Data Teams and Software Lifecycles

IE's business model allows software industry customers to increase and downsize their data teams as required. We adapted our company's organizational structure to accommodate this model because it preserves the working capital of start-ups, allows them to scale quickly, and gives their firms a higher likelihood of success, which in turn increases the lifetime value of these customers to us. In other words, it's a quintessential win-win model.

So what does the enterprise SaaS life cycle look like? Put simply, it has a distinct "roller-coaster-like" pattern.

• The initial launch of the 1.0 service requires a lot of upfront work and then the onboarding of initial customers.

• As enthusiastic early adopters are exhausted and enterprise license sales slow down, the demand for data work declines and the team needs to be reduced to a sustainable level.

• As the 2.0 and subsequent versions of the service are deployed, the pattern repeats itself with an initial surge in the requirement for data work and a corresponding plateau as the market is eventually saturated once again.

This is a critically important aspect of our service that is unique among strategic tech partners. We accomplished this organizational management challenge via a combination of trained team "buffer" resources and cross-training across projects that enables redeployment-on-demand. Surplus team members are assigned to other similar projects or undergo further training to enhance their skillsets so there is no adverse impact on our employees, and our clients get a massive tactical advantage over their competition. Another win-win for this unique model.