{"id":12832,"date":"2024-08-27T11:03:56","date_gmt":"2024-08-27T15:03:56","guid":{"rendered":"https:\/\/smartcorp.com\/inventory-optimization\/faq-mastering-smart-ipo-for-better-inventory-management-copy\/"},"modified":"2024-08-27T11:06:02","modified_gmt":"2024-08-27T15:06:02","slug":"het-belang-van-duidelijke-definities-van-serviceniveaus-bij-voorraadbeheer-2","status":"publish","type":"post","link":"https:\/\/smartcorp.com\/nl\/blog\/faq-mastering-smart-ipo-for-better-inventory-management-ai\/","title":{"rendered":"FAQ: Slimme IP&O voor beter voorraadbeheer."},"content":{"rendered":"

[et_pb_section fb_built=”1″ _builder_version=”4.16″ _module_preset=”default” custom_margin=”0px||||false|false” custom_padding=”0px||||false|false” global_colors_info=”{}”][et_pb_row admin_label=”Row” module_class=”blog_glob” _builder_version=”4.16″ locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ saved_specialty_column_type=”2_3″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text content_last_edited=”off|desktop” admin_label=”CONTENT” module_class=”post-main_text” _builder_version=”4.27.0″ header_3_text_color=”#0c71c3″ header_3_font_size=”19px” 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” use_border_color=”off” global_colors_info=”{}”]<\/p>\n

Effective supply chain and inventory management are essential for achieving operational efficiency and customer satisfaction. This blog provides clear and concise answers to some basic and other common questions from our Smart IP&O customers, offering practical insights to overcome typical challenges and enhance your inventory management practices. Focusing on these key areas, we help you transform complex inventory issues into strategic, manageable actions that reduce costs and improve overall performance with Smart IP&O.<\/p>\n

1. What is lead time demand?<\/strong>
The demand is expected to occur over the replenishment lead time. Lead time demand is determined by Smart\u2019s forecasting methods.\u00a0<\/a><\/p>\n

2. What is the Min, and how is it computed?<\/strong>
The Min is displayed in the drivers section of SIO <\/a>is the reorder point and is the sum of the lead time demand and the safety stock. When on-hand inventory falls below the minimum due to demand, you will need to order more. \u00a0Smart also has a \u201cmin\u201d in the \u201cordering rules\u201d field of <\/span>SIO<\/a>, which is the minimum order quantity you can place with a supplier.\u00a0 <\/span><\/p>\n

3. What is the Max, and how is it computed?<\/strong>
The max is the largest quantity of inventory <\/a>that will be on the shelf if you adhere to the ordering policy. The Max is the sum of the Min (reorder point) plus the defined OQ.\u00a0<\/strong><\/p>\n

4. How do you determine the order quantity (OQ)?<\/strong>
The order quantity is initially imported from your ERP system. It can be changed based on a number of user defined choices, including:<\/p>\n

Multiple lead time demand
Multiple monthly or weekly demand
Smart\u2019s recommended OQ<\/p>\n

5. What is the Economic Order Quantity?<\/strong>
It is the order quantity that will minimize<\/a> the total costs, considering the cost of holding and costs of ordering inventory.\u00a0<\/strong><\/p>\n

6. What is the \u201crecommended OQ\u201d that Smart computes? <\/strong>
It is the economic order quantity plus an adjustment if necessary to ensure that the size of the order is greater than or equal to the demand over lead time.<\/p>\n

7. Why is the system predicting that we\u2019ll have a low <\/strong>service level<\/strong><\/a>? <\/strong>
Smart predicts the service level that will result from the specified inventory policy (Min\/Max or Reorder Point\/Order Quantity), assuming adherence to that policy.\u00a0 When the predicted service level is low, it can mean that the expected demand over the lead time is greater than the reorder point (Min).\u00a0 When demand over the replenishment lead time is greater than the reorder point your probability of stocking out is higher resulting in a low service level. It may also be that your lead time for replenishment isn\u2019t entered accurately.\u00a0 If the lead time entered is longer than reality, the reorder point may not cover the demand over the lead time.\u00a0 Please check your lead time inputs.<\/p>\n

8. Why is the Service level showing as zero when the reorder point (or min) is not zero?
<\/strong>Smart predicts the service level <\/a>that will result from the specified inventory policy (Min\/Max or Reorder Point\/Order Quantity), assuming adherence to that policy. When the predicted service level is low, it can mean that the expected demand over the lead time is greater than the reorder point (Min), sometimes many times greater, which would all but guarantee a stock-out.\u00a0 When demand over the replenishment lead time is greater than the reorder point your probability of stocking out is higher resulting in a low service level. It may also be that your lead time for replenishment isn\u2019t entered accurately.\u00a0 If the lead time entered is longer than reality, the reorder point may not cover the demand over the lead time.\u00a0 Please check your lead time inputs.<\/p>\n

