There are typically two interpretations of the term “development process” – one being the tools, practices and methods applied in software development (i.e. methodology, plus build automation, standards etc.) the other being the process applied to get from requirements to working software (i.e. iterative or waterfall, plus how the analysis-design-build-test-release disciplines are executed). This post outlines one high-level approach to the latter in the context of Salesforce developments. The intent of this isn’t to be overly prescriptive, generally speaking each project requires its own defined process that factors in resources available (and their skills and experience critically) plus the nature of the work and the timescales. That said it is a truism that failed projects fail for a variety of reasons but successful projects are typically successful for the same reasons. A fundamental success factor being the adoption of a clearly defined and simple process – others being team empowerment and shared commitment.

The process above assumes an iterative process and focuses the initial iteration on the foundation of a robust data model, set of user profiles and permission sets, role hierarchy, record access model and statement of the reporting requirements for the project. Subsequent iterations improve the quality of the foundation over time, as new functional areas are developed. The data model in this context will include a statement of the org-wide defaults for each object and the specifics of each relationship (master-detail, lookup, mandatory lookup etc.). The record access model is critical – this shows how each user population maps to a user profile and role and how they gain access to the data required, i.e. sharing rule, Apex managed sharing etc. In my experience defining an approximate access model upfront and then refining during the feature build-out helps to avoid expensive refactoring later in the process and sets out a clear understanding for all contributors to the declarative and technical build. A piecemeal approach to defining a sharing model is commonplace – this rarely provides a clear and cohesive result. For the similar reasons defining a list of permission sets upfront ensures that user profiles are kept clean and focused, avoiding proliferation of profiles down the line. It may be surprising to see analytics such as reports and dashboards being considered during the foundation stage, this however is one of the primary inputs to the definition of a fit-for-purpose data model. I’ve worked on countless projects where reporting has been overlooked until a late stage, at which point it has become apparent that standard reporting features can’t produce the reports given the structure of the data. Ideally the data model should be designed from the outset to work well for both transaction processing and analytics.

A final point for consideration is the by-exception approach to identifying technical components. When breaking out the solution components required for a certain feature – expertise must be applied to ensure that standard product functionality or declarative options (workflows, reports etc.) are considered fully before bringing expensive technical options such Visualforce or Apex to bear.