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Home » How to break down silos to fill the gap between transportation planning and execution
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How to break down silos to fill the gap between transportation planning and execution

Bridging the gap saves businesses millions on transportation spend.

ProvisionAI: How to Break Down Silos to Fill the Gap Between Transportation Planning & Execution
June 6, 2023
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Franklin, TN – June 6, 2023 – ProvisionAI, the only provider of a patented optimized replenishment transportation scheduling solution, discusses breaking down operational silos to fill the gap between transportation planning and execution. ProvisionAI’s LevelLoad solution combines holistic network optimization, smart early tendering, and load-size maximization to create optimal schedules and loads that result in lower costs and better fulfillment rates.

“Often supply planners schedule replenishment, but don’t consider the impact on transportation, the ship site, or the receiving location. They leave operations scrambling to meet what they are told is “must go” shipments—if they don’t go customers won’t get what they ordered,” says Thomas A. Moore, Founder and CEO of ProvisionAI. “The reality is that not everything is needed immediately, or, with some look-ahead planning, product could have been pre-positioned.”

Transportation planners receive stock-transfer order data from ERP systems and then schedule shipments based on required delivery dates. But planners fail to look at any constraints in the network, such as space availability or crew availability to load. Not taking these variables into account when unpredictable spikes in consumer demand can trigger spikes in replenishment -- an increase in shipments from plants to distribution centers (DCs), resulting in trailers waiting days to unload. Unfortunately, these waiting trailers may incur detention costs and may even contain product needed to complete customer shipments.

At the same time the number of available trucks has been considered unlimited—but at what price in cost and service? So, by acting independently in its own silo, planning creates all the conditions for incremental cost and service failures.

ProvisionAI closes the gap between planning and execution by evening out shipment schedules and considering network constraints. ProvisionAI’s LevelLoad analyzes supply patterns to identify spikes in demand, then adjusts the need date for product that is likely to be in short supply by bringing the demand forward while pushing less-needed requirements back. LevelLoad can also submit a “placeholder” stock transfer order to secure early tendering to reserve needed carrier capacity. This smoother transportation plan which meets the constraints of labor, storage space, truck availability combined with being able to reserve trucks further in advance enables a higher adoption of loads by preferred carriers. Incrementally, because the actual contents of the “placeholder” stock transfer are not defined until just before shipping, the most needed product-as determined by the most recent supply planning solve, is sent.

“Just moving shipments around is not an option for companies with many lanes and hundreds of shipments daily," says Moore. “LevelLoad can analyze the needed shipments and make recommendations across hundreds of lanes so that shipments run smoothly and on time for a lower cost.

ProvisionAI's innovative solution harnesses the power of demand and supply-planning systems and combines transportation data with the overall network's constraints. It performs daily optimization and generates a globally optimized replenishment transportation schedule, recommending early trucking capacity reservations across the entire network. This approach creates a smooth, optimized flow of products throughout the supply chain. And it saves money while increasing customer-order fill rates.

About ProvisionAI

ProvisionAI provides global manufacturers with a transportation scheduling solution featuring optimized, capacity-constrained replenishment. LevelLoad, the flagship offering, attains long-term transportation planning objectives despite the realities of supply chain network constraints. The results include fuller loads, higher use of preferred freight carriers, and overall lower costs. Clients save millions by tendering loads early to reserve preferred carriers, filling truckloads optimally to minimize wasted capacity, improving customer order fulfillment, and ratcheting down costs. The patented technology was developed over five years by a team of logistics optimization experts that studied shippers like Unilever, Baxter, P&G, and Kimberly-Clark. For more information, visit www.provisionai.com.

http://www.provisionai.com
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KEYWORDS ProvisionAI
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