{"id":1596,"date":"2024-01-26T16:52:47","date_gmt":"2024-01-26T15:52:47","guid":{"rendered":"https:\/\/scnode.com\/?page_id=1596"},"modified":"2024-11-29T11:53:39","modified_gmt":"2024-11-29T10:53:39","slug":"problem-solving-scm","status":"publish","type":"page","link":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/","title":{"rendered":"Problem solving in supply chain processes"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"1596\" class=\"elementor elementor-1596\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a3b6d15 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-parent\" data-id=\"a3b6d15\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f2e8b68 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"f2e8b68\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">PROBLEM SOLVING IN SUPPLY CHAIN PROCESSES<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7c58e3a e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-parent\" data-id=\"7c58e3a\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d01c53b elementor-widget elementor-widget-spacer\" data-id=\"d01c53b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-edc50a0 elementor-widget elementor-widget-text-editor\" data-id=\"edc50a0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"flex-1 overflow-hidden\">\n<div class=\"react-scroll-to-bottom--css-sirrv-79elbk h-full\">\n<div class=\"react-scroll-to-bottom--css-sirrv-1n7m0yu\">\n<div class=\"flex flex-col pb-9 text-sm\">\n<div class=\"w-full text-token-text-primary\" data-testid=\"conversation-turn-11\">\n<div class=\"px-4 py-2 justify-center text-base md:gap-6 m-auto\">\n<div class=\"flex flex-1 text-base mx-auto gap-3 md:px-5 lg:px-1 xl:px-5 md:max-w-3xl lg:max-w-[40rem] xl:max-w-[48rem] group final-completion\">\n<div class=\"relative flex w-full flex-col lg:w-[calc(100%-115px)] agent-turn\">\n<div class=\"flex-col gap-1 md:gap-3\">\n<div class=\"flex flex-grow flex-col max-w-full\">\n<div class=\"min-h-[20px] text-message flex flex-col items-start gap-3 whitespace-pre-wrap break-words [.text-message+&amp;]:mt-5 overflow-x-auto\" data-message-author-role=\"assistant\" data-message-id=\"091728d2-4e03-4a8f-8f1e-572f9d5a577c\">\n<div class=\"markdown prose w-full break-words dark:prose-invert dark\">\n<p>Modern supply chains are identified by a high degree of <b>complexity<\/b>, which may be divided into some fundamental aspects:<\/p>\n<ul>\n<li><b>articulated <\/b>production and distribution <b>processes<\/b>;<\/li>\n<li>characteristic parameters subject to <b>variability<\/b>;<\/li>\n<li><b>risks <\/b>of various kinds;<\/li>\n<li>physical, procedural or conceptual <b>constraints<\/b>;<\/li>\n<li><b>changing <\/b>behavior of system <b>variables <\/b>over time.<\/li>\n<\/ul>\n<p>In general we can state that the <b>processes of<\/b>&nbsp;<b>Supply Chain Management (SCM)<\/b> field, such as planning, production, logistics, transportation and so on entail <b>data-driven decision-making situations<\/b>. Data must be appropriately collected and organized in databases to be subsequently converted into useful information through processing and visualization tools.<\/p>\n<p>However, &#8220;traditional&#8221; data processing (for example by exploiting reports) may not be sufficient to support the decision-making process: the consequences deriving from a decision have in fact a <b>systemic effect<\/b> on many other company areas.<br>Understanding the <b>effects on different company performances<\/b> then becames simultaneousluy<b> necessary and onerous<\/b>.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e75b627 elementor-widget elementor-widget-image\" data-id=\"e75b627\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"950\" height=\"304\" src=\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-1024x328.png\" class=\"attachment-large size-large wp-image-1597\" alt=\"Decision making\" srcset=\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-1024x328.png 1024w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-300x96.png 300w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-2000x640.png 2000w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-1536x492.png 1536w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-2048x656.png 2048w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-500x160.png 500w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-800x256.png 800w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-1280x410.png 1280w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-1920x615.png 1920w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-24x8.png 24w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-36x12.png 36w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-48x15.png 48w\" sizes=\"100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3064374 elementor-widget elementor-widget-text-editor\" data-id=\"3064374\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Choosing the right approach to represent and manage supply chain complexity can therefore prove to be a decisive factor for the decision-making effectiveness of SCM processes.<\/p><p>Among the most commonly used and recognized methods for evaluating the effects of a decision there are: <b>analytical methods<\/b> and <b>dynamic simulation<\/b>. Let&#8217;s analyze them briefly.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2514dd0 elementor-widget elementor-widget-heading\" data-id=\"2514dd0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Analytical Methods<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9437606 elementor-widget elementor-widget-text-editor\" data-id=\"9437606\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span lang=\"EN\"><b>Analytical methods <\/b>represent the problem as a <b>model of equations<\/b> which include\u00a0 the <b>variables to be optimized<\/b>. These equations are solved using some solving <b>algorithms <\/b>such as, for example, CPLEX. Equations cannot be excessively complex: for this reason the constraints and variables of a given problem (which are deterministic and non-stochastic in nature) must be <strong>simplified and standardized<\/strong> as much as possible.<\/span><\/p><p><span lang=\"EN\">The <strong>time interval<\/strong> considered is an integer, <strong>discretized dimension<\/strong> (subject to the so called <strong>bucketing<\/strong>) and the events are static.<\/span><\/p><p><span lang=\"EN\">The analytical method provides the decision maker with a <strong>black box view<\/strong> of the model&#8217;s <strong>solutions<\/strong>: there is visibility only on the input and output data, while understanding how a certain result was obtained may not be simple or intuitive.