Defining “value” in agile product development is a challenge for organizations of all sizes. The definition is often framed and answered from an operational perspective, focusing on metrics like on-time delivery, productivity or predictability. Enterprises also define value from an outcome perspective focusing on financial benefit, user satisfaction or product scope delivery.
Numerous challenges arise when defining value from these perspectives. When looking at value from an operational perspective, it is possible to optimize metrics without actually realizing business or user value. From an outcomes perspective, it is not always apparent how the metrics relate to one another and they can even be at cross purposes. Furthermore, it is often unclear how to combine distinct values to prioritize or improve a process or outcome.
IBM Garage has developed a sequence of steps and versatile tools to align business and user value and we refer to this as value orchestration. We use value orchestration to guide product UX strategy and experience transformation and continuously deliver value in an agile environment. This methodology has been deployed and refined across multiple industries and Fortune 500 clients. Detailed below are the methods and findings:
Step one: Understand business value through user behavior
Value orchestration begins with the understanding that business value is rooted in user behavior. We define users as any internal or external end-user of a process or tool. A business owner realizes value when their users behave in a certain way. For example, if the business owner is running an e-commerce site, they recognize value when users (new or existing customers) visit the site, purchase products and respond to advertisements. If the owner creates a workplace optimization tool, they might realize value when their employees complete tasks, do so quickly and don’t make mistakes.
In the cases above, it is straightforward to understand the business value of visiting a site, viewing an advertisement, completing a task or making an error. It is equally straightforward to imagine how the business might measure changes in these behaviors and quantify the value of those changes.
And so, the process begins with asking product stakeholders to specify how they would like their users’ behaviors to change. A business owner might say, “I would like my users to not abandon their carts so often.” Reviewing shopping data, the business owner can settle on a goal to reduce the cart abandonment rate from 75 percent to a more modest 50 percent.
Having a goal and a measure of success provides several advantages to the effort. We can answer three essential questions to which we can align any number of individuals or teams:
1. What are we trying to achieve? A reduction in cart abandonment from 75 percent to 50 percent.
2. How will we know if our solutions are working? When cart abandonment goes down.
3. When will we be “done?” When the cart abandonment rate hits 50 percent.
Once we’ve arrived at our goal, the next thing we need to do is answer, “Why are users abandoning their carts 75 percent of the time?”
Step two: Create a value model
With a goal behavior and measure identified, we build a value model that links the behavior changes to financial impacts. These formulas take the measures of user behavior as inputs and produce an implied financial impact. This financial impact will allow the team to compare the value of changes in user behaviors against one another. The value model also enables the product owner to establish a consistent benefit calculation, through which the ROI of future solutions can be assessed.
Step three: Identify root causes
Step three in our process is to identify the drivers of the user behaviors we are trying to change. We call these behavioral drivers, root cause pain points.
In the cart abandonment example we can start by conducting dedicated research through interviews and reviews of existing data to determine why customers abandon their carts. We will likely identify many pain points with varying degrees of significance. For this reason, we design our research and analysis protocols to sort root causes in order of priority. In this example, users might struggle to edit their order, access the “check out” page or enter payment information. By prioritizing these pain points in terms of impact on cart abandonment, we can prioritize the root causes to mitigate with solutions in the next step.
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