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Table of Contents:

: Process Excellence

Overview

Process design mirrors the products and services that an organization produces. Disruptive trends and technologies directly impact business process design. In response to disruptions, business processes need to rapidly evolve to meet new market dynamics to transform how machines, people, information, and other resources are managed on a global basis. Work is changing. Customer experience is now central to how business processes are designed. Given the mobility of customer demand, which appears anytime and anywhere through mobile devices and other sources, business processes need to be agile to provide the customization and experience customers expect. Workflow automation is a critical enabler for process design and especially for customer facing and supporting processes. Algorithms with artificial intelligence increasingly optimize solutions for customers.

Process improvement also has been positively affected. Customers want solutions faster based on deep insights into well-designed processes using advanced analytics. Unlike previous project-focused efforts where data were manually and slowly gathered for analysis, the new expectation is that discovery and analysis will be completed in hours or days rather than in weeks or months, with effective solutions quickly following that analysis. Projects must be properly framed to focus crisply on the real problems. Solutions need to be focused on updates to information technology or RPA rather than on creating manual interventions. In parallel, continuous improvement projects within work groups are now identified and executed by highly skilled teams having the prerequisite analytical skills, including knowledge of data mining of large databases.

Digitalization is at the core of process excellence. Applications include master data management, modeling of different types, workflow automation through RPA analytics, as well as classic methods such as Lean, Six Sigma, and other initiatives to be discussed in the following chapters. Digitalization enables analysis and modifications to local processes without creating large and expensive information technology projects. It requires the basic process-characterization skills associated with process- improvement initiatives such as Lean and Six Sigma as well as analytics. The application of process improvement in a digitalized environment requires compatable skills associated with process and analytics as well as automation. Process design is increasingly competitive and requires a workforce with advanced skills. Investment in technology is also needed. The alternative is a degradation of operational capabilities.

Customers expect digitalization to provide a seamless experience. Business process excellence is the glue that ties marketing promises into product and service design to enable supporting processes that deliver the marketing promise. Customer service excellence is now the differentiator for competitors. Translating customer requirements into measurable outcomes is highly relevant for success. This implies business excellence requires an ability to gain deep insights in very large and complicated databases with methods to answer relevant questions. Data are difficult and expensive to gather, manage, and analyze. It needs to be used wisely. The proliferation of information technology platforms and applications that can number in the hundreds or thousands do not make process design easy. But organizations need to develop strategies for excellence that meet customer experience expectations while allowing the organization to remain efficient and competitive.

Organizations design products and services to meet customer needs and value expectations. The design of the supporting processes follows this philosophy. Poorly designed supporting processes result in higher costs and process breakdowns, which cause quality and delivery issues. A process design should follow the design of its product or service. This will ensure that the process is aligned with the voice of the customer (VOC) and meets an organization’s productivity goals. To do this, the objective of good process design is to create workflows that dynamically meet external demand, within ranges of designed capacity and target service levels, and using a minimum amount of required resources to meet productivity

TABLE 5.1

Competitive Metrics - Process Design

Metric

1. Throughput time

2. Number of changes to final process design

3. Percentage of warranty, scrap, rework to standard cost

4. Actual standard cost versus target cost for the process

5. Process engineering costs as a percentage of total revenue

6. Process capability of new equipment

goals. Several metrics that enable an organization to measure and manage productivity are listed in Table 5.1.

Reducing the lead time of a process helps increase throughput rates to convert investments in labor and materials into sales. This also helps reduce resources such as inventory and makes the process more adaptable to changes in external demand or production schedules. Reducing process design changes is another indicator of how well the process was designed. The percentages of warranty, scrap, rework, and similar failure costs that measure process quality help guide improvement efforts. The goal of process design is to avoid or minimize these costs. Failure costs reflect wasted direct labor and material usage and increase the standard cost of production. It is important to measure process engineering costs as a percentage of total revenue to compare one process to another to look for improvement opportunities and to determine whether the well-designed processes have high process capability relative to meeting design specifications.