<\/span><\/p><p><span lang=\"EN\">Finally, when optimizing the parameters considered, a <strong>predefined set of objectives<\/strong> is normally considered, typically of an economic nature.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-20fc430 elementor-widget elementor-widget-heading\" data-id=\"20fc430\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Dynamic Simulation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e766548 elementor-widget elementor-widget-text-editor\" data-id=\"e766548\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In the case of simulation, the problem considered is modeled at <strong>user&#8217;s discretion<\/strong>, through a series of <strong>entities<\/strong> that interact with each other through <strong>cause-effect relationships<\/strong>. The model obtained describes, over time, how the entities behave and what types of interactions they will establish with a very high level of detail (e.g. individual operators).<\/p>\n<p>In this case <strong>time<\/strong>, unlike the analytical method, is represented as a <strong>continuous dimension<\/strong>.<\/p>\n<p>The simulation process does not have the task of optimizing any variable: on the contrary, it allows the user to <strong>understand the dynamics that regulate the model<\/strong> and verifies the performance based on the hypotheses provided, commonly called <strong>scenarios<\/strong>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96892e5 elementor-widget elementor-widget-heading\" data-id=\"96892e5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Choosing the right method for supporting decision making<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fbd7626 elementor-widget elementor-widget-text-editor\" data-id=\"fbd7626\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span lang=\"EN\">Which method should then be used to make the\u00a0decision-making process effective?\u00a0<\/span><\/p><p><span lang=\"EN\">There is no single answer: any tool, whether\u00a0dictated by experience, an electronic spreadsheet, an analytical method or<br \/>simulation, can be more or less useful for the purpose. However, you can think\u00a0of using <b>two metrics to evaluate the choice of the most suitable tool: speed of\u00a0problem resolution and precision of the result achieved<\/b>.\u00a0<\/span><\/p><p><span lang=\"EN\">The first concerns the\u00a0time necessary to logically formulate the problem and to find the solution, while the second concerns the reliability of the results obtained\u00a0and the ability of the tool to report the complexity of what is being\u00a0considered.<\/span><\/p><p><span lang=\"EN\">It is possible to briefly present the main <strong>problem solving tools<\/strong> as shown below, with their relative advantages and\u00a0disadvantages linked to their use.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8400e6a elementor-widget elementor-widget-image\" data-id=\"8400e6a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"950\" height=\"523\" src=\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1-1024x564.png\" class=\"attachment-large size-large wp-image-1898\" alt=\"Problem solving methods\" srcset=\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1-1024x564.png 1024w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1-300x165.png 300w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1-500x276.png 500w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1-800x441.png 800w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1-24x13.png 24w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1-36x20.png 36w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1-48x26.png 48w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/02\/Immagine1.png 1172w\" sizes=\"100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f6e4630 elementor-widget elementor-widget-text-editor\" data-id=\"f6e4630\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The <strong>choice<\/strong> between a <strong>simulation<\/strong>-based method and an <strong>analytical<\/strong> method <strong>is not exclusive:<\/strong> in some cases, using both tools combined allows you to achieve the best results.<\/p><p>One could think of analyzing a decision using an analytical approach and then developing alternative scenarios using simulation or vice versa, generating sub-optimal scenarios for a given problem through simulation and then moving on choosing the optimal scenario using an analytical method .<\/p><p>Some typical decisions of SCM processes that find valid decision support in simulation may concern:<\/p><ul><li><strong>Design (or re-design) of the supply chain<\/strong>: if the value chain presents systematic inefficiencies, it is necessary to intervene on the variables of the logistics network to ensure the correct level of service and cost efficiency. For example, the repositioning of storage or production sites can be one of the typical decisions made in this context. In this case the simulation can help to develop a <strong>Network Redesign<\/strong> that provides valid alternatives for the positioning of the sites, both at a geographical, operational capacity and economic level. The input data considered by the model will therefore concern the current location of the facilities, their storage capacity, production capacity and the reduction\/increase in fixed and variable costs. As an output, the model will allow to verify in detail how the level of service, the structure of costs and revenues as well as any environmental impact vary depending on the different scenarios hypothesized for the new distribution network.<br \/><br \/><\/li><li><strong>Product portfolio review<\/strong>: the simulation approach is particularly useful for evaluating the introduction or removal of SKUs in the market. An analysis of this type allows to verify the saturation of production and storage capacity, the effectiveness in responding to market needs and the possibility of cannibalization of existing products.<br \/><br \/><\/li><li><strong>Long-term production planning<\/strong>: based on the sales plans agreed with the commercial function, it is possible to simulate various scenarios for verifying the saturation of production capacity to anticipate any critical issues in the medium-long term. This results in decisions to modulate the production capacity of the plants in order to adapt it to events expected in the future, such as: seasonal peaks, new market trends, changes in market share, promotions, etc.