Artificial Intelligence (AI) and Machine Learning (ML) are two interconnected data science tools that can help businesses actively draw understandings from data, and then turn those insights into action to build lasting efficiencies, reduce costs, and raise profits.
When applied effectively to various business functions such as demand planning and supply planning, Artificial Intelligence can have an enormous impact across your organization. AI describes when machines execute tasks that mimic the capabilities of a human, such as automatically providing suggestions on ways that companies can quickly realize efficiencies.
ML is a subfield of AI and describes the process by which machines learn and adapt through iterative algorithmic activity, learning on their own without additional programming or human intervention. In other words, with ML, a demand forecasting model learns from data over time. AI can utilize the insights that Machine Learning algorithms provide, thereby becoming the “digital brain” of your business.
The relationship between Artificial Intelligence and Machine Learning mirrors another oft-conflated one: demand planning and demand forecasting, two terms used interchangeably but are decidedly different. Demand planning is the process of forecasting demand and shifting your operational strategy in order to meet that future demand; a demand forecast (or: demand prediction) is the actual result, the output of your planning process. One is a function of the other—just like AI and ML.
More and more, CPG brands are adopting and investing in innovative technologies that can bolster their demand planning process and unify their supply chain operations. These technologies can:
CPG companies often find themselves growing quickly, but manual processes can get in the way of brands reaching their full growth potential.
Switching your demand planning process from manual and static to AI-powered and automatic allows your brand more room and resources to scale.
Spreadsheets definitely can’t handle massive amounts of data the way AI and ML can, and ultimately, a technology-based forecasting method is easier to implement, quicker to onboard, and more accessible than most people think.
There are lots of reasons why a business—regardless of the industry—would employ AI, particularly in the context of a demand plan. AI can identify the relationships between shipment data, store-level sales, seasonality, inventory management, and marketing investment much faster and more in-depth than a human ever could. And since this technology can analyze more data more precisely, the natural result is highly accurate forecasting across sales, distribution, inventory levels, and more.
CPG companies typically try to streamline all parts of their business, especially when they’re getting off the ground. For instance, a brand’s operations lead usually does demand planning on top of their other operational responsibilities. Or, maybe a brand’s sales team is in charge of building demand forecasts—and their time can very obviously be better spent on the ground, selling your product. No matter who’s doing the demand planning, demand planner or not, CPG companies may not have the funds or bandwidth to bring on a new team member. In fact, AI-powered demand planning software can alleviate the task of adding new team members (without the cost of a search or salaries), and automate many of the slow, manual processes that can notoriously drag down your brand’s demand planning process.
AI can create the kind of agility your demand planning process needs in order to keep up with and stay ahead of consumer trends. Rapid changes in consumer trends can seem like an obstacle: After all, we saw what happened with the Covid-19 pandemic as customer demand for certain kinds of products—and certain brands themselves—skyrocketed. With automated and granular predictive analytics, Automated Intelligence can deliver, faster information means you can make faster shifts to keep up with demand drivers in the market.
Staying ahead means ingesting forward-looking data, and lots of it. Just one example is how AI can use that forward-looking data to optimize your e-commerce marketing dollars when selling via Amazon or Shopify. The kinds of external data you need to ingest includes keyword search statistics, social media ad spend statistics, search engine keyword performance reports, and product reviews for all competitor products—no human can wrangle all of that on their own.
Managing your business can be taxing enough, let alone managing your relationship with another business. Take distributors, for example. Brands rely on distributors to issue POs, and gaining distribution via a KeHe or UNFI can help brands scale locally and nationally. However, a CPG brand’s relationship with them often has a power imbalance; the power is oftentimes tilted in the direction of the distributor, who has its own forecasting methodology and often cuts whatever corners they can (such as taking advantage of a brand’s bulk discounts). With AI-powered demand forecasts, you can gain a better, deeper, and more granular understanding of your historical forecast accuracy. If your own forecasts are consistently accurate, it’s hard for a third-party business to argue with those numbers.
The automation technology behind AI can provide brands with the kinds of actionable insights they need to take informed action in all situations.
This includes historical data like accuracy levels and performance error filtered by channel, customer, distribution, brand, warehouse, and segment. Or, it can look like the factors that contributed to statistical forecast error, ranked by impact. Using these analytics to inform shifts in your business results in less risk, more opportunity, and sweeping efficiencies realized more quickly across your supply chain.
AI is on the scene, here and now, across the business world—and there’s no going back. As technological innovation continues to progress, though, the CPG industry must take full advantage of the processes here to stay (and yet to come!). How to do this: by fully understanding what today’s technology can do for you and for your brand. Here are some key takeaways that show why AI could be indispensable to your brand:
Automation is here to stay. Forecasts automatically generated by AI enable quick changes to be made across the supply chain in response to a rapidly changing consumer demand landscape. Plus, with automated, actionable insights in tow, your supply chain planning team can optimize key cost centers, align forecasts with purchasing and manufacturing plans, and optimize logistics and working capital more efficiently than ever before.
AI lacks emotionality—thankfully. Unlike a human, a machine doesn’t understand outlier events through an emotional lens. Since it’s not explicitly programmed, it understands all data points as just that—data points. Panicked, emotion-driven decision-making suddenly exits the equation.
Savings never go out of style. All of the advantages of leveraging AI trickle down to the rest of the business, resulting in more precise manufacturing and inventory planning, optimized capital and marketing spend, and increased efficiencies across the supply chain. The direct dollars-and-cents results of this optimization look like increased sales, greater advertising conversion rates, fewer expedited shipping costs, less working capital tied up in inventory, fewer unplanned production runs, fewer lost sales from stock outages—the list goes on.
Simply put, implementing an AI demand planning process can save your organization time and money, setting your brand up for success and growth in the long-term.
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.