{"id":12521,"date":"2024-06-24T09:14:52","date_gmt":"2024-06-24T13:14:52","guid":{"rendered":"https:\/\/smartcorp.com\/inventory-optimization\/why-inventory-planning-should-not-rely-exclusively-on-simple-rules-of-thumb-copy\/"},"modified":"2024-07-12T10:02:31","modified_gmt":"2024-07-12T14:02:31","slug":"el-costo-de-la-planificacion-de-hojas-de-calculo","status":"publish","type":"post","link":"https:\/\/smartcorp.com\/es\/blog\/el-costo-de-la-planificacion-de-hojas-de-calculo\/","title":{"rendered":"El costo de la planificaci\u00f3n con hojas de c\u00e1lculo"},"content":{"rendered":"

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Las empresas que dependen de hojas de c\u00e1lculo para la planificaci\u00f3n de la demanda, la previsi\u00f3n y la gesti\u00f3n de inventario a menudo se ven limitadas por las limitaciones inherentes de las hojas de c\u00e1lculo. Esta publicaci\u00f3n examina los inconvenientes de los enfoques tradicionales de gesti\u00f3n de inventario causados por las hojas de c\u00e1lculo y sus costos asociados, compar\u00e1ndolos con los importantes beneficios que se obtienen al adoptar tecnolog\u00edas de planificaci\u00f3n de \u00faltima generaci\u00f3n.<\/p>\n

Las hojas de c\u00e1lculo, si bien son flexibles por su infinita capacidad de personalizaci\u00f3n, son fundamentalmente de naturaleza manual y requieren una importante gesti\u00f3n de datos, aportaci\u00f3n humana y supervisi\u00f3n. Esto aumenta el riesgo de errores, desde simples errores al ingresar datos hasta complejos errores de f\u00f3rmula, que causan efectos en cascada que impactan negativamente en los pron\u00f3sticos. Adem\u00e1s, a pesar de los avances en las funciones colaborativas que permiten que varios usuarios interact\u00faen con una hoja com\u00fan, los procesos basados en hojas de c\u00e1lculo suelen estar aislados. El titular de la hoja de c\u00e1lculo posee los datos. Cuando esto sucede, comienzan a surgir muchas fuentes de datos veraces. Sin la confianza de una fuente de datos acordada, pr\u00edstina y actualizada autom\u00e1ticamente, las organizaciones no tienen la base necesaria a partir de la cual se pueden construir modelos predictivos, pron\u00f3sticos y an\u00e1lisis.<\/p>\n

Por el contrario, los sistemas de planificaci\u00f3n avanzada como Smart IP&O est\u00e1n dise\u00f1ados para superar estas limitaciones. Dichos sistemas est\u00e1n dise\u00f1ados para ingerir datos autom\u00e1ticamente a trav\u00e9s de API o archivos de sistemas ERP y EAM, transformar esos datos utilizando herramientas ETL integradas y pueden procesar grandes vol\u00famenes de datos de manera eficiente. Esto permite a las empresas gestionar tareas complejas de inventario y previsi\u00f3n con mayor precisi\u00f3n y menos esfuerzo manual porque la recopilaci\u00f3n, agregaci\u00f3n y transformaci\u00f3n de datos ya est\u00e1n realizadas. La transici\u00f3n a sistemas de planificaci\u00f3n avanzados es clave para optimizar los recursos por varias razones.<\/p>\n

Las hojas de c\u00e1lculo tambi\u00e9n tienen un problema de escala. Cuanto m\u00e1s crece el negocio, mayor es el n\u00famero de hojas de c\u00e1lculo, libros de trabajo y f\u00f3rmulas. El resultado es un conjunto de interdependencias r\u00edgidas y estrechamente entrelazadas que se vuelven dif\u00edciles de manejar e ineficientes. Los usuarios tendr\u00e1n dificultades para manejar el aumento de la carga y la complejidad con tiempos de procesamiento lentos y la incapacidad de administrar grandes conjuntos de datos y enfrentar desaf\u00edos al colaborar entre equipos y departamentos.<\/p>\n

