Understanding the basics of Lean Thinking

In their book Lean Thinking, James Womack and Daniel Jones summarized the five principles of Lean Thinking as follows:

Precisely specify value by specific product, identify the value stream for each product, make value flow without interruptions, let the customer pull value from the producer, and pursue perfection.

These five principles – value, value stream, flow, pull, and perfection – form the foundations of Lean Thinking. In this section, we will explore each of these five Lean principles in some detail. Before we get into the details, however, let's start with the basics.

The original concepts of the Lean movement were born in the Toyota Motor Company and are maintained by Toyota to this day in what is now referred to as the Toyota Production System (TPS). Toyota continues to promote the guiding principles of Lean and its managerial approach and production as a philosophy called The Toyota Way.

The founder of Toyota, Sakichi Toyoda, his son Kiichiro Toyoda, and industrial engineer Taiichi Ohno are credited with creating the initial Lean manufacturing concepts, which were then referred to as Just-in-Time (JIT) production or JIT manufacturing.

Classifying types of waste

At its most basic level, Lean Thinking employs methodologies to dramatically improve the efficiencies and throughput of business and production processes through the elimination of all forms of waste. The Japanese word Muda means waste and is often used in that context when discussing Lean production concepts.

For of this book, we'll use the English word waste going forward. In the context of Lean Thinking, waste is any form of human activity that employs organizational resources but creates no value in the eyes of the customer.

Taiichi Ohno identified the most common forms of waste as follows:

Lean thinking embodies these same categories of waste to this day. Although, an eighth category was later added to refer to the waste of unused human talent and intellect. The elimination of waste is the defining characteristic of Lean Thinking.

As mentioned at the start of this chapter, the five primary elements of Lean Thinking are value, value streams, flow, pull, and perfection. Before we look at these principles in detail, in later parts of this chapter, let's start with a quick introduction to each term.

Introducing the foundational principles behind Lean Thinking

Value is defined as what our customers want – usually expressed as goods or services. Value is not simply what we can deliver or what our markets or competitors are delivering, because those items may not be the things that customers really want. Value is an assessment of the whole product and the definition of value is subject to continuous refinement as customer needs and competitive factors change over time.

The term solution is a more accurate representation of what value is as opposed to the terms products, goods, and services. The term solution implies a product or service that specifically addresses identified end-users and customer needs, and not simply filling a niche.

Finally, the concept of value in Lean looks at costs from the perspective of what the lowest total price can be if all waste is eliminated. A more traditional approach to pricing is to assess what customers are willing to pay, reduce that number by the desired profit margin, and then work backward to estimate the highest costs the organization can tolerate However, organizations that simply focus their process improvement activities on meeting current customer and market pricing expectations will find themselves at risk from competitors who strive to do better.

Value streams include all the seller's activities or tasks from the start of value creation until the delivery of value in the form of products or services to end-user customers. Every product or service has multiple value streams defining how the products and services are conceived and designed, how they are produced, how they are sold and ordered, and how they are delivered to customers. Moreover, large and complex solutions may involve value streams extended across their external suppliers and solution delivery partners.

The goal of every Lean effort is to make each value stream as small and efficient as possible. In other words, value streams should have the least possible number of steps, use the least amount of resources, and take the least amount of time possible. Value stream analysis requires the identification of all activities from the final delivery of a product or service backward through all delivery, production, order taking, and design processes. Large and complex products with multiple components may have multiple value streams that span delivery, production, order taking, and design processes for each component.

Value streams consist of two types, value creation and value delivery. Value creation includes the activities to design, engineer, test, and produce a product or service that people want. Value delivery includes all the activities necessary to satisfy the customer and improve their experience in acquiring and using the product or service. For example, order processing, inventory management, supply chain and partner management, fulfillment, distribution, warehousing, transportation/delivery, product support, and product maintenance are all forms of value delivery activities.

As you go through this chapter, you will find that many of these activities include huge amounts of waste that need to be aggressively eliminated. The lean organization constantly challenges whether each activity is necessary and, if it is, whether it can be simplified and streamlined.

Flow is an expression of efficiency spanning value creation and value delivery activities. Flow includes the movement of materials, components, and finished goods, resources, and information. Batch processes, mismatched production rates, queuing, and delays for any reason are all a nemesis of efficient flows across value streams. Improving the effectiveness of flow is what makes it possible for small and efficient value streams. Improvements to flow reduce both development and operational costs and time to deliver, while simultaneously improving quality.

Flow is improved in a stepwise fashion, as follows:

Pull is a value stream scheduling approach that reduces Work In Process (WIP) by enforcing a simple rule that downstream activities take in new work only when they are ready. Materials and components are never pushed from one value stream activity to another. Instead, a value stream activity can only pull new work into their area when there is a customer requirement and they have the capacity to immediately start the work.

From a practicable standpoint, this means downstream activities can take in work only after a customer has submitted an order and the preceding upstream activities have completed their work and signaled that new work is available to the downstream activities. When those conditions are met, the downstream value creation/value delivery activities are allowed to pull the existing orders in for processing.

