Semarchy’s Andy Baillee argues that publishers and media groups need a robust, well-thought-out data management strategy. This takes time, care and investment, but getting it right will open up new opportunities that might otherwise have been missed.
At a time when digital transformation is rapidly changing traditional industries, publishers are sitting on an untapped data goldmine. But many are struggling to realize its true value.
Challenges and opportunities
A major problem is data silos, often resulting from various acquisitions and legacy business processes. A media company may have separate databases for print book sales, digital subscriptions, and marketing campaigns. Each new entity adds another layer of data, complicating the overall data landscape. When data is fragmented across multiple systems in this way, it becomes nearly impossible to get a unified view, hindering decision-making.
Outdated legacy systems also pose a significant challenge. Many of these systems are not designed to handle the volume and complexity of modern data. Add to that the challenges faced by academic publishers who must maintain vast archives while managing newly published digital content, which further complicates matters. A lack of effective data management further exacerbates these problems, leading to inconsistencies and duplication. Without high-quality, trustworthy data, business-critical reporting in areas such as finance, sales and customer behavior suffers. Updating or integrating these systems can be daunting, but is necessary for efficient data management.
In addition to these structural issues, managing complex data relationships is critical. Authors, editors, reviewers, distributors, and consumers all generate and interact with data in different ways. For example, an author’s data may span multiple manuscripts, editor comments, and peer reviews, all of which require a unified approach. Understanding these relationships requires sophisticated data modeling and management skills. Without these, efforts to improve customer satisfaction and loyalty through personalized content and recommendations are ineffective.
In addition, the increase in data collection brings with it strict privacy regulations and ethical considerations. Managing this complexity requires a well-thought-out approach to data management, especially for publishers handling sensitive academic or medical data.
On the other hand, there are enormous opportunities. Predictive modeling can anticipate future trends, optimize content strategy, and improve product monetization. Publishers can now use deep analytics to understand reader preferences, guide content creation, and develop successful marketing strategies. Investing in these capabilities can transform data from an operational obstacle into an opportunity for growth and innovation.
Practical examples
A prime example of tackling data challenges in the publishing industry is Elsevier, a global leader in scientific publishing. Elsevier has been known for prestigious journals such as The Lancet and Cell for nearly 150 years. However, with the advent of the digital age, Elsevier needed a robust data strategy to modernize its operations.
To address this problem, Elsevier worked with master data management (MDM) specialist Semarchy to create central hubs for customer and product data. Their first initiative was the Enterprise Customer Hub (ECH), designed to unify customer data across B2B and B2C channels. This unified view enabled Elsevier to gain deeper insights into customer behavior and preferences, thereby improving the customer experience. For example, understanding how students and researchers interact with Elsevier’s online platforms enabled more targeted and effective content recommendations.
Building on this success, Elsevier is currently working on an Enterprise Product Hub (EPH) to integrate its extensive catalogue of academic literature into modern digital platforms. The aim of this project is to improve the discoverability and accessibility of content, benefiting both traditional academics and modern digital learners. By consolidating data and ensuring consistency across all channels, Elsevier hopes to not only create new internal efficiencies but also ensure a seamless user experience.
Publishers pursuing a similar path to data mastery should consider the following tips:
- Create dedicated data hubs: Segmenting data into specialized hubs, such as customer, product, or financial data, optimizes governance and analytics by considering the unique requirements and semantics of each data type. This targeted approach improves agility and decision-making capabilities.
- Upgrading legacy systems: Many publishers work with legacy systems that do not meet modern data needs. Updating or integrating these systems is critical. Modern platforms offer scalability and can manage large amounts of data more efficiently.
- Establish a data management framework: Data quality is of utmost importance. Implementing a robust data management framework ensures data accuracy, consistency and reliability. Define data standards, metrics and validation processes to ensure high-quality data. This is especially important for complying with strict data privacy regulations, which are becoming increasingly important in today’s digital landscape.
- Use data analysis: Embedding data domains in data lakes and a broader data architecture facilitates comprehensive analytics. For example, predictive analytics can help anticipate future trends and optimize content strategy, leading to better product monetization and customer engagement.
- Invest in team training: The best data systems are useless if your team is unable to manage them. Regular training and interactive workshops ensure that your team can effectively handle new data management tools and practices. Skilled employees can realize the full potential of these systems.
Opening a new chapter
Mastering data isn’t just about keeping up—it’s about leading the way in publishing. Consolidating data, modernizing legacy systems, implementing robust governance, and leveraging advanced analytics are all important steps along the way.
The journey to mastering your data starts now. Turn today’s data challenges into tomorrow’s opportunities and lead your media organization into a data-driven future.
Andy Baillee
Vice President for UK and Ireland at Semarchy
Semarchy, a market leader in data integration and master data management, enables organizations to quickly generate business value from their data. The unified platform enables organizations of all sizes to quickly discover, manage, integrate and visualize critical information distributed across different applications. Semarchy is available as an on-premise solution and natively on popular cloud marketplaces such as Microsoft Azure, Amazon Web Services (AWS) and Google Cloud Platform (GCP). Semarchy is based in Phoenix, USA, with offices in London, UK, Lyon, France and Mexico City, Mexico.