Por otro lado, los sistemas de planificaci\u00f3n avanzados para la optimizaci\u00f3n del inventario, la planificaci\u00f3n de la demanda y la gesti\u00f3n de inventario son escalables y est\u00e1n dise\u00f1ados para crecer con el negocio y adaptarse a sus necesidades cambiantes. Esta escalabilidad garantiza que las empresas puedan seguir gestionando su inventario y sus previsiones de forma eficaz, independientemente del tama\u00f1o o la complejidad de sus operaciones. Al hacer la transici\u00f3n a sistemas como Smart IP&O, las empresas no s\u00f3lo pueden mejorar la precisi\u00f3n de su gesti\u00f3n y pron\u00f3stico de inventario, sino tambi\u00e9n obtener una ventaja competitiva en el mercado al ser m\u00e1s receptivos a los cambios en la demanda y m\u00e1s eficientes en sus operaciones.<\/p>\n

Beneficios de saltar:<\/strong> Una empresa de servicios el\u00e9ctricos luchaba por mantener la disponibilidad de piezas de repuesto sin tener un exceso de existencias para m\u00e1s de 250.000 piezas en una red diversa de instalaciones de generaci\u00f3n y distribuci\u00f3n de energ\u00eda. Reemplaz\u00f3 su proceso de planificaci\u00f3n heredado de veinte a\u00f1os que hac\u00eda un uso intensivo de hojas de c\u00e1lculo con Smart IP&O y una integraci\u00f3n en tiempo real a su sistema EAM. Antes de Smart, solo pod\u00edan modificar los niveles m\u00ednimo\/m\u00e1ximo y de stock de seguridad con poca frecuencia. Cuando lo hicieron, casi siempre fue porque ocurri\u00f3 un problema que desencaden\u00f3 la revisi\u00f3n. Los m\u00e9todos utilizados para cambiar los par\u00e1metros de almacenamiento dependieron en gran medida de la intuici\u00f3n y de los promedios del uso hist\u00f3rico. La empresa de servicios p\u00fablicos aprovech\u00f3 los escenarios hipot\u00e9ticos de Smart para crear gemelos digitales de pol\u00edticas de almacenamiento alternativas y simul\u00f3 c\u00f3mo se comportar\u00eda cada escenario en indicadores clave de rendimiento, como el valor del inventario, los niveles de servicio, las tasas de cumplimiento y los costos de escasez. El software identific\u00f3 aumentos y disminuciones m\u00ednimos y m\u00e1ximos espec\u00edficos que se implementaron en su sistema EAM, impulsando reabastecimientos \u00f3ptimos de sus repuestos. El resultado: una importante reducci\u00f3n de inventario de $9 millones que liber\u00f3 efectivo y valioso espacio de almac\u00e9n al mismo tiempo que mantuvo los niveles de servicio objetivo de 99%+.<\/p>\n

Gesti\u00f3n de la precisi\u00f3n del pron\u00f3stico: <\/strong>El error de pron\u00f3stico es una parte inevitable de la gesti\u00f3n de inventario, pero la mayor\u00eda de las empresas no lo rastrean. Como dijo Peter Drucker: "No se puede mejorar lo que no se mide". Una empresa mundial de fabricaci\u00f3n de alta tecnolog\u00eda que utilizaba un proceso de pron\u00f3stico basado en hojas de c\u00e1lculo tuvo que crear manualmente sus pron\u00f3sticos de referencia y sus informes de precisi\u00f3n de los pron\u00f3sticos. Dada la carga de trabajo de los planificadores y los procesos aislados, simplemente no actualizaban sus informes con mucha frecuencia y, cuando lo hac\u00edan, los resultados ten\u00edan que distribuirse manualmente. La empresa no ten\u00eda forma de saber cu\u00e1n preciso era un pron\u00f3stico determinado y no pod\u00eda citar sus errores reales por grupo de piezas con confianza. Tampoco sab\u00edan si sus pron\u00f3sticos estaban superando a un m\u00e9todo de control. Despu\u00e9s de que Smart IP&O entr\u00f3 en funcionamiento, el m\u00f3dulo de planificaci\u00f3n de la demanda lo automatiz\u00f3. Smart Demand Planner ahora vuelve a pronosticar autom\u00e1ticamente su demanda en cada ciclo de planificaci\u00f3n utilizando m\u00e9todos de aprendizaje autom\u00e1tico y guarda informes de precisi\u00f3n para cada pieza x ubicaci\u00f3n. Cualquier anulaci\u00f3n que se aplique a los pron\u00f3sticos ahora se puede comparar autom\u00e1ticamente con la l\u00ednea de base para medir el valor agregado del pron\u00f3stico, es decir, si el esfuerzo adicional para realizar esos cambios mejor\u00f3 la precisi\u00f3n. Ahora que existe la capacidad de automatizar el pron\u00f3stico estad\u00edstico de referencia y producir informes de precisi\u00f3n, esta empresa tiene una base s\u00f3lida desde la cual mejorar su proceso de pron\u00f3stico y la precisi\u00f3n del pron\u00f3stico resultante.<\/p>\n

