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The Toyota Way to Lean Leadership

In partnership with George Trachilis from the Lean Leadership Institute (LLI), I’m making available material from LLI’s “The Toyota Way to Lean Leadership” course. Check back every week, for the next few months, for a new chapter from the course.

Week 16: More A3 Stories
Week 15: A3 Stories
Week 14: A3 Thinking
Week 13: Why PDCA?
Week 12: Problem Solving to Develop People
Week 11: Root Cause Using 5 Whys
Week 10: Toyota Business Practices – An Example
Week 9: Toyota Business Practices Explained
Week 8: Problem Solving Towards Ideal Part I and Problem Solving Towards Ideal Part II
Week 7: What is Lean? Problem Solving, Improvement, and A3 Thinking
Week 6: Developing People
Week 5: Lean Thinking—Philosophy for the Long-term
Week 4: True North Values
Week 3: Toyota Production System Origins
Week 2: Problem Solving: The Toyota Way
Week 1: Great Company Characteristics

 
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Posted by on July 12, 2017 in leadership, lean

 

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Agile Transformation Learning Curve

Many a time, I’ve brought up the conventional learning curve (J-Curve) to help agile champions understand that there will likely be a dip in productivity while adjusting to the new lean-agile way. This dip is followed by a rapid increase in effectiveness and efficiency as the new approach is mastered and finally culminates in a plateau at a higher level.

While I’ve seen this J-Curve (on the left in the image below) unfold countless times with team members making the transition to agile; I’ve seldom encountered this with managers in large organizations. A different dynamic plays out and the transformation’s learning curve looks slightly different (on the right in the image below).

Sketches - 3

In the right hand figure, there is an initial improvement that is driven by an illusion of learning. In this stage, managers have had some introductory training and the organization has mastered the rhetoric of the new approach. People know enough to be dangerous and spend some effort in grafting the new way onto the old organizational approaches — but the same old premises are at work. While there is much activity nothing new is being done by management — no new approaches to problem solving, decision making, budgeting, horizontal relationships, etc.

The initial rise in effectiveness/productivity stalls and subsequent introspection leads to a sufficient understanding to see that “we don’t really know much.” This “A-ha!” experience is the beginning of the integration of acquired knowledge with know-how. It leads to a reset — a new beginning — and the start of real learning that results in a rapid increase in effectiveness.

I know real learning has started when I begin noticing signs of managers asking smarter questions and applying the principles learned earlier to current circumstances.

What has been your experience? Do you see this primarily in large organizations or is this a universally predictable pattern?

 
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Posted by on July 10, 2017 in Agile

 

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Misplaced Agile Transformation Priorities

Most companies that I’ve worked with begin their lean-agile transformation effort by attempting to fix/improve the development teams. However, the source of most of the problems lies either upstream (lack of sequencing of work, demand far outstripping capacity to do the work, suspect value of work requestsed, etc.) or downstream (lack of environments, wasteful and onerous deployment processes, etc.) of the development teams. And, of course, management struggles in creating an environment that is conducive for high-performing teams is well known and another area for improvement.

A significantly better approach would be to start with introducing the CALMS conceptual framework (culture, automation, lean, measurement and sharing) for driving the integration of development, support, operations and business. Over time, plan and prioritize initiatives and improvement efforts to move each of the CALMS elements forward. Simultaneously, work with the business and with stakeholders to better define and sequence customer-valued increments of functionality.

You have a higher probability of making meaningful improvements and moving the needle on the busniess metrics that matter by changing your starting point. What have your experiences been?

 
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Posted by on May 15, 2017 in Agile, Coaching, Improvements, lean

 

Six levels of waste

In a WhatsApp conversation, Charles Protzman, co-author of, “The Lean Practitioner’s Field Book” shared how he categorizes wastes. His words:

We have categorized waste into six different levels:

  1. The first level is obvious waste: low-hanging fruit (or walking on it).
  2. 5S wastes: the easiest wastes to see.
  3. The seven (eight) lean wastes.
  4. Boiled frog waste: the waste that is hard to notice because it is old and we pass by it every day.
  5. Tribal waste or sacred cows: untouchable waste in our culture and systems.
  6. Hidden unseen waste: waste we don’t typically see, as it is hidden behind or masked by other wastes; you really have to hunt for it! The hardest waste to find and yet the most dangerous.

To #3, I would add and emphasize the knowledge work wastes of scatter (lack of focus), hand-off, wishful thinking, reinvention, and lack of system discipline to make the list more relevant to software development.

This is a really good list. What do you think?

 
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Posted by on February 22, 2017 in Improvements

 

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Why do organizations limit their agile focus to just development?

