Lori Schafer in Chain Drug Review: How Pharma and OTC Brands Can Power Profits Through Precise, Unified Data

Read the original article in Chain Drug Review (page 31) here.

Pharmaceutical and over-the-counter products launch under intense scrutiny. Retail merchandising, brand sales and marketing teams must navigate complex federal regulations, pricing fluctuations and competitive private label offerings. These products face razor-thin margins and operational hurdles — from managing fast-moving inventory to preparing dense product information for omnichannel supply chains.

To ease the burden, pharma and O-T-C retailers and brands are increasingly turning to AI and GenAI to simplify the management of complex data and workflows. Much like traditional retail and consumer packaged goods companies, pharma brands can now tap into AI-driven solutions across the entire value chain. For example, a McKinsey study of CPG leaders found that 71% of surveyed companies had adopted AI in at least one business function, and 56% reported regular use of GenAI.

However, to enhance AI capabilities, the real challenge lies in centralizing, standardizing and managing the vast streams of data that flow through these organizations. Creating unified, streamlined data systems is the foundation that unlocks new efficiencies, speeds up operations, and opens new avenues for growth and profitability.

Navigating regulations and competition

Before reaping the benefits of AI and unified data, pharmaceutical and O-T-C companies must contend with unique challenges — chief among them, regulation, including:

• Drug Supply Chain Security Act (DSCSA): This regulation mandates secure monitoring of prescription drugs throughout the supply chain. The act helps prevent counterfeit or stolen drugs from entering the U.S. market by requiring highly serialized, accurate and compliant data from supplier to distributor to retailer.

• Federal Food, Drug, and Cosmetic Act (FFDCA): Enforced by the FDA, this law regulates how O-T-C drugs are marketed and mandates detailed product information — including ingredients, dosage, usage and instructions. Brands must ensure that all this information is consistently updated on packaging and across systems — a complex and time-consuming task.

Compounding these regulatory pressures is fierce competition from private label brands. As private labels sharpen their focus on health and wellness, launching more polished branding and innovative products, O-T-C and pharmaceutical private labels often still face a stigma as “generic” knockoffs. Meanwhile, challenges from pharmacy benefit managers, complex pricing models and evolving consumer expectations continue to shrink margins and complicate decision making.

Retail analytics, product content management and demand forecasting tools aim to help organizations stay competitive by improving how they manage data, product information and pricing strategy across the supply chain.

Unified data powers smarter growth

Drug brands and retailers that successfully integrate AI and GenAI into their operations must first rely on a single, cohesive stream of cleansed, unified data — one source of truth for internal and external teams. Unified data can then be used in any number of applications, from demand forecasting and order management to allocation and price optimization, with the assurance that the data is accurate and up to date. Embedding AI and GenAI capabilities into that data infrastructure enables real-time insights, faster decision making and improved collaboration.

With unified data, brands can:

• Ensure regulatory compliance: Centralized data enables AI to apply consistent regulatory standards across both online and in-store content. Natural language processing can scan product descriptions, labels and marketing assets to flag noncompliance and reduce legal risk.

• Forecast and respond to demand: For example, an O-T-C brand anticipating a spike in allergy medicine demand can integrate regional weather forecasts with sales and inventory data. AI models then recommend optimal stock levels, adjusting in real time across e-commerce and retail channels.

• Syndicate consistent product information: Managing and distributing accurate product content is a major lift — especially for prescription medications. AI-enabled unified master data systems can clean, extract, and syndicate product information efficiently across sales platforms, ensuring health care providers and patients have access to consistent, up-to-date information.

Implementing a unified data foundation with native AI and GenAI prepares drug brands and retailers for a more agile and profitable future. GenAI can create personalized promotions and marketing campaigns, while AI ensures regulatory updates and inventory changes are quickly reflected in internal systems and customer-facing channels.

Precision data is the future

Traditional processes, relying on manual-based entry of product information or using disconnected solutions, are no longer sustainable in the fast-paced world of pharma and O-T-C retail. Clean, accurate data is essential to help brands and retailers make the best possible decisions with speed and precision, as they react to constantly changing conditions. Brands that embrace AI and unified data will gain full visibility into product performance, compliance status and consumer trends — all in real time.

These capabilities support a stronger omnichannel experience for customers while easing the burden on retailer and health care system partners. In a world of increasing scrutiny, unified and precise data can help pharmaceutical retailers and brands deliver better outcomes for consumers — and better margins for the business.

Lori Schafer serves as chief executive officer of Digital Wave ­Technology.