<br \/><br \/><\/li><li><strong>Review of inventory policies<\/strong>: it is a decision-making situation that is taken by mutual agreement between the production function and the sales function, when there are important changes in the structure of the supply chain, in the demand presentation patterns or in\u00a0 financial targets for reducing working capital. In this case it may be necessary to review the parameters for managing stocks of finished products, semi-finished products and\/or raw materials to accommodate the new objectives. In this decision-making situation, simulation allows you to carry out a <strong>sensitivity analysis<\/strong> on the management parameters of the inventory policies (such as: reorder point, reorder quantity, safety stock, maximum stock, etc.), quickly identifying the optimal\u00a0\u00a0values through the comparative analysis of different scenarios.<\/li><\/ul><p>In conclusion, at different moments in time companies are called upon to make a certain number of strategic decisions of different importance, relevance and complexity. It is therefore possible to group decisions according to the convenience of using analytical rather than simulation methods, as shown in the figure.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6aa585f elementor-widget elementor-widget-image\" data-id=\"6aa585f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"950\" height=\"470\" src=\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-1024x507.png\" class=\"attachment-large size-large wp-image-1604\" alt=\"Simulation pyramid\" srcset=\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-1024x507.png 1024w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-300x148.png 300w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-2000x990.png 2000w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-1536x760.png 1536w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-2048x1014.png 2048w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-500x247.png 500w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-800x396.png 800w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-1280x633.png 1280w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-1920x950.png 1920w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-24x12.png 24w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-36x18.png 36w, https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image3-48x24.png 48w\" sizes=\"100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-899e870 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-parent\" data-id=\"899e870\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5227a6b elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"5227a6b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4a1c241 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-parent\" data-id=\"4a1c241\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-19a1dda e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"19a1dda\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-c0c0eb2 e-con-full e-transform e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"c0c0eb2\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_transform_scale_effect_hover&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:0.9,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a82848e elementor-widget elementor-widget-heading\" data-id=\"a82848e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">01<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bf9911a elementor-widget elementor-widget-heading\" data-id=\"bf9911a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Problem solving in supply chain processes<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5a470a9 elementor-widget elementor-widget-text-editor\" data-id=\"5a470a9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Problem by problem: Analytical methods and Dynamic Simulation compared<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-356ae5a elementor-align-center elementor-widget elementor-widget-button\" data-id=\"356ae5a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-xs\" href=\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Deep dive<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6542781 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"6542781\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-76aff84 e-con-full e-transform e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"76aff84\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_transform_scale_effect_hover&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:0.9,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b992f75 elementor-widget elementor-widget-heading\" data-id=\"b992f75\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">02<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-430a6f1 elementor-widget elementor-widget-heading\" data-id=\"430a6f1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Dynamic simulation as decision support<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2c9515a elementor-widget elementor-widget-text-editor\" data-id=\"2c9515a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>How to choose the right simulation methodology for a tailor made approach to reliable data-driven decision<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-155d44f elementor-align-center elementor-widget elementor-widget-button\" data-id=\"155d44f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-xs\" href=\"https:\/\/scnode.com\/index.php\/dynamic-simulation-as-decision-support-tool\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Deep dive<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2b8c722 e-con-full e-transform e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"2b8c722\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;_transform_scale_effect_hover&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:0.9,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\">\n\t\t<div class=\"elementor-element elementor-element-a6db7d3 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"a6db7d3\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cb4da88 elementor-widget elementor-widget-heading\" data-id=\"cb4da88\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">03<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3b0a32a elementor-widget elementor-widget-heading\" data-id=\"3b0a32a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">The simulation dictionary<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-227657a elementor-widget elementor-widget-text-editor\" data-id=\"227657a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Model, Scenarios, Simulations, Digital Twin: what is what?