Relatively speaking, in the context of Lean, upstream activities are those that are closest to the provisioning of raw materials and the start of value stream production processes. In contrast, downstream activities are those that are, relatively speaking, closer to delivering the product or service to customers. So, if we specify an activity in the middle of a value stream, as shown in Figure 5.1, upstream activities precede it, while downstream activities follow:

Figure 5.1 – Upstream versus downstream activities

This pull-oriented approach is in contrast to a traditional approach where orders are pushed into production immediately upon order entry or to fulfill expected demand, whether there is the capacity to start the work or not. Pushing work into a value stream process will only cause queues and delays that mask defects that ultimately increase non-value-added reworks and scrap, add carrying costs, and introduce excessive process complexities and inefficiencies.

Perfection is always sought but never quite achieved, but is still a tangible goal to obtain. In previous chapters, we spoke about using retrospectives as an approach to continuously look for ways to improve our software development activities continuously. Similarly, early Lean practitioners discovered early on that no matter how much they improved their value stream activities, they always found new areas for improvement.

The drive for continuous improvements makes sense when you recall the 80/20 rule (a.k.a. the Pareto Principle) discussed in previous chapters. When we look at the cause and effects of any activity or set of activities, we find that roughly 80% of the effects impacting our systems come from ~20% of the identified causes. If we fix the most impactful 20% of influences across our value stream and run a Pareto analysis, the same 80/20 rule applies to the new set of identified causes and effects. Continued retrospectives will always lead to the discovery of new impacts and causes to address, with the team incrementally improving performance over the duration of their charter.

But another important aspect of seeking perfection is that the failure to pay constant attention to identifying new areas for improvement leads to complacency. Such complacency will always lead organizations and teams to backslide to inefficient and error-prone practices.

Lean practices are substantially different than the traditional business practices that largely facilitated the United States' growth and dominance in manufacturing industries until the 1970s. However, a competitive global economy – led initially by Japan, but later by other nations that adopted Lean practices – forced U.S. manufacturers to respond in kind. Now we can find Lean practices applied across industries in the United States and across the World.

Now that you understand the basic principles behind Lean practices, we need to take a quick look at the benefits of Lean. This is the subject of the next section.

Profiting from Lean practices

As discussed in the previous sections of this chapter, Lean Thinking is a business enhancement approach that seeks to eliminate all forms of waste while also ensuring the organization stays focused on providing enhanced customer value. At their most basic level, Lean practices evaluate value-creating actions to dramatically minimize the size, non-value-added activities, and complexity of identified value streams.

The benefits of Lean include the following:

Determining value

Placing a focus on value is the first and most critical step in Lean Thinking. Value is not just about product features and functions. It requires the organization to look beyond producing what they or their competitors already produce and instead constantly look for ways that positively change the customer experience throughout their value creation and value delivery activities. Adding value is hard work and takes imagination because virtually everything in an organization's value chain contributes to value.

Value is defined in terms of specific products and services, useful product variants that fulfill niche market needs, specific capabilities provided by each variant, prices as evaluated by the customer, and the satisfaction of the customer experience from product awareness, through order entry, delivery, and support. Because value has such a broad scope, the surest way to fail is to build a product based on our ability to leverage existing facilities, processes, equipment and tooling, and resources. Simply put, the focus is on the wrong thing.

The focus always has to stay on the customer, and what they want. Then we must evolve our facilities, processes, equipment, and resources to deliver what they want. The evolution may not occur overnight, but every incremental change we make along the way improves our value, and subsequently our competitive average.

Organizations that choose to improve value can start by identifying the following elements of their value streams:

In other words, the organization must completely understand the process of product conceptualization and design, demand creation and order handling, and product development and delivery. These three areas encompass the central value streams of Lean.

Later, in the section on Flows, we will see that it may make sense to subdivide these value streams into smaller increments. But for now, to establish a foundational understanding of adding value, it's easier to focus on describing these three higher-level value streams.

Designing to value

A useful concept to understand and implement Lean practices is design to value. Design to value includes the specification of requirements and designs that maximize value as defined by the customer.

In a traditional sense, design to value is a marketing function that involves market research, competitive intelligence, product differentiation, branding, defining the customer experience, and often the inclusion of focus groups and prototyping to test out various product concepts. However, under Lean practices, design to value goes beyond the definition of product requirements and designs and includes the full spectrum of value creation and value delivery activities that ultimately define the complete customer experience.

In other words, the organization designs to value all value stream processes. Any weakness in any value stream can negatively impact the customer's perception of value.

Just think about this logically. We can build a product that meets every customer need. But if they don't know it exists or don't know how to buy it, what good is it? We can build the best marketing campaigns to promote our new product, but if it fails to deliver value as perceived by the customer, they won't buy it. And, if we build a good product and promote it well, we could still mess things up by failing to price it correctly or failing to deliver it promptly.