The specific processes used will vary by industry, available technology, and internal work procedures and controls. Although the product or service design has a major impact on the process design, there are efficient or best-in-class methods to design a process that significantly increase operational efficiency. As an example, call centers use simulation and queuing models, and transportation companies use transportation network and routing models. Table 5.2 lists ten major steps useful for designing processes efficiently. The first step is to align the productive resources of an organization with the VOC based on its strategic goals and objectives. This is done by accurately translating the VOC into the design into then into the new supporting process. Design engineers should have followed best methods, such as design for manufacturing (DFM), which were discussed

TABLE 5.2

Ten Steps to Design Processes

Step

1. Ensure the VOC has been effectively and accurately translated into the process design.

2. Ensure the product is designed using best-in-class methods, including DFM and DFMEA.

3. Focus on the key outputs of the process related to utility and functionality.

4. Create the simplest possible process design and ensure it has high process capability.

5. Create flexible and virtual transformation systems using best-in-class resources from around the world.

6. Ensure the work is organized so all the information necessary to perform it is localized at its source.

7. Ensure first-pass yields are high and the work is done only once; create a PFMEA for the new process design.

8. Balance the systems throughput using the its takt time and ensure that bottlenecks and capacity-constrained resources meet the takt time requirements.

9. Use visual controls in the process and across the supply chain to ensure everyone has visibility to system status.

10. Continuously improve process performance using Lean, Six Sigma, and similar methodologies.

VOC = voice of the customer; DFM = design for manufacturing; DFMEA = design failure mode and effects analysis; PFMEA = process failure mode and effects analysis.

in Chapter 4. DFM is a critical set of tools for creating designs that are easy to build, carry low cost, and have higher quality.

Another important concept discussed in Chapter 4 was the use of design failure mode and effects analysis (DFMEA). DFMEA is important in translating the VOC into production operations because it provides process engineers with a view into important design attributes and current risks related to fit, form, and function. It also provides recommended countermeasures to prevent product or service failures, both in the production process and when used by customers. Process engineering uses DFMEA and other design and process engineering documentation to design their process workflows. This is done concurrently as the design team does its work. Once all the necessary information has been made available to the process engineering group, they create the supporting process.

A process should be designed in a way that is can be easily scaled and deployed across an organization’s global supply chain. It must be flexible and provide enough capacity to meet global and regional demand. Another consideration is that its performance is readily available to those who use and control it. It should also be highly reliable, easy to upgrade and maintain, and easily transportable. This means work tooling, equipment, work instructions, testing procedures, and other documentation needed to produce the product or service should require minimum translation into local languages and be culturally neutral. The documentation should be highly visual and easy to understand without extensive training. Complicated process designs, work instructions, equipment, training requirements, and other supporting resources have higher failure risks. Risks are compounded when a new product or service design relies on new technology.

A process failure mode and effects analysis (PFMEA) is created by process engineering using DFMEA. PFMEA is critical for identifying potential failure points within the new process and where modifications are required to achieve target standard cost, lead times, and quality. Once a process has been designed, its work operations should be balanced based on required takt time. Takt time is calculated by dividing the available production time by the required number of units that must be produced during the available production time. As an example, if there were 480 available minutes in a day and 60 required units, then the takt time would be calculated as one unit every eight minutes. Bottleneck resources will adversely impact a system’s takt time if they are not available. Although most balancing analyses focus within a system’s facility at one location, balancing of workflows across operations or workstations can also be done across an entire system. In other words, if a process is geographically dispersed, its takt time can still be calculated and controlled virtually across the system. In this scenario, process measurements and controls should allow for easy interpretation of the system’s status anywhere in the world at any time. This information should also be readily available to all supply chain participants. To achieve takt time reliability over time, it is also important to deploy continuous improvement initiatives such as Lean, Six Sigma, Total Productive Maintenance, and others to continually improve the new process over time.

The complexity of a process is determined in part by the types of external interfaces with customers and other groups (i.e., the degree of contact). This concept is shown in Figure 5.1, in which a high degree of customer interface requires high level skills to meet operational requirements. High-contact processes, if not properly designed, will be less efficient, less operationally flexible, and more costly than low-contact processes (e.g., back-office transactional operations). Advances in technology, offshoring,

FIGURE 5.1

Process design at the customer interface (old paradigm).

changes in the global geopolitical environment, and increasing global competitiveness have expanded global capacity in industries such as software development, design engineering, call center management, financial transactions, and others. They have been enabled by highly skilled labor pools in countries such as India and China and in broader regions such as Southeast Asia and Eastern Europe. Offshoring has also increased product and process standardization. This facilitates the efficient global deployment of work. The resultant business benefits are lower per-unit transaction costs than previously attainable in locations where material and labor costs have been higher. Technological improvements have directly impacted our ability to work anywhere in the world, and most information-generating processes are now virtual.

