In recent years, consumer packaged goods (CPG) companies have ramped up their focus on the customer experience. Through social media marketing, direct-to-consumer retail stores and ecommerce, and customer analytics, CPG companies are striving to meet soaring consumer demand for seamless and personalized experiences with their favorite brands.

That’s all well and good. But those efforts fall short if a CPG company can’t get it’s products to retail stores or make them available for online purchase when the customer expects it.

An empty space on a store shelf or “Out of Stock” notification on an ecommerce site is more than a lost sale. It can undermine the brand loyalty that CPG companies are trying to cultivate. It’s all too easy for consumers to switch their brand allegiance with today’s abundance of product options.

High consumer expectations for on-demand product availability across multiple channels is raising the stakes for available-to-promise (ATP). ATP represents a CPG company’s ability to commit that a given quantity of a product will be available at a specified date to a physical direct-to-consumer retail store or online.

Accurate ATP commitments depend on multiple supply chain dynamics, from raw material procurement and supplier performance to demand forecasting, lead cycle times, manufacturing efficiency, inventory availability and logistics. Orchestrating data from across the supply chain to consistently hit ATP targets is difficult enough.

And now several factors are further complicating the ATP equation:

High product variety. CPG companies are producing goods in more varieties than ever. More types of dish soap, chocolate bars, soft drinks and toothpaste make managing ATP all the more difficult.

Direct-to-consumer omni-channel experience. D2C aims to nurture customer intimacy, but product unavailability or delayed shipping undermines the experience. Consumers blame the CPG company if a product is not delivered as promised.

The new customer-centric focus in CPG is reducing the margin for error in ATP and other aspects of supply chain management. We’re seeing a direct cause-and-effect between back-end supply chain processes and the front-end consumer experience. To deliver shopping experiences that delight customers, the supply chain needs to function responsively and seamlessly.

A recent survey by Accenture of supply chain managers and executives at CPG companies examined the interrelationships between supply chain management and the consumer experience. The consulting firm concluded that CPG firms need to do a better job in connecting the dots to meet shopper expectations and fuel growth.

“CPG companies are missing opportunities to use the supply chain to drive differentiation and profitable growth,” Accenture’s report states. “An intelligent supply chain will enable them to deliver the right customer experiences and, ultimately, help to differentiate and grow the business.”[1]

The Emergence of Cognitive Automation

That intelligent supply chain is now in sight with the emergence of cognitive automation, which combines data collection, artificial intelligence (AI) and machine learning so that CPG companies can vastly improve ATP accuracy and supply chain operations as a whole. This technology is today delivering groundbreaking capabilities beyond what’s been possible with conventional methods.

Traditionally, supply chain planners have rounded up information from ERP, CRM, warehouse management, logistics and other applications to calculate lead times and ultimately ATP. Those calculations are often done in spreadsheets or through ATP functions built into an order management system or ERP system. CPG companies may as well support ATP calculations with data lakes, data warehouses and analytic tools.

Despite multimillion-dollar investments and untold hours of effort, ATP calculations often end up being best guesses based on inaccurate or outdated information. The sheer complexity of information that goes into ATP overwhelms the limitations of the best human efforts and static, rules-based legacy software. CPG companies lack the end-to-end visibility that’s needed for accurate ATP.

Innovative CPG companies are instead turning to cognitive automation, with technology that can crawl dozens of applications thousands of times a day to capture real-time data about demand and available supply. Machine learning techniques can then predict ATP dates and quantities for specific customers and channels. Finally, AI-based recommendations are generated to ensure ATP dates committed to the customers are met — and deliver what I call cognitive ATP.

At Aera Technology, we’re hearing directly from global CPG companies on the improvements they’re seeing in ATP through the use of cognitive automation. These companies have new abilities to:

• Gain end-to-end visibility of global demand and supply by collecting and processing data across multiple systems in real-time
• Predict lead times required for accurate ATP date and quantities, especially important for backorders
• Monitor real-time changes of supply and demand that could impact the ATP date and quantity
• Act on AI’s prescriptive recommendations to prevent impacts on ATP dates and quantities, or authorize AI to act autonomously

By introducing AI-driven cognitive automation into the supply chain, CPG companies are poised to gain vital new visibility across the full product lifecycle that will increase their revenue, save millions of dollars in inventory costs, and build brand loyalty. Ultimately, those gains trickle up to enrich the consumer experience with reliable product availability at any time over any channel.