CPGs Are Driving Transformative Change With Deep Data and Advanced Analytics
Two weeks ago, at the Analytics Unite conference hosted by CGT and RIS in Chicago, with a group of over 40 CPG visionaries, AWS dug into the question of how data and analytics enable consumer packaged goods enterprises to unlock innovation.
In the workshop-style gathering, CPG leaders organized themselves by function and selected two to three data and analytics use cases per group. They then worked backward to determine the key actions, measures of success, breakthroughs, and blockers for each use case. They then received three mock $100 bills to “invest” in the use cases they believed had the best chance for growth at their organizations.
The casual experiment led to some exciting insights. These use cases received the most votes:
- Building supply chain resiliency through optimizing on-shelf availability
- Serving the consumer as a market of one using geo-data in targeting and personalization
- Responding to inflationary market pressures by optimizing product assortment and distribution
- Acquiring, harmonizing, and enabling data as part of democratizing data for self-service analytics
It’s no surprise that what CPGs and retailers are thinking about lines up with major headwinds in the market. When asked how they think about driving change and value, important nuances were uncovered:
A Cross-Functional, Collaborative Approach Is Necessary
Almost every use case that emerged required meaningful cross-functional collaboration. For example, not promoting products that are out of stock or struggling to procure raw materials for a product that has already been sold into retailers.
This is easier said than done for CPGs that have historically built successful brands while operating in functional silos — it’s simply not in their DNA to think cross functionally and there is an incredible amount of inertia standing in the way of progress. Even though CPGs are building bridges across functional silos more each day, especially in sales and marketing when it comes to e-commerce, they are still far away from tearing down these barriers altogether…and beyond the four walls of the enterprise.
Accessing Consumer Data Is a Roadblock for CPGs
One of the “a-ha” moments came when a retailer realized she had access to consumer data that CPGs wanted, but did not have. Sharing might be happening in pockets, but participants agreed there are no systemic models for sharing granular consumer data in near real-time between retailers and CPGs. As a result, CPGs must struggle with lagged and incomplete point-of-sale (POS) data to draw insights that, amongst other things, drive category management discussions with retailers.
There are solutions. Using data clean rooms allows for better targeting and personalization in a privacy-safe way has the potential to drive a step change in what joint business planning looks like between retailers and CPGs. This allows both parties to capture more of the value that is currently left on the table.
Data Democratization Needs to Drive Quick Changes (Processes and People)
There was unanimous support for the concept of data as an asset and as a currency for driving value. Most CPGs are exploring data catalog, library, and mesh technologies that democratize access to and use of all forms of data (production, shipments, POS, brand sentiment, third-party, and more). However, a common blocker across each use case depends on shifting the culture and the mechanisms to support a more data-driven approach to doing business overall.
The CPG industry is not at ground zero when it comes to instilling a data-driven culture. Gone are the days when marketing decisions were made based on tribal knowledge or when inventory planning decisions were made on intuition. The industry is still far from the top as CPGs are managing virtually all key decisions from sourcing, procurement, quality, trade, and marketing on offline Excel spreadsheets that pull data from various systems and stitch it together with unique assumptions that often yield conflicting insights from the same base data.
This leads to suboptimal decisions and frustrated employees. This is where CPGs need more focused efforts to communicate the value of moving off spreadsheets with one-off analyses and instead drive adoption of scalable, repeatable data, and analytics solutions that power insights in perpetuity.
Test and Learn: Implement Repeatable Mechanisms
Everyone was familiar with the mantra of “start small and scale fast.” The main issue is being able to experiment quickly and consistently. Participants revealed frustrations with measuring return on investment (ROI), getting approvals to experiment without impacting the core business, and navigating the high bar and long process that comes with getting a business case approved.
Still, CPGs are excited about solutions like digital twins and A/B testing capabilities that could help them to test and learn more effectively and efficiently, while also finding ways to balance the experimentation with scaling for value
More From AWS — Webinars On Demand
How Heineken’s Connected Brewery Ecosystem Fuels Automation
Accelerating Next-Generation Analytics at Kellogg's
View On-Demand | Read Webinar Transcript
How Herbalife Nutrition Improves the Consumer Experience Across Digital & Voice
One table said it best: “Everything comes down to value generation.” Value generation isn’t only about pilot key performance indicators (KPIs) that balance cost optimization with benefit maximization. Value has to be sustainable for a longer term.
One thing seen frequently is a failure to move from minimum viability to maximum value. While many CPGs successfully create minimum viable products (MVPs) by experimenting within certain functions, geographies, or brands, they don’t make investments in scaling to maximum value products by creating reusability and scaling through flexible data models, integrated data fabrics, and cloud-based technologies.
—Aparna Galiasso, Lead, CPG Go-to-Market Strategy & Solutions, North America, AWS
