Back to the question of whether it's best to build a DAM in-house or to use an external SaaS DAM, the most common arguments in favor of an in-house solution go like this:
- Lower prices of development and server maintenance.
- Easier to plan scalability of storage and processing power.
- (Mis)identify the need for an image library, which can be developed in a short period of time.
- An in-house solution will have built-in exactly all the features required.
- A SaaS solution is cheaper than software developed by the company.
- Making all the necessary integrations with external systems is not cost-effective.
Granted that in some cases these arguments manage to tip the scale in favor of in-house development. Even so, in most cases, the short, medium, and long-term consequences are too far-reaching, ranging from impacting your BAU to modifying your approach to digital transformation. This shows that this course of action can be an inefficient and impractical one.
Because of that, we want to share the insights of companies that have opted for a more practical, efficient, and flexible solution: engaging a cloud-based SaaS platform like Picvario. It has been reported that developing the software in-house poses the following risks:
- Expenses and costs: developing a fully-fledged solution requires very strict project management and implementation, and the cost of any delays, incidents, or even failure would fall on the company.
- Legacy systems: at the same time that the business needs of your company evolve and change, the software and systems developed and maintained in-house need to evolve at the same pace, and without disrupting the ongoing business processes. Else, the quarterly and yearly bottom line will suffer.
- Operations and BAU: if your in-house IT team is developing the software, will you have a separate team to run the business operations? Whichever the answer to this question might be, the reality is that mixing functions can hurt your business performance. According to an article by McKinsey: "On average, large IT projects run 45 percent over budget and 7 percent over time, while delivering 56 percent less value than predicted"