A range of operations data — including customer, pricing, inventory, performance, and products — is essential in ensuring the efficiency of any supply chain-powered business.
Functional areas including marketing, finance, engineering, and distribution use that data daily to make the right decisions at the right time and deliver the right products to the right place on time.
But what happens when essential data can’t be shared, or critical data is unavailable to meet business needs?
Meeting Real-time Business Requirements
With companies moving applications and data to the cloud amid accelerating AI adoption, data portability is a top business technology priority. Business and technology leaders are also susceptible to compliance risks that can negatively impact business performance. Without the proper strategy and governance processes to share and move data, companies risk using incomplete, inaccurate, and untrusted data to run their businesses.
Data portability enables companies and users to access and apply their data across different services and systems without being limited to closed, incompatible platforms. It allows companies to move their data from one environment to another safely and securely without affecting its usability.
From a customer standpoint, data portability enables individuals to control and gain transparency into how their personal data is used and processed. The General Data Protection Regulation (GDPR), enacted by the European Union in 2018, emphasizes individual user control, elevating data portability’s importance for businesses.
Essential Elements of an Effective Data Portability Strategy
Data portability is enabled through a rigorous enterprise data strategy and management framework that ensures your data can be shared and moved securely across departments, systems, and processes for authorized staff and resources to access it. Without data portability, data value is diminished, confidence is suspect, and business operations are inefficient.
The essential business data components to have in place to support data portability include:
- Documented Enterprise Data Strategy (EDS): An enterprise data strategy is an all-encompassing plan that outlines how your organization will manage and use data to meet its business goals. It includes policies, processes, and technologies for data management, security, storage, and permissions. To achieve data portability, your EDS must include data observability and tracking to control and understand data sources.
- Data unification capabilities: This is a more extensive process, combining data from disparate sources to create a unified view. It’s about cleansing and normalizing data, creating unique identifiers for each entity, and identifying and merging duplicates into trustworthy entities. Unification is required before data portability can be confidently executed.
- Enterprise Data Management (EDM) framework: This is a strategic process for managing your organization’s data, including acquisition, integration, and retrieval. A robust EDM requires well-defined documents and processes for sharing and handling data.
- Data classification and segmentation standards: Data classification is the process of categorizing data based on its sensitivity, importance, and regulatory requirements. When data is moved between systems, this process identifies and tags data types to ensure proper use and that the correct data gets to the right place for the appropriate application.
- Data governance, security, and privacy policies: Often part of your EDM strategy, data governance involves managing the availability, usability, and protection of the data in your systems. You can’t execute data portability without clear, documented policies and processes that comply with industry privacy regulations and security controls.
- Data culture and talent resources: Data portability relies on structured, trusted systems and processes. This starts with having the right pros in the room to define, monitor, and audit data activities. This group comprises business functions including IT, finance, legal, executive leaders, and data professionals.
Potential Risks and Errors
Even with a robust enterprise data strategy and framework, you must account for three common missteps when executing data portability across your business.
One of the nagging challenges with achieving data portability is stringent data auditing. With data portability, you must meticulously monitor for consistency. Anomalies are inconsistencies in data points or abnormal data behavior compared to the rest of the data set. The cause of anomalies can be intentional, such as data silos, or unintentional, including flawed data collection or input errors.
Another common challenge is data hoarding. Specific groups, departments, or staff members often store and use data from sanctioned company systems and processes. All data and functions must participate because the same data is used for sales, pricing, supply chain, and business analytics. Data portability requires all data to be accessed and managed to achieve optimal performance and ensure regulatory and privacy compliance.
A final oversight to watch for is data from sources outside your company. Purchased data lists, shared partner data, and even data from sister companies are often pushed into databases and used in vital business operations. Data portability requires controls and processes for bringing outside data and moving data from these third-party sources into core systems.
Final Thoughts
Data portability is non-negotiable in today’s real-time enterprise. It empowers your team and business to gain insights faster, operate more efficiently, and personalize customer experiences. Without an enterprise data strategy that includes data portability requirements, processes, and policies, you create unnecessary risk and limit business performance and potential.
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