Customer-Centricity – Is It for Real?

Historically, software development has been measured based on volume of output. But is that a fair assessment of development success? Like any other industry, software development organizations too need to align to customers’ needs. And, output – when it comes to software – isn’t all that matters to customers. 

It has been observed very often that despite adhering to release timelines and meeting, or even exceeding, SLA commitments, the delivered software never gets deployed into production or is abandoned very soon. What could we be missing here? Let’s revisit the Agile Manifesto. One of the core values of Agile – “Continuous collaboration over contract negotiation,” emphasizes on the importance of ongoing collaboration with your customers to deliver maximum value with every release. Focusing on delivering as per the negotiated contract, without considering the actual outcomes that customers are looking at achieving from a deployment undermines the very premise of Agile management.

Shift the Focus from Outputs to Outcomes

The need for delivering outcomes has been well established by methodologies such as ‘Lean’ and ‘Agile’. Once again referring to the Agile Manifesto, its very first principle suggests, “Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.” Nonetheless, software organizations have largely focused only on output to measure development success, instead of customer outcomes. 

Let’s take for example the most common metric used by engineering teams – velocity. It’s important to measure velocity, but only to ensure that you’re on track towards your release goals. However, what is the relationship of velocity with customer outcomes, and how do you factor in that aspect? Other metrics that engineering teams often obsess over include function points, story points, defects per line of code, and test coverage, amongst others. While these metrics should not be ignored as they help assess and improve team efficiencies, they do not take into account the value delivered to customers.

An outcome-driven product roadmap continually incorporates customers inputs to ensure that the new versions, features, functionalities, and applications shipped to the market are more likely to gain acceptance and deliver tangible value to customers.

Unified the Product Backlog. What’s Next?

“Simplicity–the art of maximizing the amount of work not done–is essential.”- Agile Manifesto.

As development teams build the product roadmap and plan releases, it’s important to ensure a single unified view of the product backlog. This provides a comprehensive picture of all requirements to be considered for inclusion in a release. Once they’ve brought together information from multiple disparate sources, including a project management tool, IT Service Management (ITSM) tool, CRM, etc., development teams need to prioritize requirements and decide what needs to be covered in the current release. As they do so, they need to prioritize the value delivered to customers with every release, over standalone metrics such as velocity, stories, function points, etc. After all, customers end up using only a fraction of all the functionalities packaged in a software product, and it’s important to continually improve their experience of those functionalities that mean the most to them.

Leverage Predictive Analytics to Measure Customer Outcomes

The next big question is what are the true indicators of value delivered to customers? Some of the key factors to consider as you assess customer outcomes include financial performance, business growth, compliance requirements, cycle times for business processes, and more. Further, their adoption and consumption of the product and its features and functionalities, retention and renewal rates, sentiment, and satisfaction scores, are some other indicators of the value delivered to customers.

Technology is a key enabler for outcome-based product backlogs. As product owners look at embracing an outcome-driven approach to defining the product roadmap they need to have real-time visibility across the application development lifecycle, service requests, product adoption and consumption metrics, customer satisfaction scores, as well as any other customer inputs. This underlines the need for a platform that can not only bring together data from across silos, but also apply advanced predictive analytics and machine learning models to analyze current and historical data to predict customer outcomes. Predictive analytics allows product owners and development teams to slice and dice transactional and historical data to uncover trends, identify potential risks and opportunities, and make informed decisions focused on delivering customer outcomes.