Scaling hits the buffers
Gemma is the CEO and co-founder of an open banking startup with a steadily growing mobile app that reduces friction in personal banking. Investors recently approved new funding to cover 18 months of development to create capabilities that would enable users to make informed spending decisions.
Gemma and her team decided to increase capacity by doubling their digital engineering headcount to meet the timeline. Six months later, Gemma only saw a marginal increase in the organization’s ability to deliver these features on time. Even worse, customer satisfaction and engagement metrics had dropped.
Gemma decided to run a few diagnostic workshops with the teams and quickly realized several things:
There was a lack of alignment across the teams and with the business strategy
As the product and technology scope increased, so did the teams’ cognitive load
Varied and divergent team practices led to a decrease in product quality
Poor quality increased failure demand, thus reducing the teams’ capacity to deliver on value demand
Ultimately, the teams’ ability to add value didn’t increase alongside the growth in headcount. Gemma's situation is not unusual. When trying to increase capacity, many leaders consider headcount. Yet, typically, it is more complex than turning up or down a dial.
Let's look at what Gemma did next to learn how to scale engineering efforts more efficiently.
Achieving alignment
Gemma had read research that strongly suggested that reducing friction through improved working practices, organizational enablement and technology alignment can significantly improve customer satisfaction and business profitability. Industry insights like these from Gallup further highlighted the importance of a clear work purpose.
Gemma and her leadership team developed a single vision to guide all company initiatives with defined goals for their customers. This ultimately helped break down silos and encouraged greater — and more effective — collaboration built on shared objectives, metrics and vocabulary. Reorganizing cross-functional teams into value streams also increased autonomy, employee engagement and the impact of the work.
Regularly reviewing progress using leading and lagging metrics helped Gemma and her leadership team prioritize initiatives based on delivered value. Lagging metrics signal whether a desired outcome has already been achieved, while leading metrics indicate progress towards achieving that outcome. Gemma made sure that these metrics were communicated and understood across the business.
Working with delivery teams, Gemma moved to a value-focused operating model. This was underpinned by a hypothesis-driven iterative method that gave teams the scope to run experiments to determine the best way to add value. This meant the organization could both deliver value and continuously optimize its practices and processes.
Releasing tied-up capacity
In addition to building alignment, Gemma was keen to understand where capacity was being consumed. After analyzing utilization with her delivery manager, it became clear that about a third of all capacity was being lost to fixes and production support. As the number of bugs increased with the additional throughput, so did the developer bandwidth required to resolve them. Prioritizing resolving the most frequently recurring issues and making the system incrementally more supportable helped reduce this capacity drain.
Reviewing software development effectiveness metrics (known as DORA metrics) also revealed that considerable time was being spent on rework due to ongoing quality issues. Having the teams focus on code quality and shifting testing left by integrating testing into the core development processes helped reduce quality issues by being able to anticipate and respond to them earlier.
Investing in a delivery platform and a lightweight technology operating model focusing on guidance and alignment further reduced friction, increased consistency and eliminated wasteful work.
Reclaiming the teams’ capacity in this way greatly increased their engineering effectiveness. This helped the technology side of the organization scale independently of headcount and take advantage of the increased workforce more efficiently.
Three months later
With these changes in flight, improvements happened quickly. Alignment across autonomous teams and a program portfolio prioritized around customer value helped spend capacity in the right places. And with improved quality, more capacity became available to deliver value instead of being wasted on fixes and support. Within a quarter, Gemma observed improvements in customer satisfaction, and the teams were back on track to deliver the new capabilities on time.
What we can learn from Gemma
By aligning your staff around customer-oriented activities, you ensure they can focus on what matters most. Continuous experimentation by your teams will further help them course-correct based on new learnings. Finally, consider where current capacity is being spent before adding people. Right-sizing technology teams is as much about effectiveness as it is about headcount.
In this way, just like Gemma, you can set up your organization to deliver optimum value early and often while maintaining and even increasing customer satisfaction metrics as your organization scales.
