The digital transformation of demand planning is moving beyond simply obtaining more accurate forecasts. For companies, the challenge lies in converting available information into decisions that allow them to adjust inventory, purchasing, production, transportation, and operational capacity in response to increasingly rapid market changes.
This was one of the main conclusions of the panel “Digital transformation in demand planning: From intuition to prescriptive logistics in manufacturing and retail”, organized by the National Council of Executives in Logistics and Supply Chain (ConaLog) , where specialists agreed that technology must be accompanied by integrated processes, reliable data and execution capacity .
The meeting brought together María Devesa, Commercial Planning and Distribution Director of El Palacio de Hierro ; Jorge Pinzón, Logistics Director of Price Shoes ; Felipe Ordóñez, CEO of Promologistics ; and Hugo Ruiz, President of ConaLog, under the moderation of Javier Serrano, Managing Partner of Operations at International Business Solutions (IBS) .
The discussion highlighted that having more information doesn’t necessarily make decisions easier. Supply chains currently face variables related to trade volatility, infrastructure, customs processes, logistics security, water and energy availability, and operational talent—factors that ultimately impact service levels, costs, working capital, and inventory.
In this scenario, improving the forecast loses its value if that information doesn’t change operations . Ruiz explained that, in his experience with predictive models, increasing indicators like forecast accuracy didn’t necessarily translate into better results for the supply chain.
“If we don’t manage to turn that number into a specific action in terms of changing production plans, purchasing and supply plans, it’s useless to us,” Ruiz said.
The specialist highlighted that tools such as artificial intelligence (AI) can help analyze large amounts of information and support conversations between the commercial, financial, logistics and operations areas, but the decision on what to modify and what result to seek remains in the hands of the organizations.
Hence, the goal is not to accumulate inventory as an automatic response to uncertainty, but to determine how much product is needed, where it should be located, and what capacity will be necessary to meet demand , including transportation and distribution centers.
From data to a connected operation
At El Palacio de Hierro, the transformation of inventory management required first organizing the information. Devesa explained that the company carried out a data project starting in 2022, which included cleaning up the catalog and creating a new architecture to subsequently support the planning tools.
Currently, inventory management, distribution, and store replenishment rely on a platform for daily decision-making. The company also aims to implement a new business planning process by 2027 that will integrate inventory management, pricing, and supplier relationships.
The need to strengthen these capabilities also stems from the growth of e-commerce. Devesa indicated that the digital channel represents approximately 15% of El Palacio de Hierro’s total sales, while the expectation is that it will reach 30% in the next five years, which adds pressure to guarantee product availability across different points of contact.
For Felipe Ordóñez, the speed of the market forces us to abandon rigid prediction models and recognize that each business faces different demand behaviors.
“The deviations we have in our prediction models don’t stay in Excel or in the tool; they are seen in the income statement,” he stated.
Planning must also extend to transportation providers. Jorge Pinzón pointed out that one strategy for managing peak demand is to share scenarios in advance with logistics partners , rather than passing the problem on to them once the capacity need has already materialized. He emphasized the importance of building trust and sharing information about potential variations.
The human factor , however, remains another key element of the transformation. During the panel, it was noted that the speed at which artificial intelligence and supply chains are evolving outpaces even the rate of talent development, meaning companies will also need to cultivate profiles with greater analytical, learning, and leadership capabilities.
Thus, the move towards more prescriptive logistics does not depend solely on incorporating new platforms. Technology can anticipate scenarios and process information faster, but its impact emerges when data, people, business areas, and operations work on the same process and the signals obtained are ultimately transformed into concrete actions within the supply chain.
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