McKinsey estimates that 16 to 26 percent of exports could be relocated and readjusted in the next year. That’s over $4 trillion in supply chain value that’s up-for-grabs, disconnected, and ultimately ready to be reaped. But, while that certainly presents an opportunity, it only presents an opportunity to a few key players. In McKinsey’s Reckoning With Supply-Chain Disruptions from COVID-19 white paper, they suggest that companies who are able to adjust their demand forecasting stand to gain grounds, create resiliency, and position themselves in the “new normal” supply chain.
59 percent of organizations are happy with their forecasting processes. Yet, that’s not spread evenly. Small and mid-market companies are far less likely to be satisfied with their forecasting techniques. It makes sense. Large organizations have the liquidity and talent to create well-oiled forecasting frameworks. The mid-market doesn’t. You have to prove value to stakeholders fast, and every investment in tech directly impedes near-term growth. To be clear, the mid-market is in a tricky position.
On the surface, predictive forecasting has the very real opportunity to reduce lost revenue (overstocks and stock-outs cost retailers over $1.1 trillion a year), but actually implementing forecasting solutions is difficult. Worse yet, there’s no clear-cut roadmap. How do you jump from predicting stock-outs to long-term financial, sales, and analytical predictions that help you make smart decisions?
After all, trying to make a play for that $4 trillion worth of value flow requires some future-telling. In an effort to help the mid-market, let’s discuss what a typical forecasting flow looks like for supply chain companies. Here’s a step-by-step of how you can introduce predictive analytics into your organization — the right way.
“There are companies within each industry that are leaders… that have used big data analytics to forecast demand, who scan the horizon and see shocks coming and respond. But there’s no industry that’s done a great job.” — Susan Lund, Partners at McKinsey, Washington, DC
According to PwC, forecasting is the single most important value driver for nearly every inventory-based business. In fact, leaders across the Chemicals and Processes (87%), Industrial Products (98%), Retail and Consumer Goods (95%), and Technology and Telecom (94%) rate predictive forecasting as a “very important” driver of value in 2020.
Yet, despite rallying calls for better analytic processes, most supply chain leaders are failing at forecasting and analytics. There’s a disconnect between the obvious value of forecasting and the value that companies are actually reaping in the real world.
On the surface, it seems simple. Predictive analytic solutions can help your supply chain company:
But that’s the surface noise. Actually unlocking those benefits requires careful planning, legwork, and the right tools. So, let’s go beyond the surface layer. Here are a few tips to help you create a holistic forecast-ready supply chain environment.
Predictive analytics echoes benefits throughout your entire supply chain. So it can be tempting to go all-out and integrate a large-scale forecasting solution. But, before you start binding predictive tools to your ERP, you need to think about value. How are you going to prove value to stakeholders? Broad implementations are great, and they should absolutely be your ultimate goal. But we highly recommend starting somewhere that’s instantly tangible — inventory.
The value of predictive analytics on inventory control is massive. Tracking expirations, dead stock, stock outs, and excess inventory can help you immediately reduce inventory burdens and increase liquidity. We consider inventory as the most immediately valuable component of the modern, forecast-driven supply chain. By incorporating stellar inventory controls, you can start to generate ROI on your investment. Often, we see supply chain businesses make the mistake of broad implementation. They weave multiple vendor solutions together and create robust forecasting networks.
But, while this will prove immensely valuable in the long-run, it can bog down workflows, create immediate losses, and force you to second-guess the value of forecasting — which can put an immediate wrinkle in your plans.
In other words, start with something tangible like inventory. Then, work your way towards sales, promotions, and the intangible components of forecasting, which can all be harder to measure and prove value against. Your goal should be to generate a rapid ROI. This way, stakeholders get excited, you feel accomplished, and you can get a grip on what forecasting is going to be like when you implement it across your entire supply chain.
Now we can discuss post-inventory forecasting. Eventually, once you see returns on your inventory-based analytics, you’ll likely want to expand your forecasting throughout your supply chain framework. But where do you start? We recommend starting with “demand forecasting.” In other words, focus forecasting on driving predictive value to your sales teams, promotions, and inventory flow. The overall goal of demand forecasting is threefold.
It’s a common misconception that predictive analytics can only react to mid-horizon changes. Modern analytics are fast, intelligent, and actionable. For example, McKinsey suggests that supply chain companies immediately leverage forecasting tools to deal with the post-COVID environment.
“Planning systems with machine-learning capabilities can base their forecasts on many more factors and learn the “next normal” much faster than traditional approaches for building business continuity, preserving cash, and strengthening supply-chain resilience.” —Resetting Supply Chains for the Next Normal
To facilitate broader demand-driven analytics, you should consider investing in the right ERP (e.g., Dynamics, NetSuite, Epicor, Eclipse, JDE) or pre-built legacy systems. Then, consider investing in a supply chain planning suite that compliments (and naturally integrates with) your ERP. Eventually, you can continue to add new layers to your ERP to drive more value into your supply chain.
To clarify, we recommend that supply chain businesses (or any inventory-based business) take the following approach to implementing forecasting into their business and technology architecture:
The truth is: building a forecasting roadmap isn’t easy. We can help. StockIQ is an end-to-end supply chain management suite. Our forecasting solution was built (from the ground-up) to help you find tangibility in your forecasting investments. We provide inventory, sales, and promotional forecasting, and StockIQ naturally integrates with the world’s leading ERPs. Better yet, we can custom-design an instance for you. So, whether you’re relying on legacy systems or popular ERPs, we can tailor our solution to your needs.
StockIQ provides forecasting value across multiple layers, and we’re ready to help you recognize the value of forecasting without rigging together complicated tech stacks. Are you ready to experience (and predict) the future of the supply chain? Contact us.