Integration is the process of connecting at least two applications or systems running on common or different platforms. Integrating two systems lets them talk to each other and share data. You cannot sync data or move data between different systems without integration. The sharing of data is one of many benefits of Salesforce integration.
Integration is a high priority for many organizations for a good reason. It gets results faster and increases productivity. As an example, integrating QuickBooks with Salesforce makes it possible for both systems to share customer account information, customer sales, sales opportunities, and financial data.
Experience and current best practices recommend three main considerations for every Salesforce integration project:
1. Document what and how often information needs to move between systems
Take the time to map out what data needs to move from one system into another. After identifying the data to sync, determine which direction the data needs to move and the how often.
2. Review API limits
Like Salesforce, some external systems have an API that places limits on the amount of data it can transfer in a 24-hour period. Be prepared for these restrictions by documenting the limits for all systems involved in the integration.
3. Identify the type of integration involved: Real-time or batch
Real-time integration happens as soon as a record is created or updated. Batch integration occurs at intervals, which are not immediate. Every integration project must identify and document the type of integration required to ensure the best outcomes.
Although these are the most important considerations in an integration project, a successful integration depends on many factors related to the individual systems and the integration objectives.
The success of a Salesforce data integration project depends on transferring clean, accurate data. Here are the most common Salesforce data integration mistakes to avoid. In preventing these mistakes, you will increase the project's success rate.
1. Starting without a clear scope.
A project will fail when an organization doesn't develop collaborative goals that identify specific business process needs. To prevent this, document expected outcomes before the project begins. This is also the time to identify what other applications to integrate and which business processes they affect.
2. Failing to document systems of record.
At the start of the project, everyone needs to be clear on which system will store the master records. If any data mismatch occurs, the set system of record will make the call for correct data. Knowing this early on helps in the setup of data validation rules when integrating.
3. Propagating bad data.
It is essential to clean and remove obsolete or bad data prior to integrating. When needless outdated records move from one system to another, it leads to data integrity and duplication problems in multiple systems.
4. Discounting how real-time integration works.
Many people incorrectly assume that importing and exporting data from Salesforce is the same thing as integrating in real-time. In reality, exporting data files in batches provides only a snapshot of information at a moment in time. Regardless how often data is imported and exported as files, some applications will not be in sync with real-time changes. Understanding this reality will help ensure data is accurate and consistent.
5. Lacking a data management strategy.
It is critical to address data validation and quality issues at the start of a Salesforce integration project. The plan includes a strategy on how to handle data management issues. Examples of such issues: whether to merge or reject duplicate records and how to properly map data fields for type of record conflicts and custom fields.
6. Overlooking data rate limits.
Integrators tend to be unaware of Salesforce's data import limits. For example, business accounts and contacts owned by a company can be imported 500 at a time. On the other hand, the limit is 50,000 at a time for business accounts and contacts owned by different users. Since there is no work-around, planning for such limits will avoid run-time errors from occurring during the integration process.
7. Omitting quality assurance and user acceptance testing.
Integration projects often fail because the team does not pay attention to testing as much as to the implementation itself. During quality assurance testing, the IT team's purpose is to validate that errors are handled correctly. Business users perform user acceptance testing to verify that correct information moves into the right places.
Now that you know what to consider and what to avoid, you can move forward with your Salesforce integration project. The process contains three major phases.
1. Pre-planning
Define the goals of the integration. This will be the driving force for all conversations and decisions, including selecting a project lead. With goals defined and a project lead selected, identify where the data originates (the root source) and where it needs to go. Designate how often the data should sync between the two systems. Determine the protocol for dealing with issues that arise after integration goes live.
2. Decision-making
Schedule a kick-off call with the right people to review the information gathered during pre-planning. Give participants the opportunity to express concerns and provide recommendations. During this phase, research development costs and ask how software updates and upgrades may affect integration.
3. Execution
By this point, you have a plan that incorporates all considerations and prevents common mistakes. Move forward to verify integration with all affected systems and users. Document test scenarios to use in a sandbox-like environment. Have all parties complete their testing. Once done, execute the integration in production and address problems by following the protocols created during pre-planning.
Organizations that address all of the considerations and dodge the common mistakes boost their chances of Salesforce integration success. A well-planned integration saves time and money and reduces errors. Furthermore, data will be clean and transfer properly.
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