Overview

Presently, telemedicine represents a rapidly growing segment of the healthcare industry, providing immediate access to limited and vulnerable patients who cannot receive care through traditional means. It is estimated that nearly 70% of healthcare providers use telemedicine in some capacity.

At one of the largest managed healthcare providers in the country, with over 10 million members and over 100,000 physicians and nurses, investing in telehealth was the logical next step in improving care and enhancing its patients’ experience.

But when providing services to a massive network of members and physicians, care and precision are vital in maintaining high-functioning telehealth services. One product line was under particular pressure, as they developed and supported a patient portal application for their extensive network of patients and healthcare workers.

To increase efficiency and shorten time-to-market, they turned to Viz™ to help understand how to accelerate the delivery of value and where their work was slowing down. They sought to discover which investments in people, process and technology would help them go faster. And they wanted clear data visualizations to share with their leadership and peers to advocate for those investments.

Highlights

  • Bottleneck exposed: Product owner resources
  • 85% of work is stalled: Work intake must change
  • Predictability can improve: Flow Times are currently misinforming commitments

The Solution

In February 2020, the enterprise began using Viz to generate Flow Metrics from their software delivery portfolio, primarily managed in Atlassian Jira. These end-to-end value stream metrics measure the rate of business value delivery for software products through the lens of its customers. Shortly after plugging Viz into their existing tool infrastructure, the insights began surfacing.

Insight #1 from Bottleneck Detection: Invest More Upstream of Development

Flow Efficiency is the percentage of time that work is actively worked on compared to the total time spent in a value stream. If Flow Efficiency is low, this indicates that work spends a lot of time in waiting states, which points to bottlenecks, inefficient processes, a lack of resources and, most notably, waste.

For one value stream, Flow Efficiency was steadily declining, meaning that wait times were steadily increasing. This product was three times slower than other value streams. But why?

The product’s leaders utilized Viz flow analytics to determine where the work was piling up and slowing down. Contrary to popular belief, the bottleneck was not with developers, rather with the product owner who prepared the value stream’s work. Stories spent excessive time in the Draft state, waiting to be defined (see Figure A).

The product value stream was under-resourced at the frontend, and now, thanks to Viz, they had the business case to add product owner resources to prevent development team starvation and boost overall velocity.

Insight #2 from Flow Load Analysis: Stop Starting and Start Finishing

Flow Load measures the amount of work in progress (WIP) for a given product value stream. When WIP is too high, velocity decreases and time- to-market gets longer.

For one product value stream, Viz revealed a very high and stagnant Flow Load (see Figure B). Diagnostics on their throughput indicated that only a small current of work was actually moving through the value stream to completion. A staggering 85% of their work was stalled and neglected. Moreover, they discovered that it would take nearly three months to complete all the work that had been started but never finished. Current time-to-market predictions had been ignoring incomplete work, which led to misinformed commitments and an erosion of the business’s trust.

The pressure from the business to take on more work was perpetuating a ‘push’ work intake mechanism on a value stream trying to practice lean-agile’s pull mechanism. Backed by data, they could now make the case for working through the existing WIP before taking on new feature development.

Impact of learnings from Viz:

  • Leaders learned where to spend their next dollar. Investment is needed at the top of the funnel to increase feature velocity and prevent developer starvation. “My rule of thumb on any kind of data like this is it should either change my behavior or predict the future,” said the Sr. Director of IT & Operations.
  • Product owners learned that in order to shorten flow times and deliver faster, they must enforce stronger WIP limits and implement a lean-agile pull mechanism for new work.
  • Scrum Masters learned that they must work through a backlog of incomplete work before taking on new features.

Looking to connect with like-minded business and technology professionals?

The Flow Framework Community provides a professional, inclusive, and supportive environment for learning, questioning, and networking on all topics related to the Flow Framework, Flow Metrics, and value stream management (VSM). flowframework.org/community

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