H\u00e1galo bien y mant\u00e9ngalo bien:\u00a0 <\/strong>Otro cliente del negocio de repuestos ha utilizado las soluciones de previsi\u00f3n de Smart desde 2005: \u00a1casi 20 a\u00f1os! Se enfrentaron a desaf\u00edos al pronosticar piezas con demanda intermitente vendidas para respaldar su negocio de posventa de autom\u00f3viles. Al reemplazar su enfoque basado en hojas de c\u00e1lculo y cargas manuales a SAP con pron\u00f3sticos estad\u00edsticos de demanda y stock de seguridad de SmartForecasts, pudieron reducir significativamente los pedidos pendientes y las ventas perdidas, con tasas de cumplimiento que mejoraron de 93% a 96% en solo tres meses. La clave de su \u00e9xito fue aprovechar el m\u00e9todo patentado de Smart para pronosticar la demanda intermitente: el m\u00e9todo de arranque "Smart-Willemain" gener\u00f3 estimaciones precisas de la demanda acumulada durante el tiempo de entrega que ayud\u00f3 a garantizar una mejor visibilidad de las posibles demandas.<\/p>\n

Conexi\u00f3n de pron\u00f3sticos al plan de inventario:<\/strong> Los sistemas de planificaci\u00f3n avanzados respaldan la gesti\u00f3n de inventario basada en pron\u00f3sticos, que es un enfoque proactivo que se basa en pron\u00f3sticos y simulaciones de demanda para predecir posibles resultados y sus probabilidades asociadas. Estos datos se utilizan para determinar los niveles \u00f3ptimos de inventario. La previsi\u00f3n basada en escenarios o probabil\u00edstica contrasta con la naturaleza m\u00e1s reactiva de los m\u00e9todos basados en hojas de c\u00e1lculo. Un cliente desde hace mucho tiempo en el negocio de las telas, anteriormente tuvo que lidiar con excesos y desabastecimientos debido a la demanda intermitente de miles de SKU. No ten\u00edan forma de saber cu\u00e1les eran sus riesgos de desabastecimiento y, por lo tanto, no pod\u00edan modificar proactivamente las pol\u00edticas para mitigar el riesgo m\u00e1s que hacer suposiciones muy generales que tend\u00edan a generar un exceso de existencias. Adoptaron el software de planificaci\u00f3n de inventario y demanda de Smart Software para generar simulaciones de demanda que identificaron valores m\u00ednimos disponibles y cantidades de pedido \u00f3ptimos, manteniendo la disponibilidad del producto para env\u00edo inmediato, destacando las ventajas de un enfoque de gesti\u00f3n de inventario basado en pron\u00f3sticos.<\/p>\n

Mejor colaboraci\u00f3n: <\/strong>\u00a0Compartir previsiones con proveedores clave ayuda a garantizar el suministro. Kratos Space, parte de Kratos Defense & Security Solutions, Inc., aprovech\u00f3 los pron\u00f3sticos inteligentes para brindar a sus fabricantes por contrato mejores conocimientos sobre la demanda futura. Utilizaron los pron\u00f3sticos para asumir compromisos sobre compras futuras que permitieron al CM reducir los costos de materiales y los plazos de entrega de los sistemas dise\u00f1ados bajo pedido. Esta colaboraci\u00f3n demuestra c\u00f3mo las t\u00e9cnicas avanzadas de pron\u00f3stico pueden conducir a una colaboraci\u00f3n significativa en la cadena de suministro que genera eficiencias y ahorros de costos para ambas partes.<\/p>\n

\u200b<\/p>\n

 <\/p>\n

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Las empresas que dependen de hojas de c\u00e1lculo para la planificaci\u00f3n de la demanda, la previsi\u00f3n y la gesti\u00f3n de inventario a menudo se ven limitadas por las limitaciones inherentes de las hojas de c\u00e1lculo. Esta publicaci\u00f3n examina los inconvenientes de los enfoques tradicionales de gesti\u00f3n de inventario causados por las hojas de c\u00e1lculo y sus costos asociados, compar\u00e1ndolos con los importantes beneficios que se obtienen al adoptar tecnolog\u00edas de planificaci\u00f3n de \u00faltima generaci\u00f3n. <\/p>","protected":false},"author":157,"featured_media":12524,"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>

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

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