Therefore, value is an all-encompassing concept that looks across value streams to ensure we are delivering the right product, at the right time, to the right customers, at the right price, with the right delivery and support services. If we do these things well, we will establish a competitive advantage that cannot easily be surmounted by our competitors – unless we stop looking for ways to constantly improve upon value.

In conclusion, the achievement of value is not an instant process. It's not even an end goal. Rather, the achievement of value is a constant journey and an evolutionary process.

Now that we have a deeper understanding of what value is, we can move on to understand how value streams affect our ability to deliver value. That is the subject of the next section.

Understanding the value stream

The analysis of our value streams is the second step in Lean Thinking. A value stream is the set of all specific actions required to bring a product or service to the customer. In the previous sections, we spoke of three critical value chains an organization must identify and analyze. Let's take a look at those three areas in a slightly different manner.

Identifying the states of value

As with the identification of value, analysis is required to truly understand the dynamics and scope of work involved in each value stream. The organization must identify the value streams for every product and every product family with the goal of exposing and eliminating all forms of waste. During this analysis, the organization can expect to find three states of value across each of the activities they identify and analyze. These three states are as follows:

The best-case scenario for an activity is of course that it adds unambiguous value, which is the first possible state. In other words, the activity clearly and provenly provides capabilities that a customer is willing to pay for. In this situation, there is no need to change anything.

In some cases, technology limitations or investments in existing capital may add waste to an activity, but realistically the organization does not have a viable approach to address the issue in the short term. This is the second state of value where there is non-value-added waste. In the Toyota production system, this type of waste is referred to as Type I Muda. While this type of waste is non-value-adding, the activity is required – at least in the short run – to support our customer's needs. Over time, as technologies and economics permit, the organization may be able to eliminate some or all of their Type I Muda.

The third possible state is that an activity provides no value to the targeted customer. In the Toyota production system, this type of waste is referred to as Type II Muda. This type of waste must be eliminated as soon as possible. The elimination of Type II Muda provides the quickest opportunity to improve the value of a product or service.

As you conduct value stream analysis, don't forget to look across all third parties that participate in your value stream, including suppliers and partners. This should be a collaborative and voluntary effort to remove all waste in the value stream. If your value-stream partners do not see the value in eliminating waste or helping your organization improve your value stream, then start looking for new partners.

Providing transparency across your value streams

A Lean enterprise is an entity that seeks to eliminate any activity that does not directly contribute and add value to the products and services it develops and delivers. Lean development places the focus on value creation and the elimination of waste and unnecessary activities. While some entities may practice Lean development in an ad hoc manner, the Lean enterprise installs the principles of Lean development as the foundation of its culture.

The hallmark of a Lean enterprise is complete transparency and efficiency across the value stream, including the activities supported by external partners and suppliers. If your suppliers are unwilling to participate in a value stream analysis activity, then perhaps they're not the partners you should be working with. Also, if you're partners and suppliers are not open to being completely transparent in their activities that support your value stream, they too are probably not the right set of suppliers and partners you should have going forward.

Now that we understand the basics of analyzing value streams, we need to expand our understanding of how the flow of objects across value streams impacts our assessments and our value. This is the subject of the next section.

Identifying and improving flows

The third step in Lean Thinking is to identify flows across the value streams. Flows are identified in terms of objects that participate in the activities across each value stream. The objects can be information, raw materials, resources, components, and finished goods.

In traditional business models, organizations often aligned resources around functions and departments. The thought behind these practices is that functional and hierarchical organizational structures lead to better management and more efficiencies by logically grouping resources and skills around specific business or technology processes. In actual fact, the opposite is true. The movement of work through functional departments and hierarchical organizational structures creates a number of problems. These problems include the following:

When organizations align their resources by functional departments, there is a tendency to seek economies of scale through the procurement of high-capacity equipment and large-scale production processes. This is the antithesis of Lean Thinking, where the ideal goal is to build each product one at a time, just in time, and in the most efficient and rapid process possible. Instead, large-scale production processes and equipment become behemoths that need constant feeding and attention, and thereby become barriers to efficient production flows.

Feeding the monster

Since the organization may have a number of functional departments, each individually optimized around the tools and technologies they employ, it's virtually impossible to match their production flow rates. As a result, products that move into the functional departments often sit in a queue until an economically efficient volume of work is ready for processing and the equipment is set up for the new batch run. Anytime we have queues and delays, we can expect to see higher levels of defects, the result of which is increased reworks and scrap, and extended production cycle times.

For example, materials that accumulate in queues before processing may hide any number of defects. The defects cannot be found and fixed until they move on to downstream processes. When they do move, a shop may find they have a batch load of defective products.

Also, large-scale and batch production processes base their efficiencies on the volume of products that can be handled simultaneously. Intuitively, it may seem that a batch production process is more efficient than a process that can only work on one product at a time. However, products accumulating in queues, simply because they are waiting on enough products to economically run the batch process, adds to the overall time it takes to get the final products finished and ready for delivery.

