CPGs drive transformative change with deep data and advanced analytics


Two weeks ago, at United Analytics conference led by CGT and SIR in Chicago, with a group of more than 40 CPG visionaries, AWS explored how data and analytics enable consumer packaged goods companies to unlock innovation.

In the workshop-style meeting, CPG leaders organized themselves by function and selected two to three data and analytics use cases per group. They then worked backwards to determine key actions, success metrics, breakthroughs, and blockers for each use case. They then received three fake $100 bills to “invest” in the use cases they believed had the best chance of growth for their organization.

The casual experience led to some exciting ideas. These use cases received the most votes:

  1. Strengthen supply chain resilience by optimizing shelf availability
  2. Serve the consumer as a single market using geographic data in targeting and personalization
  3. Respond to inflationary market pressures by optimizing product assortment and distribution
  4. Data Acquisition, Harmonization, and Activation for Data Democratization for Self-Service Analytics

It’s no surprise that What CPGs and retailers plan to align with key market headwinds. When asked How? ‘Or’ What they think about driving change and value, important nuances have been discovered:

A cross-functional and collaborative approach is needed

Almost every use case that emerged required significant cross-functional collaboration. For example, not promoting out-of-stock products or having difficulty sourcing raw materials for a product that has already been sold to retailers.

That’s easier said than done for CPGs that have historically built successful brands while operating in functional silos – it’s just not in their DNA to think cross-functionally and there’s an amount incredible inertia that hinders progress. Even though CPGs are building more bridges between functional silos every day, especially in e-commerce sales and marketing, they are still a long way from completely breaking down those barriers…and beyond the four walls of the enterprise. .

Access to consumer data is a barrier for CPGs

One of the “a-ha” moments came when a retailer realized they had access to consumer data that CPGs wanted, but didn’t. Sharing can happen in pockets, but participants agreed that there are no systemic models for sharing granular, near real-time consumer data between retailers and CPGs. As a result, CPGs must struggle with lagged and incomplete point-of-sale (POS) data to derive insights that, among other things, fuel category management discussions with retailers.

There are solutions. The use of data cleanrooms allows for better targeting and personalization while respecting privacy and can lead to a step change in joint business planning between retailers and CPGs. This allows both parties to capture more of the value that currently remains on the table.

The democratization of data must lead to rapid changes (processes and people)

The concept of data as an asset and as a currency of value creation was unanimously supported. Most CPGs are exploring data catalog, library, and meshing technologies that democratize access to and use of all forms of data (production, shipping, point of sale, brand sentiment, third parties, etc.) . However, a common barrier to every use case hinges on changing culture and mechanisms to support a more data-driven approach to doing business in general.

[More From Analytics Unite: Kimberly-Clark, Estee Lauder, Kroger: Tapping a Customer-Centric Approach to Data]

The CPG industry is not 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 at the top, as CPGs manage virtually all key sourcing, sourcing, quality, trade and marketing decisions on offline Excel spreadsheets that extract data from various systems and associates them with unique assumptions that often yield conflicting information from the same basic data.

This leads to suboptimal decisions and frustrated employees. This is where CPGs need more focused efforts to communicate the value of ditching spreadsheets with point-in-time analytics and drive adoption of scalable, repeatable data and analytics solutions that power insights. for life.

Test and learn: implement reproducible mechanisms

Everyone knew the mantra of “start small and scale fast”. The main problem 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 lengthy process that comes with approval of a business case.

Still, CPGs are excited about solutions like digital twins and A/B testing capabilities that could help them test and learn better and more efficiently, while finding ways to balance experimentation with value scaling.

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One table said it best: “It all comes down to creating value.” Value creation is not just about driving key performance indicators (KPIs) that balance cost optimization and benefit maximization. The value must be sustainable over the longer term.

One thing we frequently see is the inability to go from minimum viability to maximum value. While many CPGs succeed in creating minimum viable products (MVPs) by experimenting with certain functions, geographies, or brands, they fail to invest in scaling products to maximum value by creating reusability and upgradability. scale through flexible data models, integrated data structures, and the cloud. -based technologies.

—Aparna Galiasso, Head, CPG Go-to-Market Strategy & Solutions, North America, AWS


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