<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-62c0a8f elementor-align-center elementor-widget elementor-widget-button\" data-id=\"62c0a8f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-xs\" href=\"https:\/\/scnode.com\/index.php\/simulation-dictionary\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Deep dive<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2f61fad e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"2f61fad\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-acc813c e-con-full e-transform e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"acc813c\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_transform_scale_effect_hover&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:0.9,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e291d0c elementor-widget elementor-widget-heading\" data-id=\"e291d0c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">04<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5e4a442 elementor-widget elementor-widget-heading\" data-id=\"5e4a442\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Skills and technologies<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bcd8bc0 elementor-widget elementor-widget-text-editor\" data-id=\"bcd8bc0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Learn about the skills and technologies involved in this cutting-edge technology<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1da599f elementor-align-center elementor-widget elementor-widget-button\" data-id=\"1da599f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-xs\" href=\"https:\/\/scnode.com\/index.php\/skills-and-technologies\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Deep dive<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7a2af1b e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"7a2af1b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-ac49b59 e-con-full e-transform e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"ac49b59\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_transform_scale_effect_hover&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:0.9,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1d933d9 elementor-widget elementor-widget-heading\" data-id=\"1d933d9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">05<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-04aa716 elementor-widget elementor-widget-heading\" data-id=\"04aa716\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Simulation modelling roadmap<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b8c8654 elementor-widget elementor-widget-text-editor\" data-id=\"b8c8654\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>From beginner to level expert: the road ahead<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6023cfb elementor-align-center elementor-widget elementor-widget-button\" data-id=\"6023cfb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-xs\" href=\"https:\/\/scnode.com\/index.php\/simulation-roadmap-beginning-digital-journey\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Deep dive<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ef86fa6 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"ef86fa6\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-6d919bc e-con-full e-transform e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"6d919bc\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_transform_scale_effect_hover&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:0.9,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_scale_effect_hover_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-aa1c285 elementor-widget elementor-widget-heading\" data-id=\"aa1c285\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">06<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f406aa6 elementor-widget elementor-widget-heading\" data-id=\"f406aa6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Applying Simulation to the S&amp;OP process<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eb924b6 elementor-widget elementor-widget-text-editor\" data-id=\"eb924b6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>MRP, Scheduling, and in between Simulation Modelling: discover how<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7c5504c elementor-align-center elementor-widget elementor-widget-button\" data-id=\"7c5504c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-xs\" href=\"https:\/\/scnode.com\/index.php\/applying-simulation-to-sop-process\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Deep dive<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-5c9ebb7 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-parent\" data-id=\"5c9ebb7\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c8402e3 elementor-widget elementor-widget-spacer\" data-id=\"c8402e3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8a1f832 elementor-widget elementor-widget-html\" data-id=\"8a1f832\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<a href=\"https:\/\/stocksnap.io\/photo\/technology-network-PN7RVGLUUD\">Photo<\/a> by <a href=\"https:\/\/stocksnap.io\/author\/hdwallpapers\">HD Wallpapers<\/a> on <a href=\"https:\/\/stocksnap.io\">StockSnap<\/a>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>PROBLEM SOLVING IN SUPPLY CHAIN PROCESSES Modern supply chains are identified by a high degree of complexity, which may be divided into some fundamental aspects: articulated production and distribution processes; characteristic parameters subject to variability; risks of various kinds; physical, procedural or conceptual constraints; changing behavior of system variables over time. In general we can state that the processes of&nbsp;Supply Chain Management (SCM) field, such as planning, production, logistics, transportation and so on entail data-driven decision-making situations. Data must be appropriately collected and organized in databases to be subsequently converted into useful information through processing and visualization tools. However, &#8220;traditional&#8221; data processing (for example by exploiting reports) may not be sufficient to support the decision-making process: the consequences deriving from a decision have in fact a systemic effect on many other company areas.Understanding the effects on different company performances then becames simultaneousluy necessary and onerous. Choosing the right approach