From chaos to insights: Digital transformation trends for CPG

Transforming disconnected data into actionable intelligence

Despite increased investment in digital technology, many consumer packaged goods companies still operate with disorganized and disconnected product data. Learn how organizations that make the leap to transform their data strategy can improve margins and increase collaboration across the CPG supply chain.

Digital transformation for CPG: Why now?

Consider a $3B+ organization with more than 30,000 products, using 100 percent manual, paper-based data management. Does this sound alarming?

It should. Unfortunately, this is more common than not within the consumer packaged goods (CPG) industry.

On average, CPG companies have reported an 8 percent increase in technology budgets over the past three years, indicating an increase in digital technology investments. However, many of these companies are missing a cohesive data management strategy: a component critical to supporting digital technology investments. With the lack of attention to the digital transformation trends for CPG, insightful results often can’t be developed, and the promised benefits of going digital can diminish.

Digital transformation trends for CPG

How should organizations focus their efforts and ensure they are taking the right steps to achieve improved returns on their digital transformation investments?

  • Develop a data strategy and governance program across enterprise initiatives and make data a mandatory first step towards any transformation program
  • Invest in data transformation tools to aggregate, digitize, and enrich and derive insights from unstructured data for prioritized business use cases

To build a strong foundation for digital transformation and enablement, companies should follow these steps.

As an outcome from companies focusing efforts and investments on improving product data, significant R&D and CPG supply chain benefits can be realized,2 including:

  • Achieving end-to-end visibility to core product information
  • Accelerating product time to market
  • Reducing cost of quality metrics due to reliable data (e.g scrap, rework, and recalls)
  • Reducing compliance, regulatory, and quality risk
  • Minimizing new product development and direct material costs
  • Increasing internal product development resource capacity

CPG digital transformation trails other industries

Most CPG organizations are thinking about digital transformation, but they may not grasp the totality of steps necessary to act. The ability to manage product data is a key component in driving digital adaptation within any industry.

CPG companies today are still lagging in the stages of “passively digital” and “exploring digital,” but may already have enterprise-wide strategies and goals to “becoming digital.” A major deterrent to executing faster digital transformations and reaping maximum benefits in “becoming digital” can be an organization's lack of data management capabilities that would deliver strong product data quality and accuracy.

Organizations that attempt “being digital” will have connected enterprise systems, defined data governance and charter, and cognitive tools to automate processes as well as  analytics to provide insights across the value chain. It will in turn help realize the benefits promised from further digital technology investments.

Steps to begin transforming data into insights

Data management and transformation begins with a data readiness program that assesses your unstructured data across the enterprise and identifies business value opportunities.

Transforming chaotic data and gaining insight

  • Aggregate unstructured data into a staging database, where the data can be classified, cleansed, and enriched. Additionally, data de-duplication, nomenclature standardization, and data tokenization in the extraction layer supports multiple efforts in analytics and digital thread enablement 
  • Move data to a single source of truth, where it can be made searchable, accessible, and available for analysis to drive insights
  • Utilize analytical tools to derive insights that can lead to cost reduction, higher product quality, increased profitability, and the ability to accelerate product delivery

Enabling the transformation from data to insights

Cognitive and analytics tools are critical to any data management strategy, as they provide insights from usable product data. These tools accelerate the digitization of unstructured data alongside data enrichment leveraging "supervised learning" algorithms. Post digitization, these tools can then provide critical metrics around product data, such as the percentage specification re-use, percentage technically equivalent materials, amount of recycled packaging components in a product, and many others.

In addition, supplementary insights can be derived from the newly digitized, enriched, and harmonized data. The data is merged with supplier, procurement, and third-party benchmark data to clearly identify cost and complexity reduction opportunities across the enterprise. For instance, when combining this digitized product data with procurement data, significant material cost savings opportunities can be identified. Improved bill of materials (BOM) data quality can also lead to better demand planning and forecasting.

Moving forward with digital transformation trends for CPG

CPG industry is slightly behind compared to other industries in terms of deriving insights from product data and leveraging it to bring innovative products to market faster. To achieve maximum benefits of "becoming digital," organizations should attain senior leadership commitment to begin investing in product data transformation enablers. Manual data management and processes without governance and high-quality data can be expensive and inaccurate.

Once companies take these first steps to build a strong data foundation, they are well prepared to invest in network technologies to drive an End to End digital transformation. Enabling accurate product data by creating a single source of truth, integrating systems, and designing complementary business processes, frees up internal resources to focus on enterprise innovation and growth.

Potential next steps:

  • Develop a data strategy and governance program across enterprise initiatives and make data a mandatory first step toward any transformation program
  • Invest in solutions with improved digital technologies for prioritized business use cases along with the larger transformation programs
  • Receive senior leadership commitment to take individual business units into the future with insightful data

Taking such measures will help companies avoid falling short of their industry competitors over the next 2-4 years.


1 Ellen Eichhorn and Stephen Smith, “2019 CIO Agenda: Consumer Goods in a Climate of Change,” Gartner, June 22, 2018.
2 Based on Deloitte’s own consultative experience of working with clients on product life cycle management assessments and implementations.

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