The implementation of data integration solutions can be a double-edged sword. You know such solutions offer your company major benefits, yet you are also concerned about some significant challenges. What do you choose - sticking with legacy integration systems that might work well now, but are not guaranteed to work in the future, or move to a modern system that is more reliable, but might pose implementation difficulties?Read on to learn how you can overcome data integration challenges by following three best practices: understand the data and your goals for it, demonstrate value, and provide self-service functionality.
The Challenges of Data Integration Solutions Implementation
On its face, the challenges that confront organizations seeking to implement data integration solutions may seem insurmountable.
For a start, there are data silos, repositories of information scattered across the company usually containing duplicate information in various formats. Then, there are cultural barriers. You may encounter strong resistance from people who simply do not believe the project is necessary. A third obstacle is the argument of who gets control of the project. Does it belong to IT or to another department?
Obstacles include data silos, cultural barriers, and issues about who controls the project.Though it might seem as though these issues are impossible to solve, they are actually not. You can overcome problems provided you follow a set of best practices.
Best Practice 1: Who Understands the Data and Your Goals for It?
Every project needs someone to champion it. Sometimes it is an individual, and sometimes it is a team of people. When it comes to data integration solutions, whoever champions this initiative must have a keen understanding of what kind of information the organization has at its disposal, where it is stored, and what the company's intentions are towards the data (if they want to use it to enter a new market, if they want to improve efficiency, if they want to launch a new product, etc.).
Without such a champion, the project will never get off the ground. Moreover, a thorough understanding of the information you possess and what you intend to do with it enables the project champion to create a clear roadmap so that implementation can proceed smoothly and successfully.
Best Practice 2: Demonstrate Value
In a way, data integration is akin to manufacturing. Both processes add value to the finished product.
How is that possible? Part of the integration process is transformation, changing the format of the data so it is in an accessible format. This step adds value because when information is in an accessible format, it is available on more platforms and devices.
Best Practice 3: Provide Self-Service Functionality
Over the years, data integration solutions have evolved. When they first came on the market, they were meant for use by the IT department. Times have changed, though.
Data integration does not have to be IT's job.Today, data integration does not have to be the sole province of the IT department. Rather, it should be put into the hands of end-users. By giving the power of data integration directly to the people that need it most, they can choose the information sources they need to integrate. Not only do end-users gain a unified view of the data, they are no longer dependent upon the IT department to take care of this process.
Data integration can yield numerous benefits, especially when you utilize best practices. That being said, you do not have to go it alone. EDI service providers can make the process smooth and hassle-free. To learn more, see some of our recent success stories.