Seems like I’ve been suffering from frequency illusion (aka blue car syndrome) recently. I’d been mulling over the fact that a majority of clients I serve don’t invest wisely in DevOps or simply don’t know how to proceed. A recent one, for example, has been crafting a DevOps strategy for over a year with nothing to show for it. Sadly, the DevOps initiative and group is considered separate from all the teams doing agile. Interestingly, I suddenly started seeing lots of data supporting my belief — most likely, I was primed to see it crop up everywhere.

Forrester’s 2014 report, “How Can You Scale Your Agile Adoption?” and Cloudbees’, “Four Quadrants of DevOps Maturity” reinforce the notion that the late stages of the software development cycle are usually given the short shrift.

We know that software development entails more than just development. To keep the discussion simple, software development can be thought of a sequence of activities (and associated information and work product flows) encompassing understanding customer and stakeholder needs, planning, designing the offering, coding, building, integrating, testing, releasing/promoting, deploying, operating, and getting feedback for the next cycle.

While a decent percentage of companies are focusing their agile efforts on the pre-integration stages, less than 15% have introduced agile principles, techniques, and practices in the integration and post-integration steps. So, while companies get better at developing software they still are gated and held back by unnecessary delays in the later stages of the life-cycle.

As an aside, I’m not considering funding, sequencing of work across the stakeholders, and requirements being pushed to teams without regard to their capacity and ability to deliver here — areas that still need tremendous work in most organizations. Also, SAFe has rightly emphasized attending to the team structures but often overlooked in agile transformations are the facts that teams don’t have all the skills needed, team membership is unstable due to shortage of necessary skills, there is a lack of focus on minimizing dependencies (highlighting dependencies is not the same as minimizing them), and the business and teams aren’t often aligned.

This issue of lack of agility, post-coding manifests itself in a few major ways:

  • Teams struggle with lack of environments for developing, integrating, and testing.
  • Extreme risk aversion in the second half of the cycle at times often precludes teams from promoting their own code — they then face significant challenges in testing their work in a timely manner.
  • Deploying to higher environments can at times be a cumbersome, bureaucratic process — infrequent promotions and deployments delay defect discovery and slow down feedback. Consequently, feedback cycles of 2 weeks or less in development balloon to weeks and even months in the latter stages.
  • In a handful of cases, development organizations start using tools (whether open source or not) that Operations does not have the skill or personnel to support.

Quite a few companies treat DevOps and Operations as separate from development. Most don’t treat DevOps as a function but as a team. DevOps teams with managers are just another silo and a significant number of people think they do DevOps just because they have a team called DevOps. Even worse, I’ve far too often seen QA, Automation, and Development as separate groups with their own goals and agendas. Throw in the fact that different vendors (often competing for additional business) often perform each of these activities and you just make the situation worse.

So, here are a few things to think about:

  • How can we change the mindset of the folks doing and managing the second half of the activities to be more agile?
  • How can we create a true DevOps function, where the business, development teams, and operation staff collaborate from the start? How do we break down the boundaries between these roles?
  • How can we encourage larger organizations to start their agile journey with aligning on a DevOps strategy quickly and improving the DevOps function to immediately address the huge delays and waste?
  • How can we make it easy for developers to request and get environments to build and test against?
  • How can we help companies recognize that a repeatable infrastructure and application deployment process is extremely necessary?

We would love to continue the discussion and talk about our experience in making Agile work for DevOps. Please reach out to us (Jon at 702-389-8160 or Alex at 949-667-1008), or if in Las Vegas, attend a DevOps centric meetup (more information at http://hatech.io/community.html#meetups).

 
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Posted by on February 20, 2017 in Agile, Improvements

 

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Increasing Predictability

The previous two blogs (3 things that matter when embarking on an Agile transformation and five stages to organizational agility), listed Predictability as an important initial step on the journey to Agile at Scale, where, predictability implies the ability to accurately answer, “When will it be done?”

Smooth flow — the effective, efficient, and sustainable paced delivery of customer value — and predictability go hand-in-hand; you cannot have one without the other. Uneven flow is usually discerned, on your cumulative flow diagram, by large buildups of work somewhere in the process.