to represent and manage supply chain complexity can therefore prove to be a decisive factor for the decision-making effectiveness of SCM processes. Among the most commonly used and recognized methods for evaluating the effects of a decision there are: analytical methods and dynamic simulation. Let&#8217;s analyze them briefly. Analytical Methods Analytical methods represent the problem as a model of equations which include\u00a0 the variables to be optimized. These equations are solved using some solving algorithms such as, for example, CPLEX. Equations cannot be excessively complex: for this reason the constraints and variables of a given problem (which are deterministic and non-stochastic in nature) must be simplified and standardized as much as possible. The time interval considered is an integer, discretized dimension (subject to the so called bucketing) and the events are static. The analytical method provides the decision maker with a black box view of the model&#8217;s solutions: there is visibility only on the input and output data, while understanding how a certain result was obtained may not be simple or intuitive. Finally, when optimizing the parameters considered, a predefined set of objectives is normally considered, typically of an economic nature. Dynamic Simulation In the case of simulation, the problem considered is modeled at user&#8217;s discretion, through a series of entities that interact with each other through cause-effect relationships. The model obtained describes, over time, how the entities behave and what types of interactions they will establish with a very high level of detail (e.g. individual operators). In this case time, unlike the analytical method, is represented as a continuous dimension. The simulation process does not have the task of optimizing any variable: on the contrary, it allows the user to understand the dynamics that regulate the model and verifies the performance based on the hypotheses provided, commonly called scenarios. Choosing the right method for supporting decision making Which method should then be used to make the\u00a0decision-making process effective?\u00a0 There is no single answer: any tool, whether\u00a0dictated by experience, an electronic spreadsheet, an analytical method orsimulation, can be more or less useful for the purpose. However, you can think\u00a0of using two metrics to evaluate the choice of the most suitable tool: speed of\u00a0problem resolution and precision of the result achieved.\u00a0 The first concerns the\u00a0time necessary to logically formulate the problem and to find the solution, while the second concerns the reliability of the results obtained\u00a0and the ability of the tool to report the complexity of what is being\u00a0considered. It is possible to briefly present the main problem solving tools as shown below, with their relative advantages and\u00a0disadvantages linked to their use. The choice between a simulation-based method and an analytical method is not exclusive: in some cases, using both tools combined allows you to achieve the best results. One could think of analyzing a decision using an analytical approach and then developing alternative scenarios using simulation or vice versa, generating sub-optimal scenarios for a given problem through simulation and then moving on choosing the optimal scenario using an analytical method . Some typical decisions of SCM processes that find valid decision support in simulation may concern: Design (or re-design) of the supply chain: if the value chain presents systematic inefficiencies, it is necessary to intervene on the variables of the logistics network to ensure the correct level of service and cost efficiency. For example, the repositioning of storage or production sites can be one of the typical decisions made in this context. In this case the simulation can help to develop a Network Redesign that provides valid alternatives for the positioning of the sites, both at a geographical, operational capacity and economic level. The input data considered by the model will therefore concern the current location of the facilities, their storage capacity, production capacity and the reduction\/increase in fixed and variable costs. As an output, the model will allow to verify in detail how the level of service, the structure of costs and revenues as well as any environmental impact vary depending on the different scenarios hypothesized for the new distribution network. Product portfolio review: the simulation approach is particularly useful for evaluating the introduction or removal of SKUs in the market. An analysis of this type allows to verify the saturation of production and storage capacity, the effectiveness in responding to market needs and the possibility of cannibalization of existing products. Long-term production planning: based on the sales plans agreed with the commercial function, it is possible to simulate various scenarios for verifying the saturation of production capacity to anticipate any critical issues in the medium-long term. This results in decisions to modulate the production capacity of the plants in order to adapt it to events expected in the future, such as: seasonal peaks, new market trends, changes in market share, promotions, etc. Review of inventory policies: it is a decision-making situation that is taken by mutual agreement between the production function and the sales function, when there are important changes in the structure of the supply chain, in the demand presentation patterns or in\u00a0 financial targets for reducing working capital. In this case it may be necessary to &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/\" class=\"more-link\">Leggi tutto<span class=\"screen-reader-text\"> &#8220;Problem solving in supply chain processes&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"om_disable_all_campaigns":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":""},"ppma_author":[18],"class_list":["post-1596","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Problem solving in supply chain processes - SCNODE.COM<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Problem solving in supply chain processes - SCNODE.COM\" \/>\n<meta property=\"og:description\" content=\"PROBLEM SOLVING IN SUPPLY CHAIN PROCESSES Modern supply chains are identified by a high degree of complexity, which may be divided into some fundamental aspects: articulated production and distribution processes; characteristic parameters subject to variability; risks of various kinds; physical, procedural or conceptual