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OMP offers advanced capabilities for the integrated management of product changeovers in demand and supply. The modification of finished goods codes and raw material codes in response to promotions or other events is optimized in an end-to-end way for the complete value stream, taking into account network demands and their requested transition days while minimizing the value of raw and pack material remnants. The result will be better service levels and less scrap.

OMP offers dedicated functionalities to manage events in a collaborative way and using data from past promotions or other predictors. Furthermore, it is possible to run scenarios and assess promotion profitability by considering the effect on the end-to-end supply chain. This results in promotion service levels being improved.

OMP helps in designing and planning varying supply chains. It allows the appropriate inventory targets to be set at all levels, taking into account demand and supply lead time variability, service levels and many more parameters. You can achieve the desired service level while minimizing the working capital invested in inventories.

Scenarios in OMP allow you to simulate the impact of changes to any data element. You can compare multiple scenarios in detail, or via KPIs such as projected inventory values or machine loads. Simulations show the true impact of planning decisions, supporting collaborative decision-making within the company.

OMP offers bulk batch split and batch balancing functionality as part of its optimization feature-set to ensure bulk manufacturing and finished goods production are aligned. The solver will select specific finished goods to temporarily deviate from the desired safety stocks. In this way, bulk leftovers are used to produce these finished products, reducing the risk of obsoletes.

OMP has advanced features in supply planning and detailed scheduling, allowing these operational constraints to be taken into account realistically. As a result, machine utilization will improve, and the mix of output products will be better aligned with market demand.

OMP will source products from the most appropriate plant dynamically, considering constraints such as different plant capacities, line speeds, raw/pack material availability in the short term, and financial impacts. Planners can thus mobilize the production network flexibly, boosting machine utilization and supply chain agility.

Demand fluctuations can always hit, resulting in sales misses in the short term. OMP allows exceptional emergency transports between distribution centers to be planned for in the event that SKU market representation allows rebalancing between distribution centers. Planners will get full visibility of the cost and service impacts of the various alternatives and can select the most appropriate, in line with company and supply chain strategies.

Shelf-life constraints for products such as fresh food can be considered at multiple levels in the supply chain. On the demand side, the requested minimum remaining shelf life will be considered at the level of material, DC, or customer. On the supply side, it will be matched to total shelf life. Systematic planning for the expected shelf life will minimize scrap due to expiries while ensuring service levels.

You can define bulk or finished goods campaign rules to group production runs with similar characteristics, reducing change-over times and allowing lean manufacturing. Smart solvers are available to automatically determine the optimal campaign length and sequence, applying fixed or dynamic rhythm wheels as you prefer.

Bottleneck tanks and other storage equipment can be modeled. Their degree of occupation is linked to filling and emptying production steps within or across multiple orders. Availability can be used as either a soft or a hard constraint, with smart solvers available to optimize the tank flow schedule.

In OMP, point-of-sales data and other external time series, such as Google Analytics, are integrated into the short-term forecasting model to more accurately detect trends. In combination with the accelerated planning cycle, this will avoid stockouts and logistics costs resulting from expedited shipments.

OMP covers a wide variety of sales channels for both demand and supply planning. It will allow visibility of all sales channels, including e-commerce channels, and allow you to track specific sales orders throughout the downstream supply chain.

OMP offers various optimization techniques, allowing you to easily develop a distribution and inventory deployment plan in line with your company and supply chain strategies. Supported strategies include different types of fair share deployments, margin-based optimization techniques, and Demand-Driven Material Requirements Planning (DDMRP). Full carrier constraints can be considered too. Your inventory is available where you want it, allowing you to improve delivery to your customers.

Modeling in OMP can be done at different levels, with the capacity to roll up and drill down to the desired level of detail. Planning information can be summarized and visualized at different levels, for example by country, packaging size, brand, sales channel, and group of packaging lines. In addition, time horizons can be set up in days, weeks, months and quarters with flexible aggregation options. OMP provides visibility at the level of detail to fit your purpose.

Customers and raw/pack material suppliers are modeled as an integrated supply chain node in OMP and as such give full inventory visibility. Through the OMP cloud portal, customers and suppliers can collaborate on the plan (forecasts, committed supplies, planned capacity, etc.) in an integrated way. In addition, contractual agreements with minimum/maximum volumes or values over various time-periods and product groups can be modeled.

Any demand and supply element can be pegged according to first-in-first-out, first-expiry-first-out or many more advanced allocation rules. This gives the planner true end-to-end visibility over the internal and external network, from raw/pack materials, bulks and finished goods to final network demand.

We believe there is great value in integrating different planning functions into one end-to-end supply chain model. OMP allows you to combine the different activities for a specific value stream into one planning process supported by one application. This makes the planning process more efficient and significantly improves response lead times in the event of demand or supply events.

Solvers in OMP allow you to optimize for multiple KPIs such as margin optimization or packaging material waste reduction. For example, planners can compare the financial impact of a rush order with expedited shipment versus rebalancing goods with another DC. Through developing experience with this, you can further automate option selection.