Lorem ipsum color sit amet, consectetur adipiscing elite. Suspended Varius Enim in Eros Elementum Tristique. Duis cursus, mi quis viverra ornare, Eros Dolor Interdum Nulla, ut commodo diam libre vitae erat. Aenean faucibus nibh et usto cursus di rutrum lorem imperdit. Never ut without vitae risus tristique possesses.
Lorem ipsum color sit amet, consectetur adipiscing elite. Suspended Varius Enim in Eros Elementum Tristique. Duis cursus, mi quis viverra ornare, Eros Dolor Interdum Nulla, ut commodo diam libre vitae erat. Aenean faucibus nibh et usto cursus di rutrum lorem imperdit. Never ut without vitae risus tristique possesses.
Lorem ipsum color sit amet, consectetur adipiscing elite. Suspended Varius Enim in Eros Elementum Tristique. Duis cursus, mi quis viverra ornare, Eros Dolor Interdum Nulla, ut commodo diam libre vitae erat. Aenean faucibus nibh et usto cursus di rutrum lorem imperdit. Never ut without vitae risus tristique possesses.

With Pyplan, Alpura transformed its operational execution, increased demand accuracy and accelerated critical decisions throughout its national network.

In the dairy industry, where products have a turnover of less than 12 days and bankruptcies can compromise revenues and quality, speed and precision in execution are decisive for competitiveness. Alpura faced this challenge in an even more complex environment: multiple commercial channels, a distributed network throughout Mexico and more than 15,000 possible combinations between SKUs, customers and distribution centers. The lack of synchronization between data sources, manual processes and daily reports that consumed more than three hours per day made it especially difficult to identify critical deviations before they impacted the operation.
In addition, the absence of an integrated MRP system limited the ability to connect demand, inventory and supply, generating late reactions and improvised adjustments. Although Alpura had already advanced with modules of Demand Planning and Business Profitability, daily execution continued to depend on disconnected Excel sheets, different versions of information and processes that prevented us from having a single and reliable view of the business. In short: the team needed a more agile, automated and predictive way to manage real demand to make decisions with immediate impact.
In this context, Alpura sought to integrate tactical planning with operational execution under a digital model that would: detect deviations in real time, prioritize risks and opportunities, reduce the time spent on data consolidation and align all areas around the same information. The company needed a solution capable of absorbing multiple sources, automating their processing and offering control panels where Demand Planning, S&OP and S&OE could operate in a coordinated manner.
The objective went beyond having a more accurate forecast: it was about building an intelligent process that would connect real demand, inventories, supply and distribution under a continuous flow. This required specific modules such as Demand Control, Demand Sensing, Inventories, DRP, and prioritization mechanisms to manage extraordinary orders, potential bankruptcies or abrupt market changes. The strategic ambition was clear: to move from a reactive model to a predictive and prescriptive one, where the operation could anticipate events and not simply respond when it's too late.
The solution implemented with Pyplan focused on an integral module of Demand Control, directly connected to operational databases and aligned with existing Demand Planning and Business Profitability applications. This integration made it possible to consolidate multiple sources, define control tolerances and activate automatic alerts for any relevant deviations. With a unified, flexible and fully scalable model, Alpura managed to have a single version of the truth for the entire operation.
The platform enabled advanced analysis, automation of daily monitoring and immediate visibility of demand behavior, allowing the team to react with unprecedented speed. Pyplan's generative AI and intelligent agents made it easier to detect anomalies early, simulate alternative scenarios, and recommend more effective responses. This approach integrated the tactical planning of the S&OP with the execution of the S&OE, achieving a more stable, accurate operation oriented to decisions based on data.
The benefits were overwhelming: greater precision in demand control, drastic reduction of operating times, full integration of dispersed sources, and a more robust prioritization process that allowed us to focus efforts where there really was an impact. In addition, the rapid identification of gaps and collaboration between areas transformed the way in which Alpura interprets and executes its daily operation. The end result is a more synchronized, agile chain ready to sustain business growth with discipline and advanced technology.
Take your planning to the next level with Pyplan.
Talk to our specialists and find out what's possible:https://pyplan.com/es/entre-en-contacto/

Control, traceability and consistency in each Bajada number

How Pyplan's influence diagrams transform complex rules into clear decisions

Quality, structure and scalability from the first model