{"id":11825,"date":"2023-11-27T11:03:57","date_gmt":"2023-11-27T15:03:57","guid":{"rendered":"https:\/\/smartcorp.com\/forecasting\/how-are-we-doing-kpis-and-kpps-key-performance-indicators-parameters-copy\/"},"modified":"2023-11-27T11:30:09","modified_gmt":"2023-11-27T15:30:09","slug":"direct-naar-het-brein-van-de-baas-inventarisanalyse-en-prestaties","status":"publish","type":"post","link":"https:\/\/smartcorp.com\/nl\/blog\/direct-naar-het-brein-van-de-baas-inventarisanalyse-en-prestaties\/","title":{"rendered":"Rechtstreeks naar het brein van de baas \u2013 voorraadanalyse en rapportage"},"content":{"rendered":"

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Ik begin met een bekentenis: ik ben een algoritme-man. Mijn hart leeft in de \u2018machinekamer\u2019 van onze software, waar razendsnelle berekeningen heen en weer gaan door de AWS-cloud, waardoor vraag- en aanbodscenario\u2019s worden gegenereerd die worden gebruikt als leidraad voor belangrijke beslissingen over vraagvoorspelling en voorraadbeheer.<\/p>\n

Maar ik erken dat het doelwit van al die mooie, woedende berekeningen het brein van de baas is, de persoon die verantwoordelijk is om ervoor te zorgen dat op de meest effici\u00ebnte en winstgevende manier aan de vraag van de klant wordt voldaan. Deze blog gaat dus over Smart Operational Analytics<\/strong> (SOA), waarmee rapportages voor het management worden gemaakt. Of, zoals ze in het leger worden genoemd, sit-reps.<\/p>\n

Alle berekeningen die door de planners met behulp van onze software worden begeleid, worden uiteindelijk gedestilleerd in de SOA-rapporten voor het management. De rapporten richten zich op vijf gebieden: voorraadanalyse, voorraadprestaties, voorraadtrends, leveranciersprestaties en vraagafwijkingen.<\/p>\n

Voorraadanalyse<\/strong><\/p>\n

Deze rapporten houden de huidige voorraadniveaus in de gaten en identificeren gebieden die verbetering behoeven. De nadruk ligt op de huidige voorraadaantallen en hun status (voorhanden, onderweg, in quarantaine), voorraadwisselingen en excessen versus tekorten.<\/p>\n

Voorraadprestaties<\/strong><\/p>\n

Deze rapporten houden Key Performance Indicators (KPI's) bij, zoals opvullingspercentages, serviceniveaus en voorraadkosten. De analytische berekeningen elders in de software begeleiden u bij het behalen van uw KPI-doelen door Key Performance Predictions (KPP's) te berekenen op basis van aanbevolen instellingen voor bijvoorbeeld bestelpunten en bestelhoeveelheden. Maar soms komen er verrassingen voor, of wordt het operationele beleid niet uitgevoerd zoals aanbevolen, waardoor er altijd enige discrepantie zal zijn tussen KPP's en KPI's.<\/p>\n

Voorraadtrends<\/strong><\/p>\n

Weten waar de zaken er vandaag voor staan is belangrijk, maar zien waar de zaken zich ontwikkelen is ook waardevol. Deze rapporten onthullen trends in de vraag naar artikelen, voorraadgebeurtenissen, het gemiddelde aantal beschikbare dagen, de gemiddelde verzendtijd en meer.<\/p>\n

Prestaties van leveranciers<\/strong><\/p>\n

Uw bedrijf kan niet optimaal presteren als uw leveranciers u naar beneden halen. Deze rapporten monitoren de prestaties van leveranciers op het gebied van de nauwkeurigheid en snelheid van het invullen van aanvullingsorders. Als u meerdere leveranciers voor hetzelfde artikel heeft, kunt u deze met elkaar vergelijken.<\/p>\n

Vraagafwijkingen<\/strong><\/p>\n

Uw gehele voorraadsysteem is vraaggestuurd en alle voorraadbeheerparameters worden berekend na het modelleren van de artikelvraag. Dus als er iets vreemds gebeurt aan de vraagzijde, moet u waakzaam zijn en u voorbereiden op het herberekenen van zaken als min- en max-waarden voor artikelen die zich vreemd beginnen te gedragen.<\/p>\n

Overzicht<\/strong><\/p>\n

Het eindpunt van alle enorme berekeningen in onze software is het dashboard dat het management laat zien wat er aan de hand is, wat de toekomst biedt en waar de aandacht op moet worden gevestigd. Smart Inventory Analytics is het onderdeel van ons software-ecosysteem gericht op de C-Suite van uw bedrijf.<\/p>\n

\u00a0<\/strong>\"Smart<\/a><\/p>\n

Figuur 1: Enkele voorbeeldrapportages in grafische vorm<\/p>\n

 <\/p>\n

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

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In deze blog wordt de software in de schijnwerpers gezet die rapporten voor het management maakt, de stille held die de schoonheid van furieuze berekeningen vertaalt naar bruikbare rapporten. Kijk hoe de berekeningen, op ingewikkelde wijze begeleid door planners die onze software gebruiken, naadloos samenkomen in Smart Operational Analytics (SOA)-rapporten, waarbij vijf belangrijke gebieden worden verdeeld: voorraadanalyse, voorraadprestaties, voorraadtrends, leveranciersprestaties en vraagafwijkingen. <\/p>","protected":false},"author":122,"featured_media":11828,"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>

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