Tips & Tricks

Data Governance for Reliable CRM

Data Governance is a new and evolving Management Specialization that focuses on maintaining data quality and value for the modern business or enterprise. Data drives purchasing, manufacturing, operational and most importantly marketing activities for organizations. Real and usable data is now a driver of sound strategic and everyday decisions.

Good Data Governance Principles

  • Data policy

An organization should have a set of guiding principles for the proactive collection, storage, access, classification, maintenance and security of data.

Not all data generated is useful. Collection of important data could require effort. A data collection plan describes the subsets of data to be collected and the relative importance of each data element. Once data is collected guidelines should be in place to describe storage, validation, access and update procedures.

Most importantly, roles and responsibilities to ensure data integrity have to be established as a data policy. Employees with a good record of compliance are rewarded and penalties defined for non-compliance.

  • Processes for Data Quality

Each process in data governance is a set of steps that contribute to data quality, value, security and clarity of usage.

A process to rank data according to their value to the organization is an instance of a key process under data governance.

A strong communication culture is vital also to data governance. Formalized error reporting, Rewards programs for strong compliance to pre-defined policies are instances of processes for effective communication. A good data governance plan also includes specific processes for data access and data security.

  • Data quality

Ranking sources of data is a major step towards maintaining data quality through data governance. Some sources are highly reliable but may not have all the data, compelling organizations to acquire data from multiple sources. Ranking of external data sources gives the users an idea of how reliable or usable the data is.

Periodic checks and audits, constant updates, clarity of data descriptors-metadata around the data, enhance data quality.

  • Risk management

Risks to the integrity, value and security of data have to be detected in advance and proactively managed to prevent data loss, contamination and non-availability of essential data.

Potential business losses from inaccurate or incomplete data have to be documented and employees educated on such risks to motivate better compliance and contribution to policies.

  • Data management

Modern data management is facilitated by use of technology. While used of technology and software leaves an audit trail on user behaviour thereby contributing to data integrity, vendors offer built in processes and data structures for specific lines of businesses that save a lot of time and work. Data Management Software vendors optionally provide reliable data with their software that organizations can instantly use.

Assigning of external Data Stewards, using an industry standard metadata registry format and periodic data cleaning are services that a data management software vendor usually provides as added extras.

Good data is the fuel for modern business. Good data governance protects capital and ensures minimal gap between corporate strategy and implementation.

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