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We find that practitioners are not always sure about the meanings of these words, which can impede effective business communication, particularly when implementing inventory optimization and forecasting software. \u00a0Sometimes two companies (supplier and customer, supply chain software vendor and customer, etc.) use the same word but apply different meanings to it.\u00a0 This post aims to clarify some basic definitions.<\/p>\n
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A prescription of what to do when there is a stockout. Under a backorder policy, any units demanded but not provided immediately are provided later, when available.<\/p>\n
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An item availability metric that measures the fraction of items demanded that are supplied immediate from stock on hand. Expressed as a percentage: A 90% fill rate means that 90% of the units demanded, on average, are immediately available. Fill rate differs from service level in that it takes account of how large a stockout is, not just how often a stockout happens. Accordingly, fill rate and service level can be very different numbers. What’s the difference between fill rate and service level?<\/a><\/p>\n <\/p>\n Lead time is the interval between inventory realizing that you need more stock, i.e., detecting that inventory has dropped to or below the reorder point or min, and its arrival back in stock. The lead time might be composed of several intervals: the time to sense the problem, the time to request purchasing to get more, the time until purchasing actually cuts a purchase order, the time for the vendor to deliver, and then the time to restock. The shorter the lead time, the more lean and agile your operation. You can use SmartForecasts to do \u201cwhat if\u201d analysis, examining the gains to be made from reducing lead times.<\/p>\n <\/p>\n The level of inventory which, when reached or breached, triggers replenishment. Identical to the reorder point R. The Min is comprised of the cycle stock (expected lead time demand) and safety stock (to protect against demand and supply variability).<\/p>\n <\/p>\n A fixed number of\u00a0units to order when the reorder point has been reached or breached<\/p>\n <\/p>\n Order quantities are often negotiated with suppliers rather than simply calculated from an item\u2019s demand history. Some suppliers require that any order be at least of a certain size. If you would like to order 7 but your supplier has an order quantity minimum of 10, you are stuck ordering 10.<\/p>\n <\/p>\n A way to determine inventory requirements based on an easy-to-understand rule such as \u201corder 10 days\u2019 worth of supply every time inventory falls to 5 days of supply.\u201d<\/p>\n <\/p>\n The amount of days added to the lead time to accommodate for increases in supplier lead time. \u00a0 By increasing safety time, orders will be triggered sooner thereby minimizing the risk of stockouts.<\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_line_height=”1.79em” background_size=”initial” background_position=”top_left” background_repeat=”repeat” z_index_tablet=”500″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength_tablet=”1px” link_text_shadow_horizontal_length_tablet=”0px” link_text_shadow_vertical_length_tablet=”0px” link_text_shadow_blur_strength_tablet=”1px” ul_text_shadow_horizontal_length_tablet=”0px” ul_text_shadow_vertical_length_tablet=”0px” ul_text_shadow_blur_strength_tablet=”1px” ol_text_shadow_horizontal_length_tablet=”0px” ol_text_shadow_vertical_length_tablet=”0px” ol_text_shadow_blur_strength_tablet=”1px” quote_text_shadow_horizontal_length_tablet=”0px” quote_text_shadow_vertical_length_tablet=”0px” quote_text_shadow_blur_strength_tablet=”1px” header_text_shadow_horizontal_length_tablet=”0px” header_text_shadow_vertical_length_tablet=”0px” header_text_shadow_blur_strength_tablet=”1px” header_2_text_shadow_horizontal_length_tablet