Impediments are a major cause of uneven flow and lack of predictability; however, there are a number of other contributing factors. A partial list would include some of the usual suspects:

  • Backflows (defects and rework)
  • Starts and stops (do-wait cycles — delays between steps, task switching, people being pulled in multiple directions to work on different efforts)
  • Large work items and large batches
  • Work-in-process being canceled and being taken off the Kanban or Scrum board
  • Organizational silos and a lack of communication, cooperation, coordination, and collaboration across departmental boundaries
  • Lack of swarming within the “team” to complete work quickly
  • Scope of work being changed once it has been committed to (often by adding scope or acceptance criteria)
  • Dependency on external vendors or teams
  • Hesitancy in roadblock removal
  • Overtime (initial increase in rate of work completion followed by a decrease due to burnout)
  • Mismatch between available skills and the task complexity
  • Variability inherent in the work itself

To the above, you could also add a couple of other non-readily visible causes:

  • Expediting some items to the detriment of other items — e.g., items in an expedite lane being given preferential treatment, thereby, slowing down all the other work in-process items
  • Non-FIFO implementations (where teams cherry-pick items from their process queues to work on) prioritize some items over others. This results in the non-preferred items taking longer to complete than they would have otherwise, i.e., cycle times for preferred items have been artificially reduced at the expense of the other items.

And, of course, the biggest culprit of all:

  • Mismatched input and output rates that cause work-in-process (WIP) to constantly increase and Cycle Times to lengthen. Ideally, your CFD should have parallel and narrowly spaced, arrival and departure lines.

While one of the main tenants of Lean is waste removal, sustained waste removal is not possible without the ability to first see the waste. Similarly, improving flow is difficult without first being able to see what is impeding flow.

To start your journey to becoming more predictable, do the following:

1. Visualize the work flow

Understand the scope of your system and the activities that help convert the inputs into the desired outputs:

  • Create a flow diagram
  • Identify the boundaries of the system (the input/entry and the output/exit stages) you are concerned with improving
  • Identify the steps and each step’s input, output produced, and policies (conditions of doneness)
  • Identify the Definition of Ready, Definition of Done, cadences, and event triggers

2. Capture data

Agree on what flow and predictability related metrics make sense in your context and then determine what data to capture and where to get that data from. Understand where things currently stand by getting baseline numbers for these chosen metrics.

3. Implement tactics to limit causal factors

Brainstorm, discuss, agree, and implement tactics to limit causal factors to unpredictability and irregular flow:

  • Mismatched rates of incoming work and completion of work
  • Instability of teams (their composition and number)
  • Lack of clarity of requirements and when to implement them
  • Scope creep for in-process work
  • Starts and stops
  • Delays due to waiting (for work to be done)
  • Work being canceled while in-process
  • Arbitrary aging due to blocks, excess WIP, and poor pull (including non-FIFO and expedite)
  • Overtime to compensate for excess WIP and mandated artificial deadlines

An output of this step should be a list of explicit process policies that address the above mentioned. Additionally, an agreement on how the whole team will handle defects, rework, and canceled work on their Scrum or Kanban board will go a long way in reducing confusion and waste.

4. Get to a stable, WIP-limited, pull-based, system

Get to a point where your Cumulative Flow Diagram indicates smooth flow via parallel and narrowly spaced, arrival and departure lines. You do this by tackling the factors that inhibit flow and predictability (item 3 above).

Remember that some variation always exists (and always will) within your system and can be seen in your story completion time scatter plots. Your goal, therefore, should not be to drive out all the causes of variation completely, but to identify and understand the special-cause variations that make your process inherently unpredictable. You can then take actions to address these special causes.

5. Improve flow continuously (start reducing time to market)

Once you have a stable system, from Step 4 above, you are then ready to experiment to improve the process and to increase your ability to rapidly respond to change. A stable, well-running process is necessary even if you are in a lean startup environment where you are trying to figure out your market and making sure that you are building the products your customers want — a smooth and dependable process will give you the confidence to change direction quickly without worrying about delays. Predictability and Adaptability are not mutually exclusive – you can have one with the other.

While Step 2 provides an initial indication of where you are starting from, Step 4 provides a solid baseline for you to base your improvements on. Every improvement you now make should be to improve the baseline measures. For example, if you think that adding an Expedite swim lane is necessary to address emergencies you can track the change on approximate average cycle time and actual throughput to determine the efficacy of the intervention. Likewise, you can gauge the impact, on delivery, of introducing Classes of Service and treating them differently.

Hopefully, the above will help you in your agile transformation journey. Comments and further conversations welcome.

 
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Posted by on February 8, 2017 in Agile, Coaching, Improvements

 

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Five Stages To Organizational Agility

Building on the previous blog post about the importance of focusing on and continually improving flow, quality, and value delivery, we can turn to the stages to achieving organizational agility. Achieving organizational agility involves deliberately improving the following (in order):

  1. Visibility
  2. Predictability
  3. Time-to-market (Flow)
  4. Value / Outcome driven
  5. Organizational Agility

All steps are underpinned by cycles of: assessing, defining the improvement strategy, training, and coaching.

