{"id":94186,"date":"2024-03-18T10:34:59","date_gmt":"2024-03-18T03:34:59","guid":{"rendered":"https:\/\/bahtera.jp\/asprova-indonesia\/"},"modified":"2025-03-20T09:25:43","modified_gmt":"2025-03-20T02:25:43","slug":"asprova-indonesia","status":"publish","type":"post","link":"https:\/\/bahtera.jp\/en\/asprova-indonesia\/","title":{"rendered":"Key Points for Sales and Implementation of Production Schedulers in Indonesia"},"content":{"rendered":"

While the recognition of production schedulers in Indonesia is still low, they address core production management tasks\u2014such as daily load calculations for sub-resources like molds and personnel, and creating production schedules for main resources like machines with those as constraints\u2014that even expensive ERP packages cannot handle.
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Production Scheduler in Indonesia<\/p>\r\n\t\t\t\t\t\t\t\r\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t

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In Indonesia’s Japanese manufacturing industry, the adoption of production management systems has been increasing. However, when it comes to one of the key challenges in production management\u2014creating feasible production plans that take machine and equipment loads into account\u2014manual work using Excel remains the standard practice. As a result, the demand for production schedulers is expected to grow in the future.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\r\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t

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Pre-Sales of Production Schedulers in Indonesia<\/h2>\n

I work in technical sales for Asprova, a production scheduler application for manufacturing, in Indonesia. Due to its low recognition here, it\u2019s hard for prospects to envision its cost-effectiveness. While I wouldn\u2019t say they start with outright rejection, presentations and demos usually begin from a negative baseline.<\/p>\n

\u201cIt only handles production planning, yet it\u2019s so expensive?\u201d<\/div>\n

Hearing this daily can make sales pitches feel defensive.
\nHowever, production schedulers can do two things that costly production management packages cannot:<\/p>\n

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    \n
  1. Calculate loads for production resources\u2014personnel, machines, molds, trollies, etc.\u2014from monthly to daily levels based on forecasts.<\/li>\n
  2. Create daily production schedules based on confirmed orders, factoring in the constraints from point 1.<\/li>\n<\/ol>\n<\/div>\n

    In truth, these two functions are the core of manufacturing production management. One could argue, \u201cIt\u2019s incredibly well-regarded because it does this at a fraction of the cost of production management packages\u2014don\u2019t you know that?\u201d or \u201cIt\u2019s such a cost-effective choice; it\u2019s rare not to go with it\u201d (though I\u2019d phrase it more politely in practice).
    \n\"\"That said, I believe the success of production management package implementation hinges on master data and inventory accuracy. Without reliable data, implementing a production scheduler is challenging\u2014this is a key premise.
    \nIn China, there\u2019s a saying, \u201cBeat the chicken to scold the dog\u201d<\/span>\u2014poor chicken\u2014but with production schedulers, I adopt a slightly passive-aggressive sales approach, or rather, a pull strategy.<\/p>\n

    The Significance of Japanese Engineers (SEs) in Indonesia<\/h2>\n

    When selling systems to Indonesian factories, it\u2019s common for a Japanese decision-maker and an Indonesian staff member to attend from the client side. I explain in Indonesian to the local staff, interspersing Japanese at key points to appeal to the Japanese decision-maker. Anticipating typical questions from Indonesian staff and weaving them into the demo is crucial, so I can pull out a \u201cYes, here it is\u201d demonstration from my pocket when asked.
    \nThis raises the question: Is there a need for Japanese SEs in Indonesia? First, Japanese salespeople are essential. Selling to Japanese firms means pitching to Japanese decision-makers, which only a Japanese person can effectively do\u2014unless it\u2019s a rare global company where English is the lingua franca and nationality or native language doesn\u2019t matter. In Indonesia\u2019s Japanese expatriate community, I believe a highly communicative Japanese salesperson is indispensable.
    \nBut what about SEs? Frankly, Indonesia has tons of highly skilled locals. It\u2019s easier to find an Indonesian SE more capable than a Japanese one than to find an exceptional Japanese SE here. Thus, Japanese SEs in Indonesia inevitably need sales skills.
    \nIf it\u2019s just technical expertise, Indonesians are better and cheaper. My view: Japanese SEs aren\u2019t necessary here.
    \nFor orders, a Japanese salesperson conducts marketing, then brings an Indonesian technician to demo for promising prospects, earning sufficient trust. While sales needs some technical knowledge, spending years studying tech is less efficient than focusing on list marketing or golf networking to win deals.
    \nGiven this, the significance of a Japanese SE in Indonesia might be providing clients with, \u201cThere\u2019s a Japanese tech expert, so I can ask questions in Japanese if needed\u201d\u2014a sense of reassurance. Performing demos as a Japanese might reinforce this.
    \nI demo in Indonesian for local staff, but even after a self-satisfying demo, I\u2019m always asked, \u201cNo Indonesian technicians?\u201d Indonesians want to ask in Indonesian, Japanese in Japanese.
    \nEven in Indonesia, where English is widely used and globalization outpaces Japan, it\u2019s still \u201cmother tongue, no matter what.\u201d<\/p>\n

    Challenges in Explaining a Lesser-Known Production Scheduler in Indonesia<\/h2>\n