constraints; changing behavior of system variables over time. In general we can state that the processes of&nbsp;Supply Chain Management (SCM) field, such as planning, production, logistics, transportation and so on entail data-driven decision-making situations. Data must be appropriately collected and organized in databases to be subsequently converted into useful information through processing and visualization tools. However, &#8220;traditional&#8221; data processing (for example by exploiting reports) may not be sufficient to support the decision-making process: the consequences deriving from a decision have in fact a systemic effect on many other company areas.Understanding the effects on different company performances then becames simultaneousluy necessary and onerous. Choosing the right approach to represent and manage supply chain complexity can therefore prove to be a decisive factor for the decision-making effectiveness of SCM processes. Among the most commonly used and recognized methods for evaluating the effects of a decision there are: analytical methods and dynamic simulation. Let&#8217;s analyze them briefly. Analytical Methods Analytical methods represent the problem as a model of equations which include\u00a0 the variables to be optimized. These equations are solved using some solving algorithms such as, for example, CPLEX. Equations cannot be excessively complex: for this reason the constraints and variables of a given problem (which are deterministic and non-stochastic in nature) must be simplified and standardized as much as possible. The time interval considered is an integer, discretized dimension (subject to the so called bucketing) and the events are static. The analytical method provides the decision maker with a black box view of the model&#8217;s solutions: there is visibility only on the input and output data, while understanding how a certain result was obtained may not be simple or intuitive. Finally, when optimizing the parameters considered, a predefined set of objectives is normally considered, typically of an economic nature. Dynamic Simulation In the case of simulation, the problem considered is modeled at user&#8217;s discretion, through a series of entities that interact with each other through cause-effect relationships. The model obtained describes, over time, how the entities behave and what types of interactions they will establish with a very high level of detail (e.g. individual operators). In this case time, unlike the analytical method, is represented as a continuous dimension. The simulation process does not have the task of optimizing any variable: on the contrary, it allows the user to understand the dynamics that regulate the model and verifies the performance based on the hypotheses provided, commonly called scenarios. Choosing the right method for supporting decision making Which method should then be used to make the\u00a0decision-making process effective?\u00a0 There is no single answer: any tool, whether\u00a0dictated by experience, an electronic spreadsheet, an analytical method orsimulation, can be more or less useful for the purpose. However, you can think\u00a0of using two metrics to evaluate the choice of the most suitable tool: speed of\u00a0problem resolution and precision of the result achieved.\u00a0 The first concerns the\u00a0time necessary to logically formulate the problem and to find the solution, while the second concerns the reliability of the results obtained\u00a0and the ability of the tool to report the complexity of what is being\u00a0considered. It is possible to briefly present the main problem solving tools as shown below, with their relative advantages and\u00a0disadvantages linked to their use. The choice between a simulation-based method and an analytical method is not exclusive: in some cases, using both tools combined allows you to achieve the best results. One could think of analyzing a decision using an analytical approach and then developing alternative scenarios using simulation or vice versa, generating sub-optimal scenarios for a given problem through simulation and then moving on choosing the optimal scenario using an analytical method . Some typical decisions of SCM processes that find valid decision support in simulation may concern: Design (or re-design) of the supply chain: if the value chain presents systematic inefficiencies, it is necessary to intervene on the variables of the logistics network to ensure the correct level of service and cost efficiency. For example, the repositioning of storage or production sites can be one of the typical decisions made in this context. In this case the simulation can help to develop a Network Redesign that provides valid alternatives for the positioning of the sites, both at a geographical, operational capacity and economic level. The input data considered by the model will therefore concern the current location of the facilities, their storage capacity, production capacity and the reduction\/increase in fixed and variable costs. As an output, the model will allow to verify in detail how the level of service, the structure of costs and revenues as well as any environmental impact vary depending on the different scenarios hypothesized for the new distribution network. Product portfolio review: the simulation approach is particularly useful for evaluating the introduction or removal of SKUs in the market. An analysis of this type allows to verify the saturation of production and storage capacity, the effectiveness in responding to market needs and the possibility of cannibalization of existing products. Long-term production planning: based on the sales plans agreed with the commercial function, it is possible to simulate various scenarios for verifying the saturation of production capacity to anticipate any critical issues in the medium-long term. This results in decisions to modulate the production capacity of the plants in order to adapt it to events expected in the future, such as: seasonal peaks, new market trends, changes in market share, promotions, etc. Review of inventory policies: it is a decision-making situation that is taken by mutual agreement between the production function and the sales function, when there are important changes in the structure of the supply chain, in the demand presentation patterns or in\u00a0 financial targets for reducing working capital. In this case it may be necessary to &hellip; Leggi tutto &quot;Problem solving in supply chain processes&quot;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/\" \/>\n<meta property=\"og:site_name\" content=\"SCNODE.COM\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-29T10:53:39+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"3791\" \/>\n\t<meta property=\"og:image:height\" content=\"1214\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Tempo di lettura stimato\" \/>\n\t<meta name=\"twitter:data1\" content=\"8 minuti\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/\",\"url\":\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/\",\"name\":\"Problem solving in supply chain processes - SCNODE.COM\",\"isPartOf\":{\"@id\":\"https:\/\/scnode.