1. Visibility

Visibility presupposes a culture of transparency, openness, and safety (protection from retribution and loss of reputation, health, money, and relationships). Without such a culture, you will not have true visibility and visual management will be a sham. Michael Ballé, in The Lean Manager, defines Visual Management as “seeing together, so we know together, so we can act together.” When information is hidden, people cannot see together and are likely to act in sub-optimal ways.

2. Predictability

With clear visibility you can begin to gauge and improve the predictability of your overall process. Predictability implies the ability to accurately answer, “When will it be done?” Making your processes more predictable and being able to reliably and consistently meet delivery commitments is the first step in building trust with business partners, stakeholders, and customers. Predictability can be gauged by studying Cumulative Flow Diagrams and work item completion cycle time scatter plots. These give you a baseline from which to start your improvement efforts.

It is important as a first step to regulate the arrival rate of new work to the completion rate of work by the teams. Work should not be started at a faster rate than work is completed. If it does, then you are faced with a situation of ever increasing work-in-process (WIP) and lengthening cycle times — the perfect recipe for increasing unpredictability. Stabilize the system (i.e., prevent cycle times from increasing) to have any hope of achieving the goal of predictability.

3. Time to Market (Flow)

Once you have a baseline and a sustainable stable system, you can begin experimenting with a view to increase flow and predictability. A fundamental approach is to begin by removing impediments. Use the scientific method. Determine what to improve, propose a hypothesis (an impediment to remove), plan the implementation, define expected outcomes, implement the change, compare the actual results to those expected, and then determine next steps: persevere, pivot, perish (or kill).

Improving flow (to shorten the cycle to discover ideas, develop and deliver solutions, and validate learning) can be discerned by the increasing rate of progress of work items from left-to-right on the team’s work-flow visualization board and by the lack of large buildups of work somewhere in the process. Flow is enabled by ensuring alignment around intent while granting autonomy around actions — state the goals clearly, but let teams navigate towards the goals by determining the best approach locally.

4. Value- or Outcome-Driven

While value is important, it has been mentioned fourth for a reason. If the delivery system is broken, inefficient, or unpredictable, it makes little difference what is fed into that system or in what order. With a stable, smoothly flowing, system you can now really start focusing on ensuring that you are providing the most value possible.

Improve your capability to define and deliver working solution increments that meet customer needs and solve their problems. Use a clearly defined purpose and these sequenced increments to align business, technology, and operations. You will now likely run into challenges with how funds are budgeted and allocated to projects and/or products. Having conversations with Finance about alternate approaches will now be much easier because you (IT) already have a track record of execution and predictable delivery.

Being value- or outcome-driven implies building the right thing, being focused on product rather than execution, and having the skills to figure out earlier what to make. Start with the end in mind then ask, “What experiments can be run to affect the outcomes?”, “What capabilities do we need to develop to realize the outcomes?”, and “What behaviors do we need to develop?”

5. Organizational Agility

There is a laser focus on identifying measurable goals, determining probable success factors, identifying necessary conditions for those factors to occur, and implementing a plan that helps create the required necessary conditions. Leaders are proactive in designing organizational structures, rules, and policies that enable agility throughout the organization. Agile practices have permeated the culture and have eliminated most or all of the business pain points. Finance, budgeting, HR, and governance groups are all agile and can work with agile artifacts for satisfying audit/governance needs.

Everyone understands the dictum that “Lean is not about removing waste but about problem solving towards a vision!” and without prompting continually strive to improve himself, the process, and the organization. This is also where leaders can set challenging goals for teams and help them improve via self-development learning cycles.

An Approach to Achieving the Agile at Scale

Table 1 provides a little more information on steps 2-4 discussed above for improving your organization’s ability to deliver value to customers. Over time move from Level 1 to Level 3 for the three areas: Product, Team, Management.

3-step-approach

Table 1. Steps to realizing Agile at Scale

This journey is not easy and can easily take you a couple of years or more to become truly nimble and customer-focused. There is significant additional detail about the practices recommended and behaviors required for each of the nine cells above.

Conclusion

While this blog provides a high-level view of the approach we recommend, it doesn’t go into all the detail needed to move from stage-to-stage (visibility to predictability to flow, etc.), what aspects to pay heed to, and how to sell and implement the changes.

We would love to continue the conversation with you. Reach out to us if you’d like more information or if you think you aren’t seeing the business benefits you had originally envisioned before starting on your agile journey.

 
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Posted by on February 8, 2017 in Agile

 

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