It wasn’t that long ago that you implemented your new enterprise resource planning (ERP) system at work, right? If so, why does it feel like a lifetime?
When teams spend countless hours wrestling with inaccurate forecasts, excess inventory, and frustrated stakeholders, it’s easy to start thinking that all the trouble of adding a new system to the tech stack was for nothing.
If you find yourself in this situation, rest assured that you can achieve accurate inventory forecasts. The trouble you’re having now isn’t your new ERP’s fault. The platform is likely doing exactly what it was designed to do. The issue lies in the fact that what you need is an inventory planning solution integration, too.
By pairing these two powerful software solutions, you can gain clarity, start producing accurate forecasts, and move past this challenging phase into an era of operational excellence.
Quick insights for decision-makers
- Forecasting challenges that persist after implementing a new ERP are not necessarily issues with the platform’s configuration.
- ERPs are best suited for managing historical data, but they lack predictive capabilities.
- To resolve forecasting challenges without creating additional issues and spreadsheets, businesses should consider implementing a specialized demand forecasting platform on top of their ERP.
- Real-world use cases prove the quantitative and qualitative value of pairing these two advanced tools for accurate forecasting in volatile supply chains.
- Netstock provides advanced forecasting capabilities and seamlessly integrates with more than 60 leading ERPs, enabling businesses to maintain their investment and overcome costly challenges.
The gap between ERP promise and forecasting reality
When you implemented your new ERP, you probably thought it would solve all your problems. While it solved some, you’re left with a gap between historical records and knowledge of what to do next to meet customer demand.
This is a common situation that happens when business decision-makers misunderstand the fundamentals of ERPs. ERPs are powerful tools that organize inventory across multiple locations and record historical item and transaction data. What they can’t do is look ahead.
Still, your investment in the platform was a smart one because it planted the seed that makes accurate inventory forecasting possible. After all, how good is a forecast if it’s built on incorrect or assumed data?
That’s where Netstock comes in. When you integrate your existing ERP with Netstock, the advanced solution turns historical data into actionable, intelligent forecasts that guide business decisions. While Netstock does this, your ERP continues doing what it does best, too. That is, maintaining accurate records.
For accurate inventory forecasting, you need this pairing of transactional accuracy and predictive analytics. So remember: your ERP investment wasn’t wrong. It just wasn’t complete!
Getting it right from the start: What success actually looks like
Success looks like: a fully functioning ERP that maintains clear, reliable data, while an advanced forecasting solution like Netstock analyzes that data to generate predictions you can actually use. Accurate forecasts are those you can trust when reporting them to stakeholders, which also means success involves lower stress, increased confidence, and stronger leadership support.
Now, if you want to get technical, “right” means forecasts that are accurate 80% or more of the time, with safety stock levels that balance service without tying up cash, and reorder recommendations that support real-time demand signals. Having the right forecasts allows planners to spend less time second-guessing general rules and recommendations and more time addressing exceptions that require human adjustments.
Businesses that operate in this successful state are able to do so because they don’t view their ERP as a standalone solution or the end of the line. They treat the system as the data backbone that allows the integration of purpose-built predictive analytics tools.
One such company is Surface Art, a tile distribution company based in Seattle, Washington. Surface Art struggled with forecast accuracy and inventory visibility when they were operating with their ERP alone. By integrating Netstock with Sage ERP, the business benefited from enhanced demand forecasting made possible by leveraging Netstock’s AI recommendations. This enabled proactive purchasing decisions, resulting in a 5-10% improvement in product availability and higher sales.
“Netstock allows us to manipulate forecasts on the fly, ensuring we’re always prepared for high-demand seasons,” said Kevin Stupfel, President of Surface Art.
Businesses that approach forecasting in this manner – with a pairing of powerful tools on their side – avoid common ERP implementation challenges faced by those who settle for a single solution. The key to their success is that they recognize what an ERP does well and choose specialized solutions to fill the gaps.
Why accurate inventory forecasting demands more than ERP alone
Accurate inventory forecasting is simply not possible with just an ERP. Yes, forecasting is possible with the data ERPs record and advanced spreadsheet formulas, but going this route consumes valuable time, resources and is prone to human error.
Remember, the ERP is the foundation, and the data is essential, but accurate stock forecasting requires predictive intelligence that helps you make informed decisions.
