How Best-In-Class Companies Solve Their Product Data Challenges

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Infographic showing customer's product information being organized through Knowde's Proprietary Knowledge Engine, becoming Product Master Data in a PIM, then feeding business systems including customer website, marketplace, eCommerce, and other systems

The chemical industry is going through a digital transformation; businesses need to adapt to the changing landscape or risk stalling their growth and losing out to their competition. Best-in-class chemical, polymer, and ingredient companies recognize the importance of digital transformation in differentiating themselves from industry peers and enabling further business growth. 

Companies tackle their digital transformation initiatives in different ways, but the most successful companies all start from the same place. In order to digitally transform, they first have to solve the core problem that is holding them back from transforming: organizing and digitizing product data.

Identifying the Core Problem: Disorganized Product Data 

Companies typically feel the pain caused by poor product data more acutely downstream, which makes it challenging to diagnose the core issue. These pains include but are not limited to:

  • Discrepancies in product knowledge across regions or businesses.
  • Ineffective upselling and cross-selling due to large, complex product catalogs.
  • Poor customer website experiences — the inability to display, search, or filter product catalogs.
  • Difficulty managing documents for easy customer access.
  • Challenges felt by customers trying to evaluate products or make informed decisions based on product information.
  • Inefficiencies across multiple standalone subsidiary and/or acquired companies.
  • Manual and tedious order processes — customers cannot easily reorder or discover new products within the supplier’s product portfolio and existing customer experience relies too heavily on manual support from Sales and Support teams.
  • Lack of transparency into order status and management post sale.

All of these signals indicate a product data problem, which is the core problem that needs to be addressed first.

Image of worldwide data from different sources, including folders, PDFs, text documents, SAP, and more, over silhouettes of the United States, France, and China

Looking for more information about what product master data is? Check out this article: Product Master Data & Product Information Management 101

The Steps to Digital Transformation

A strong product master data management strategy is the foundational requirement that enables all downstream digital transformation efforts. Organizations must standardize around a unified approach to set up data governance. They must define and agree on product data modeling, data cleansing, change management, and quality assurance activities. These are critical requirements for initiatives like a customer portal or website project to ensure the quality of product data both at the time of launch but also down the road as the portfolio and information associated with it inevitably changes.

Different businesses commence this process with various degrees of readiness and alignment, and thus the exact sequence of events to transform digitally can vary company to company. But there is one priority all companies embarking on this journey must consider first — getting product data in order. Here’s how the most advanced chemical companies are thinking about this process:

Start with organizing product data as the foundation for all other digital improvements.

Digital transformation starts with getting all of your product information organized into a single source of truth. This Product Master Data (PMD) becomes your central, global repository of product information, housed within a Product Information Management (PIM) system. Organizing product data according to a standardized, best-in-class taxonomy is imperative for the complex products in our industry. Partner with an industry-specific vendor that, 1) specializes in structuring chemical product data, and 2) can get your Product Master Data into a PIM system, rather than taking this on internally or hiring consultants that lack the required skills. Find a service provider with a combination of the following characteristics: chemical domain knowledge, chemical and related products taxonomical experience, NLP/ML experience and PMD expertise.

Enable internal teams on the full product portfolio.

Make your entire product catalog easily searchable and browsable by application or technical attribute for your sales and other internal teams. This enables your internal teams to more effectively use your product catalog for sales activities and sell the full breadth of your portfolio.

Empower your customers to self-serve and find product information online.

Enhance the product discovery process for your customers, either through a customer portal, your existing website, digital marketplaces and beyond. Enable customers to search and filter based on product name, industry-specific identifiers, and selected properties in order to find detailed product information and descriptions, and allow them to download or request documents. Request management (e.g. samples, quotes, documents) can be integrated with an existing CRM to increase operational efficiency.

Connect business systems with integrations and APIs.

Product data can be shared with your key software tools, such as your CRM and ERP via integrations and APIs.

Roadmap to digital transformation includes organizing your product data, enabling your sales team to better sell, empowering your customers to find your products online, and powering your business systems with clean data.

Organizing Your Product Data is Where Your Digital Transformation Begins

Getting product data in order is the first step to any digital transformation endeavor. Best-in-class companies may have varying digital transformation strategies, but the most successful companies all start from the same place. In order to digitally transform, companies must first solve the core problem that is holding them back from transforming: organizing and digitizing product data.