Key Takeaways
Generative AI automation for CPG companies is the subject. The post argues that traditional automation, namely RPA, fails to deliver ROI in consumer packaged goods: bot-centric infrastructure is costly, demands consultants and engineers, and breaks the moment anything changes, even a shifted spreadsheet column. Multi-step processes like vendor onboarding and inventory management stay stubbornly manual because their high volume of exceptions breaks brittle bots. Meanwhile CPG leaders battling inflation across transportation, materials, and labor increasingly prize their most valuable asset: time. The proposed answer is generative AI automation that lets ordinary business users build and manage their own automations in plain English, critical when less than 1% of people can code. By automating document processing, CRM updates, onboarding, and claims, CPG firms compound time and cost savings, free staff for strategic work, and ultimately spend more time understanding and serving their customers. See the Kognitos platform.
Automation in the CPG industry is not new, but it is evolving rapidly. Performing tasks accurately and at scale, both on the production floor and in the office, not only delivers a competitive edge to the company as a whole, but brings peace of mind to the employees and managers involved in these processes.
On the other hand, there is a steep learning curve to adopting any kind of new technology (think back to when you first implemented your ERP). The time lost in learning, mistakes made in the process, and sheer frustration is all said to be an “investment” towards a future with streamlined processes…
Until the next new software, of course.
Traditional automation in CPG (RPA) fails to deliver the desired ROI for two main reasons:
- The bot-focused infrastructure makes it expensive to deploy, coupled with the additional costs of hiring consultants and engineers make it difficult to justify for most CPG companies.
- The inability to easily make changes to the automation. If there is anything out of the ordinary with your automated process (this can be as little as a column in a spreadsheet moving 2 inches to the left) the automation breaks.
And coordinating between IT and business units is often challenging.
Multi-step procedures such as vendor onboarding and inventory management still remain stubbornly manual due to the high volume of exceptions which break traditional RPA Automation.
In all fairness, CPG leaders have pushed the hard for operational excellence during and after the pandemic, an unprecedented event which shook global supply chains. As the global economy opens again, CPG leaders face a new challenge: Battling inflationary pricing across transportation, raw materials, and labor.
Market leader, P&G, was able to grow gross profits 9.7% since 2020 by prioritizing the single most important asset in the company: Time.
The average IT professional is reported to spend 4.5 hours a week searching for documents according to an IDC white paper published in 2012.
That’s over half a workday lost every week of highly skilled and expensive labor to the company. Our technology has advanced to the point where it is capable of saving this lost time, but not all business users can utilize these capabilities without having coding knowledge.
We believe technology should empower the user, not the other way around. Today, less than 1% of the world knows how to code. So, if we can’t speak the language of computers, why don’t we make computers speak our language?
This is the fundamental idea behind Generative AI Automation.
Imagine billions of business users creating and managing their own automations using simple english. The time and cost saved from automating manual tasks such as processing documents, updating CRM, vendor onboarding, and claims management (among others) can be significant when compounded over time. Additionally, Generative AI automations empower business users by allowing them to spend their time being strategic and, of course, happier without tedious and manual work.
The competitive advantage from automation for the CPG industry goes beyond the obvious time and cost benefits, it allows them to spend more time better understanding and serving their customers.
How CPG Companies Can Use Generative AI for Better Automation
- Identify CPG processes with the highest document processing and exception handling burden. Trade promotion reconciliation, retailer invoice deduction management, demand planning data aggregation, and new product launch documentation are CPG processes with high document processing and exception handling burden.
- Deploy AI for retailer deduction processing and dispute management. Retailer deductions are a high-volume, high-variation document processing challenge for CPG companies. AI automation extracts deduction claims, matches against trade promotion data, and routes disputes with context. Automated deduction processing is the highest-ROI CPG automation target.
- Automate demand planning data collection across retailer and distributor sources. CPG demand planning requires data from multiple retailer and distributor systems in different formats. AI automation aggregates demand data across sources, normalizes to a standard format, and feeds the demand planning system automatically.
- Configure AI for new product launch documentation across channels. New product launches require consistent product data across all retailer channels: item setup forms, pack configurations, UPC assignments, and marketing assets. AI automation manages the routing and tracking of new item setup across retailer portals.
- Measure deduction resolution cycle time and demand data availability. Deduction resolution cycle time (days from deduction claim to resolution) and demand data lag (days from sell-through to demand planning system update) are the primary CPG automation metrics.
