{"id":2630,"date":"2020-02-03T14:37:57","date_gmt":"2020-02-03T14:37:57","guid":{"rendered":"https:\/\/www.factorydata.com\/?p=2630"},"modified":"2020-02-03T14:37:57","modified_gmt":"2020-02-03T14:37:57","slug":"disadvantages-using-vehicles-operation-vio-data-decision-making","status":"publish","type":"post","link":"https:\/\/www.factorydata.com\/en\/disadvantages-using-vehicles-operation-vio-data-decision-making\/","title":{"rendered":"Disadvantages of using vehicles in operation (VIO) data for decision-making"},"content":{"rendered":"

The number of \u201cvehicles in operation\u201d refers to all vehicles registered in a specific area and is calculated using each country\u2019s vehicle registration database. Usually, this registration database contains information on the make, model, year and other related information, although it is never of a personal nature (as would be, for example, owner name or address).<\/h4>\n

\"VIO-Traffic\"<\/a><\/p>\n

<\/h4>\n

Currently, some companies commercialize the information on vehicles in operation compiled by different countries, including by zip code (available in the United States and some other countries). They link this information to a standard vehicle reference database, such as Tecdoc, MAM or ACES\/PIES, to facilitate its use.<\/h4>\n

The goal is to use the vehicles in operation information to help us make decisions about our inventory and somehow interpret this information as a solid estimate of future demand which can be integrated into our inventory management flow.<\/strong><\/h4>\n

But, is there really a direct relationship between the vehicles in operation and the level of demand for their components in the aftermarket?<\/strong><\/h4>\n

\"VIO-Uncertainty\"<\/a><\/p>\n

 <\/p>\n

Let\u2019s see: when we\u2019re talking about wear parts or parts that are replaced according to the vehicle’s established maintenance schedulings, the vehicles in operation information may be a very relevant data.<\/h4>\n

But when we’re talking about alternators, starter motors, turbos, AC compressors, etc., determining their future demand level is a much more complicated task<\/strong>.<\/h4>\n

Why is there no direct relationship between vehicles in operation and future demand?<\/strong><\/h4>\n

1.- The service life of parts is very difficult to estimate, as a breakage may occur at any time or never.<\/h4>\n

\"VIO-Cons1\"<\/a><\/p>\n

2.- It is difficult to link all existing parts to a vehicle application data, especially for certain application segments like: Industrial, Agriculture, Marine, etc.<\/h4>\n

\"VIO-Cons2\"<\/a><\/p>\n

3.- Information on real vehicle operation hours would be needed to accurately analyze application segments like: Industrial, Agriculture, Marine, etc.<\/h4>\n

\"VIO-Cons3\"<\/a><\/p>\n

4.- Vehicle manufacturers offer widely disparate warranty periods that may last as long as 7 years.<\/h4>\n

\"VIO-Cons4\"<\/a><\/p>\n

5.- Some segments of vehicle owners (Leasing and Renting companies, etc.) delegate the responsibility for part provision to the original equipment manufacturer (OEM).<\/h4>\n

\"VIO-Cons5\"<\/a><\/p>\n

<\/h4>\n

For all these reasons, when we want to analyze parts that are not wear or maintenance parts, the number of vehicles in operation is hardly a determining data when it comes to making a reliable prediction on the future demand<\/strong>.<\/h4>\n

There are other approaches to the problem of estimating part demand, based on the analysis of real-time part demand. These solutions present various advantages:<\/h4>\n
    \n
  1. \n

    They are not based on future projections, but rather are precise calculations on the volume and tendency of current demand.<\/h4>\n<\/li>\n
  2. \n

    They can be applied to all application segments, as they are an approach that is totally independent of the parts\u2019 vehicle applications.<\/h4>\n<\/li>\n
  3. \n

    By working on product level instead of application level, the complexity of analysis is reduced by a factor of 25 to 1.<\/h4>\n<\/li>\n
  4. \n

    Maximum precision in the calculation of demand obtained for each part analyzed, making it possible to assign each product an exact ranking of its market demand position.<\/h4>\n<\/li>\n
  5. \n

    The data on demand can also be segmented on the country or territory level and, in this case, down to the client level.<\/h4>\n<\/li>\n<\/ol>\n

    Clearly, real-time demand analysis provides us with a more accurate, more comprehensive and much simpler estimate of demand.<\/strong><\/h4>\n

    Market Expert<\/strong>: Demand-driven platform for product analysis & assortment planning.<\/h4>\n

    By Joan Cab\u00f3s
    \nCEO & founder<\/p>","protected":false},"excerpt":{"rendered":"

    The number of \u201cvehicles in operation\u201d refers to all vehicles registered in a specific area and is calculated using each […]<\/p>","protected":false},"author":1,"featured_media":2629,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[20],"tags":[28,110,40,42,16],"class_list":["post-2630","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-neo-en","tag-assortment-planning","tag-big-data","tag-future-demand","tag-market-demand","tag-market-expert"],"yoast_head":"\nDisadvantages of using vehicles in operation (VIO) data for decision-making - 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