With 90% of businesses already using the cloud and the Internet of Things getting bigger every day, the future of how we utilize data is uncertain, but important. When applications and programs share data, or essentially talk to each other through integration, there’s less room for human error in translation, and increased efficiency can be achieved. But, with all this potential for growth comes a downside of vulnerability. Although integration with the smart devices and IoT around us all is necessary to move your business forward, knowing the risks of the process can ensure sensitive data’s safety both during and after integration—a crucial step towards protecting your company’s integrity and your bottom line.
Defining Terms Before Data Integration
Before a data integration, one of the main risks to assess is how your definition of key terms might not match up on the other side. For example, when integrating the data from an insurance application with your new HR software, you’ll likely be dealing with terms like policy and benefit. But what if what’s sometimes called a policy in one system is called a benefit in the other? Chaos will result. If terms like these aren’t properly defined beforehand, easily-avoided errors could only become obvious after the damage is done. For example, part of the allegations made by now-bankrupt tech company Ciber against the Washington State Board for Community & Technical Colleges was that the state’s inability to integrate data was part of the reason Ciber’s fully-developed software solution was never tested, implemented, or paid for.
Best Practices for Formatting Data during Integration
Although it seems simple, the level of detail required for a data integration can obviously cripple the unprepared. When merging two systems, you have to ensure that the data of both systems is formatted the same way, or at least in a way that allows communication. If one data set is formatted with fractions, for instance, while the other is whole numbers, problems with integration will ensue. “Small” details like this tend to get passed down the chain until they become no one’s job, like when Target launched operations in Canada in 2013. One of the many issues that crippled the chain’s ability to find success in the new market was caused by data integration. They attempted to import data into their new version of the retail software SAP, assuming this would be an easy process because there was no data to convert. However, upon launch, their internal supply chain collapsed. An investigation found that only 30% of the data was actually correctly integrated, because the task of entering the data was left to entry-level employees who all used different formatting methods for the numbers at their various stores.
Security for Data during Integration
Because data can be so sensitive, security is always a large risk during integration. Even the way you access the data can impact security, especially open transactions in the cloud. It’s crucial to protect the data as you attempt to integrate it. For example, Just ask Pacific Gas and Electric,. In 2016, a blogger from MacKeeper discovered a live database of PG&E’s sensitive customer information for over 47,000 users. As PG&E was involved in a new ERP rollout, the company gave a third-party vendor its data to populate and test a form. After the rollout, no one thought to remove this portal from the Internet, where it existed ripe for the use of hackers.
The price of efficiency in the future is patience and diligence during the integration process. Thorough analysis of all systems that you intend to integrate, full-time monitoring of the integration process, and continuous analysis during and after any changes are all necessary. However, familiarity can make it easy to overlook details or not use due diligence during evaluation. The solution to this problem is to work with unbiased, expert consultants like iLAB. We offer the unparalleled experience of a global company with diverse perspectives, and we have plenty of time to protect your bottom-line.