    With production management systems, processing flows are somewhat predictable. Clients often know more than sellers about what they are, can do, and cannot do. Post-implementation pitches focus on, \u201cYour daily workflow will look like this, you\u2019ll get this info, you\u2019ll enable this analysis.\u201d
    \nFor unexpected questions like \u201cCan it do this?\u201d\u2014unless it\u2019s extremely complex\u2014I can say, \u201cNot with the standard package, but customization or add-on subsystems can make it possible.\u201d Clients can\u2019t demand more on the spot, avoiding negative \u201cNo\u201d answers and keeping demos smooth.
    \nBut with a production scheduler, less known in Indonesia, it\u2019s different. It starts with \u201cWhat\u2019s a production scheduler?\u201d\u2014requiring explanations of capabilities and limits. Questions like \u201cHow\u2019s it different from a production management system?\u201d \u201cIt manages inventory too, right?\u201d \u201cIt comes with lots of standard reports, doesn\u2019t it?\u201d assume \u201cIt\u2019s probably like a production management system.\u201d
    \nWhen asked, \u201cIt manages inventory, right?\u201d or \u201cShow me standard P\/O and invoice formats,\u201d I can only say, \u201cNo, it doesn\u2019t\u201d or \u201cThat\u2019s not its purpose\u201d\u2014it\u2019s not built for that. Unlike production management systems, I must clearly state, \u201cWhat it can\u2019t do, it can\u2019t do.\u201d
    \nThis makes demos prone to derailment. Clearing the first hurdle\u2014convincing clients \u201cA production scheduler lacks inventory management or invoice issuance like a production management system\u201d\u2014finally allows demos and evaluations of its true functions.
    \nProduction management systems analyze current conditions with past data, while production schedulers use parameter settings for repeated rescheduling to achieve desired outcomes. When clients ask, \u201cCan it do this?\u201d even if possible, failing to demo it on the spot is as good as \u201cNo.\u201d
    \nClients demand demos for real shop-floor scenarios\u2014\u201cFinish parts for ASSY a day earlier,\u201d \u201cAssign to a sub-molding machine if the main one\u2019s full,\u201d \u201cShow handling a broken press,\u201d \u201cBatch same items to reduce setups,\u201d \u201cHow do you handle NG items in performance data?\u201d\u2014saying, \u201cShow it now with that scheduler you\u2019re pitching.\u201d This is the second hurdle.
    \nProduction scheduler demos typically face these two barriers, making them challenging.<\/p>\n

    The Biggest Reason Production Scheduler Demos Are Difficult<\/h2>\n

    The above hurdles involve interpersonal dynamics, but the biggest reason production scheduler demos are tough lies in the system\u2019s inherent nature.
    \nProduction management systems, as \u201ccurrent analysis systems based on performance data,\u201d must produce logical, trustworthy results. Production schedulers, however, \u201crepeatedly reschedule using parameter settings to approach desired results,\u201d with numerous properties in planning parameters, masters, and orders\u2014making influencing factors highly complex.
    \nThe evaluation process for assigning resources involves many elements, so even \u201ccorrectly\u201d weighting properties doesn\u2019t guarantee an optimal schedule\u2014it merely trends results in a direction.
    \nGetting the desired schedule often requires trial and error, like taming a wild horse.
    \nA common demo misconception is, \u201cYour system automatically creates the optimal schedule for our factory, right?\u201d\u2014expecting an AI engine to judge optimality from preset resource parameters and orders, delivering the planner\u2019s ideal result. That\u2019s impossible.
    \nOptimizing production plans might broadly mean \u201ca leveled plan without capacity overload or delivery delays,\u201d but in Indonesia\u2014prone to demand swings, currency fluctuations, and logistics chaos\u2014the biggest issue is equipment line stoppages from raw material shortages. Issuing production instructions to avoid stoppages, considering raw material inventory (absolute quantity) and open purchase orders (increase\/decrease), is key.
    \n\u201cWhat\u2019s optimization?\u201d is like \u201cWhat\u2019s the world\u2019s best food?\u201d\u2014answers vary by person, time, and place. Rarely can one envision the optimal schedule during rescheduling, so a production scheduler\u2019s role may be to assist in finding \u201cwhat\u2019s optimal\u201d for the current shop floor.<\/p>\n

    Scheduling Directions in Boom and Bust Times<\/h2>\n

    Production management systems typically divide management by process (location), matching shop-floor or building separations. Physical distances or walls between processes hinder material and information flows, limiting lead time and work-in-progress reductions.
    \nConversely, production schedulers visualize end-to-end process flows, fostering production flow and overall optimization awareness. Clarifying material requirements and process input timing reduces inter-process inventory.
    \nIn booming Indonesia, throughput maximization trumps inventory or lead time reduction. While human instinct might cram short orders into idle equipment, production schedulers simulate capacity maximization with existing resources.
    \nDuring busts\u2014like post-Lehman or China\u2019s demand slowdown\u2014when domestic manufacturing demand drops, operators may feign busyness, creating waste. Production schedulers logically reveal true busyness, enabling decisions like \u201cIf idle, don\u2019t produce excess\u2014do other tasks.\u201d
    \nIn Indonesia, labor disputes halting production can delay deliveries and harm clients. Preparing a BCP (Business Continuity Plan) for contingencies, while reflecting incidents in the scheduler for rescheduling, helps devise specific countermeasures.<\/p>\n","protected":false},"excerpt":{"rendered":"

    While the recognition of production schedulers in Indonesia is still low, they address core production management tasks\u2014such as daily load calculations for sub-resources like molds and personnel, and creating production schedules for main resources like machines with those as constraints\u2014that even expensive ERP packages cannot handle.<\/p>\n","protected":false},"author":2,"featured_media":88006,"parent":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[619],"tags":[],"class_list":["post-94186","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-production-scheduler"],"_links":{"self":[{"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/posts\/94186","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/comments?post=94186"}],"version-history":[{"count":0,"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/posts\/94186\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/media\/88006"}],"wp:attachment":[{"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/media?parent=94186"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/categories?post=94186"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bahtera.jp\/en\/wp-json\/wp\/v2\/tags?post=94186"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}