=”0px” header_2_text_shadow_vertical_length_tablet=”0px” header_2_text_shadow_blur_strength_tablet=”1px” header_3_text_shadow_horizontal_length_tablet=”0px” header_3_text_shadow_vertical_length_tablet=”0px” header_3_text_shadow_blur_strength_tablet=”1px” header_4_text_shadow_horizontal_length_tablet=”0px” header_4_text_shadow_vertical_length_tablet=”0px” header_4_text_shadow_blur_strength_tablet=”1px” header_5_text_shadow_horizontal_length_tablet=”0px” header_5_text_shadow_vertical_length_tablet=”0px” header_5_text_shadow_blur_strength_tablet=”1px” header_6_text_shadow_horizontal_length_tablet=”0px” header_6_text_shadow_vertical_length_tablet=”0px” header_6_text_shadow_blur_strength_tablet=”1px” box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” global_colors_info=”{}”]<\/p>\n The portion of inventory that is expected to cover the lead time demand. In an inventory control system, the reorder point is comprised of the cycle stock and the safety stock. The more safety stock, the lower the risk of stocking out.<\/p>\n An inventory\u00a0management\u00a0process that predicts future inventory levels, costs, and service level performance. \u00a0<\/strong><\/p>\n <\/p>\n Lead time demand is a random quantity totaling all the demands that arrive during the lead time. SmartForecasts\u2019 key analytical computation is estimation of the probability distribution of lead time demand. From this flow assessments of service level, fill rate, and reorder point (min).<\/p>\n <\/p>\n A prescription of what to do when there is a stockout. Under a loss policy, any units demanded but not provided immediately are considered lost: either the customer gets those units elsewhere or just doesn\u2019t get them at all.<\/p>\n <\/p>\n An item is produced or ordered from a supplier when ordered by the customer. \u00a0 Inventory is not automatically replenished with Make to Order items.<\/p>\n <\/p>\n The \u201corder-up-to\u201d level in min\/max systems. The actual order quantity is random in the min\/max system: How much is ordered depends on the current gap between available inventory and the max.<\/p>\n <\/p>\n As with order quantities, order multiples are often imposed by suppliers, who may insist that order quantities be an even multiple of some basic unit. For instance, if a supplier only provides six packs,\u00a0you cannot order either 5 or 7 units; instead, you must order 6 or 12\u00a0<\/strong><\/p>\n <\/p>\n Represents a replenishment policy driven by the Order Up to Level and a fixed replenishment frequency.\u00a0\u00a0 For example, every two weeks (the replenishment frequency)<\/p>\n <\/p>\n The amount of inventory added to the average lead time demand to accommodate random increases in demand, thereby minimizing the risk of stockouts, with their attendant lost sales or backorders. The safety stock is strongly influenced by the volatility of demand. In an inventory system, a replenishment order is triggered when the supply of inventory is forecasted to hit the safety stock level. The order is placed at the Reorder Point.<\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.16″ text_line_height=”1.86em” background_size=”initial” background_position=”top_left” background_repeat=”repeat” z_index_tablet=”500″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength_tablet=”1px” link_text_shadow_horizontal_length_tablet=”0px” link_text_shadow_vertical_length_tablet=”0px” link_text_shadow_blur_strength_tablet=”1px” ul_text_shadow_horizontal_length_tablet=”0px” ul_text_shadow_vertical_length_tablet=”0px” ul_text_shadow_blur_strength_tablet=”1px” ol_text_shadow_horizontal_length_tablet=”0px” ol_text_shadow_vertical_length_tablet=”0px” ol_text_shadow_blur_strength_tablet=”1px” quote_text_shadow_horizontal_length_tablet=”0px” quote_text_shadow_vertical_length_tablet=”0px” quote_text_shadow_blur_strength_tablet=”1px” header_text_shadow_horizontal_length_tablet=”0px” header_text_shadow_vertical_length_tablet=”0px” header_text_shadow_blur_strength