From data soup to star recipe: Why smart F&B companies are now choosing a modern data platform

The new reality of the Food & Beverage industry

The Food & Beverage industry is at a critical tipping point. While consumers are increasingly demanding quality, transparency and availability, margins are being squeezed by rising commodity prices, complex supply chains and increasing regulations. Retailers expect just-in-time deliveries with perfect traceability. Hospitality customers demand flexibility and customization. And consumers? They want to know where their product comes from, how fresh it is, and whether it fits their diet – all at a competitive price.

In this complex reality, data is no longer a nice-to-have, but a strategic necessity. Companies that can effectively leverage their data create a sustainable competitive advantage. In this regard, a modern data platform is not a luxury but the backbone of future-proof business operations. It connects fragmented systems, transforms raw data into actionable insights, and enables you to make decisions faster and smarter than ever before.

The pain points impeding growth

Before discussing the solution, it is essential to recognize the challenges that virtually every F&B company struggles with:

• Fragmented data sources without central direction – ERP, MES, WMS, LIMS, EDI and CRM systems each speak their own language, without standardized keys or connections
• Blind spots in sell-out and customer behavior – Retail data lingers with distributors, hospitality insights disappear into the fog, and the complete customer profile remains a puzzle with missing pieces
• Chaos in master data – The same SKU has three different codes, EANs are scattered across systems, and no one knows which packaging unit is really the right one
• Opaque actual margins – Between gross and net is a black box of promotions, incoterms, logistics costs and excise taxes that no one can fathom in real time
• Poor incident traceability – If a recall occurs, it takes hours to trace from batch to end customer, with all the reputational damage that entails
• Demand forecasting based on gut feeling – Seasonal patterns, weather and local events are ignored, resulting in out-of-stocks and waste

The solution: An intelligent data platform as a growth accelerator

A modern data platform not only solves these challenges, it transforms them into competitive advantages. Here’s how:

Central data hub with standardized integration

It starts simple: all your systems finally talk to each other. The ERP system knows what’s in the warehouse. Production can see what sales has sold. Quality control can track which raw materials are in which batches. No revolutionary AI, just your data finally coming together.

The platform uses linking and standardization to turn those different “dialects” into one language. EAN codes, lot numbers and SKUs are matched. And yes, as you grow, intelligent features can be added to this – automatic anomaly detection, predictive analytics, whatever you want. But just start connecting what you already have.

Real-time dashboards that really make a difference

Start simple: a clear dashboard that finally shows your inventory, production and orders in one place. No more opening five Excel files to know what needs to be produced this week. Supply chain managers instantly see their current stock by location. Sales teams can finally check real-time availability before making promises to customers.

As your data maturity grows, the possibilities become more exciting. Sell-out heatmaps by region show where your products are really selling. OEE monitoring on production lines identifies bottlenecks before they become problems. And batch-by-batch yield analyses help you extract those last percent of efficiency from your production.

Master data governance that works

Start with the pain points that everyone recognizes. That new flavor variant that is called “Mayo Lemon 500ml” in the ERP system, but is registered as “MAY-CIT-05” in production? A data platform captures these connections, once, centrally. New products are now created according to a fixed pattern with automatic synchronization to all systems.

It doesn’t have to be perfect from day one. Start with your top 100 SKUs, expand to the entire catalog, and gradually implement more stringent validation rules. The platform grows with your data maturity. And those duplicate customer records that have been causing confusion for years? We’ll tackle those too, step by step.

Advanced analytics & AI for proactive steering

Start with the basics that deliver immediate value. Historical sales figures coupled with production data provide insight into your actual lead times. Simple trend analysis helps identify seasonal patterns – yes, BBQ meat sells better in August than in December, but exactly how much? An automatic alert when inventory falls below critical levels prevents out-of-stocks.

When these foundations are in place, new doors open. Machine learning models can predict demand patterns based on weather, events and historical data. Promo effectiveness is no longer evaluated after the fact, but optimized in advance. And for the real frontrunners? Weather-sensing algorithms that automatically adjust production runs when a heat wave is predicted. But just start with insight – the rest will follow naturally.