There is also a tendency to want to feed these monolithic systems, whether there is customer demand or not. After all, the organization has invested heavily in these large-scale systems and the executives and managers will feel a great deal of pressure to keep them constantly busy and running at their most efficient capacities. But busywork is not necessarily – in fact, probably is not – value-added work.

As a result, an organization so aligned may not see value in expending time and resources to simplify tooling and reduce setup and changeover times as they represent a relatively small amount of the total time involved in the overall batch production process.

In contrast, Lean Thinking seeks to eliminate batch production and concentrate on developing efficient flows and developing products on a JIT basis to meet current customer demands. This means that the objective of Lean processing is to eliminate batch processes while simultaneously reducing setup and changeover times.

It is difficult for a manufacturer to walk away from investments they have made in expensive large-scale manufacturing processes and equipment, and so they may instead be inclined to keep their existing equipment and run it with smaller batch sizes. However, there are two problems with that strategy. First, the batch equipment is not likely economical to run with lower batch sizes. Second, if the manufacturer produces multiple product lines and product variants, the changeover and setup times become significant factors in terms of lengthening the overall production cycle times associated with the smaller batch sizes.

The bottom line is that corporate investments in large-scale production assets add to the resistance to change over to Lean practices. Moreover, the executives and managers of those facilities may not fully understand the production inefficiencies caused by their functional organizational structures and investments in large-scale batch processes.

Waiting, always waiting

Delays in production processing are a huge problem in the traditional model. There are several factors that contribute to delays, such as mismatched cycle times across activities, inconsistent batch sizes across disparate activities, significant setup and changeover times, and the impact of introducing multiple product variants across the same production lines. As a result, it's not uncommon, under the traditional model, for materials and finished goods to spend way more time sitting in queues than they spend undergoing the value-added production-oriented processes.

In addition, manufacturers need a place to store all this, accumulating inventories. As a result, the built-in delays from mismatched flows force the organization to spend money on the expansion of facilities to hold the increased materials. Compounding the problem, there are increased inventory carrying costs associated with procuring the additional raw materials that end up waiting in multiple queues along the length of the value stream. Finally, the queuing of materials and delays in work in progress hide product defects and errors, which leads to additional reworks and scrap, also contributing to increased costs.

Mapping the value stream

The concept of mapping value streams also originated in the Toyota Motor Corporation, though the concept was originally referred to as material and information flows. I prefer the latter term as every business manages the flow of both information and materials. The flow of information and materials is what we manage across a value stream. A value stream map provides a way to visually display and analyze the flow of information and materials across the organization, and their contributions, or lack thereof, to adding value.

In their book Lean Thinking (Womack and Jones, 2003), the authors describe value streams as a set of all specific actions required to bring a specific product (whether a good or service, or, increasingly, a combination of the two) through the three critical management tasks. They list these three management tasks as follows:

Problem-solving tasks – includes activities spanning product conceptualization through design and engineering to production launch

Information management tasks – includes all information handling activities required to take and process an order, and then schedule and deliver the product or service

Physical transformation tasks – includes all activities to transform raw materials into a finished product delivered to the customer

Value stream mapping is a useful tool to show the flows across each identified value stream across the three management tasks. An organization often creates separate maps to show the current state and the desired future state for each value stream. The objective of the contrasting value stream maps is to identify all forms of waste in the current state and show how they are eliminated when achieving the targeted future state.

For those readers who have further interest in this subject, there are a number of vendors who provide tools and templates as aids in value-stream mapping. There is not an overarching standard, particularly when it comes to value stream mapping symbols. So, my recommendation is to work with your organization to establish a governance body to determine standard tools, templates, and symbols.

In the next section, you will see a very simple map of a value stream and learn how the information is used to analyze and improve the flow within the value stream.

Identifying and fixing value stream flows

Figure 5.2 shows a basic sequential flow across a value stream consisting of five activities, from Activity A to E. The arrows represent the direction of flow. For this example, we'll assume no effort has yet been made to reduce batch sizes or match the rate of flow across each participating activity.

Looking at the data in the columns below each activity, we can see that Activity A can process two parts in 5 minutes for an average of 2.5 minutes per part. Following this logic across the remaining activities, we see Activity B has a flow rate of 3 minutes per part, Activity C has a flow rate of 2.5 minutes per part, Activity D has a flow rate of 1.33 minutes per part, and Activity E has a flow rate of 2 minutes per part:

Figure 5.2 – Sequential flows across a value stream

Based on this data, it should be apparent that the primary bottleneck in our system occurs at activity B, as its flow rate of 3 minutes per part is the slowest across the five activities. However, if parts are released into the value stream rate of 3 minutes per part or slower, we should not see queues of parts building at activity B or any of the other activities. This strategy ensures that the rate of entry of parts into the system does not exceed the ability of the system to handle the flow of incoming parts.