_tablet=”1px” header_2_text_shadow_horizontal_length_tablet=”0px” header_2_text_shadow_vertical_length_tablet=”0px” header_2_text_shadow_blur_strength_tablet=”1px” header_3_text_shadow_horizontal_length_tablet=”0px” header_3_text_shadow_vertical_length_tablet=”0px” header_3_text_shadow_blur_strength_tablet=”1px” header_4_text_shadow_horizontal_length_tablet=”0px” header_4_text_shadow_vertical_length_tablet=”0px” header_4_text_shadow_blur_strength_tablet=”1px” header_5_text_shadow_horizontal_length_tablet=”0px” header_5_text_shadow_vertical_length_tablet=”0px” header_5_text_shadow_blur_strength_tablet=”1px” header_6_text_shadow_horizontal_length_tablet=”0px” header_6_text_shadow_vertical_length_tablet=”0px” header_6_text_shadow_blur_strength_tablet=”1px” box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” global_colors_info=”{}”]<\/p>\n A classic but not always useful estimate of the \u201cbest\u201d order quantity. \u00a0The EOQ takes account of three factors: the average level of demand, the cost of holding inventory, and the cost of making a replenishment order. SmartForecasts provides alternative order quantity recommendations based on additional factors: the long-run stability of the system (i.e., you have to order at least enough to keep your head above water) and any supplier-imposed order minimums and multiples.<\/p>\n An inventory management process that yields an inventory with the lowest possible cost and maximum possible service. \u00a0 Inventory Forecasting methods that employ traditional rule of thumb policy or service level targeting are not sufficient to optimize inventory since the choice of service level is arbitrary and will not yield the maximum overall service for the lowest total cost.<\/p>\n <\/p>\n Otherwise known as \u201csell one, buy one.\u201d Represents a replenishment policy driven by a reorder point or min and a replenishment quantity that is equal to what was consumed. The replenishment frequency parallels the demand frequency as an order is placed to replenish each time inventory is consumed.<\/p>\n <\/p>\n Represents a replenishment policy driven by the Min and the Max.\u00a0\u00a0 When supply breaches the Min, an order is placed up to the Max.\u00a0\u00a0 With Min\/Max policy, the order quantity will vary depending on the gap between supply and max<\/p>\n <\/p>\n Represents a replenishment policy driven by the reorder point (R) and the reorder quantity (Q). With a Q,R policy, the replenishment quantity is always the same.<\/p>\n <\/p>\n The level of inventory which, when reached or breached, triggers replenishment. Also the same as the min in min\/max systems. Example: If reorder point is 7, any inventory level\u00a0 from 7 on down will trigger a replenishment order. \u00a0The Reorder Point or ROP is comprised of the the cycle stock and safety stock.<\/p>\n <\/p>\n An item availability metric that measures the ability to avoid stocking out during a replenishment lead time. Expressed as a percentage: A 90% service level implies a 10% chance of stockout. \u00a0What’s the difference between fill rate and service level?<\/a>\u00a0 In inventory forecasting, safety stock and reorder point levels can be planned with a user defined service level target.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” admin_label=”section” module_id=”archives” _builder_version=”4.16″ custom_padding_tablet=”50px|0|50px|0″ custom_padding_phone=”” transparent_background=”off” padding_mobile=”off” make_fullwidth=”off” use_custom_width=”off” width_unit=”on” locked=”off” global_colors_info=”{}”][et_pb_row admin_label=”row” _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text admin_label=”Featured Articles” _builder_version=”4.16″ header_font_size=”24px” background_size=”initial” background_position=”top_left” background_repeat=”repeat” z_index_tablet=”500″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength_tablet=”1px” link_text_shadow_horizontal_length_tablet=”0px” link_text_shadow_vertical_length_tablet=”0px” link_text_shadow_blur_strength_tablet=”1px” ul_text_shadow_horizontal_length_tablet=”0px” ul_text_shadow_vertical_length_tablet=”0px” ul_text_shadow_blur_strength_tablet=”1px” ol_text_shadow_horizontal_length_tablet=”0px” ol_text_shadow_vertical_length_tablet=”0px” ol_text_shadow_blur_strength_tablet=”1px” quote_text_shadow_horizontal_length_tablet=”0px” quote_text_shadow_vertical_length_tablet=”0px” quote_text_shadow_blur_strength_tablet=”1px” header_text_shadow_horizontal_length_tablet=”0px” header_text_shadow_vertical_length_tablet=”0px” 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[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row admin_label=”row” _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_tabs active_tab_background_color=”#eeeeee” inactive_tab_background_color=”#ffffff” admin_label=”Article tabs” _builder_version=”4.25.1″ background_color=”#edf2f7″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” hover_enabled=”0″ z_index_tablet=”500″ body_text_shadow_horizontal_length_tablet=”0px” body_text_shadow_vertical_length_tablet=”0px” body_text_shadow_blur_strength_tablet=”1px” tab_text_shadow_horizontal_length_tablet=”0px” tab_text_shadow_vertical_length_tablet=”0px” tab_text_shadow_blur_strength_tablet=”1px” body_link_text_shadow_horizontal_length_tablet=”0px” body_link_text_shadow_vertical_length_tablet=”0px” body_link_text_shadow_blur_strength_tablet=”1px” body_ul_text_shadow_horizontal_length_tablet=”0px” body_ul_text_shadow_vertical_length_tablet=”0px” body_ul_text_shadow_blur_strength_tablet=”1px” body_ol_text_shadow_horizontal_length_tablet=”0px” body_ol_text_shadow_vertical_length_tablet=”0px” body_ol_text_shadow_blur_strength_tablet=”1px” body_quote_text_shadow_horizontal_length_tablet=”0px” body_quote_text_shadow_vertical_length_tablet=”0px” body_quote_text_shadow_blur_strength_tablet=”1px” box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” use_border_color=”off” locked=”off” global_colors_info=”{}” sticky_enabled=”0″][et_pb_tab title=”2024″ _builder_version=”4.25.1″ _module_preset=”default” background_color=”#edf2f7″ background_enable_color=”on” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n Smart Software is excited to announce that we are joining Epicor,\u00a0<\/span><\/strong>a global leader of\u00a0industry-specific enterprise software<\/a>.\u00a0The acquisition brings together two companies tightly aligned in helping organizations get to the right insights at the right time and take action to maximize business performance.<\/p>\n In joining Epicor, Smart Software customers will benefit from significant scale, development, and investment in our inventory planning and optimization solutions, over time giving you even more capabilities and product options. In acquiring Smart Software, Epicor is complementing and strengthening its portfolio of best-in-class ERP solutions, helping makers, movers, and sellers worldwide streamline and simplify their supply chains to gain a competitive advantage.\u00a0As your strategic business partner, our top priority as we integrate the organizations in the coming months is to continue to provide you with the highest level of service and support you expect.<\/p>\n For more information on the news, please visit the\u00a0Epicor Newsroom<\/a><\/p>\n [\/et_pb_tab][et_pb_tab title=”2023″ _builder_version=”4.24.2″ _module_preset=”default” background_color=”#edf2f7″ background_enable_color=”on” global_colors_info=”{}”]<\/p>\n Smart Software is pleased to announce the award of US Patent 11,656,887<\/strong>.<\/a> \u201cSystem And Method to Simulate Demand and Optimize Control Parameters for a Technology Platform.\u201d<\/p>\n The patent directs \u201ctechnical solutions for analyzing historical demand data of resources in a technology platform to facilitate management of an automated process in the platform.\u201d One important application is optimization of parts inventories.