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Value Stream Management

From Waste to Value: Value Stream Management and AI in Action

Slash waste and optimize software delivery workflows by integrating Value Stream Management and generative AI

Published By Michelle Wong
From Waste to Value: Value Stream Management and AI in Action

In today’s fast-paced world of business and technology, efficiency in software delivery is not just important; it’s crucial. The idea of cutting waste, a principle from manufacturing, is relevant more than ever in software development and knowledge work as a means to increase efficiency.

In this article, we’ll uncover six key sources of waste that may be slowing down your organization. We’ll also see how combining Value Stream Management (VSM) with generative Artificial Intelligence (AI) can help spot and reduce waste, making your workflow more efficient for today’s fast-paced and competitive environment.

Waste Minimization in Manufacturing: Valuable Takeaways

The journey of reducing waste in manufacturing holds an important lesson for today’s software industry. Let’s look at a clear example from the 1970s electronics industry.

Think about amplifiers, a crucial part of audio systems. Back then, getting one took weeks and was as expensive as $1,000 in today’s money. But now, you can have the same component overnight for a fraction of the cost. This was made possible because the manufacturing industry found ways to cut waste in how they made and delivered products. As a result, they achieved a remarkable 266 times faster delivery and an 82% cost reduction.

This transformation in manufacturing serves as a blueprint for the software industry. Today, companies are applying those principles in delivering greater. This includes delivering customer-centric products and enhancing speed to market. However, the challenge remains in identifying and eliminating waste, which can significantly hinder transformation efforts.

The Six Sources of Waste in Software Delivery

Even though companies are adopting modern solutions to enhance delivery workflows, many still face ongoing inefficiencies, with up to 79% of work in software development being lost to waste.

This highlights the critical need for understanding where waste is coming from within the software delivery lifecycle and developing strategies to mitigate it. Let’s explore the six most common sources of waste.

1.     Aged or canceled work

This type of waste, making up approximately 5% of total effort, refers to time spent on tasks that won’t be finished or won’t be relevant in the end. It leads to a direct loss of resources and delays for other teams waiting for these tasks.

2.     Waste due to repetitive manual work

Representing about 6% of total effort, this waste category comprises low-value processes that should be automated. Automation not only saves time but also improves quality, reduces rework, lowers costs, and increases agility by shifting worker capacity to higher-value tasks.

3.     Overproduction

Taking up approximately 9% of the total work effort, overproduction refers to producing work faster than it can be consumed. This leads to inefficiencies, as teams produce more than what is required, resulting in a buildup of backlog.

4.     Excessive rework

Accounting for about 11% of the total work effort, rework involves redoing tasks more than once, often due to bugs or quality issues. The key is managing rework predictably and continuously improving to avoid significant swings in rework volume.

5.     Excessive work in progress

This source of waste, about 17% of total effort, stems from the overhead of excessive multitasking. Managing the Flow Load (the amount of work in progress) and Flow Velocity (the rate of production) is crucial for improving productivity.

6.     Misaligned work

The most significant source of waste, accounting for 30% of total work effort, is misaligned work. This happens when teams work on lower-priority items, causing a ripple effect of inefficiency throughout the organization. Aligning work with strategic priorities is essential for eliminating this waste.

Leverage VSM and AI Integration to Reduce Waste

The integration of VSM and generative AI represents an opportunity to significantly reduce waste in the software delivery lifecycle. Generative AI brings to the table the ability to continuously analyze and interpret vast quantities of data from the software development process. This includes the ability to identify intricate patterns, pinpoint bottlenecks, and uncover inefficiencies that might elude manual analysis. This data-driven approach is especially potent when coupled with the use of Flow Metrics within VSM.

Flow Metrics, which include key indicators like Flow Time, Flow Efficiency, Flow Distribution, Flow Load, and Flow Velocity, serve as the linchpin for identifying and eliminating waste. They offer real-time insights into the pace and efficiency of work as it progresses through the value stream.

By leveraging Flow Metrics, organizations can precisely locate points of waste, whether in the form of excessive wait times, frequent context switching, or inefficient handoffs between teams.

Moreover, Flow Metrics within VSM allow teams to proactively detect and address potential sources of waste before they materialize. These metrics offer predictive capabilities, enabling teams to forecast bottlenecks, resource shortages, or quality issues. Armed with this foresight, organizations can take pre-emptive actions to streamline processes, allocate resources judiciously, and ensure the efficient flow of work.

In essence, the integration of VSM and AI provides a comprehensive and data-driven approach to waste reduction. It empowers organizations to continuously monitor and optimize their value streams, fostering a culture of ongoing improvement. By leveraging Flow Metrics, teams can not only identify waste but also enhance the overall flow of work, achieving greater efficiency and delivering higher value to stakeholders.

Next Steps for Reducing Waste and Inefficiencies

Eighty percent of a company’s capacity can be tied up in the collective waste produced throughout the software delivery lifecycle. By trimming even a modest fraction of this waste, organizations can unlock a substantial increase in their development capacity. This can lead to remarkable returns on investment and time to value for organizations, especially as they scale their operations.

Drawing from the rich legacy of the manufacturing sector, the software industry has gained invaluable insights into how to conquer inefficiencies in delivery processes. These lessons do more than just illuminate the path for necessary operational optimizations to trim down waste; they strategically align every action with the overarching goals of the organization, ensuring that each step taken is a meaningful stride toward fulfilling its core objectives.

By harnessing the power of AI and employing advanced value stream management techniques fueled by Flow Metrics, businesses can not only significantly reduce waste but also revolutionize their workflows. This paves the way for a dramatic boost in productivity and effectiveness, propelling organizations toward unprecedented levels of growth. For more on how your organization can eliminate waste, increase efficiency, and reduce costs, read the eBook Flow Metrics: A Business Leader’s Guide

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Written by Michelle Wong

Michelle Wong is the Content Strategist for Planview's value stream management and software toolchain integration solutions for software delivery. Her content focuses on digital transformation topics including Project to Product, Flow Framework, DevOps, Agile, and SAFe.