However, if parts come in at a quicker rate than 3 minutes per part, the parts will begin to queue at the slowest activities. For example, if the parts come in at 2.5 minutes per part, we should expect to see the parts begin to queue at activity B. If there are no limits placed on the work in progress, those incoming parts will continue to queue at activity B for as long as the organization allows assuming there is space to store the parts.

If we increase the incoming flow rate to 2 minutes between parts, our queuing problems become worse. Now activities A, B, and C cannot handle the load and parts will queue at all three activities. The best-case scenario, at least in the short run, is to limit either the incoming flow of parts to a rate of 1 part every 3 minutes to prevent the buildup of parts at any of the activities. At this rate of flow, the production through our value stream system is a constant 20 parts per hour.

In the long run, if the higher customer demand rate of two parts per minute is sustained, the organization must improve the efficiency of their value stream if they want to address the full demands of the market. That's the subject of the next several subsections.

Fulfilling increased customer demands

So, you may be wondering what you should do if customer demand is greater than the slowest rate of production? The short answer is you cannot fulfill market demands until you improve your production capacities and flows. Pushing in all the additional orders when you do not have sufficient capacity will make matters worse, that is, increased carrying costs for raw materials, increased production complexities and inefficiencies, the hiding of defects, and therefore increased scrap and rework.

If you are the only provider of the product, under the economic concepts of supply and demand, you may be able to raise prices and obtain a higher profit, even though you cannot fulfill all the orders. But that assumes you have an inelastic market. In other words, customer demand will not change markedly with increased prices.

In this case, you can safely produce up to your full production rates and use the excess profits to improve value stream efficiencies. These improved efficiencies will further lower your costs and you can thereby sell even more products at higher margins – until the competition steps in with a viable product at a lower price.

If you have an elastic market, where customer demand is highly correlated with changes in pricing, your only choice to capture the remaining market is to improve your capacity and production efficiencies. In other words, your customers won't pay a higher price, and the only way you can capture the larger market is to increase capacity while lowering your product costs. As we'll see in the next subsection, that may not be easy to do in the short run.

Matching demand and production rates

Going back to our example in Figure 5.2, let's assume customer demand supports a production rate of 60 parts per hour, that is, a flow rate of one part per minute. If we push parts into our value stream system at that rate, the parts will only queue at all the activities since none of the activities have the capacity to match that rate of flow.

The best long-term solution is to add capacity at each activity by streamlining and improving the efficiency of work at each activity to handle the flow rate of one part per minute. That will take some time and effort to achieve. In the shorter run, the organization may be able to add capacity in the form of new equipment and additional resources to achieve the desired flow rate of 1 minute per part. That approach comes at a higher cost.

Building in takt time

It should be clear that, regardless of the circumstances, the organization needs to limit the intake of new customer orders to match the production capacity of its slowest value creation activities. We accomplish this by measuring the takt time between the intake of customer orders matched to the total time available for production.

The term takt time was initially derived from the German word Taktzeit, which translates in English to cycle time or pulse time. The pulse time aspect of this term describes a precise interval of time, such as the rhythmic timing of music, while the cycle time aspect of the term came from the German aircraft industry in the 1930s as a production management technique to gauge the interval of time an aircraft spent between assembly stations. Toyota implemented the concept of takt time back in the 1950s and continues to employ the concept to this day.

From a mathematical perspective, takt time is calculated as the total time available for production divided by customer demand in terms of individual products or services. The equation looks like this:

Here, T = takt time; Ta = total time available to work; and D = customer demand in terms of units per time period.

In a single product situation with no product variants, the calculation is quite simple. Using the example cited in Figure 5.2, customer demand is 60 parts per hour, which is its takt time. But let's see how we got to that figure.

If we assume two 8-hour shifts per day, with a total of 18 full days and 4 half days, and no downtime, the total hours available for production are calculated as follows:

Ideally, the estimates for customer demand come directly from customer orders. For this exercise, let's assume the order backlog for the upcoming month is 19,200 widgets. We now have enough information to calculate the takt time:

OK, I cheated a bit in that I had already defined the takt time as 60 widgets per hour in the previous subsection. But you should now be able to see how I got there.

Changing over between product variants

Note that in this example we have not even discussed setup or tooling requirements associated with changing over equipment to build variants of a product. Those activities add time to each step of the value stream that requires a changeover. Moreover, the amount of time and resources devoted to the changeover accumulates with each product variant introduced into the production schedule, as measured over a specific period of time. Changeover and setup activities are a form of Type I Muda, unavoidable in the short term, but an area of improvement that we should address as soon as it's practical to do so.

To the greatest extent possible, the organization should set up individual value stream processes to accommodate unique activity flows to reduce, if not eliminate, setup and changeover activities. Also, we know that the organization should aggressively work to build capacity at each activity to match expected demand rates either by improving the efficiencies of each process or by adding capacity in the form of new equipment and resources to match the demand for each product variant.