<\/p>\n [\/et_pb_tab][et_pb_tab title=”2022″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n Smart Software named a Microsoft Co-sell-ready partner<\/strong><\/a> as a leading demand planning and inventory optimization solutions provider.\u00a0 Microsoft customers leverage Smart\u2019s web-native platform for Inventory Planning and Optimization (Smart IP&O) to develop consensus forecasts, manage demand, and optimize stocking policies.<\/p>\n [\/et_pb_tab][et_pb_tab title=”2021″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n We are so grateful to announce Smart Software\u2019s 40th anniversary. Forty years of Innovation for Demand Forecasting, Inventory Planning, and Supply Chain Analytics. Smart, Hartunian, and Willemain was incorporated in June 1981<\/a> by Charles Smart, Thomas Willemain, and Nelson Hartunian, our visionary founders.<\/p>\n [\/et_pb_tab][et_pb_tab title=”2020″ _builder_version=”4.16″ background_color_gradient_direction_tablet=”180deg” background_color_gradient_direction_phone=”180deg” background_color_gradient_stops_tablet=”#2b87da 0%|#29c4a9 100%” background_color_gradient_stops_phone=”#2b87da 0%|#29c4a9 100%” background_color_gradient_start_position_tablet=”0%” background_color_gradient_start_position_phone=”0%” background_color_gradient_end_position_tablet=”100%” background_color_gradient_end_position_phone=”100%” hover_transition_duration_tablet=”300ms” hover_transition_duration_phone=”300ms” hover_transition_delay_tablet=”0ms” hover_transition_delay_phone=”0ms” body_text_shadow_horizontal_length_tablet=”0px” body_text_shadow_horizontal_length_phone=”0px” body_text_shadow_vertical_length_tablet=”0px” body_text_shadow_vertical_length_phone=”0px” 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body_ol_text_shadow_horizontal_length_phone=”0px” body_ol_text_shadow_vertical_length_tablet=”0px” body_ol_text_shadow_vertical_length_phone=”0px” body_ol_text_shadow_blur_strength_tablet=”1px” body_ol_text_shadow_blur_strength_phone=”1px” body_quote_text_shadow_horizontal_length_tablet=”0px” body_quote_text_shadow_horizontal_length_phone=”0px” body_quote_text_shadow_vertical_length_tablet=”0px” body_quote_text_shadow_vertical_length_phone=”0px” body_quote_text_shadow_blur_strength_tablet=”1px” body_quote_text_shadow_blur_strength_phone=”1px” global_colors_info=”{}”]<\/p>\n Supply and Demand Chain Executive 2020 Online Magazine features an article about inventory optimization at BC Transit, entitled \u201cOptimizing Parts Management at BC Transit.<\/a>\u201d <\/strong>\u00a0Eric Nelson, Director for Supply Services at BC Transit explains how Smart IP&O has helped ensure that they have the right part in the right place at the right time to equip their entire service network with 35 repair locations.<\/p>\n [\/et_pb_tab][et_pb_tab title=”2019″ _builder_version=”4.16″ background_color_gradient_direction_tablet=”180deg” background_color_gradient_direction_phone=”180deg” background_color_gradient_stops_tablet=”#2b87da 0%|#29c4a9 100%” background_color_gradient_stops_phone=”#2b87da 0%|#29c4a9 100%” background_color_gradient_start_position_tablet=”0%” background_color_gradient_start_position_phone=”0%” background_color_gradient_end_position_tablet=”100%” background_color_gradient_end_position_phone=”100%” hover_transition_duration_tablet=”300ms” hover_transition_duration_phone=”300ms” hover_transition_delay_tablet=”0ms” hover_transition_delay_phone=”0ms” body_text_shadow_horizontal_length_tablet=”0px” body_text_shadow_horizontal_length_phone=”0px” body_text_shadow_vertical_length_tablet=”0px” body_text_shadow_vertical_length_phone=”0px” body_text_shadow_blur_strength_tablet=”1px” body_text_shadow_blur_strength_phone=”1px” tab_text_shadow_horizontal_length_tablet=”0px” tab_text_shadow_horizontal_length_phone=”0px” tab_text_shadow_vertical_length_tablet=”0px” tab_text_shadow_vertical_length_phone=”0px” tab_text_shadow_blur_strength_tablet=”1px” tab_text_shadow_blur_strength_phone=”1px” body_link_text_shadow_horizontal_length_tablet=”0px” body_link_text_shadow_horizontal_length_phone=”0px” body_link_text_shadow_vertical_length_tablet=”0px” body_link_text_shadow_vertical_length_phone=”0px” body_link_text_shadow_blur_strength_tablet=”1px” body_link_text_shadow_blur_strength_phone=”1px” body_ul_text_shadow_horizontal_length_tablet=”0px” body_ul_text_shadow_horizontal_length_phone=”0px” body_ul_text_shadow_vertical_length_tablet=”0px” body_ul_text_shadow_vertical_length_phone=”0px” body_ul_text_shadow_blur_strength_tablet=”1px” body_ul_text_shadow_blur_strength_phone=”1px” body_ol_text_shadow_horizontal_length_tablet=”0px” body_ol_text_shadow_horizontal_length_phone=”0px” body_ol_text_shadow_vertical_length_tablet=”0px” body_ol_text_shadow_vertical_length_phone=”0px” body_ol_text_shadow_blur_strength_tablet=”1px” body_ol_text_shadow_blur_strength_phone=”1px” body_quote_text_shadow_horizontal_length_tablet=”0px” body_quote_text_shadow_horizontal_length_phone=”0px” body_quote_text_shadow_vertical_length_tablet=”0px” body_quote_text_shadow_vertical_length_phone=”0px” body_quote_text_shadow_blur_strength_tablet=”1px” body_quote_text_shadow_blur_strength_phone=”1px” global_colors_info=”{}”]<\/p>\n Don\u2019t Be a Victim of your Forecast Models \u2013 Special Section in Foresight Magazine<\/a>.<\/strong> In this feature section, Tom Willemain provokes a good deal of thought about the role of statistical models in supply chain forecasting, a field that he believes lags far behind finance in embracing algorithms over gut instinct. Download Special Section on Forecast Modeling in Spring 2019 Issue of Foresight Magazine<\/a><\/strong><\/p>\n [\/et_pb_tab][et_pb_tab title=”2018 and prior” _builder_version=”4.17.6″ global_colors_info=”{}”]<\/p>\n Right-Sizing Inventory with Demand Forecasting,\u201d interview with Chief Material Officer at Metro-North Railroad. <\/a><\/strong> See \u201cFour Steps to Service Level-Driven Inventory Planning\u201d in SupplyChain Management Review.<\/a><\/strong> Minnesota\u2019s Metro Transit adopts service-level driven method of inventory planning from Smart Software.<\/a><\/strong> Video Interview with SupplyChainBrain, \u201cService Level-Driven Demand Planning\u201d<\/a><\/strong> Conquering Supply Chain Variability at Rev-A-Shelf,\u201d in Supply & Demand Chain Executive Online<\/a><\/strong> Now You See It, Now You Don\u2019t Inventory,\u201d New technologies to address intermittent demand, in Aviation Week Online<\/a><\/strong> Webinar Replay: Agile Demand Forecasting, the Rev-A-Shelf Experience.<\/a><\/strong> Feature Article: MCI\u2019s Parts Planning Excels with Smart Software\u201d in BusRide Maintenance Magazine<\/a><\/strong> Webinar replay: CFO View of Demand Forecasting, with Bud Schultz, NKK Switches. Originally broadcast 9\/26\/2013.<\/a><\/strong> Featured Review: \u201cSmart Software for Service-level Driven Forecasting\u201d by Technology Evaluation Centers.<\/a><\/strong> Feature Article: \u201cForecasting \u2013 It\u2019s More than Inventory Management,\u201d in Supply & Demand Chain Executive.<\/a><\/strong> Feature Article: \u201cSmall Operational Changes Bring Big Cost-Cutting Results for Transit Agencies\u201d in APTA Passenger Transport Magazine<\/a><\/strong> Feature Article: \u201cMeeting the Service Parts Inventory Planning Challenge\u201d in BUSride Maintenance Magazine<\/a><\/strong> SmartForecasts Review: \u201cSmarter Inventory Management: Forecasting public transportation needs with the complete software package\u201d in APICS Magazine<\/a><\/strong> Transit Talk Blog: \u201cHow to Discover Hidden Cost Savings in Your Transit Operations\u201d<\/a><\/strong> Cover Story: A Northeast Commuter Railroad Struggles to Optimize Its Spare Parts Inventory<\/a><\/strong> “Prestolite Charges up Its Inventory Management”<\/a><\/strong> “How to Survive the Economic Crunch”<\/a><\/strong> “Smooth Ride: Forecasting solution improves product deployment and reduces transportation costs”<\/a><\/strong> “Prevost Parts increases replacement part availability and reduces inventory through improved demand forecasting” by Alex Daudelin.<\/a><\/strong> “The Right Tools” by Charles Smart, president of Smart Software.<\/strong><\/a> “Forecasting-As Important as Ever” by Charles Smart, president of Smart Software.<\/strong><\/a>Lead Time<\/h3>\n
