Repair and Return Planning

Know whether to wait for repairable parts to be returned to service or if purchasing additional service spares yields better service levels.

Capital Project Planning

Know whether to wait for repairable parts to be returned to service or if purchasing additional service spares yields better service levels.

Probabilistic Forecasting

Generate thousands of possible lead time and demand scenarios to optimize stocking policies and deliver differentiated service levels without inventory bloat.

Smart’s Service Parts Planning offering combines the core inventory optimization, demand planning, and analytics modules from the Smart IP&O Platform including its patented forecasting engine for intermittent demand plus purpose-built accelerator add-ons. It delivers inventory policy decision support, analytics, and prescriptive recommendations that ensure you have the right part available at exactly the right time. You’ll minimize downtime, reduce expedites, ensure your SLAs are met, and deliver exceptional customer service.

Smart Service Parts Planning Overview and Features

Repair & Return Planning

By simulating the processes of part breakdown and repair, part planners will know whether service levels are best achieved by waiting for repairs to be returned to service or if additional spares should be purchased from suppliers.

Voorraadplanning

Smart embraces a fundamentally different approach to inventory planning than traditional forecasting, inventory planning and order management systems. Rather than simply suggesting what should be ordered and stocked to meet an arbitrary service level, Smart predicts service performance, costs, and other key performance predictions associated with the current and proposed policies.

Smart Optimization

When using the optimization feature, Smart projects holding cost, stock out cost and ordering cost for each item and prescribes the optimal planning parameters that achieve the least-cost service level for each item. The planning parameters being optimized are either reorder point/order quantity or Min/Max.

Optimal Policies

Smart will prescribe optimal service level targets that are projected to yield the lowest total cost, accounting for stock out costs, holding costs and ordering costs. The optimal policy is automatically compared to the current policy. Users can conduct what if analysis that modifies the policy according to business rules, such as service level targets. Below we’ve described the core functionality.

Predictive Exceptions

Smart’s Exception Management features identify which items are predicted to have significant changes in service level and/or inventory value. It also alerts to which items aren’t being ordered in the ERP or order management system according to the consensus plan. Exception lists are produced automatically, making it easy for you to review any problematic items and decide how to manage them moving forward.

 

Demand Groups

Smart classifies items into nine groups based on volume and frequency of usage/demand. Administrators can establish thresholds that define high, medium and low volume and frequency. The nine-cell Demand Groups table shows the counts of items, projected average service levels and projected average inventory values as well as the marginal totals. By selecting the symbol within each cell, you can jump to a display of the workbench for that subset.

 

Asset Tracking

By knowing the exact asset(s) each service part supports, planners can better estimate the consequence of stock out and make more informed decisions about risk adjusting stocking levels.

 

Probabilistic Forecasting

Smart’s patented probability forecasting engine automatically generates tens of thousands of demand simulations per item and compares these simulations to the inventory policy. This stress tests the policy over thousands of realistic demand scenarios. Calculations are performed automatically as part of the daily import process. Users aren’t required to learn functionality to run the simulations—it’s baked into the process. Each time new transactional data are provided, the metrics are recalculated based on up-to-date information on demand, lead times and costs. As these variables change, so will the metrics.  

 

 

Scenario analyse

In order to make the right inventory decisions, businesses need to simulate the impact of proposed policy changes. Smart’s planning workbench offers the ability to compare multiple inventory policy scenarios. Four different types of scenarios are utilized: Live, What If, Named and Goal.

 

Collaboration and Consensus

All Named, Live, and Goal policies can be shared with other users on the platform. Alerts within Smart indicate when a policy has been shared among users. Recipients can import a shared policy into their workbench and assess it for themselves. Collaborative functionality within Smart is important for organizations with multiple planners responsible for their subset of items, locations, suppliers, etc. It lets each planner generate and share policies that they judge will best balance service versus cost.

 

Multiple Replenishment Methods

Smart is designed to generate planning parameters that can be used in any ERP replenishment policy. Results that can be exported include Min/Max, Reorder Point/Order Quantity, Safety Stock and Lead Time Demand Forecast.

Mass Apply

The Mass Apply radial will auto-apply numerical values entered into headers to all What If entries for the group. Mass Apply can be used to specify identical driver values for all items in a filtered group.

Capital Project & Scheduled Maintenance Planning

Know exactly what parts and budget are needed to support planned maintenance and capital projects without extensive data gathering and manual reporting.

Gepatenteerde intermitterende vraagvoorspelling

Gives you the most accurate way to forecast usage when product demand is irregular and has a large proportion of zero values. This pattern is typical of spare parts and big-ticket items.

The Goal Scenario

The Goal scenario represents the consensus inventory plan and may only be produced by forecast lead users. It contains the item-specific inventory planning parameters that will be saved to the ERP system. To convert a Named scenario into the Goal scenario, follow these steps. First, copy that scenario to What If by selecting the encircled ↑ icon to the right of the scenario. Second, select Apply to All Items and Recalculate. Now, the What If scenario is equal to the Named Scenario intended for the goal. Finally, click Make Goal, which converts the What If scenario into the Goal scenario..

What If Analysis

What If scenarios can be run at the summary and item levels. Users can try out What If scenarios at the summary level by changing the service level average, ceiling or floors from the Drivers tab. Users can also prescribe the same target service level for all items by entering the desired value for the ceiling and floor. Users can conduct What If scenarios on individual items by doing so in the designated item section.

Optimization Function

The Optimization function provides an option to calculate planning parameters automatically for each item. Optimization computes the operating cost and service level associated with each choice of drivers (e.g., Min and Max). Then it searches through the possible choices of drivers to identify the least cost item-specific driver values subject to a limit on the Minimum acceptable service level.

Projected Metrics

Projected metrics forecast how a specified inventory policy will perform in the future. Smart reports on a variety of projected metrics, including service levels, fill rates, turns, stock-out costs, holding costs, ordering costs, and inventory value.

Ipad with business data of improved Demand & Inventory Planning 2

De impact van een verbeterde Demand & Inventory Planning

Het optimaliseren van stock levels betekent dat besparingen die op een subset van artikelen zijn gerealiseerd, opnieuw kunnen worden toegewezen om een bredere portefeuille van 'in stock'-artikelen te dragen, waardoor inkomsten kunnen worden vastgelegd die anders verloren verkopen zouden zijn. Een toonaangevende distributeur was in staat om een breder assortiment onderdelen op voorraad te houden met besparingen die werden gebruikt door voorraadverminderingen en een grotere beschikbaarheid van onderdelen door 18%

Minder kritieke artikelen waarvan wordt voorspeld dat ze 99%+-service levels zullen bereiken, bieden kansen om de voorraad te verminderen. Door te mikken op lagere servicelevels voor minder kritieke artikelen, zal de voorraad in de loop van de tijd de juiste maat hebben voor het nieuwe evenwicht, waardoor de bewaarkosten en de waarde van de aanwezige voorraad afnemen. Een groot openbaar vervoersysteem verminderde de voorraad met meer dan $4.000.000, terwijl de service levels werden verbeterd.

 Klanten die onze demand en inventory forecasting software gebruiken

MRO- en aftermarket-reserveonderdelen

Productie

Verdeling

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