3 Essential Demand Planning Analytics That Every CPG Brand Should Automate

by Sophie Guimaraes & Jonathan Zalman

4 minutes

CPG: Fast and Furious

The CPG industry has always been fast-moving. Though certain aspects of the industry are still playing catch-up—the CPG’s supply chain planning, for example, is lovingly old-school—its evolution is driven in large part by technology, which has had an everlasting impact on seemingly every single aspect of the supply chain. Furthermore, like many other consumer-centric industries, CPG is uniquely susceptible to watershed events, like crises or viral trends, that could have a major impact on various aspects of supply chain management.

As a result, CPG brands should proactively invest in the kinds of technologies that will help them realize value as quickly as possible, and evolve holistically, and this extends to their demand planning systems. In this article, we’ll explore the benefits of automation on the demand planning process—in particular, how automating key data-driven insights with demand planning software can help brands take action to drive supply chain efficiencies, raise profits, and stay ahead of the competition.

Here are three essential demand planning and demand forecasting statistics that your brand should automate today.

1.  Contributing Factors

CPG brands share a multitude of goals across the board, and one of them is achieving the best forecast accuracy possible. But it’s difficult to make strides toward this goal without asking: What, exactly, is contributing to a past forecast error? 

It may seem like a simple question, but without automating a demand forecast, it isn’t simple at all. In past times, finding sources of statistical forecast error meant working through what could feel like a sea of data, from sales and supply numbers to marketing, logistics, and more. As a result, brands were slow to implement the necessary changes to their operations, and there was no accountability in terms of where the sources of error were and why. 

Uniting AI + Human Intelligence for Truly Agile Planning [Unioncrate]


An automated contributing factors feature sorts through all of that data, fast. And it doesn’t only sort through it; the right automated demand planning platform can show errors automatically spliced and diced for you by brand, product, customer, channel, and ship-to. Now, you can identify sources of error that could look like...

  • Supply constraints and inventory planning issues
  • An overachieving promotion
  • Insufficient manufacturing output
  • Shipping issues because of delayed logistics
  • Inaccurate forecasts, especially those done manually or without aligned, centralized, and automated data

This automated granularity gives you and/or your demand planner a fuller, more holistic picture of where improvements could be made. And demand forecasting AI can even rank them automatically according to impact. With a holistic understanding of error, your brand can implement changes to your demand plan—and therefore enjoy better margins and increased efficiencies—sooner than later.

Forecasts vs. actuals on the Unioncrate platform
Forecasts vs. actuals on the Unioncrate platform


2.  Sales Drivers

The factors that drive errors are one thing, but the factors that drive historical and future sales are something entirely different. What influences sales can include everything from historical data, inventory, and seasonality to product transitions, obsolescence, customer demand variability, and so much more. By analyzing the dynamic relationships between these datasets across various time periods, you can find what’s driving your sales.

But, as you probably could have guessed, this would take a long, long time for a human to do manually—and you have other things you need to worry about. Enter: an automated demand planning and demand forecasting platform, which allows for this internal and external data to be centralized, ranked, and immediately available at your fingertips. Suddenly, you can understand what drives your sales—both past and predicted—at the click of a button, and you can use those actionable insights to eliminate blind spots from your demand planning process.

The Next Evolution of Supply Chain Planning [Unioncrate]

3.  Historical Performance Analysis

Contributing factors and demand drivers are useful in their own right, but what belies them are your actuals—and historical performance analytics are your one-way ticket to making sense of your actual vs. forecasted sales.

Historical performance analysis works via statistical forecasting formulas, such as WMAPE, MAPE, MAD, or BIAS, to assess accuracy and conclude how much actuals deviated from predictions. These automated Machine Learning algorithms allow for granularity at the SKU level, which can then be filtered by channel, customer, distribution, brand, warehouse, and segment. This automated granularity lets you see—without any sort of number-crunching or data-hunting—a fuller picture of consumer demand, such as unit shipments forecasted vs unit shipments shipped for a specific retailer. From here, you can optimize manufacturing output and warehouse inventory levels to prevent excess inventory and align with true, accurate demand.

And automation can take it further still: The right technology would give you all historical performance analytics, as well as predictive analytics, on one performance page. You would be able to see accuracy and error percentages all in one place, as well as automated priority rankings of profit margins across SKUs—something that’s nearly impossible to do manually. All that’s left for you to do is decide what all of these insights mean for your operations.

Monthly fiscal forecasts, ft. a ranked list of factors contributing to error [Unioncrate]
Monthly fiscal forecasts, ft. a ranked list of factors contributing to error


A Path Paved By Automation

A demand forecasting software's actionable, automated analytics illuminate a path forward so you can make confident decisions about your brand. Take it a step further and think about how investing in intelligent automation can translate into dollars and cents: The benefits of automation—unified data, high sales forecast accuracy, and speedy alignment—directly lead to optimized working capital, better-allocated resources, and foresight into how supply chain disruptions—or lack thereof—can affect financing of inventory and payment terms to manufacturers or customers.

Now, put these analytics into action. Instead of spending unnecessary hours parsing through demand uncertainty while figuring out where to take your business next, leverage an automated demand planning solution to decide what changes to make—and make them confidently.


About Unioncrate

Unioncrate is an AI-powered Supply Chain Planning Platform that gives CPG brands the technology they need to compete and win in a rapidly changing consumer landscape. Our automated demand and supply forecasts deliver unmatched accuracy, collaborative visibility, and actionable intelligence, simplifying a manual-heavy process and slashing hours from your week.

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