Accurate and timely data is essential for smart business decisions, but many organizations struggle to get the information they need for effective planning. This challenge can seriously hinder a company’s ability to make informed choices and forecast future trends. At o9 Solutions, we understand this problem and offer a strategic approach to help you overcome these hurdles.
Our recent webinar, “Data Readiness: How to Build a Foundation for AI-Driven Demand Planning,” addressed a common issue for many businesses: being stuck with outdated systems and manual processes. We highlighted how a strategic approach to data readiness can unlock significant improvements, especially for mid-market companies aiming to boost their forecasting accuracy and operational efficiency.
As explored in a recent webinar “Data Readiness: How to Build a Foundation for AI-Driven Demand Planning,” featuring Algo experts Samuel Parker and Tom Bond, building a strong data foundation is not just important, it’s non-negotiable for successful AI implementation.
The Root of the Problem: Why Demand Planning Fails
According to Algo’s Samuel Parker and Tom Bond, the foundation of effective demand planning crumbles when faced with a few key data challenges. Many companies are trapped in a web of disparate systems, with data scattered across ERPs like NetSuite and SAP, POS systems, and other tools. The time and effort spent manually stitching this information together is a major drain on resources and a constant source of errors.
Without real-time visibility, decisions are based on stale data, forcing teams into a reactive cycle that increases forecast inaccuracy.
Moreover, a poor data structure and hierarchy make it impossible to get high-level insights. Instead of strategic analysis, teams are forced into granular, time-consuming planning. The biggest issue, however, is a lack of trust. When teams don’t have confidence in the accuracy of the data, they will inevitably rely on manual overrides and gut feelings, completely undermining the value of any advanced forecasting model. This “garbage in, garbage out” principle is a harsh reality for many businesses.
The Hidden Costs of Unready Data
These data challenges translate directly into significant operational inefficiencies and missed opportunities:
- Excessive Manual Effort: Teams spend countless hours on data reconciliation, cleaning, and preparation, diverting valuable resources from strategic planning. One client even rebuilt their forecast weekly from scratch due to data sync issues.
- Inaccurate Forecasts: Without a reliable and complete data foundation, AI engines (or even traditional forecasting methods) produce flawed results, leading to overstocking, stockouts, and reduced profitability.
- Limited Strategic Insight: When planners are bogged down in data mechanics, they have little time to analyze market trends, understand consumer behavior, or identify root causes of forecast deviations.
- Slow Time-to-Value for New Tech: Investing in advanced AI or planning tools without addressing underlying data issues is akin to building a skyscraper on sand – it’s destined for instability and failure.
Algo’s Solution: Practical Steps to Data Excellence
At Algo, we understand that “perfect data” is an elusive goal. Our focus is on practical, impactful steps that deliver tangible value quickly. We guide clients through a three-phase journey:
- Discover & Prioritize: We begin by deeply understanding your current state. What data do you have? Where are its strengths and weaknesses? What are the biggest “pain points” for your planning team? We then prioritize the essential data elements that, when addressed, will yield the most immediate improvements in forecast accuracy and process efficiency. Our initial sessions often involve working with existing data mapping templates to jumpstart this process.
- Normalize the Data: This is where we roll up our sleeves. We actively work with your team, often through dedicated workshops and collaborative sessions, to clean, transform, and structure your data. This includes:
- De-duplication: Eliminating redundant or conflicting entries.
- Standardization: Ensuring consistent formats and definitions across all sources.
- Hierarchy Building: Structuring master data (like product and location hierarchies) to enable aggregated planning and detailed analysis.
- Data Validation: Implementing rules to ensure ongoing data quality.
- Operationalize & Automate: The final step is to integrate your cleaned and normalized data into your forecasting and planning systems. We help establish robust data pipelines, often leveraging APIs for real-time data exchange, to ensure a continuous flow of high-quality data. This automation not only reduces manual effort but also fuels your AI engine with the reliable inputs it needs to thrive.
The Transformative Impact
The results of this focused data readiness journey are significant:
- Improved Forecast Accuracy: With trusted, complete, and timely data, your AI models can deliver far more precise forecasts, often seeing 10-20% improvements in accuracy from data alignment alone.
- Reduced Manual Effort: Automating data processes frees up your planning team’s time, allowing them to shift from data wrangling to strategic analysis and anomaly management.
- Enhanced Business Trust: When your team sees tangible improvements in data quality and forecast reliability, their confidence in the planning process soars, fostering a culture of data-driven decision-making.
- Accelerated ROI from AI: A strong data foundation ensures that your investment in AI-driven demand planning truly pays off, delivering consistent value and competitive advantage.
Don’t let daunting data challenges hold your demand planning back. By starting small, focusing on key wins, and partnering with experts who understand the nuances of data readiness, you can build the foundation for a more accurate, efficient, and AI-powered future.
Ready to build your foundation for AI-driven demand planning? Let’s talk about your data.
About the author
Algo
Combining human centered AI with deep domain expertise, Algo’s analytics enriched supply chain intelligence platform helps suppliers and retailers plan, collaborate, simulate and execute a more efficient supply chain.
