Building a Successful Salesforce Data Governance Strategy

Data governance is a critical aspect of using Salesforce, ensuring that its data is managed and used in a secure, compliant, and effective manner. In this article, we will explore several best practices for implementing a robust Salesforce data governance framework within your organization. By following these best practices, you can help to ensure that your organization’s Salesforce data is managed and used in a way that maximizes its value while minimizing risk.

Establish clear ownership and roles for data management and governance within your organization

Clear ownership and roles for data management and governance mean that specific individuals or teams are responsible for defining, implementing, and enforcing data policies and procedures. These roles may include data stewards, data owners, data custodians, and data governance committees, depending on the size and complexity of your organization.

To establish clear ownership and roles for data management and governance, you should start by defining your organization’s data governance structure and assigning specific roles and responsibilities to relevant individuals or teams. You should also ensure that these roles are clearly communicated and understood across the organization, including training and support where necessary. This can help to create a culture of data responsibility, where everyone understands their role in managing and governing data effectively.

Develop and enforce data quality standards to ensure consistency and accuracy of data across your organization

The first step towards developing and enforcing data quality standards is to define the standard. A data quality standard should include guidelines for data entry, data formatting, data validation, data normalization, and data storage. The standard should also include guidelines for data cleansing, data integration, and data archiving. The standard should be easily understandable, accessible, and agreed upon by all stakeholders, including executives, data owners, and users.

The next step is to implement the data quality standard. The implementation process involves ensuring that all data sources conform to the defined standard. Organizations can use data quality tools to automate this process, but it is important to ensure that the data quality tools are configured to meet the organization’s unique requirements. Implementing the data quality standard requires a holistic approach and should include all data sources, including internal and external data sources.

Data quality monitoring is an important step in enforcing data quality standards. Organizations should monitor the quality of their data on an ongoing basis to ensure that it continues to meet the defined standard. Data quality monitoring can be done using automated tools, such as Salesforce’s Data.com Clean, or through manual checks. Monitoring should be done at different stages of data processing, such as data entry, data integration, and data analysis.

Implement a data retention policy to manage the lifecycle of your data and comply with regulatory requirements

First and foremost, implementing a data retention policy is critical for compliance with regulatory requirements. Many industries are subject to laws and regulations that govern the storage and handling of data. Failure to comply with these regulations can result in hefty fines and other legal consequences. By implementing a data retention policy, organizations can ensure that they are meeting regulatory requirements and avoiding legal risks.

A data retention policy can also help organizations manage the lifecycle of their data more effectively. By setting clear guidelines for when data should be deleted, companies can avoid holding onto unnecessary data, which can be costly and time-consuming to manage. A well-designed data retention policy can also help organizations prioritize which data is most important to their business and ensure that it is properly secured and managed throughout its lifecycle.

So, how can organizations go about implementing a data retention policy? The first step is to assess the types of data they collect and how it is used. This includes identifying sensitive or confidential data and understanding any regulatory requirements that may apply to that data. Based on this assessment, organizations can determine how long each type of data should be stored and when it should be deleted.

Next, organizations should develop a clear and concise data retention policy that outlines these guidelines. The policy should be communicated to all employees who handle data, and regular training should be provided to ensure that everyone understands their role in complying with the policy. It’s also important to regularly review and update the policy as needed to ensure that it remains current and effective.

Use Salesforce’s native data security features

Sharing rules are a powerful tool for controlling access to data within Salesforce. By default, all records are visible to all users within an organization, but sharing rules enable administrators to define specific criteria that limit access to particular records. For example, you might create a sharing rule that only allows sales reps to view the records of the accounts they are assigned to, while limiting access to sensitive financial data to specific finance team members. Sharing rules can be configured based on a wide range of criteria, including record ownership, geography, and other custom fields.

Field-level security is another important feature of Salesforce’s data security framework. This feature enables administrators to restrict access to specific fields within a record. For example, you might use field-level security to ensure that only authorized personnel can view sensitive financial information within a customer record. Field-level security can be configured for both standard and custom fields, and can be used in combination with sharing rules to provide a granular level of access control.

It’s important to remember that security is an ongoing process, not a one-time configuration. Regularly review your sharing rules and field-level security settings to ensure they remain aligned with your organization’s access requirements. And as your organization’s data access requirements evolve, be prepared to make adjustments to your security settings accordingly.

Set up an audit trail to track changes to your data and identify potential security or compliance risks

An audit trail is a record of every change made to a particular data record, including who made the change, what the change was, and when it occurred. In Salesforce, you can set up an audit trail by enabling the “Field History Tracking” feature for specific objects, which will then track changes made to those objects.

Once you’ve set up your audit trail, it’s important to regularly monitor it for any unusual or suspicious activity. This can include looking for changes made outside of normal business hours, changes made by users who don’t typically work with the object in question, or changes made to sensitive data fields. By monitoring the audit trail, you can quickly identify any potential security or compliance risks and take action to mitigate them.

It’s also essential to have a clear process in place for addressing any issues identified through the audit trail. This might involve communicating with users who made the changes to clarify their intentions, revoking access to specific data fields for certain users, or taking other steps to address security or compliance concerns.

Use data encryption to protect sensitive data

In Salesforce, you can encrypt sensitive data using platform encryption. With platform encryption, you can encrypt data at rest without compromising the ability to search, report, or analyze it. Salesforce supports a variety of encryption methods, including AES-256, which is a widely accepted industry standard. When you use platform encryption, the encryption keys are managed by Salesforce, and you have full control over who can access the data. You can also choose which fields to encrypt, which provides an additional layer of protection.

Train your employees

The training program should be tailored to the needs of each department and role within the organization. For example, sales and marketing teams may require training on data segmentation and lead scoring, while the IT department may require training on data security and compliance. The training should be provided in a variety of formats, including webinars, in-person sessions, and self-paced e-learning modules.

It is important to make the training program engaging and interesting for employees. Using real-world examples and scenarios can help to illustrate the importance of data governance and how it impacts the organization as a whole. Additionally, including interactive elements, such as quizzes and role-playing exercises, can help to reinforce key concepts and ensure employees are retaining the information.

Ongoing education and training should also be a priority. As new tools and processes are introduced, it is important to provide training on these changes to ensure that employees are using them in a way that is compliant with data governance policies. Regular refresher courses can also help to reinforce key concepts and ensure that employees are up-to-date on the latest best practices.