One of the first books to demonstrate why a system cannot exceed its slowest activity in the production system was The Goal by Eliyahu Goldratt, first published in 1984 (Goldratt, 2014 – 30th-year edition). The book was written as a fictional novel, which made it an interesting and entertaining read. Here are two story-form but fictional books related to I.T. that discuss similar concepts: The Phoenix Project (Kim et al. 2016) and The Unicorn Project (Kim, 2019).

Managing the transformation to Lean Thinking flows

Many, if not most, markets are highly segmented with multiple niches having customers that prefer products with different features and options. In large-scale operations with batch processes, the introduction of new product variants can dramatically increase the amount of queuing and delays across value stream activities. The organization has to continue feeding its production monsters and production managers will resist slowing down production to support the setup and changeover required to work on new product variants. As a result, the tendency is to accumulate enough customer demands for each product variant until the volume justifies changing over the equipment.

In contrast, Lean Thinking seeks to implement the continuous flow of individual products across the value streams, at a constant rate, with virtually no setup or changeover requirements. Rather than implementing large-scale batch processing systems, Lean Thinking practitioners prefer lot sizes of one, with matched activity processing speeds, no delays, no cues, no non-value-added activities, and no requirement to move or transport parts or people between value stream activities. The infrastructure within an existing business may be a long way off achieving these goals. In truth, there is no short-term solution to address the business transformation problem to implement Lean Thinking concepts.

The most ideal situation is to implement Lean Thinking before the organization makes significant investments in capital equipment and value stream processes. Nevertheless, that's not the reality for most existing organizations. Depending on the business situation, the organization may choose to implement Lean Thinking concepts in support of developing and introducing new product lines. But if the organization is facing competitive pressures and financial troubles, they may have to move aggressively away from their existing processes and systems.

Moreover, when an organization is facing a crisis, they must look at their previous investments as sunk costs. In other words, their previous investments cannot be refunded or recovered, and the organization must be willing to walk away from equipment and processes that prevent them from being competitive. It may be possible to reduce setup and changeover times and improve operational efficiencies sufficiently to extend the life of some of their production equipment. But the longer-term solution is to invest in developing flexible value creation and value delivery systems that are efficient and Lean.

Likewise, the organization must move away from suboptimal organizational structures built around functional departments and instead align their assets and resources around the creation of value. The existing organization must work diligently to connect and aggregate activities and resources to optimize the flow of information and materials across value streams to improve their value creation and value delivery capabilities.

Furthermore, the organization cannot stop its efforts to implement Lean practices at the boundaries of the organization. Instead, the organization must assess value stream activities across the entire value chain, to include third-party suppliers and partners. In other words, the components, subassemblies, services, and information provided by external parties that contribute to the development and delivery of the final solution are all included in the whole product concept of Lean Thinking. Therefore, value stream analysis has to reach across the activities of those third-party contributors.

Obtaining buy-in across the enterprise

Organizations that choose to implement Lean Thinking principles must avoid disruption in business functions and reduced morale among employees during the transformation. Organizational resistance is a real phenomenon that must be addressed. Much of what an organization does is embedded in its culture, and people working in that environment often perceive their value, roles, and opportunities through the prism of the cultures they work in.

A practical approach to building buy-in among employees and other stakeholders is to help them reimagine their work as contributing to value creation and value delivery activities, as opposed to denigrating past practices or their previous contributions to the organization. They must see themselves in the Lean enterprise as valued and empowered employees who can make a difference and have a positive impact. It is, after all, to their benefit to support the development of a viable and profitable organization. Employees will feel more inclined to support a change to Lean practices when they know they have a direct and important role in the organization's future.

The successful Lean enterprise rethinks existing conventions, organizational structures, business functions, and career progressions around product line value. When the employees, contractors, and suppliers believe they are important to the long-term success of the business and will be valued for their efforts, they will support the transformations to create and deliver value-based products and services. Alternatively, if they feel their jobs are at risk, they will resist or leave.

It's important to note that the installment of Lean development practices across an enterprise doesn't happen overnight, and neither does overcoming organizational resistance. Largely, people want to be part of successful activities and organizations. And therefore, people will adapt and adopt over time as the new Lean development strategies prove successful.

While it is possible to adopt a Lean development practice across a single product line, it's not likely to stick if that's as far as the organization is willing to go. Executives and managers will view the effort as out of line with their mainstream practices. It's better to have executive sponsorship and make any initial changes part of a longer-term adoption strategy.

Smaller organizations can look across their product development streams and begin to align and synchronize their process flows, and reduce activity cycle times, to quickly obtain better efficiencies while simultaneously ensuring they are building the products their customers want. Those successes will help drive similar improvements in the value delivery streams.

Larger organizations may start out with reorganizing production facilities along high-value product lines and then begin to work on the synchronization and coordination of flows and reducing cycle times to eliminate bottlenecks. Over time, other product lines and value delivery streams can begin to work on improving their activities.

But no matter the size of the organization, continuous improvements are the norm in Lean development, not the exception. Cultural change must ultimately occur to help make Lean stick within the organization.

