In today’s business landscape, every company must embrace technology to stay competitive. This means having a strong digital product lifecycle management (PLM) strategy in place. PLM streamlines product processes from ideation to development to market launch to maintenance, ensuring a seamless customer experience. The foundation of a successful PLM strategy lies in organized and managed product data, which is often a challenge for enterprises. To leverage technologies like AI for innovation, businesses need to prioritize data organization and management.
Gartner reports that 80% of organizations struggle to scale digital businesses due to outdated governance processes. Data is a valuable asset that must be properly organized, standardized, and governed to provide value. Investing in data governance upfront is essential, as it can be costly and time-consuming to fix disorganized data assets later on. Data governance programs should focus on security, organization, compliance, and prevention of data leaks.
Challenges of Data Governance in Product-Centric Organizations
1. Acquisitions and Mergers
When companies acquire or merge with others, mismatched data models can lead to operational inefficiencies. It’s crucial to align data models and governance practices to avoid manual data remediation in the future.
2. Siloed Business Units
In organizations where different teams manage their own data, silos can lead to data duplication, inconsistencies, and inefficiencies. Connecting data across business units is key to enabling unified product management and informed decision-making.
Strategies for Success in the Digital Landscape
To succeed in today’s data-driven world, organizations must implement PLM processes, adopt a unified data approach, and strengthen data governance. These initiatives not only mitigate risks but also unlock the potential of AI technologies. Prioritizing these solutions empowers businesses to leverage data for innovation and competitive advantage.
Discover how IBM can assist you in implementing effective data management solutions.
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