Integration unlocks scalability that businesses are unable to accomplish otherwise. For the everyday user, it also translates to less manual data entry and more productivity. It’s for these reasons and more that businesses see software integration as a logical step towards growth and innovation. However, like any investment, integration comes with innate costs.
The cost of integration differs based on a multitude of factors. For example, if you’re integrating a legacy system with limited API access, you must reconstruct that program’s business logic to make the connection. This takes time and testing, and it inevitably drives up costs. On the other hand, the standard integration of cloud services doesn’t require many bells and whistles and would therefore be less expensive.
Integration costs aren't always black and white. Avoid any surprises on the price of your integration by being aware of all possible cost drivers. Here are some of the biggest factors that can drive up the cost of integration.
#1 The complexity of your transformations and mappings
Mapping data from the source to the target system can become complex depending on the types of transformations needed. These types of projects require specialized skills and custom coding that can drive up the baseline cost of your integration project. For example, healthcare providers with Electronic Health Records (EHR) systems use specific clinical terminologies and coding systems like SNOMED CT and ICT-10 in their EHR system. Mapping these terminologies to a solution like CRM would be more complicated than mapping something like CRM and a patient portal. The patient portal may require a few custom fields, but the data transformations are far less complicated.
#2 Real-time vs. Batch processing
Real-time data processing is when the integrated data is updated as soon as new information is available. This processing frequency is useful in scenarios where up-to-date information is crucial to decision-making and analytics. For example, fraud detection, supply chain visibility, and traffic management are all areas where real-time data processing is essential. Not every business use case requires real-time data processing for integration.
Batch processing is when data is updated at intervals defined by the integration. For example, data may be updated each hour or at the end of each day. Real-time data integration takes more time to set up and execute than batch processing, and it requires more resources to maintain. Therefore, real-time data integration is often quoted higher than batch processing.
#3 Data quality and cleanliness
Every integration project requires clean, organized data. Without it, the project will not yield the desired results. Poor data quality can significantly increase integration costs because making the data usable for the integration is a labor-intensive process. Many integrators offer data cleansing services to prepare you for integration but be advised that this is an added cost.
#4 Data compliance requirements
Compliance and data privacy regulations may require additional security measures and auditing when integrating data. Ensuring the data integration processes compy with these requirements can add complexity and cost to the project.
Integration processes may require regular auditing and reporting documentation. Data retention and deletion policies may affect how the integration uses data and for how long. In addition, certain regulations mandate where data can be stored and processed. This can influence the choice of data integration tools, which can potentially increase costs as well. If you know you are subject to strict compliance, make sure to present this information to potential integrators up front so they can factor in those strategies and costs.
#5 Third-party costs
Your integration provider will charge a fee, of course. But what other fees should you think about? Some third-party vendors offer subscription-based APIs that allow organizations to access specific data or services on an ongoing basis, typically subject to usage fees. If your project requires custom connectors, the cost to develop those will drive up your integration costs. Data cleaning and enrichment from a third-party can add costs, too.
#6 Storage and security
Storing integrated data in the cloud can become very expensive very quickly. That’s why it’s so important to be discriminating about which data fields you want mapped and how much data you think is necessary to pass between your systems. The volume of data and retention policies can impact your expenses and should be considered. In addition, if you require custom encryption or access controls for your integrated data, that will also drive your costs higher.
The ROI of integration is unmistakable. The ability to scale, collaborate between departments, increase the potency of your analytics, and make better business decisions will ultimately improve your bottom line. The key is to integrate thoughtfully and budget realistically for what you are trying to accomplish. By keeping these cost drivers in mind and communicating any concerns with your integration provider early on, you can execute a successful and cost-effective integration project.
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