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5 Ways Data Governance Speeds New Production Introduction

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Agility and flexibility are key attributes for successful consumer packaged goods (CPG) companies. Being first to market or a fast follower that quickly responds to changing consumer tastes and preferences can make or break a new product.  Hitting that window of opportunity with the right product is what the new product introduction (NPI) process is designed to do. Data drives this process, and proper data governance improves the communication, coordination, and decision making resulting in a more agile organization and an accelerated new product introduction. 

Beginning with the product formula in the product development phase, data is collected and shared across the organization, spanning multiple process steps and handoffs.  Accurate and timely data is the fuel that drives the process and if at any point there is missing, incorrect, or misunderstood information the result is either expensive and time-consuming rework, or excessive wait times causing missed deadlines.  Data governance helps minimize these risks by applying more rigorous standards and practices that ensure accuracy and proper context for each data point.

Context is important for new products in the CPG industry due to the downstream dependencies for packaging and production driven by the mix of product ingredients. It can get complicated, as the NPI process typically includes suppliers, channel partners, customers and services vendors such as marketing or promotion companies, as well as the broader product lifecycle that includes all factors of production such as people, process, systems, and data.

So, how can better data governance help keep the NPI process running smoothly? 

5 Ways to Keep the NPI Process Running Smoothly

  1. Pre-emptively address dependencies. Here are a few dependencies you should look out for: regulatory concerns, patent/trademark searches, sourcing alternatives, and production constraints.  Throughout the new product introduction process, codify why you should govern data, what data you should govern and how it should be governed. This will drive consistency and clear understanding of business objectives, metrics, and well-defined processes.
  2. Create a product that can be tested and validated by real customers with their feedback incorporated into the development process. This requires good stewardship of data that ensures standards and rules are established and diligently followed resulting in consistent capture and comparison of market test data.
  3. Understand and communicate various branding and packaging requirements. Metadata management helps your organization speak a common language by keeping up-to-date glossaries, catalogs, and dictionaries.  These can provide updated information, based on regional requirements, for local or regional branding changes.  They also can provide updated regulatory requirements.
  4. Quickly capture market feedback and communicate to the product team in a consistent manner. Using all the data governance tools in your toolbox, you eliminate inconsistency and ambiguity caused by vague or ill-defined terminology and create greater trust in your data.
  5. Coordinate go/no-go decisions. Effective data management and governance supports the tight orchestration of activities and aggregation of key product introduction metrics used to make timely, smart decisions.

CPG firms that use data as a differentiator in their product development and introduction process can achieve greater speed-to-market and more customer-focused products that get traction and market acceptance. The key is using proper data governance and a comprehensive master data management approach that delivers the right data resulting in smarter decisions at critical points throughout the product lifecycle.

For more information on data governance for CPG companies, you can check out our white paper: Leverage Data Governance to Drive Speed and Flexibility in New Product Introduction.  This paper focuses on new product introduction challenges created by the trend towards greater transparency in labeling.  The paper also explores how effective data management and governance can support the coordination of activities required to impact key product lifecycle management metrics that drive speed and flexibility in the NPI process.

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Steve Russ

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