Agile  | 5 MIN. READ

The Importance of Local Value Streams Explained: Agile Transformation Step 5

Andy Czuchry, November 21, 2018

The Importance of Local Value Streams Explained: Agile Transformation Step 5If you’ve been reading these blogs as a series and applying the lessons learned, then your organization could be well on its journey to an agile transformation. Every step in this seven step process is organized sequentially for a reason — you have to learn to crawl before you can run.

In the first few steps we gained alignment around strategic goals, created visibility from the c-suite down to the teams and back up again, prioritized and sequenced tasks, and quantified our work in process (WiP). Now it’s time to take transformation to an even more strategic level across the system.

The fifth dimension of an agile transformation requires you to deal with your local value stream. A local value stream includes all of the tasks or sequential steps within your control that are required to turn a single concept or project idea (often called the trigger) into the desired outcome for the consumers of the idea (often called consumption).

Task-Blind

While the idea of value streams is not new to agility, how they are applied often is limited and benefits here from broader context and visibility. I say this because companies often assess value streams directly in terms of tasks that need to be done. A project plan is defined and individuals are assigned tasks to complete with deadlines — but there is little context or collaboration between these activities. When we take this task-oriented view we become blind to opportunities to achieve real agility.

An agile local value stream takes a holistic view of the entire outcome delivery process, looking for ways to reduce waste and speed productivity. To find the improvement opportunities, we need to look at each step in terms of time and energy actively spent, as well as the time lost in wait delays between tasks. All time has value, so the passive time between tasks must be calculated to get an accurate picture of the value stream, and find ways to accelerate value delivery.

The key shift is focusing on time from the perspective of the value and not from the perspective of the people doing the work. This means observing when the value waits and progresses, not when the people wait and are busy. This changes the view from task-oriented to value-flow oriented. In other words, we focus on the time for the value to stream all the way from the starting point to the consumption point, rather than the task-oriented time of the people doing the work.

Redoing Tasks

I recently worked with a healthcare organization to help them improve the speed and efficiency of processing medical charts. The value stream involved several incremental steps, including requesting the chart, receiving the chart, mapping the data, verifying data accuracy, etc.

It was a well-defined process, but on closer look, we found many unnecessary gaps and delays due to error-prone manual processes and expensive manual redundancies. For example, one of the steps required verifying the mailing address of the patient or provider. This step is important because if the chart request is sent to the wrong address it would violate data privacy regulations. As a result, three different teams who handle charts all dedicated time to verifying the same address in different contexts — a process that included requesting verification and then waiting for a response, which could take hours or even days. The people themselves moved on and became busy with the next set of tasks on other activities, but the progress for processing the specific chart request was effectively on hold and delayed.

By examining the entire value stream, through the lens of time and flow of value in the chart requests rather than only the tasks completed by the people, we were able to identify inefficiency in this process. In response, the organization created an automated address verification process that was conducted at the beginning of the chart request process, using an algorithm to validate the data against existing records. This reduced the manual effort spent on address verification, reducing the time to verify from hours to minutes, and eliminated additional address review steps later in the value stream.

What is Time Worth?

When we look at value streams in terms of the way time is used to move value through the process, rather than what tasks are performed by the people or systems, wasted time and inefficiencies are easy to spot. In this case we found a simple solution that made the process faster and more responsively agile.

No matter how good an individual is at completing a task, it is not enough. They may add efficiency to one aspect of the value stream, but it is often to the detriment of others in the system or to the flow of the value itself. To achieve agility, each objective should be planned from concept to consumption from the perspective of the value and it should involve all relevant stakeholders in order to create the most efficient workflow for the value being delivered. By taking an end-to-end approach, execution teams and business leaders can identify hidden risks, determine better sequences, and get feedback from stakeholders early enough in the process to prevent expensive delays in value delivery and the long waits that emerge down the line.

 

Learn how to enable innovation skill-building at scale here or download our free ebook Kickstart Innovation: A Guide for Organizations.

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Andy Czuchry Jr, PhD is a proven business transformation leader with extensive experience driving strategic and operational transformations that significantly increase business-value outcomes for mission-critical objectives. Over the past 10 years of his 25+ year career in business and technology innovation, Andy has led nearly a dozen organizational transformations in national and global organizations spanning across all disciplines, both within and beyond the traditional agile core.

Andy earned Ph.D. and Master’s degrees in Information and Computer Science (Artificial Intelligence, with a minor in physiological psychology) from the Georgia Institute of Technology. He earned his bachelor’s degree from Dartmouth College in Computer Science and Mathematics with a focus in applied algorithm development. Andy maintains numerous certifications in the domains of Agility, Lean Six Sigma, and Program Management. He is the holder of two patents issued by the US Patent Office, as well as a recognized global leader with 20+ peer-reviewed papers published in elite business and technology journals and conferences.

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