To consistently ensure high data quality, you need to create a data quality culture. The key to implementing a data quality culture is to focus on the right things at the right time. Initially, it’s all about user adoption. Over time you need to understand usage trends, adopt standards, and then train on common best practices.
Consider reinforcing exceptional data quality behavior with rewards. Use disincentives to discourage poor data quality behavior. Data integrations can help gain efficiencies and increase data quality for the company. Lastly, consider automation to create even more efficiency.
Let’s discuss the process by which companies can manage data quality for their organizations using Salesforce. I recommend following this simple sequential approach when developing a data quality program.
- Standardize, Cleanse, Enrich
- Automate & Integrate
Let’s explore each of these points in more detail.
Analyzing the data is the first step in correctly managing data quality. Spend time understanding your data sources. For example, are you utilizing Salesforce’s Web-to-Lead or Web-to-Case functionality where data entry can be captured from a variety of web sources, or is the core of data entry coming from the sales organization?
Understanding your data sources will help you to understand the strengths and weaknesses of the data. Also, consider rating the data by: completeness, accuracy, validity, relevance, integrity, level or standardization, and duplication for each source. Once you establish a data rating, you can more easily identify problem areas that need attention and determine how to make improvements. Lastly, it’s important to understand your data mapping and usage from an object (e.g. Account, Contact, Opportunity) and field (e.g. City, State, Country) level, so data is not duplicated between entities.
Establishing a plan for your data quality initiatives is a crucial component for success. I recommend finding an executive sponsor that can help establish any budgetary needs and drive data quality initiatives. Also, be sure to identify owners that are accountable for certain areas of data quality. For example, sales managers might be responsible for the data quality of Account and Contact records, whereas marketing managers might be responsible for the quality of Lead records.
Once an executive sponsor and owners are established, identify and prioritize goals, such as targets and metrics for data completeness, duplication rates, bounce rates, etc. Next, define how you will measure the success of your data quality goals. Leverage Salesforce reports and dashboards to monitor and provide transparency to your goals. Create a communication plan that will inform owners of the organization’s goals and their progress towards those goals. Your communication plan should also consider the end users that are entering data into Salesforce. Consider a kick-off seminar or an email newsletter campaign to inform them of the charter, goals, metrics and incentives.
Standardize, Cleanse and Enrich
After you analyze your data and establish a plan for your data quality initiatives, you arrive at the stage that is considered the heart of data quality management. You need to take the following sequential steps to develop a system to ensure data quality throughout the Salesforce environment:
- Standardize – Find opportunities to standardize data values such as country names, postal standards, phone numbers, titles, etc.
- Cleanse – Find and replace bad or missing data, implement naming conventions, transform data, etc.
- Enrich – Consider enriching your data using Data.com or D&B to add value to your records.
- De-dupe – Eliminate duplicate record and define an on-going de-duplicate process.
- Validate – Use a sandbox environment to perform your data cleansing activities to validate your change before implementing within your production instance.
Automate & Integrate
Companies can become much more efficient on their operating expense by reducing the number of manual tasks that users need to perform. Salesforce offers out-of-the box tools, such as workflow rules and approval processes to automate your organization’s standard processes. Configuring workflow rules allows organizations to automatically send emails, create tasks, update fields and send outbound messages upon a specific action.
Configuring approval processes can also streamline your business processes. An approval process is an automated process your organization can use to approve records in Salesforce. An approval process specifies the steps necessary for a record to be approved and who must approve it at each step. A step can apply to all records included in the process, or just records that have certain attributes. An approval process also specifies the actions to take when a record is approved, rejected, recalled, or first submitted for approval.
Look to use Salesforce workflow and approval process to automate manual tasks for users. You can streamline your business processes and improve user adoption while keeping users focused on their key objectives.Integrating data from other systems into your Salesforce environment can also add value to your users since they won’t have to search multiple disparate systems. At a minimum, use custom links to tie external systems and Salesforce together to create a portal for the users. Doing so can result in your data becoming more reliable for customers when interacting with your company. When planning to integrate external systems to Salesforce, I recommend using the Salesforce External ID. An External ID is a custom field that has the “External ID” attribute, meaning that it contains unique record identifiers from a system outside of Salesforce.
There are a number of paths to integration success. Below I’ve provided some options for you to consider when looking at your Salesforce integration needs.
The Salesforce AppExchange directory is a great place to find pre-built solutions and tools for use with your Salesforce environment. Hundreds of partners with pre-packaged integration solutions are listed. Only multi-tenant architectures can deliver such a unique integration advantage.
Native Desktop Connectors
Native Desktop Connectors support rapid integration to Microsoft Outlook and Lotus Notes (who uses this anymore!?!?) for email; and Microsoft Excel and Word for integrating Salesforce data with Microsoft Office.
Native ERP Connectors
Native ERP Connectors allow salesforce.com customers to rapidly deploy the most common integration use cases for Enterprise Resource Planning (ERP) applications with SAP and Oracle.
Companies like MuleSoft’s CloudHub, SnapLogic, Boomi, Jitterbit, Tibco, and Informatica are providing certified connectors to salesforce.com to accelerate customer development of sophisticated business process integrations. Salesforce has worked with with an abundance of integration middleware vendors to develop connectors that make salesforce.com essentially plug-and-play with their solutions.
Salesforce.com provides developer toolkits to support popular development environments such as J2EE, and .NET. Customers can create highly custom integrations and leverage their development environment investments and skill-sets.
As you can see, managing and cleansing data can take a significant amount of time. It’s important to understand that maintaining data quality is an ongoing effort and your data quality will deteriorate if not maintained. As you implement these best practices, you’ll want to ensure that you maintain the data quality going forward. Follow these three best practices for maintaining data quality:
- Train & Communicate – Train your users from the beginning on naming conventions, processes and best practices to prevent duplicates. Data integrity is a collective responsibility. Share how the data will be used to create transparency and an atmosphere of collaboration. Consider organizing tests and certifications, and re-train users as needed.
- Enforce – Ensure that record ownership and sharing rules are correct, since ownership is a crucial component in preventing bad data. I also recommend putting limitations or policies on mass-importing of data to ensure imports are not corrupting your data quality. Consider developing an incentive and disincentive program to reward a high level of data quality.
- Monitor – Monitor data quality by setting up Salesforce reports and dashboards or other third party AppExchange tools. Consider setting up workflow alerts and emails to monitor data. Communicate these metrics to key stakeholders and users.
Drop a comment below to let me know if you have other tips that you have used to help with data quality in your Salesforce implementations.