5 Killer NetSuite Implementation Tips
NetSuite implementation is an enormous undertaking spanning many functional areas of an organization. For this reason, implementing NetSuite into your operational schema can be rife with problems, many of which can take weeks or even months to resolve.
However, you can avoid the most common pitfalls by putting our expertise to use during your NetSuite cloud implementation:
- Are You Setting Realistic Expectations?
According to Gartner, 70 – 80% of BI projects fail. A major cause for this failure is unmet expectations for the business. A major cause for this failure is unmet expectations for the business. Unmet expectations come in many forms. The project can have budget over-runs due to poor planning. The project can have schedule creep for the same reasons. This risk of project failure is what we refer to as the Implementation Chasm.
- Can’t Cross the Chasm?
Despite a huge need to get more value from data, most businesses remain staring at the implementation chasm not knowing how to cross it. Most BI implementations fail to “start a fire.” They fail to move from the early adopter phase to the early majority phase often because of a lack of a strategic leap that would power the crossing of the chasm.
But what if you could get to your strategic leap faster? How can that be done?
- Consider Using an Accelerator!
Crunch Data has an approach that combines the use of our C-Connect Middleware, Accelerator Apps and a Rolling Release Project Management approach to help our customers build out analytics solutions atop of leading systems like NetSuite ERP. Integrating cloud data from any cloud source takes time. Our SuiteAccelerator App (www.suiteaccelerator) helps get you access to NetSuite Cloud data faster and it helps organize that data in an understandable manner. The app meets most of the AR / AP, Income and Expense analytics requirements out of the box. The accelerator app accounts for 80% of the work. Any additional customization or additions are divided into separate, logical work streams that can be executed largely in parallel, thus significantly shortening the overall implementation timeline.