9. But my actual service levels aren\u2019t as low as Smart is predicting, why? <\/strong>
That may be true because Smart predicts your service level if you adhere to the policy.\u00a0 It is possible you aren\u2019t adhering to the policy that the service level prediction is based on.<\/a>\u00a0 If your on-hand inventory is higher than your Max quantity, you aren\u2019t adhering to the policy.\u00a0 Check your input assumptions for lead time.\u00a0\u00a0 Your actual lead times might be much shorter than entered resulting in a predicted service level that is lower than you expect.<\/span><\/p>\n

10. Smart seems to be recommending too much inventory, or at least more than I\u2019d expect it would; why? <\/strong>
You should consider evaluating the inputs, such as service level and lead times.\u00a0 Perhaps your actual lead times aren\u2019t as long as the lead time Smart is using.\u00a0 We\u2019ve seen situations where suppliers artificially inflate their quoted lead times to ensure they are always on time.\u00a0 If you use that lead time when computing your safety stocks, you\u2019ll inevitably over-stock.\u00a0 So, review your actual lead time history (Smart provides the supplier performance report for this) to get a sense of the actual lead times and adjust accordingly.\u00a0 Or it is possible you are asking for a very high service level that may be further compounded with a very volatile item that has several significant spikes in demand.\u00a0 When demand significantly fluctuates from the mean, using a high service level target (98%+) will result in stocking policies that are designed to cover even very large spikes.\u00a0 Try a lower service level target or reducing the lead time (assuming the specified lead time is no longer realistic) and your inventory will decrease, sometimes very substantially.<\/p>\n

11. Smart is using spikes in demand I don\u2019t want it to consider, and it is inflating inventory, how can I correct this?<\/strong>
If you are sure that the spike won\u2019t happen again, then you can remove it from the historical data via an override using Smart Demand Planner. You\u2019ll need to open the forecast project containing that item, adjust the history, and save the adjusted history.\u00a0 You can contact tech support to help you set this up. If the spikes are part of the normal randomness that can sometimes occur, it\u2019s best to leave it alone. Instead, consider a lower service level target.\u00a0 The lower target means the reorder points don\u2019t need to cover the extreme values as often resulting in a lower inventory.<\/p>\n

12. When I change the Order Quantity or Max, my cycle service levels don\u2019t change, why?<\/strong>
Smart reports on \u201ccycle service level\u201d and \u201cservice level.\u201d\u00a0 When you change your order quantities and Max quantities this will not impact the \u201ccycle service level\u201d because cycle service levels report on performance during the replenishment period only.\u00a0 This is because all that protects you from stockout after the order is placed (and you must wait until the order arrives for the replenishment) is the reorder point or Min. Changing the size of the order quantity or Max on hand (up to levels) won\u2019t impact your cycle service levels. \u00a0Cycle service level is influenced only by the size of the reorder points and the amount of safety stock being added whereas Smart\u2019s \u201cservice level\u201d will change when you modify both reorder points and order quantities.<\/p>\n

13. My forecast looks inaccurate.\u00a0 It\u2019s not showing any of the ups and downs observed in history, why?<\/strong>
A good forecast is the one number that is closest to the actual compared to other numbers that could have been predicted.\u00a0 When the historical ups and downs aren\u2019t happening in predictable intervals then often, the best forecast is one that averages or smooths through those historical ups and downs.\u00a0 A forecast predicting future ups and downs that aren\u2019t happening in obvious patterns historically is more likely to be less accurate than one that is forecast a straight or trend line only.<\/p>\n

14. What is optimization? How does it work?<\/strong>
Optimization is an option for setting stocking policies where the software picks the stocking policy that yields the total lowest operating cost.\u00a0 For example, if an item is very expensive to hold, a policy that has more stockouts, but less inventory would yield total lower costs than a policy that had fewer stockouts and more inventory.\u00a0\u00a0 On the other hand, if the item has a high stock out cost then a policy that yields fewer stockouts but requires more inventory would yield more financial benefit than a policy that had less inventory but more stockouts.\u00a0 When using the optimization feature, the user must specify the service level floor (the minimum service level).\u00a0 The software will then decide whether a higher service level will yield a better return.\u00a0 If it does, the reordering policies will target the higher service level.\u00a0 If it doesn\u2019t the reordering policies will default to the user defined service level floor.\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0This webinar provides details and explanations on the math behind optimization.\u00a0 https:\/\/www.screencast.com\/t\/3CfKJoMe2Uj<\/a><\/p>\n

15. What is a what-if scenario?<\/strong>
What-if scenarios enable you to try out different user-defined choices of inventory policy and test the predicted impact on metrics such as service levels, fill rates, and inventory value. To explore these scenarios, click on the Drivers tab, either at the summary level or the \u201cItems\u201d level, and enter the desired adjustments. You can then recalculate to see how these changes would affect your overall inventory performance. This allows you to compare various strategies and select the most cost-effective and efficient approach for your supply chain.<\/p>\n

