From Complex to Easy: Understanding Integration Options with Anaplan
According to Gartner, organizations are starting to pursue frictionless sharing of data-utilizing tools that are flexible and able to deliver value throughout the integration chain with limited rework. Gartner Data Integration platform 2017
Spaulding Ridge believes this paradigm shift is not only best practice, but critical for organizations to evolve legacy systems into modern, efficient, and scalable architectures. To achieve this “integration nirvana” Spaulding Ridge lives by four core pillars of integration:
LOOSELY COUPLED TECHNOLOGY
Easy adaptation to changing business tides is the goal of loosely-coupled technology. Investing months in the integration of a single process can needlessly drain resources when organizations are frequently replacing business-critical applications.
CHOOSE TECHNOLOGY THAT WILL GROW WITH YOUR ORGANIZATION
Deciding on the right integration technology is critical in producing a sustainable integration group within your organization. In the case of Anaplan, choose a particular integration tool that offers the best flexibility and will grow as your organization adds new applications.
UNDERSTAND & STAY UP TO DATE ON CURRENT INTEGRATION LANDSCAPE
Staying current with the newest tools can seem daunting. However, numerous releases are nothing more than a reinvention of the same process that’s been practiced for years. What’s new is the angle from which they approach the problem; understanding that angle can provide a different perspective. Let’s say you’re deciding between a database driver connection versus a RESTful API connection. While the database driver may be the easiest approach, it may not be the longest lasting, as the industry is shifting away from drivers and toward web service calls using REST.
ADDRESSING INTEGRATION PROCESSES DURING IMPLEMENTATION WILL REDUCE TECHNICAL DEBT DOWN THE ROAD
By doing “just enough” to get the ball rolling you’ll end up hitting roadblocks down the road, creating technical debt. At some point this technical debt becomes unserviceable and requires increased time and resources to continue business as usual. While deploying correctly the first time may be an obvious solution, those at the forefront of their industry should also be asking whether or not Artificial Intelligence and/or Machine Learning could be utilized to address some of the challenges.