Moving from Push to Pull oriented deliveries

In our initial discussions around the example described in Figure 5.1, we assumed a push scenario where the organization allowed customer demands to set the rate of flow through the value stream. That is not an ideal scenario and is made worse as additional product variants are introduced into the value stream, each having different flows, setup and changeover requirements, and activity processing speeds.

Pushing parts into a value stream based upon customer demand causes issues when capacity is not sufficient to meet demand. Even if capacity exceeds demand, it's still a bad practice to fill a shop with work simply to prevent the idling of equipment and people within the facility. You may end up building products customers never want. In the meantime, you are spending money on things that you can't sell. It's better to limit the introduction of new work into the facility based on capacity, as set by the slowest activity in the value stream, up to the limits of proven customer demand.

The best approach to limit work into a facility is by implementing a pull-based order entry strategy, which is the subject of the next section.

Changing from Push to Pull

The fourth step in Lean Thinking is to move from Push to Pull oriented systems. Pull processing supports three important Lean objectives:

A Lean enterprise eliminates the traditional paradigm of pushing products to market based on estimates of customer needs or to reduce inventories of products made due to excess capacity. Instead, the Lean enterprise pulls work into production when capacity is available and limited to actual customer orders or proven demand levels. A push-based production system exists solely to maximize the economies of scale across functionally aligned and large-scale batch processes. But, as noted in the previous section, feeding these production monsters does not come without inducing serious and unintended consequences.

Managing production rates

The problem with push-oriented systems is that it's very unlikely input flows will match production capacities, or that production capacities will be matched across the value streams. Also, push-based production systems evolved to feed the monsters so as to achieve maximum economies of scale across large batch processes. Tending to those monsters are teams of highly skilled specialists, which makes it more challenging to align resources around value.

This concern should be pretty apparent from the Figure 5.1 example in the previous section. And that example is actually relatively simple. Imagine working in a machine shop that must produce any number of parts and product variants, each of which has a different setup and changeover requirements, different production rates, and also different flows through the shop. Pushing parts into such an environment quickly introduces production complexities and queuing that are impossible to predict and address.

The previous discussions on flow demonstrate that one part of the solution is to define value streams with predictable flows across similar product variants and set up the production processes and equipment accordingly, and to minimize setup and changeover requirements. That's only half of the solution. The other half is that we must limit demand to the minimum capacity of the value stream activities. The best way to achieve that goal is the implementation of pull production concepts.

Recall from the Figure 5.1 example that the slowest production process was Activity B at a flow rate of 3 minutes per part. That is the maximum rate that value stream can support. Any attempts to introduce new objects into the stream at a faster rate will only result in the formation of queues and subsequent production delays.

Early Manufacture Resource Planning (MRP) systems attempted to address the scheduling problem by maintaining accurate records of orders, inventories, and production sequencing information. But they were push-based systems that only exacerbated the queuing and delays associated with batch processing. Instead, the manufacturing facilities needed an approach to pull work into their operations only when capacity becomes available with materials and order information made available JIT to sustain an efficient flow.

Processing work just in time

The fix to these sorts of problems came with the implementation of JIT concepts, first introduced by Taiichi Ohno at Toyota. First and foremost, JIT addresses the issue of flow with a concentrated effort to align value stream activities with the goal of implementing efficient flows and minimizing setup and changeover requirements between product variants. The next step is to implement level scheduling concepts, which simply ensures information or objects are not introduced into the value stream any quicker than the slowest activity that can accept them.

But if we have multiple product variants flowing through a value stream, each with different activities, flows, and flow rates, how can we determine the optimal flow rate for the system at any given time? To manage flow rates in such an environment, we need an effective way to visualize and control work in process. This flow-rate sequencing strategy is what pull-based production systems accomplish.

Pulling work on a first-in, first-out basis

Pull-based production systems implement a first-in, first-out (FIFO) production scheduling philosophy. In a product manufacturing context, this means orders come into the value stream for processing as they are received. The scheduling typically occurs at the beginning of a new shift, and the schedule consists of a list of each product requirement for each product variant, in FIFO order, plus the number of products required for each variant. The manufacturing facility then pulls those orders into the shop as production capacity becomes available in the downstream processes.

So, using our example from back in Figure 5.1, the operators at Activity A would see the new order list at the beginning of the shift and they would pull the highest-ordered item from the list to work on. When Activity A is completed, a visual aid – usually in the form of a Kanban card – indicates to the operators at Activity B that there is work that they can pull from Activity A.

Each Kanban card is a visual representation of a requested work item. The purpose of a Kanban card is to inform people in subsequent downstream activities to move, procure, or develop more of a component for delivery against a customer order. The Kanban card simply lists the information about the order and the product variant associated with it.

The data provided on Kanban cards can vary significantly, based on the unique requirements of each production environment. Basic information on a Kanban card often includes the part number, part description, quantity, lead time, the name of the supplier, the name of the scheduler/planner, bin location, order date, and due date.

