:40","slug":"littles-law-for-product-development","status":"publish","type":"post","link":"https:\/\/staging.opexlearning.com\/resources\/littles-law-for-product-development\/263\/","title":{"rendered":"Product Development Process and Application of Little&#8217;s Law"},"content":{"rendered":"<div class=\"a296a24fa2fc69ef5487857f02f111e8\" data-index=\"9\" style=\"float: none; margin:10px 0 10px 0; text-align:center;\">\n<script async src=\"\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js\"><\/script>\r\n<!-- Single Post readerboard -->\r\n<ins class=\"adsbygoogle\"\r\n     style=\"display:inline-block;width:728px;height:90px\"\r\n     data-ad-client=\"ca-pub-8207522353004717\"\r\n     data-ad-slot=\"1144967431\"><\/ins>\r\n<script>\r\n(adsbygoogle = window.adsbygoogle || []).push({});\r\n<\/script>\n<\/div>\n<p>A queueing system is a model with the following structure: customers arrive and join a queue to wait for service given by n servers. After receiving service, the customer exits the system. A fundamental result of queueing theory is little&#8217;s law. This article shows how the Product Development Process and Little&#8217;s Law are best friends, if you let them.\u00a0You can also view all 40+ articles on <a title=\"articles on queueing theory\" href=\"https:\/\/staging.opexlearning.com\/resources\/queueing-theory\/\">Queueing Theory<\/a>.<\/p>\n<p><strong>Theorem<\/strong>: for a queueing system in steady state, the average length of the queue is equivalent to the average arrival rate multiplied by the average waiting time. in other words,<\/p>\n<blockquote><p>L = \u00ce\u00bbW<\/p><\/blockquote>\n<p>Little&#8217;s Law is a fundamental principle in business, mathematics, and has applications to many real-world problems. One of those real-world problems is in product development.<\/p>\n<p>First, a definition:<\/p>\n<ul>\n<li><strong>WIP\/TIP<\/strong>: Work-in-process of Things-in-process. For the purposes of this article, they are synonymous. Being &#8220;in-process&#8221; means the work or things have entered a state-of-affairs but have not yet exited. The &#8220;work&#8221; can be anything: materials, components, sales orders, software code, software testing, projects, customer inquiries, checks, phone calls to return reports suppliers to qualify, repair orders, or emails waiting to be answered, etc.<\/li>\n<\/ul>\n<p>For product development, we can use a transformation of Little&#8217;s Law, like the following:<\/p>\n<blockquote><p>[(Throughput) = (Things-in-Process) \/ (Average Completion Rate)]<\/p><\/blockquote>\n<p>What this equation tells us and what experience has shown time-after-time, is that the number one driver of Product Development Cycle Time are the &#8220;things-in-process&#8221;. There is no quicker way to reduce the cycle time by which your company can get a product from concept-to-delivery than through first prioritizing all the projects or products and focusing on the ones that make strategic and tactical sense, and killing the lower priority projects.<\/p>\n<p>You might be thinking: &#8220;True, but couldn&#8217;t we also increase the average completion rate&#8221;? You&#8217;re right, but the impact of doing that is much lower than reducing the TIP &#8212; that is, influencing the average completion rate is rather difficult and is often a function of available resources, scope creep, market demands and changes, etc. Here&#8217;s the bottom line: the number one driver for shipping products quicker is by focusing on the important ones and killing the unimportant ones.<\/p>\n<h2>Product (Project) Selection Prioritization Matrix<\/h2>\n<p>One easy but effective way or prioritizing a list of projects or products is to group-rank them based on variables. Below is an example of a prioritization matrix that I&#8217;ve used in the past:<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-10942\" src=\"https:\/\/staging.opexlearning.com\/resources\/wp-content\/uploads\/2006\/11\/matrix-prioritization.jpg\" alt=\"matrix-prioritization\" width=\"500\" height=\"285\" srcset=\"https:\/\/staging.opexlearning.com\/resources\/wp-content\/uploads\/2006\/11\/matrix-prioritization.jpg 500w, https:\/\/staging.opexlearning.com\/resources\/wp-content\/uploads\/2006\/11\/matrix-prioritization-300x171.jpg 300w\" sizes=\"(max-width: 500px) 100vw, 500px\" \/><\/p>\n<p>Here are some general steps:<\/p>\n<ol>\n<li>List all the projects\/products<\/li>\n<li>As a group of core stakeholders and decision-makers, agree on a selection criteria, or list of variables on which to judge each item on the list.<\/li>\n<li>As a group, score each item against each variable. Use a likert scale that makes sense.<\/li>\n<li>Multiply the various scores across to get an overall score.<\/li>\n<li>Rank the projects and sort from highest overall score to the lowest. Then, review to see if the ranking makes sense.<\/li>\n<li>If done right, then the important initiatives rise to the top and the unimportant ones fall to the bottom.<\/li>\n<li>Decide as a group, based on available resources and strategy, where the cut-off score will be. Cut, then discard the items below that score and focus on the ones above that score. I don&#8217;t suggest you table or postpone items below the cut-off, because realistically they will be discarded.<\/li>\n<\/ol>\n<h2>Conclusion<\/h2>\n<p>To drive throughput, you can influence the size of WIP\/TIP or increase the average completion rate. A balanced approach is good, but you&#8217;ll gain a higher yield by focusing on reducing WIP\/TIP. In order to do that, you must decide as an organization what to focus on &#8212; on items that will bring the biggest return to your customer, shareholders, and the company.<\/p>\n<!--CusAds0-->\n<div style=\"font-size: 0px; height: 0px; line-height: 0px; margin: 0; padding: 0; clear: both;\"><\/div>","protected":false},"excerpt":{"rendered":"<p>A queueing system is a model with the following structure: customers arrive and join a queue to wait for service given by n servers. After receiving service, the customer exits the system. A fundamental result of queueing theory is little&#8217;s law. This article shows how the Product Development Process and Little&#8217;s Law are best friends, [&hellip;]<\/p>\n","protected":false},"author":12327,"featured_media":10942,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[29],"tags":[641,643,642,640],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Product Development Process and Application of Little&#039;s Law<\/title>\n<meta name=\"description\" content=\"Product Development Process and Application of Little&#039;s Law. 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