Semarchy’s Andy Baillie argues that publishers and media groups need a robust, well-thought out data management strategy. It demands time, care and investment, but getting it right opens new opportunities that otherwise might have been missed.
In an era where digital transformation is rapidly reshaping traditional industries, publishing companies are sitting on an untapped goldmine of data. Yet, many struggle to extract its true value.
Challenges and opportunities
One big issue is data silos, often resulting from various acquisitions and legacy business operations. A media company might 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 like this, gaining a unified view becomes nearly impossible, hindering decision-making.
Outdated legacy systems also pose a considerable challenge. Many of these systems were not designed to handle the volume and complexity of modern data. Add this to the challenges faced by academic publishers, maintaining massive archives while also managing newly published digital content, things become more complicated. A lack of effective data governance further exacerbates these issues, leading to inconsistencies and duplications. Without high-quality, trustworthy data, business-critical reporting on areas like finance, sales, and customer behaviour suffers. Upgrading 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 crucial. Authors, editors, reviewers, distributors, and consumers all generate and interact with data in different ways. For instance, an author’s data may span multiple manuscripts, editor comments, and peer reviews, all requiring a unified approach. Understanding these relationships requires sophisticated data modelling and management skills. Without this, efforts to improve customer satisfaction and loyalty through personalised content and recommendations fall flat.
Moreover, the surge in data collection brings about stringent privacy regulations and ethical considerations. Navigating these complexities requires a well-thought-out approach to data management, particularly for publishers handling sensitive academic or medical data.
On the other hand, the opportunities are vast. Predictive modelling can anticipate future trends, optimise content strategy, and improve product monetisation. Publishers can now use deep analytics to understand reader preferences, guide content creation, and develop winning marketing strategies. Investing in these capabilities can turn data from an operational obstacle into an opportunity for growth and innovation.
Real world examples
A prime example of overcoming data challenges in the publishing industry is Elsevier, a global leader in academic publishing. For nearly 150 years, Elsevier has been renowned for prestigious journals like The Lancet and Cell. However, as the digital age gained momentum, Elsevier needed a robust data strategy to modernise its operations.
To tackle this, Elsevier partnered with Master Data Management (MDM) specialists, Semarchy, to create centralised 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 single view enabled Elsevier to gain deeper insights into customer behaviours and preferences, thereby enhancing the customer experience. For example, understanding how students and researchers interact with Elsevier’s online platforms allowed for 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 with modern digital platforms. This project seeks to improve content discoverability and accessibility, benefiting both traditional scholars and contemporary digital learners. By consolidating data and ensuring consistency across channels, Elsevier hopes to not only create new internal efficiencies but also ensure a seamless user experience.
Publishing companies looking to go on a similar journey of data mastery should consider the following tips:
- Create dedicated data hubs: Segmenting data into specialised hubs, such as customer, product, or financial data, optimises governance and analytics by addressing unique requirements and semantics of each data type. This targeted approach enhances agility and decision-making capabilities.
- Upgrade legacy systems: Many publishing companies operate on outdated systems that can’t handle modern data needs. Upgrading or integrating these systems is crucial. Modern platforms offer scalability and can manage large volumes of data more efficiently.
- Establish a data governance framework: Data quality is paramount. Implementing a robust data governance framework ensures data accuracy, consistency, and reliability. Define data standards, metrics, and validation processes to maintain high-quality data. This is particularly important for compliance with stringent data privacy regulations, which are increasingly crucial in today’s digital landscape.
- Leverage data analytics: Embedding data domains within data lakes and a broader data architecture facilitates comprehensive analytics. For instance, predictive analytics can help anticipate future trends and help optimise content strategy, leading to better product monetisation and customer engagement.
- Invest in team training: The best data systems are useless if your team isn’t equipped to manage them. Regular training and interactive workshops ensure your team can handle new data management tools and practices effectively. Skilled employees can leverage these systems to their full potential.
Turning a new page
Mastering data isn’t just about keeping up – it’s about leading the way in publishing. Embracing data consolidation, modernising legacy systems, putting in place robust governance, and leveraging advanced analytics are key steps in this journey.
The journey to mastering your data starts now. Turn today’s data challenges into tomorrow’s opportunities and guide your media business into a data-driven future.
Andy Baillie
VP of UK and Ireland at Semarchy
Semarchy, a leader in the data integration and master data management markets, enables organizations to rapidly generate business value from their data. Its unified platform enables organizations of any size to quickly discover, govern, manage, integrate, and visualize critical information scattered across applications. Semarchy is available as an on-prem solution and is natively available 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.