In conjunction with enabling initiatives such as Lean and Six Sigma, processes should be holistically created and controlled in contrast to those that may depend on isolated operations. Permeable systems should be created using technology to create virtual processes that enable an entire supply chain to interact according to business rules with customers, suppliers, and internal stakeholders both dynamically and virtually. These permeable systems integrate back-office operations with customer-facing operations. As an example, an improvement project was started in a global call center to reduce average handling time (AHT) to answer customer questions. The process had a long AHT and a low customer service level. Service level was defined as the time from the start of a customer call to accurately answering a customer’s questions. AHT is the time an agent spends on the phone providing the information to a customer. AHT also includes follow-up activities necessary to close out a customer inquiry. It should be noted that AHT and service level targets vary by customer market segment.

In this situation, operational standards required that agents be assigned to different market segments based on their skill and experience levels. In the more complicated market segments, customers asked in-depth questions about their service package. As a result, the target AHT for that segment was longer than other segments. The project was focused on one market segment. The historical AHT for this market segment, based on historical statistics, showed the AHT was 120 seconds versus the 90-second target. It was found, through data collection and analysis, that the AHT sometimes exceeded 240 seconds for certain agents. Several process issues were identified after mapping and analysis. The major contributor to longer AHT was a lack of standardization, training, and mistake-proofing.

It was found agents did not have standardized scripts to guide their customer interactions. This forced them to answer the customer’s questions in a non-standardized manner. AHT increased with the variation of the customer calls. In addition, agents did not have easy access to the information needed to answer customer questions. This resulted in more lost time. Another factor that contributed to the high AHT was poor agent training, which was exacerbated by high turnover within the call center. The solutions included standardizing the process by market segment through implementation of Lean methods, including process improvements (e.g., the 5-S method) and mistake-proofing strategies. After completion of the project, the AHT across 500 agents was reduced by more than 20% with appropriate AHT and service level targets set by market segment.

FIGURE 5.2

Process design at the customer interface {new paradigm).

Figure 5.2 shows a new paradigm that is evolving, in which process standardization is enabled through technology and initiatives. These systems are characterized by higher operational efficiencies, as well as higher quality and lower per-unit transaction costs. There is continued movement toward automated self-service systems. Many major retailers have customers who shop in clubs or online. These processes are highly efficient and flexible with respect to customer interaction (i.e., purchase and returns).

Complicating process design is the fact that product and services have specific delivery systems. These are based on available technology and cost. Figure 5.3 shows four types of production systems. These are job shops, batch operations, assembly operations, and continuous operations. It classifies these four systems into dimensions of volume, variety, and their operational flexibility. A job shop production system is characterized by operations performed by dedicated machines and highly trained people. Products and services moving through a job shop require unique

FIGURE 5.3

Operations strategy based on volume versus variety (old paradigm).

sequencing and combinations of work operations. Job shops can produce a diverse range of products and services. An example would be visiting a hospital and being moved from department to department based on the type of medical service being received from the system. Another example would be the manufacture of a customized product that requires several machine setups specifically for the work. Unless the underlying product or service design has been highly standardized using DFM and related methods, customized products or services must be produced using a process based on a job shop design.

In batch operations, products or services are produced periodically in batches having similar setups. Examples include short runs of similar products or services. Normally, batching can be done if similar work can be grouped based on similar features and functions by design. Batched work is produced on a periodic basis depending on demand. Lead times depend on the size of the batch and its throughput rate. Chemical mixing and periodic software releases are examples of batch operations.

Assembly operations use a combination of supporting operations, such as job shop, batching, and others, to produce high product variety at high volumes. Their capacity is matched to the required takt time. This implies all system components must be balanced with each other to meet the system’s takt time. The manufacture of automobiles, appliances, and similar high-volume standardized products having a variety of model types are examples of assembly operations where similar models are produced at once.

