From the severe flooding in Southeast Asia affecting raw material availability, the unexpected tech boom in South America redefining consumption patterns, to the colossal port congestion in Africa leading to shipping delays, 2023 has underscored one reality for businesses: uncertainty is the only certainty.
Layered on top of this is a rapidly changing consumer mindset, pivoting more towards sustainability and local sourcing. It’s an intricate web of challenges and opportunities.
In order to survive, planners have to evolve. From being laser-focused on forecasting, they need to expand their horizons and become adept data orchestrators, weaving together disparate data streams into a cohesive, actionable strategy.
Centralizing Data: The Heart of Modern Demand Planning
The bedrock of this transformation is data centralization. By centralizing data on a single, unified platform, organizations are better positioned to simultaneously analyze vast datasets, leading to more accurate and responsive short-term demand plans.
Take the case of a leading retailer spanning over 1000 stores. Previously, data was scattered across multiple systems, hindering their ability to forecast accurately. Once they centralized their data:
They integrated real-time sales data from every store, revealing that certain SKUs were consistently understocked during promotional periods.
By tapping into externaldatasets, they could correlate sales spikes to local events, weather changes, or even trending social media topics, refining their short-term forecasts.
The agility of centralized data allowed them to implement automatedreplenishment systems, reducing stock-outs by 30%.
Instead of operating in reactive mode, store managers received real-time dashboard updates, enabling swift inventory decisions that could be executed in a matter of hours.
Leveling Up with Planning in a Box: A Game-Changer for Demand Planners
At its core, Planning in a Box is an integrated Decision Intelligence platform designed to serve as the single source of truth for planners. Instead of juggling multiple tools or spreadsheets, demand planners now have a centralized hub where all relevant data streams merge.
But it’s not just about data centralization; Planning in a Box brings the power of Generative AIto your demand plans. Without replacing your current system, it seamlessly infuses Generative AI-powered insights into your strategies.
Real-time Data Integration: Combined with Demand ML, the platform offers real-time data feeds into the demand planning process. Whether it’s salesdata from an outlet in New York or inventorylevels from a warehouse in London, everydatapointis ingested in real-time, enabling immediate response to changing market conditions.
Gen AI Capabilities: Built with Generative AI capabilities, Planning in a Box delves deep into historicaldata, seasonaltrends, and marketindicators, providing forecasts with unparalleled accuracy.
Granular Forecasting: Beyond broad strokes, the platform can dissect data to the minutest level—be it SKU, channel, or day. This granularity ensures that demand planners have detailed insights, allowing them to make micro-adjustments that can have macro impacts.
Seamless Synchronization Across the Supply Chain: Empowering every stakeholder, from DCs, logistics, S&OP, to stores, Planning in a Box ensures that every part of the supply chain is in tune. With integrated insights, every decision is informed, and every action is coordinated.
Navigating the Shift to a Generative AI-Powered Ecosystem with Planning in a Box
As planners transition from traditional forecasting techniques to an AI and Generative AI-powered ecosystem, the tension is palpable. Questions like ‘Should I blindly trust this data?’ and ‘What if it’s wrong?’ frequently surface. Planning in a Box understands these concerns and addresses them in three pivotal ways:
Glass-box Methodology: Instead of hidden calculations, Planning in a Box employs a transparent approach. Every forecast comes with a clear trail, showing planners the factors influencing the predictions. For instance, while forecasting demand for winter jackets, the system might highlight the role of an imminent cold wave or the impact of recent marketing trends, allowing planners to understand and trust the AI’s reasoning.
Collaborative Features with Spreadsheet Familiarity: The platform integrates features that teams are already familiar with, like spreadsheets, enabling easy adaptation. Moreover, it promotes collaborative decision-making, allowing teams to discuss, annotate, and adjust forecasts within a shared, intuitive space.
Scalable Adaptability: As demand planners refine their skillset and grow comfortable with AI-driven insights, Planning in a Box evolves alongside them. Advanced features become accessible, providing them with deeper insights and more nuanced control over their forecasting endeavors.
Your Next Evolution in Demand Planning
It’s not just about more numbers; it’s about smarter, Generative AI-powered insights. Demand planners at Tacori, AB InBev, CISCO, and Levi’s have already tapped into this transformative shift. Be the next to harness the power of Planning in a Box. Request a demo now
ABOUT THE AUTHOR
Aparna P is a results-driven Digital Transformation leader and Principal Solutions Architect with a combination of business acumen and technical expertise. A Google Certified Cloud Digital Leader and a Google Cloud Certified Professional Data Engineer, she is passionate about using technology to solve business problems.