From quick wins to transformation

The strength of a modern data platform lies in the combination of rapid, visible improvements and long-term potential, some examples:

First quick wins

• Overview at last: all data in one place instead of scattered across systems
• Time savings: hours of searching or data retyping reduced to a few mouse clicks
• Fewer errors: automatic checks prevent manual input errors

Operational improvements

• Better decisions through real-time visibility into inventory and production
• Faster response to market demand through up-to-date sales data
• More effective quality control through complete traceability

Strategic advantages

• Data-driven pricing and assortment decisions
• Predictive capabilities for demand forecasting and maintenance
• Continuous optimization of the entire value-chain

Case study: From Excel chaos to initial insights

A typical Wednesday at a Belgian cookie manufacturer. The production manager calls the warehouse: “How many butter wafers do we have left?” Excel is opened, numbers are called out. Meanwhile, sales asks if that big order for Delhaize can be delivered. “I’ll have to check with planning.” Quality control emails that batch #2451 has been rejected. But where did that batch go? Three hours and ten phone calls later, there is finally clarity.

After implementation of a basic data platform and some initial BI reports: One screen shows the current stock of butter wafers per location. The Delhaize order is automatically checked against available stock as well as planned production. That rejected batch? Two clicks and Quality Control knows exactly which pallets are where. No rocket science, just all the information in one place that can be used across the teams. And that easily saves several hours a day of searching.

The next step? Now that the basics are in place, the same company is experimenting with automatic restocking based on sales patterns. Not because they have to, but because the data is there. Step by step, at their own pace.

The Volve approach: start fast, grow smart

At Volve, we believe that data transformation doesn’t have to take years. Thanks to our Infrastructure as Code (IaC) approach and templates, your basic platform is up and running within weeks. No months of implementations, but quick initial results that we build on together.

Phase 0: Engagement & Discovery

We start by getting to know your organization, processes, and current data landscape. We identify quick wins, map the critical data sources, and together define the use cases that really make a difference for your business. This phase is crucial and lays the foundation for success.

Phase 1: Initial platform setup (typically ~8 weeks)

This is where the magic of Infrastructure as Code happens. We deploy your cloud-native data platform with our templates – not reinventing the wheel, but proven components that we adapt to your specific situation. The basic links with e.g. your ERP are realized. Your first dashboards (or other use cases) go live. You have instant visibility into your key KPIs.

Phase 2: Incremental value creation (ongoing)

Now that the platform is in place, we are building new functionalities step by step. The beauty? The platform grows with you. Today a simple inventory report, next month a link to your LIMS system, six months from now perhaps a first predictive model.

Each new “data consumer” – whether it’s a dashboard or AI model – is developed in short sprints. You set the pace and priorities. We ensure that each addition delivers immediate value, in tandem with the internal teams.

Phase 3: Optimization & Adoption (ongoing)

A platform is not valuable until people use it. We train your teams, implement governance where needed, and continue to optimize the platform based on usage and feedback. From power users to occasional users – everyone needs to be able to work with it.

What makes Volve unique here?

“Think data, speak human” – this philosophy is in the DNA of everything we do. We understand that behind every data set are people who need to make decisions. People who are not waiting for complex technical stories, but for clear answers that help them grow.

Where others may overwhelm you with technical jargon and years of trajectories, we try to make data accessible to everyone in your organization. From operator to CEO. We translate complexity into simplicity, without losing the nuance.

Our strength lies in combining your industry knowledge with our expertise. We sufficiently speak the language of Food & Beverage – we understand the difference between THT and TGT, know the complexities of multi-tier promotions, and know how critical traceability is – but need you for the extra-mile that makes you just that little bit different. But most of all, we believe in the human factor. Data is only valuable if people can and want to work with it. That is why we invest as much in adoption as in technology.

The future is data-driven. The question is: when do you step in?

The Food & Beverage industry is on the brink of a data revolution. Companies that invest in a solid data platform now are building an unbridgeable lead. They see opportunities where others see problems. They anticipate where others react. And they grow where others consolidate.

A modern data platform is not an expense, but an investment in sustainable growth. The difference between surviving and thriving in a market that is only getting more complex. The technology is there. The expertise is available. The business case is proven.

The only question that remains: are you ready to make your data work for your future?