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-1024x328.png\",\"datePublished\":\"2024-01-26T15:52:47+00:00\",\"dateModified\":\"2024-11-29T10:53:39+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#breadcrumb\"},\"inLanguage\":\"it-IT\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"it-IT\",\"@id\":\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#primaryimage\",\"url\":\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1.png\",\"contentUrl\":\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1.png\",\"width\":3791,\"height\":1214,\"caption\":\"Decision making\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/scnode.com\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Problem solving in supply chain processes\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/scnode.com\/#website\",\"url\":\"https:\/\/scnode.com\/\",\"name\":\"SCNODE.COM\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/scnode.com\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/scnode.com\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"it-IT\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/scnode.com\/#organization\",\"name\":\"SCNODE.COM\",\"url\":\"https:\/\/scnode.com\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"it-IT\",\"@id\":\"https:\/\/scnode.com\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/09\/SCNODE-logo.png\",\"contentUrl\":\"https:\/\/scnode.com\/wp-content\/uploads\/2024\/09\/SCNODE-logo.png\",\"width\":1570,\"height\":1571,\"caption\":\"SCNODE.COM\"},\"image\":{\"@id\":\"https:\/\/scnode.com\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.linkedin.com\/company\/scnode\/?viewAsMember=true\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Problem solving in supply chain processes - SCNODE.COM","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/","og_locale":"it_IT","og_type":"article","og_title":"Problem solving in supply chain processes - SCNODE.COM","og_description":"PROBLEM SOLVING IN SUPPLY CHAIN PROCESSES Modern supply chains are identified by a high degree of complexity, which may be divided into some fundamental aspects: articulated production and distribution processes; characteristic parameters subject to variability; risks of various kinds; physical, procedural or conceptual constraints; changing behavior of system variables over time. In general we can state that the processes of&nbsp;Supply Chain Management (SCM) field, such as planning, production, logistics, transportation and so on entail data-driven decision-making situations. Data must be appropriately collected and organized in databases to be subsequently converted into useful information through processing and visualization tools. However, &#8220;traditional&#8221; data processing (for example by exploiting reports) may not be sufficient to support the decision-making process: the consequences deriving from a decision have in fact a systemic effect on many other company areas.Understanding the effects on different company performances then becames simultaneousluy necessary and onerous. Choosing the right approach to represent and manage supply chain complexity can therefore prove to be a decisive factor for the decision-making effectiveness of SCM processes. Among the most commonly used and recognized methods for evaluating the effects of a decision there are: analytical methods and dynamic simulation. Let&#8217;s analyze them briefly. Analytical Methods Analytical methods represent the problem as a model of equations which include\u00a0 the variables to be optimized. These equations are solved using some solving algorithms such as, for example, CPLEX. Equations cannot be excessively complex: for this reason the constraints and variables of a given problem (which are deterministic and non-stochastic in nature) must be simplified and standardized as much as possible. The time interval considered is an integer, discretized dimension (subject to the so called bucketing) and the events are static. The analytical method provides the decision maker with a black box view of the model&#8217;s solutions: there is visibility only on the input and output data, while understanding how a certain result was obtained may not be simple or intuitive. Finally, when optimizing the parameters considered, a predefined set of objectives is normally considered, typically of an economic nature. Dynamic Simulation In the case of simulation, the problem considered is modeled at user&#8217;s discretion, through a series of entities that interact with each other through cause-effect relationships. The model obtained describes, over time, how the entities behave and what types of interactions they will establish with a very high level of detail (e.g. individual operators). In this case time, unlike the analytical method, is represented as a continuous dimension. The simulation process does not have the task of optimizing any variable: on the contrary, it allows the user to understand the dynamics that regulate the model and verifies the performance based on the hypotheses provided, commonly called scenarios. Choosing the right method for supporting decision making Which method should then be used to make the\u00a0decision-making process effective?\u00a0 There is no single answer: any tool, whether\u00a0dictated by experience, an electronic spreadsheet, an analytical method orsimulation, can be more or less useful for the purpose. However, you can think\u00a0of using two metrics to evaluate the choice of the most suitable tool: speed of\u00a0problem resolution and precision of the result achieved.