Safer, Smarter, Stronger: Why Forecasting Belongs In-House

Imagine this: It’s a typical day. Your team is running efficiently, relying on accurate forecasts to plan shipments, restock shelves, and confidently meet customer demand. Inventory is flowing, sales trends are clear, and operations feel predictable. Suddenly, your forecasting system breaks without warning.  You have no visibility into recent sales or current store inventory levels. Your warehouse doesn’t know how much product to ship or where to send it. Supply chains stall, fresh produce rots, and customer expectations go unmet. This nightmare became a reality for several major companies in late 2024 when their third-party forecasting provider, Blue Yonder, was hit with a ransomware attack.

This incident sheds light on a growing risk: reliance on external platforms for critical operational intelligence. Outsourced forecasting may offer quick access to “out of the box” functionality, but it also introduces fragility, generic insights, and a loss of ownership over a core business process.

It’s time to rethink the model. Bringing forecasting in-house is more than a technical upgrade – it’s a strategic investment. It strengthens operational resilience, enables custom and proprietary insights, and empowers cross-functional collaboration between business and IT.

Critical Operations Require Resilient Systems

The Blue Yonder incident proved that even mature third-party platforms aren’t immune to outages or cyberattacks. When a third-party forecasting system is down, there’s nothing to do but sit and wait for service to be restored, regardless of how critical that system is to your operations.

Relying solely on a third-party forecasting system is like depending entirely on the city’s power grid. When the power goes out, you’re in the dark — literally. But if you’ve invested in a backup generator, the lights stay on and operations keep running.

By bringing forecasting in-house and hosting it through a modern technical architecture, you're not just building a tool, you're building resilience.

When weighing these options, it’s important to consider the criticality of the operation. Most individual households don’t have generators, but hospitals do because they can’t afford downtime. It might be inconvenient for the lights to go out at home or for the food in your fridge to spoil, but it’s catastrophic when life-saving equipment stops working in a healthcare facility. The same principle applies to forecasting. When a system directly affects your customers, your supply chain, or your revenue, resilience isn’t optional — it’s essential.

While third-party tools can be useful in lower-risk scenarios, the core forecasting that drives supply chain decisions and shapes the customer experience carries too much strategic weight to outsource and is best served by an in-house solution.

By bringing forecasting in-house and hosting it through a modern technical architecture, you're not just building a tool, you're building resilience.

Proprietary Insights Drive Better Results

Most off-the-shelf forecasting solutions are designed for broad applicability, not for the unique dynamics of your business.  You know the intricacies of your business better than anyone. Even companies in commoditized markets have their own “secret sauce” – a mix of customer preferences, local knowledge, and strategic nuance that drives performance.

Take grocery retailers, for example. Even in the same metro area, different chains operate with vastly different approaches. One might lean into organic produce, another might specialize in private-labels, and a third may thrive during game-day weekends or local events (such as the NFL Draft, which was recently held in Green Bay near Snow Fox Data’s headquarters). These differences aren’t captured by a generic model trained for mass-market forecasting.

With in-house forecasting, you can tailor models to the factors that matter to you – store-specific sales patterns, regional holidays, weather conditions, promotional timing, and operational constraints. These inputs make your models smarter and your decisions sharper.

Owning the forecasting pipeline also means tighter integration with your internal systems – ERP, sales, inventory, and logistics. This enables richer feature sets, better data flow, and ultimately more accurate forecasts that reflect how your business actually runs.

Empowering Teams and Streamlining Costs

In-house forecasting breaks down silos and fosters true cross-functional ownership. Business and IT teams collaborate to design, test, and evolve the solution together. That’s a different approach from a dynamic where IT maintains a connection to a third-party “black box” that feeds data to downstream systems.

When forecasting lives inside your walls, business teams naturally get closer to the data, and IT gains a deeper understanding of operational drivers and strategic priorities. That synergy unlocks faster iteration – model updates happen in days, not weeks – and teams can respond to shifts like promotions or local demand spikes in real time.

For many organizations, the ROI goes beyond improved forecasting – it delivers real dollar savings while reducing risk and growing internal expertise.

Instead of logging a vendor support ticket and waiting, or hoping that the generic system eventually catches a trend, your teams are in control. You can respond to real-time signals like sales surges or weather disruptions and fine-tune forecasts with context that only your team understands. This leads to faster decisions, fewer delays, and more accurate actions where they matter most.  

There’s also a meaningful financial upside. A typical third-party forecasting platform can cost $200,000 to $500,000 in yearly licensing alone before factoring in integrations, training, vendor support, or data access fees. These tools often charge by user count or usage tiers, making long-term scaling expensive, with total costs easily exceeding $1 million per year.

By contrast, once in-house models are deployed, they incur only incremental infrastructure and staffing costs that are often absorbed by your existing data and IT teams. You control the roadmap, avoid ballooning vendor fees, and reinvest in capabilities that compound your competitive advantage.

For many organizations, the ROI goes beyond improved forecasting – it delivers real dollar savings while reducing risk and growing internal expertise.

Owned Forecasting Is Easier Than You Think

Building or improving your forecasting capability doesn’t have to be a massive, multi-year project. In fact, it often takes less time and delivers more value than trying to force-fit a third-party tool into your business. While these tools can appear turnkey at first, the reality is often messy and complex.

Experience across our team has shown that third-party implementations are rarely as fast or seamless as they are promised to be. Time is frequently lost in the hidden complexity of configuring integrations, making vendor workflows compatible with internal processes, training users, and retrofitting features to fit your needs. Add vendor timelines and one-size-fits-all assumptions to the mix, and the process slows even further.

By contrast, an in-house forecasting solution:

• Protects your proprietary insights.
• Capitalizes on what makes your business unique.
• Strengthens operational resilience and reduces risk.
• Supports agility through tight feedback loops.
• Reduces long-term delivery cost.

Start small. Build a pilot model, focus on a key product line or region, and scale from there. The key is to own the process, so you can adapt quickly, improve continuously, and align your forecasting with your strategy.

Not sure how to turn your forecasting into a competitive advantage? We’re here to help. Contact us for a consultation and find out how our experts can help you make a difference with data. 

| FEATURED AUTHOR: JON JORGENSON, SENIOR DATA CONSULTANT