Cloud Service (SaaS) Development

Our Approach

We design from the start on the premise that data and permissions are separated by organization

If a service is built to fit only the first company, then once more organizations start using it you end up rebuilding the data separation, the permissions, and the per-organization settings. Because data already in use has to be moved, rebuilding later is a large undertaking.

At the requirements definition stage, we decide the data separation for each organization, the permissions for each feature, and the settings each organization can change. In a health checkup app for municipalities, we built in from the start a mechanism that manages data separately for each municipality.

Our Approach

We write out who does what, and when, for each user role before deciding on the screens

In a cloud service, people in different roles work with the same data: the operator, administrators at customer organizations, and users on site. If you start building without sorting out what each role does, the screens and permissions keep multiplying later.

For each role, we sort out “who does what, when, and what triggers it,” and align our understanding one screen at a time using wireframes. We took the same approach when developing a training management system used by four parties: the operator, participating companies, trainees, and workplace members.

Our Approach

We add what is needed to offer it externally and grow it into a service

A system built for internal use is designed around your own company’s operations alone. To offer it to other companies, you need data separation for each organization, settings for each contract, and a way to handle inquiries and system failures.

Di-ORDER, an ordering and order management system for construction sites, grew from a system built for internal use into a service offered to other construction companies. According to the service website, 22 companies have adopted it.

Our Approach

After launch, the same team keeps adding features and making improvements

For a cloud service, the real work begins after launch. Unless you can keep adding features in response to usage and to feedback from customer organizations, the service will not keep being used.

For a university admissions matching service, the same team kept developing after launch and added AI features in stages. According to the operating company’s announcement, the number of users has grown to 11 times the previous year’s level.