In continuous workflow processes, low-variety products and services are transformed at a high rate on a continuous basis (i.e., a unit flow system). These systems have high design commonality up to a point at which they may become slightly differentiated into different products or services. Examples include petroleum refining and other types of processing industries, or high-volume service transactions such as call centers. These have a common internal process that can produce slightly differentiated products and services based on highly skilled agents assigned to a customer segment.

Figure 5.4 shows how many industries are expanding the technological barriers that have historically constrained operational strategy to a single production system having lower throughput rates and higher per-unit costs (e.g., job shop, batch operations, or assembly operations). These industries are migrating toward mass customization of products or services. DFM and Lean methods help simplify processes and allow the cost-effective production of a variety of products. Greater process and operational flexibility are also enabled through common designs and by reducing lead times through a variety of methods. These include value flow mapping, bottleneck management, mixed-model scheduling systems, transfer batching, and several other tools and methods that increase operational flexibility. These will be discussed in Chapter 6.

FIGURE 5.4

Operations strategy based on volume versus variety (new paradigm).

One way to understand how a process should be designed is to consider the hierarchy of the product or service it will produce. In manufacturing, this is reflected by a bill of material (BOM) hierarchy. A BOM is used with other documentation such as the DFMEA as a basis to design a production system. It shows hierarchal relationships between each level of the design and how it should be built using work instructions and other job aids. As an example, an automobile has four wheels and each tire has five lug nuts. The BOM would include four wheels per automobile and five lug nuts per wheel related in a hierarchal manner. This concept also applies to services. McDonald’s builds hamburgers. The BOM of a hamburger would specify one roll split in half, one hamburger patty, tomato, lettuce, pickles, and any other materials placed on it. The engineers designing McDonald’s process would build its process to include this BOM as well as those for its other products. As a third example, customers who purchase mutual funds and other financial services have a product and service portfolio (i.e., the BOM) that provides their financial advisor with information useful in managing their investments.

Table 5.3 lists twenty process-related steps that ensure a new product or service can be successfully produced. Several of these require supporting documentation from the design phase of the project, including a preliminary process description based on a BOM or the service description based on use cases by customers or other persona. These are developed by process engineers as part of the CE team during design development. The descriptions should include operational spatial relationships and the key inputs, process operations, and outputs at each step of the process.

A DFMEA and preliminary quality control plan should be available to the process engineers to ensure a new design has been fully evaluated relative to its failure points. Process engineering also works with suppliers to design equipment, tooling, and facilities (if necessary), as well as measurement equipment, testing equipment, and other supporting resources. This information is used to create a PFMEA. The PFMEA is comparable to the DFMEA, except that the process design is aligned to the critical design characteristics or specifications of each operation. If a specification requires a certain surface roughness, process engineering will ensure machines can meet this requirement. For a call center that requires an AFIT of less than 60 seconds, the process engineers will ensure the system has the capacity to meet this specification.

The pre-launch control plan is built using information from the DFMEA and PFMEA to communicate important information necessary

TABLE 5.3

Twenty Steps to Create New Product or Service Processes

Step

1. Preliminary process flow chart

2. Product assurance plan

3. DFMEA

4. Preliminary quality control plan

5. New equipment, tooling, and facilities requirements

6. Gages and testing equipment requirements

7. Product and process quality systems review

8. Process flow chart

9. Floor plan layout

10. PFMEA

11. Pre-launch control plan

12. Process instructions

13. Measurements systems analysis

14. Production trial run

15. Preliminary process capability study

16. Production part approval

17. Production validation testing

18. Packaging evaluation

19. Production control plan

20. Quality planning sign-off and management support

DFMEA = design failure mode and effects analysis; PFMEA = process failure mode and effects analysis,

for successful production. Work instructions, training, measurement systems, preliminary process capability studies, and related documentation are also created to support the process. This information is used to plan the production trials to evaluate how well the combined design and process meet the original customer requirements (i.e., critical-to-customer characteristics). Production trials are used to finalize changes needed to commercialize the product. These validation activities ensure that customer requirements are met under actual production conditions. If production validation testing is successful, the new production system will be scaled to full commercialization. In parallel, design components of the packaging are evaluated. Then the quality control plan and related documentation are updated. The deliverables consist of a process flow chart, work and inspection procedures, floor plans, and an updated production schedule. The project schedule includes the balance of the deliverables that are necessary to support the new process.

 
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