﻿{"id":895,"date":"2025-12-08T10:14:59","date_gmt":"2025-12-08T04:44:59","guid":{"rendered":"https:\/\/blogs.infosys.com\/infosys-cobalt\/?p=895"},"modified":"2025-12-08T10:14:59","modified_gmt":"2025-12-08T04:44:59","slug":"decision-making-made-easy-using-anaplan-optimizer","status":"publish","type":"post","link":"https:\/\/blogs.infosys.com\/infosys-cobalt\/cloud-applications\/oracle\/anaplan\/decision-making-made-easy-using-anaplan-optimizer.html","title":{"rendered":"Decision Making Made Easy Using Anaplan Optimizer"},"content":{"rendered":"<p>Large organizations often face complex planning challenges, and when it comes to achieving business objectives within constraints, they necessitate trade-offs to make the best decisions possible. Understanding and predicting each possible outcome is really time consuming, and impossible in many cases. That\u2019s where Anaplan optimizer is used, Business leaders must be able to properly evaluate these planning scenarios and make timely and accurate decisions.<\/p>\n<h4><strong>Anaplan optimizer overview:<\/strong><\/h4>\n<p>Anaplan\u2019s optimization engine helps determine the optimal solution, improves planning efficiency, and makes decision-making faster.<\/p>\n<p>Anaplan optimizer uses linear programming, mathematical concepts to maximize or minimize specified objectives. \u00a0Once configured, it gives planners an objective and systematic way to consider all options, find the best solution, and steer the company in the right direction. Many common business issues are essentially resource allocation issues across targets. Anaplan optimizer can be used for improved allocation and scheduling in various business domains like supply chain, stock allocation, financial planning, sales, transportation routing etc.,<\/p>\n<h4><strong>How does optimizer work in Anaplan?<\/strong><\/h4>\n<p>With linear programming optimization, you must define objective functions and set multiple variables and constraints for the planning process. \u00a0The solution to optimization is to maximize profit or minimize cost. Optimizer can provide recommendations for a variety of complex issues, including staffing, capitalization, inventory, and much more. Figure 2 shows the structure of the optimization model.<\/p>\n<p>i)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Objective function:\u00a0 Linear equation that specifies the target, function of input variables. Objective function includes variables and constraints. The first step in optimization is to identify the problem and create the equation or formula.<\/p>\n<p>ii)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Constraints:\u00a0 Assumptions for variables, for example the maximum number of products manufactured, available distribution centers, etc., you can set many constraints. Constraints are Boolean linear functions, used to restrict the values for variables.<\/p>\n<p>iii)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Variables:\u00a0\u00a0 When you solve an equation, you will get many sets of solutions; they are variables. Optimizer will choose the most feasible solution. Variables are generally numerical values or Boolean values.<\/p>\n<p style=\"text-align: left;\">We can add the optimizer action in the dashboard or New UX pages and run the process to find the feasible solution.<\/p>\n<h4>Use Case:\u00a0 Supply Chain Network<\/h4>\n<p>Imagine a Juice manufacturing company, producing 3 types of juices, and using 3 packaging types. The supply chain planner must manage the raw materials warehouse, manufacturing plants, Distribution centers, he needs to know what to produce to increase profit and minimize cost, and decide what distribution center should serve customer warehouse, transportation facilities and what manufacturing plants should supply to the DCs.<\/p>\n<p>Supply chain planning is the process of forecasting demand and managing inventory so that we can keep costs down and deliver products faster. The goal of supply chain optimization is to fulfill global demand in the most efficient and profitable way.<\/p>\n<p>Anaplan optimizer can be used to generate optimized plans based on global demand forecast which is already present as input in Anaplan model.\u00a0 For example, distribution center and maximum plant production capacity constraints are specified in the model. Transportation costs are added to the linear equation; the objective is to reduce the transportation cost from plant to DC\u2019s.\u00a0 The optimizer generates a result which specifies what products should be shipped from each plant to Dc\u2019s and in what quantity. Supply chain managers can create multiple scenarios and compare them, select the suitable one for business. Planners can be confident in the supply chain decision they make because all possible factors have been factored into the equation.<\/p>\n<h4>Conclusion:<\/h4>\n<p>Using Anaplan optimizer, we can achieve the optimal solution in the most efficient and profitable way. Business leaders can run optimization scenarios that link the financial implications of choice to a sales or supply chain problem, allowing for quick decision-making across the entire organization. Anaplan\u2019s platform powers Optimizer, and all scenario customizations are done through the user interface. Anaplan optimizer has some limitations as well, such as the fact that it solves only linear equations and does not support version and time, and the best practice for optimizer is yet to be defined.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Large organizations often face complex planning challenges, and when it comes to achieving business [&hellip;]<\/p>\n","protected":false},"author":256,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[85],"tags":[84],"coauthors":[100],"class_list":["post-895","post","type-post","status-publish","format-standard","hentry","category-anaplan","tag-anaplan"],"acf":[],"_links":{"self":[{"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/posts\/895","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/users\/256"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/comments?post=895"}],"version-history":[{"count":5,"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/posts\/895\/revisions"}],"predecessor-version":[{"id":4621,"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/posts\/895\/revisions\/4621"}],"wp:attachment":[{"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/media?parent=895"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/categories?post=895"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/tags?post=895"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.infosys.com\/infosys-cobalt\/wp-json\/wp\/v2\/coauthors?post=895"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}