By addressing common questions and challenges, we’ve provided actionable insights to help you improve your inventory management practices. With Smart IP&O, you have the tools you need to make informed inventory decisions, reduce costs, and enhance overall performance.<\/strong><\/p>\n

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\"\"<\/a><\/p>\n

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Effective supply chain and inventory management are essential for achieving operational efficiency and customer satisfaction. This blog provides clear and concise answers to some basic and other common questions from our Smart IP&O customers, offering practical insights to overcome typical challenges and enhance your inventory management practices. Focusing on these key areas, we help you transform complex inventory issues into strategic, manageable actions that reduce costs and improve overall performance with Smart IP&O.<\/p>","protected":false},"author":157,"featured_media":12821,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"

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Recently, I had an interesting conversation with an inventory manager and the VP Finance. We were discussing the benefits of being able to automatically optimize both reorder points and order quantities. The VP Finance was concerned that given their large supplier required minimum order quantities, they would not be able to benefit.\u00a0 He said his suppliers held all the power, forcing him to accept massive minimum order quantities and tying his hands. While he felt bad about this, he saw a silver lining: He didn\u2019t have to do any planning. He would accept a large inventory investment, but his customer service levels would the exceptional.\u00a0 Perhaps the large inventory investment was assumed to be the cost of doing business.<\/p>

I pushed back and pointed out that he was not as powerless as he felt. He still had control of the other half of the procurement process: while he couldn\u2019t control how much to order, he could control when to order by adjusting the reorder point. In other words, there is always room for careful quantitative analysis in inventory management, even when you have one hand tied behind your back.<\/p>

An Example<\/strong><\/p>

To put some numbers behind my argument, I created a scenario then analyzed it using our methodology to show how consequential it can be to use inventory optimization software even in constrained situations. In this scenario, item demand averages 2.2 units per day but varies significantly by day of week. Let\u2019s say the imaginary supplier insists on a minimum order quantity of 500 units (way out of proportion to demand) and fills replenishment orders in either three days or ten days in equal proportions (quite inconsistent). To spread the blame around, let\u2019s also suppose that the imaginary supplier\u2019s imaginary customer uses a foolish rule that the reorder point should be 10% of the minimum order quantity. (Why this rule? Too many companies use simple\/simplistic rules of thumb in lieu of proper analysis.)<\/p>

So, we have a base case in which the order quantity is 500 units, and the reorder point is 50 units. In this case, the fill rate is 100%, but the average number of units on hand is a whopping 330. If the customer would simply lower the reorder point from 50 to 15, the fill rate would still be 99.5%, but the average stock on hand would drop by 11% to 295 units. Using the one hand not tied behind his back, the inventory manager could cut his inventory investment by more than 10%, which would be a noticeable win.<\/p>

Incidentally, if the minimum order quantity were abolished, the customer would be free to arrive at a new and much better solution. Setting the order quantity to 45 and the reorder point to 25 would achieve a 99% fill rate at the cost of a daily on-hand level of only 35 units: nearly a 90% reduction in inventory investment: a major improvement over the status quo.<\/p>

Postscript<\/strong><\/p>

These calculations are possible using our software, which can make visible the otherwise unknown relationships between inventory system design choices (e.g., order quantity and reorder point) and key performance indicators (e.g., average units on hand and fill rate).\u00a0 Armed with this ability to conduct these calculations, alternative arrangements with the supplier may now be considered. For example, what if, in exchange for paying a higher price per unit, the supplier agreed to a lower MOQ. Using the software to conduct an analysis of the key performance indicators using the \u201cwhat if\u201d costs and MOQs would reveal the cost per unit and MOQ that would be needed to develop a more profitable deal.\u00a0\u00a0 Once identified, all parties stand to benefit.\u00a0 The supplier now generates a better margin on sales of its products, and the buyer holds considerably less inventory yielding a holding cost reduction that dwarfs the added cost per unit.\u00a0 Everyone wins.<\/p>

\u00a0<\/p>

\u00a0<\/p>

\"\"<\/a><\/p>

[\/et_pb_text][et_pb_code module_class=\"comment_sect\" _builder_version=\"4.10.7\" global_colors_info=\"{}\"]jQuery(document).ready(function($) { \/\/ Stuff to do as soon as the DOM is ready. Use $() w\/o colliding with other libs$(window).on('load', function(){ if ($(window).width() < 2000 ) { $(\".comment_sect\").append($(\"#comment-wrap\")) } if ($(window).width() < 2000) { $(\"#et-main-area\").prepend($(\".blog_bg \")) } if ($(window).width() < 2000 ) { $(\".post-main_text\").prepend($(\".et_post_meta_wrapper\")) } }); });[\/et_pb_code][et_pb_code admin_label=\"Comment \" module_class=\"com-title\" global_colors_info=\"{}\"]<\/p>

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