Not only do we talk a lot about value in our Agile practices, we make value our priority—the driving force behind most of our daily decisions. Delivering value to customers is the primary objective of an Agile team. This philosophy, along with its foundation of guiding principles, is commonly called Value-Driven Delivery.
But for a lot of Agile teams, the science of value is an enigma. Where does business value come from? Is it real? Are we really going to generate that much revenue, save that much money, or see such improvements in satisfaction? Is it even possible to accurately measure these results? Do we ever check-up on the realization of those benefits to make sure we made the right initial decisions during development?
Value is commonly expressed in terms of currency. After all, the goal of most businesses is to make money. So naturally, business value would be quantified using dollars. Many algorithmic methods forecast business value, such as: Return on Investment (ROI), Internal Rate of Return (IRR) or even Net Present Value (NPV). Business value may even be calculated more simply, derived from cost savings or cost avoidance.
More often than not, however, business value is qualitative—merely someone’s opinion of how important a feature or app is to a user. Similar to quantitative projections, qualitative business value scores are also simply predictions of how well users will respond to a particular feature or app. Either way, there is no guarantee that delivering the feature or app will generate revenue, reduce costs, or improve satisfaction. Yet these are the predictions that drive the daily decisions of Agile teams!
To ensure the best possible course of action is taken, Agile teams must measure the impact of their deliveries and validate the predictions made during development. This is the only way to be 100% sure. In the mobile world, this is easily accomplished. Assume derived-value is proportional to usage, and measure app usage through downloads and analytics. Usage statistics can be further collected and analyzed by including telemetry in the application code and distribution software.
The number of app downloads, for instance, can be used to measure the size of the user-base. For revenue-generating features, this count can be representative of market potential. For cost-saving features, the download count could represent a coefficient of the maximum savings potential. In-app analytics-hooks provides developers even tighter precision by capturing session-activity and even use-counts for specific events. All manner of usage statistics may be gathered with just a few simple sensors embedded in the code. This telemetry can then be cleverly configured to collect usage data and validate value predictions.
With this data, Agile mobile development teams can reasonably correlate usage statics to value in order to realize benefits of any kind (revenue, cost savings or satisfaction). But if anything delivered is not used, no benefits could ever be returned. Through the continuous delivery of useable mobile app features, value may even be validated during development cycles. By measuring a particular feature’s usage, one can validate its value and even calculate further predictions, leading to better overall decision-making. These predictions and subsequent validations are essential to building confidence in any Value-Driven Delivery philosophy.