Consider what goes into a reliable forecast:
- Pattern recognition across thousands of SKUs that can account for seasonal trends and promotions
- Multi-variable modeling that includes lead time variability, supplier performance, economic indicators, and customer behavior
- Real-time adaptability that adjusts in response to new sales data, supplier shifts, and more
- Scenario planning, or “what-if” testing, allows planners to explore outcomes before allocating cash to inventory decisions
- Machine learning refinement that continuously improves accuracy as the system learns from past forecast successes and errors
The reality is simple: ERPs weren’t designed to handle these tasks! Expecting your ERP to handle advanced forecasting is like asking your accounting software to write your annual strategy. Sure, the data is there, but the analytical capabilities aren’t.
This doesn’t diminish the value of your ERP investment. It just makes it clear where specialized tools add the most value.
The most common ERP inventory implementation challenges (and why they happen)
Even the most well-executed ERP implementations face predictable forecasting obstacles. Understanding what causes these challenges helps businesses plan for the future rather than freeze in frustration.
| Challenge: | Why it Happens: | Impact: |
| Static forecasting models | ERPs usually use basic averaging methods that don’t or can’t adapt to changing demand patterns or account for multiple variables simultaneously. | Persistent forecast errors lead to chronic stock-outs and overstock. These imbalances eat up profit and bring down service levels. |
| Limited scenario planning | Standard ERP reporting shows the current state of things, but lacks tools to model potential alternatives so planners can test different ordering strategies before committing. | Decisions get made on gut instinct or historical assumptions rather than quantifiable, current data. This increases the financial risk of decisions in volatile or changing supply chains. |
| Manual workarounds abound | Since built-in ERP inventory forecasting isn’t an option, teams export data to spreadsheets and create static, error-prone processes. | Time is wasted on manual data manipulation instead of strategic analysis. Human errors compound over time. |
| Delayed visibility into problems | ERP reports show what happened historically. They don’t flag issues (like potential stock-outs) proactively. | Reactive inventory management takes time that could be used for proactive planning. Expensive problems are only noticed after they become unavoidable. |
| Difficulty handling complexity | Multi-location inventory, variable lead times, supplier performance issues, and demand volatility overwhelm static, out-of-the-box ERP logic. | Planners fall back on over-ordering as a buffer. This ties up working capital unnecessarily. |
These challenges are structural limitations of systems designed for different purposes, rather than ERP inventory implementation issues. ERPs organize and record. Specialized forecasting solutions predict and optimize.
Recognizing this distinction transforms how organizations approach the problem. Instead of assuming (and hoping) better ERP configurations will solve forecasting challenges, IT decision-makers and leadership can address the gap by integrating purpose-built demand planning tools.
How Netstock closes the forecasting gap without disrupting your ERP
Purpose-built predictive inventory forecasting solutions like Netstock are the key to closing your forecasting gap and moving beyond the frustrations left by only utilizing an ERP system. The best part is that adding Netstock’s cloud-based solution to your tech stack doesn’t require you to part ways with your existing platforms. Instead, Netstock seamlessly integrates with 60+ leading ERPs to take your processes a step further.
Machine learning and predictive analytics
Netstock applies machine learning algorithms, trained on over 15 years of global supply chain data, to your specific business patterns. Using data from the ERP connection, the system analyzes historical sales, identifies seasonal trends, adjusts lead time variability automatically, and more. AI that recognizes patterns and can recommend adjustments based on these variables means forecasts are more accurate and better serve current customers and business needs. Additionally, planners receive alerts when SKUs trend toward excess or risk stock-outs, which means issues can be managed before they impact the business’s bottom line.
Real-time inventory visibility
Netstock delivers visibility in easy-to-use executive dashboards. This reporting capability turns raw ERP data into actionable insights decision-makers can actually use.
The impact on different job roles can be seen in the following ways:
- CFOs can see exactly where working capital is available or tied up.
- Operations leaders can quickly identify which suppliers are underperforming and those that are underutilized.
- Demand planners have access to AI-driven recommendations for SKUs across every location.
Scenario modeling
“What-if” scenario modeling lets internal teams test different strategies and see possible outcomes before committing. What if a supplier’s lead time increases by two weeks? How does a 13% decrease in demand for a specific SKU affect the next shipment’s profit margin? What’s the financial impact of adjusting safety stock levels for a product line before the holidays? These questions can be answered with informed data when intelligent forecasting is in place.
Moving from implementation challenge to strategic strength
ERP inventory implementation challenges aren’t failures. They’re signals that your business needs a more sophisticated solution: one that pairs transactional accuracy with predictive intelligence.
Real-world use cases prove that businesses that get this right don’t view forecasting struggles as something to fix within their ERP. They see that different systems serve different purposes. A combination approach unlocks forecasting capabilities neither would be able to do on its own.
That’s why the first implementation doesn’t have to be perfect, but it should be strategic. Understand how Netstock connects with your specific platform, what data flows between systems, and take the first steps toward more accurate forecasting.
