Data is the backbone of decision-making in the Food Away From Home industry. But if that data arrives too late, it becomes less actionable, less valuable—decisions are delayed, opportunities are missed, and inefficiencies pile up. This delay, known as data latency is a hidden revenue killer. If your team is making decisions based on outdated numbers, you’re not just behind—you’re losing money.
The industry has accepted this lag for too long, but we don’t have to. Let’s break down the problem—and how we fix it.
What Is Data Latency? The Slow Leak in Your Business Pipeline
Data latency is the time it takes for information to travel from an operator’s purchase to a manufacturer’s usable insight. In foodservice, this process can take weeks—or even months—due to delays at multiple points in the supply chain.
There are three main types of latency:
- Purchase visibility latency — The time between when an operator buys a product and when the manufacturer sees the data.
- Data processing latency — The time required to cleanse and prepare raw data for use.
- Insight latency — The time it takes to turn data into actionable insights.
Each of these delays contributes to slower decision-making and missed opportunities.
Who Feels the Pain? (Hint: It’s Everyone in the Supply Chain)
No one escapes the consequences of data latency. Data delays impact everyone in the supply chain.
Manufacturers struggle to track performance, manage trade spend, and optimize promotions.
Distributors face challenges in aligning with partners due to outdated or incomplete data.
Operators lack timely insights to make purchasing decisions that maximize profitability.
Each stakeholder has different priorities and systems, making it difficult to align on a faster data-sharing approach.
Some of the biggest challenges caused by data latency include:
- Slow response times – Sales teams operate on instinct rather than real-time insights.
- Missed revenue opportunities — Promotions and product launches lose momentum before results are clear.
- Operational inefficiencies — Finance teams spend too much time chasing down numbers instead of focusing on strategy.
- Disconnected decision-making — Without a single source of truth, each team relies on fragmented and outdated reports.
Where Are the Biggest Bottlenecks? Data Stuck in the Pipeline
Data latency creates bottlenecks at every level of the supply chain. Missed revenue opportunities occur when sales teams can’t act on insights that arrive too late. Operational inefficiencies emerge as slow reporting and manual data processing waste valuable time. Financial risks increase when manufacturers need to set aside larger trade accruals to account for uncertain claims. Collaboration becomes more difficult when outdated data prevents partners from aligning on pricing, promotions, and category management.
In some cases, data isn’t just late—it’s incomplete. Different sources may use inconsistent formats, making it difficult to piece together an accurate view of performance. Even when data does arrive, it often requires significant cleanup before it can be used effectively.
When Does Data Latency Hurt the Most? Timing Is Everything
The impact of data delays is most severe when businesses need to act fast but can’t. A promotion might end, but no one knows if it was successful until months later. A new product launch could be underway, yet early demand signals remain unclear. Trade claims may pile up, leaving manufacturers scrambling to reconcile the numbers. In each of these scenarios, waiting for data means missing critical moments to optimize performance.
By the time decisions are made, the opportunity has often disappeared.
Imagine being able to pivot marketing efforts mid-campaign based on live performance data instead of waiting months to analyze results. What if you could identify and address a pricing issue before it erodes profitability? These opportunities exist and we believe this is possible.
How Do We Fix It? The Power of Data Collaboration
Industry-wide collaboration is the solution to solving the data latency issue.
To reduce data latency, the industry needs to align stakeholders so that everyone in the supply chain has an incentive to ensure data moves faster. Improving technology—through automation, AI-powered forecasting, and better integrations—can streamline processes. Standardizing data formats and sharing methods would also eliminate inefficiencies and prevent delays.
As a first step, we’re bringing key players in the FAFH industry together for a collaborative circle on solving the data latency challenge. Stay tuned for updates!