\u00a0 The first concerns the\u00a0time necessary to logically formulate the problem and to find the solution, while the second concerns the reliability of the results obtained\u00a0and the ability of the tool to report the complexity of what is being\u00a0considered. It is possible to briefly present the main problem solving tools as shown below, with their relative advantages and\u00a0disadvantages linked to their use. The choice between a simulation-based method and an analytical method is not exclusive: in some cases, using both tools combined allows you to achieve the best results. One could think of analyzing a decision using an analytical approach and then developing alternative scenarios using simulation or vice versa, generating sub-optimal scenarios for a given problem through simulation and then moving on choosing the optimal scenario using an analytical method . Some typical decisions of SCM processes that find valid decision support in simulation may concern: Design (or re-design) of the supply chain: if the value chain presents systematic inefficiencies, it is necessary to intervene on the variables of the logistics network to ensure the correct level of service and cost efficiency. For example, the repositioning of storage or production sites can be one of the typical decisions made in this context. In this case the simulation can help to develop a Network Redesign that provides valid alternatives for the positioning of the sites, both at a geographical, operational capacity and economic level. The input data considered by the model will therefore concern the current location of the facilities, their storage capacity, production capacity and the reduction\/increase in fixed and variable costs. As an output, the model will allow to verify in detail how the level of service, the structure of costs and revenues as well as any environmental impact vary depending on the different scenarios hypothesized for the new distribution network. Product portfolio review: the simulation approach is particularly useful for evaluating the introduction or removal of SKUs in the market. An analysis of this type allows to verify the saturation of production and storage capacity, the effectiveness in responding to market needs and the possibility of cannibalization of existing products. Long-term production planning: based on the sales plans agreed with the commercial function, it is possible to simulate various scenarios for verifying the saturation of production capacity to anticipate any critical issues in the medium-long term. This results in decisions to modulate the production capacity of the plants in order to adapt it to events expected in the future, such as: seasonal peaks, new market trends, changes in market share, promotions, etc. Review of inventory policies: it is a decision-making situation that is taken by mutual agreement between the production function and the sales function, when there are important changes in the structure of the supply chain, in the demand presentation patterns or in\u00a0 financial targets for reducing working capital. In this case it may be necessary to &hellip; Leggi tutto \"Problem solving in supply chain processes\"","og_url":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/","og_site_name":"SCNODE.COM","article_modified_time":"2024-11-29T10:53:39+00:00","og_image":[{"width":3791,"height":1214,"url":"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_misc":{"Tempo di lettura stimato":"8 minuti"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/","url":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/","name":"Problem solving in supply chain processes - SCNODE.COM","isPartOf":{"@id":"https:\/\/scnode.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#primaryimage"},"image":{"@id":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#primaryimage"},"thumbnailUrl":"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1-1024x328.png","datePublished":"2024-01-26T15:52:47+00:00","dateModified":"2024-11-29T10:53:39+00:00","breadcrumb":{"@id":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#breadcrumb"},"inLanguage":"it-IT","potentialAction":[{"@type":"ReadAction","target":["https:\/\/scnode.com\/index.php\/problem-solving-scm\/"]}]},{"@type":"ImageObject","inLanguage":"it-IT","@id":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#primaryimage","url":"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1.png","contentUrl":"https:\/\/scnode.com\/wp-content\/uploads\/2024\/01\/SimExp-image1.png","width":3791,"height":1214,"caption":"Decision making"},{"@type":"BreadcrumbList","@id":"https:\/\/scnode.com\/index.php\/problem-solving-scm\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/scnode.com\/"},{"@type":"ListItem","position":2,"name":"Problem solving in supply chain processes"}]},{"@type":"WebSite","@id":"https:\/\/scnode.com\/#website","url":"https:\/\/scnode.com\/","name":"SCNODE.COM","description":"","publisher":{"@id":"https:\/\/scnode.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/scnode.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"it-IT"},{"@type":"Organization","@id":"https:\/\/scnode.com\/#organization","name":"SCNODE.COM","url":"https:\/\/scnode.com\/","logo":{"@type":"ImageObject","inLanguage":"it-IT","@id":"https:\/\/scnode.com\/#\/schema\/logo\/image\/","url":"https:\/\/scnode.com\/wp-content\/uploads\/2024\/09\/SCNODE-logo.png","contentUrl":"https:\/\/scnode.com\/wp-content\/uploads\/2024\/09\/SCNODE-logo.png","width":1570,"height":1571,"caption":"SCNODE.COM"},"image":{"@id":"https:\/\/scnode.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.linkedin.com\/company\/scnode\/?viewAsMember=true"]}]}},"coauthors":[{"link":"https:\/\/scnode.com\/index.php\/author\/scnode-com\/","display_name":"scnode.com"}],"author_meta":{"author_link":"https:\/\/scnode.com\/index.php\/author\/scnode-com\/","display_name":"scnode.com"},"relative_dates":{"created":"Pubblicato 2 anni fa","modified":"Aggiornato 1 anno fa"},"absolute_dates":{"created":"Pubblicato il 26 Gennaio 2024","modified":"Aggiornato il 29 Novembre 2024"},"absolute_dates_time":{"created":"Pubblicato il 26 Gennaio 2024 16:52","modified":"Aggiornato il 29 Novembre 2024 11:53"},"featured_img_caption":"","featured_img":false,"series_order":"","_links":{"self":[{"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/pages\/1596","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/comments?post=1596"}],"version-history":[{"count":58,"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/pages\/1596\/revisions"}],"predecessor-version":[{"id":3304,"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/pages\/1596\/revisions\/3304"}],"wp:attachment":[{"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/media?parent=1596"}],"wp:term":[{"taxonomy":"author","embeddable":true,"href":"https:\/\/scnode.com\/index.php\/wp-json\/wp\/v2\/ppma_author?post=1596"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}