In a traditional manufacturing environment, Kanban cards physically move with their associated work items. In modern Lean practices, a Kanban card may be information written on sticky notes placed in lanes on a whiteboard, with each lane representing a sequence or state of processing through the value stream. You'll see how the sticky notes work in Lean software development practices in later sections of this chapter. But before we move on to discussing the application of Lean practices to software and systems development, let's finish this section with an expansion on the Lean concept of continuously seeking perfection.

Seeking perfection

Seeking perfection is the fifth and final step in Lean Thinking. Conceptually, in Lean Thinking, perfection is the elimination of all waste while providing maximum customer value. At this point in time, the organization has implemented the first four elements of Lean: defining and delivering value, value stream identification, balancing flows, and pulling work in lockstep with customer demands. Now we need to make sure we keep improving.

At a more granular level of understanding, the organization has developed systems and processes to fully understand what customers value; the organization has identified their value streams that support value creation and value delivery activities they have structurally reorganized their functional departments and batch processing systems to support continuous flow along the value streams; and the organizations have established pull-based scheduling mechanisms to match demand to its production flows and capacity.

But there is always more that can be done to improve value and value stream performance. And that comes with improvements through the continued discovery and elimination of waste. That is, recall that waste is defined as any activity that consumes resources but creates no value for the customer.

Producing something that customers don't want is a form of waste. You've also learned that other common forms of waste include waiting, overproduction, extra-processing, transportation, motion, inventory, and defects. The continued discovery and removal of waste in all these areas is how we travel the road to perfection.

Finding perfection is a journey, not a destination

With all the work that has been done to understand value in the eyes of the customer, identify our value streams, improve the flows across our values streams, and pull work in at a rate equal to customer demand, it's tempting to sit on our laurels and think we are done. But we can still do better. This is the underlying concept behind the Lean principle of continuous improvement – the reality is we are never done!

For example, it's a certainty that customer preferences and needs will continue to evolve over time, which will change our customers' definitions of value. Also, following the principles of Pareto analysis, we can continue to look at the leading causes of bottlenecks, failures, and defects in our systems to make those activities more efficient, thus improving our production flow rates and efficiencies across a value stream.

Continuous improvement takes time, energy, and resources, but it's critical to the long-term success of the organization. In practical terms, the more we continue to improve, the less likely it is that a competitor will be able to find a way to leapfrog our production capabilities or offer more value.

Finding waste through transparency

Another critical enabler to seeking perfection is the concept of transparency. This concept was discussed in Chapter 3, The Scrum Approach, albeit in a slightly different context. In Scrum, the concept of transparency is that all information should be made freely available to all team members, executives, and other stakeholders. The goal is not to hide issues but rather bring them to light so that everyone can get involved to eliminate the impediments that are preventing the team from achieving its goals.

In Lean Thinking, transparency gives the organization access to the information it requires to accurately assess customer value and value stream efficiencies. So, the concept of transparency has similarities in Scrum and Lean Thinking, though the point of reference is somewhat different, that is, eliminating impediments versus improving value and flow.

The concept of transparency in Scrum has a focus on providing visibility of information that is necessary to support the inspect and adapt elements of empiricism, that is, using empirical evidence through sensory experiences and experimentation to make sound decisions. In contrast, transparency in Lean is providing access to information that allows the organization to analyze all value stream activities in terms of enhancing customer value, that is, transparency helps identify waste. Nevertheless, in both cases, the act of transparency is what allows the organization to continuously improve.

There's another aspect of the Lean principle of continuous improvement that we need to understand if we truly want to seek perfection, and that is defining metrics that accurately define our current state and desired future state. In the next subsection, you'll learn some of the metrics that aid the Lean Thinking team toward their goal of constantly seeking perfection.

Defining the metrics of perfection

Truly, perfection is the goal from the very start of any Lean Thinking approach to improving value creation and value delivery activities. Many of the metrics that we use to assess value stream performance and measuring value do not change over time. In other words, many metrics remain useful for as long as the organization exists to create value for its customers.

We can assess progress from the very beginning of a Lean change initiative, as we begin to analyze existing capabilities when the organization is still functionally aligned around large-scale batch processing systems. We continue to measure performance as we work to align value stream flows and implement JIT capabilities with pull-based scheduling techniques. And, when we have achieved high value and value stream efficiencies, we continue to use those same metrics to assess the current state against potential future state improvements.

The following list shows some of the metrics that every Lean-thinking organization should track and seek to improve over time:

You should not view the items noted in the preceding list as the only metrics your organization will need. Every organization has unique business situations and needs and should always assess their activities in terms of value and efficiencies. During those assessments, other factors come up that need to be improved, and therefore measured and monitored.

When seeking perfection, the focus is not on the competition. That's a moving target, and you can likely improve upon whatever the competition is doing, anyway. Instead, compete against imperfections by improving value and identifying and eliminating all forms of waste.