Min level of inventory<\/h3>\n
Order Quantity<\/h3>\n
Order Quantity Minimum<\/h3>\n
Rule of Thumb<\/h3>\n
Safety Time<\/h3>\n
Cycle Stock<\/h3>\n
\u00a0<\/h3>\n
Inventory Forecasting<\/h3>\n
Lead Time Demand<\/h3>\n
Loss Policy<\/h3>\n
Make\/Procure to Order<\/h3>\n
Max level of inventory<\/h3>\n
Order Quantity Multiple<\/h3>\n
Order Up to Policy<\/h3>\n
Safety Stock<\/h3>\n
Economic Order Quantity (EOQ)<\/h3>\n
\u00a0<\/h3>\n
Inventory Optimization<\/h3>\n
Lot for Lot Policy<\/h3>\n
Min\/Max Inventory Policy<\/h3>\n
Q,R or R,Q Policy<\/h3>\n
Reorder Point<\/h3>\n
Service Level<\/h3>\n
Article Archives<\/h2>\n
Supply & Demand Chain Executive<\/em> \u2014 June 26<\/p>\n
SupplyChain Management Review<\/em> \u2014 April 12, 2015<\/p>\n
Mass Transit Magazine<\/em> \u2014 February 2015<\/p>\n
SupplyChainBrain<\/em> \u2014 June 30, 2014<\/p>\n
Supply & Demand Chain Executive<\/em> \u2014 April 9, 2014<\/p>\n
Aviation Week<\/em> \u2014 April 7, 2014<\/p>\n
SmartSoftware Inc.<\/em> \u2014 January 2014<\/p>\n
BusRide Maintenance Magazine<\/em> \u2014 September 2013<\/p>\n
SmartSoftware Inc.<\/em> \u2014 September 2013<\/p>\n
Technology Evaluation Centers<\/em> \u2014 May 2013<\/p>\n
Supply & Demand Chain Executive<\/em> \u2014 February 2013<\/p>\n
APTA Passenger Transport Magazine<\/em> \u2014 June 2012<\/p>\n
BUSride Maintenance Magazine<\/em> \u2014 April 2012<\/p>\n
APICS magazine<\/em> \u2014 January\/February 2012<\/p>\n
Mass Transit Magazine<\/em> \u2014 September, 2011<\/p>\n
SupplyChainBrain<\/em> \u2014 May\/June 2011<\/p>\n
When retirements drained its planning expertise and a bad mix of too much inventory put a strain on cash flow, the company brought in a new forecasting tool to power its planning process. S&DCE Aug\/Sep 2010<\/strong><\/p>\n
Current economic conditions are challenging everyone\u2019s business. This is especially true for companies in the manufacturing and distribution sectors that have a large percentage of their supply chain resources tied up in inventory. With credit tight, these companies are looking for ways to preserve as much cash as possible. Because inventory is cash sitting on the shelves, a prime way to reduce costs and increase cash flows is to improve the forecasting and planning of inventory requirements. SDCExec.com May 2009<\/strong><\/p>\n
See how Prevost Parts, a division of Canadian bus manufacturer Prevost Car, has used SmartForecasts to improve inventory allocation and distribution effectiveness in the North American aftermarket for its 25,000 motorcoach and urban bus parts. Learn about Prevost Parts’ evaluation criteria in selecting SmartForecasts over five other applications considered, and the importance of Smart’s unique intermittent demand forecasting capability in solving Prevost’s forecasting and safety stock estimation problems. APICS May 2005<\/strong><\/p>\n
Read an article about how Prevost Parts, the parts division of Canadian bus manufacturer Prevost Car, uses SmartForecasts to more effectively distribute replacement parts for the North American motorcoach and transit bus markets. Learn why the company selected SmartForecasts over SAP’s demand planning application and now expects both a 25% increase in forecast accuracy and close to a 20% reduction in inventory stocking levels. Geston Logistique\u00a0March 2004<\/strong><\/p>\n
Learn how the right statistical forecasting tools combined with collaborative inputs from management, salespeople and customers can greatly improve forecast accuracy and streamline a company’s demand planning process. APICS May 2003<\/strong><\/p>\n
Read why demand forecasting is still essential in this new manufacturing age. APICS Nov\/Dec 2001<\/strong><\/p>\n