Business intelligence

Business intelligence (BI) is a business management term, which refers to applications and technologies that are used to gather, provide access to, and analyze data and information about company operations. Business intelligence systems can help companies have a more comprehensive knowledge of the factors affecting their business, such as metrics on sales, production, internal operations, and they can help companies to make better business decisions.

Rationale for using BI

Business Intelligence applications and technologies can enable organizations to make more informed business decisions, and they may give a company a competitive advantage. For example, a company could use business intelligence applications or technologies to extrapolate information from indicators in the external environment and forecast the future trends in their sector. Business intelligence is used to improve the timeliness and quality of information and enable managers to better understand the position of their firm in comparison to its competitors.

Business Intelligence applications and technologies can help companies analyze the following: changing trends in market share, changes in customer behavior and spending patterns, customers' preferences, company capabilities and market conditions. Business intelligence can be used to help analysts and managers determine which adjustments are most likely to affect trends.

BI systems can also be designed to provide managers with information on the state of economic trends or marketplace factors, or to provide managers with in depth knowledge about the internal operations of a business.

BI Technologies
For the BI (Business Intelligence) technology system to work effectively, companies address the need to have a secure computer system which can specify different levels of user access to the data 'warehouse', depending on whether the user is a junior staffer, manager, or executive. As well, a BI system needs to have sufficient data capacity, a plan for how long data will be stored (data retention). Analysts also need to set benchmark and performance targets for the system.
Business intelligence analysts have developed software tools to gather and analyze large quantities of unstructured data, such as production metrics, sales statistics, attendance reports, and customer attrition figures. Each BI vendor typically develops Business Intelligence systems differently, to suit the demands of different sectors (e.g., retail companies, financial services companies, etc.).

Business intelligence software and applications includes a range of tools. Some BI applications are used to analyze performance, projects, or internal operations, such as:

• AQL - Associative Query Logic;
• Scorecarding;
• Business activity monitoring;
• Business Performance Management and Performance Measurement;
• Business Planning;
• Business Process Re-engineering;
• Competitive Analysis;
• User/End-user Query and Reporting;
• Enterprise Management systems;
• Executive Information Systems (EIS);
• Supply Chain Management/Demand Chain Management;
• Finance and Budgeting tools.

Other BI applications are used to store and analyze data, such as:

• Data mining (DM),
• Data Farming,
• Data warehouses;
• Decision Support Systems (DSS) and Forecasting;
• Document warehouses
• Document Management;
• Knowledge Management;
• Mapping,
• Information visualization,
• Dashboarding;
• Management Information Systems (MIS);
• Geographic Information Systems (GIS);
• Trend Analysis;
• Software as a service (SaaS) Business Intelligence offerings (On Demand);
• Online analytical processing (OLAP)
• Real time business intelligence;
• Statistics and Technical Data Analysis;
• Web Mining, Text mining
• Systems intelligence.

Other BI applications are used to analyze or manage the "human" side of businesses, such as Customer Relationship Management (CRM) and Marketing tools and Human Resources applications.Web Personalization For examples of implemented Business Intelligence systems, see the BI screenshot collection at The Dashboard Spy


Key Intelligence Topics
Business intelligence often uses key performance indicators (KPIs) to assess the present state of business and to prescribe a course of action. Prior to the widespread adoption of computer and web applications, when information had to be manually inputted and calculated, performance data was often not available for weeks or months. Recently, banks have tried to make data available at shorter intervals and have reduced delays. The KPI methodology was further expanded with the Chief Performance Officer methodology which incorporated KPIs and root cause analysis into a single methodology.

Businesses that face higher operational/credit risk loading, such as credit card companies and "wealth management" services often make KPI-related data available weekly. In some cases, companies may even offer a daily analysis of data. This fast pace requires analysts to use IT systems to process this large volume of data.

Designing and implementing a business intelligence program
When implementing a BI programme one might like to pose a number of questions and take a number of resultant decisions, such as:

• Goal Alignment queries: The first step determines the short and medium-term purposes of the programme. What strategic goal(s) of the organization will the programme address? What organizational mission/vision does it relate to? A crafted hypothesis needs to detail how this initiative will eventually improve results / performance (i.e. a strategy map).
• Baseline queries: Current information-gathering competency needs assessing. Does the organization have the capability of monitoring important sources of information? What data does the organization collect and how does it store that data? What are the statistical parameters of these data, e.g. how much random variation does it contain? Does the organization measure this?
• Cost and risk queries: The financial consequences of a new BI initiative should be estimated. It is necessary to assess the cost of the present operations and the increase in costs associated with the BI initiative? What is the risk that the initiative will fail? This risk assessment should be converted into a financial metric and included in the planning.
• Customer and Stakeholder queries: Determine who will benefit from the initiative and who will pay. Who has a stake in the current procedure? What kinds of customers/stakeholders will benefit directly from this initiative? Who will benefit indirectly? What are the quantitative / qualitative benefits? Is the specified initiative the best way to increase satisfaction for all kinds of customers, or is there a better way? How will customers' benefits be monitored? What about employees,… shareholders,… distribution channel members?
• Metrics-related queries: These information requirements must be operationalized into clearly defined metrics. One must decide what metrics to use for each piece of information being gathered. Are these the best metrics? How do we know that? How many metrics need to be tracked? If this is a large number (it usually is), what kind of system can be used to track them? Are the metrics standardized, so they can be benchmarked against performance in other organizations? What are the industry standard metrics available?
• Measurement Methodology-related queries: One should establish a methodology or a procedure to determine the best (or acceptable) way of measuring the required metrics. What methods will be used, and how frequently will the organization collect data? Do industry standards exist for this? Is this the best way to do the measurements? How do we know that?
• Results-related queries: Someone should monitor the BI programme to ensure that objectives are being met. Adjustments in the programme may be necessary. The programme should be tested for accuracy, reliability, and validity. How can one demonstrate that the BI initiative (rather than other factors) contributed to a change in results? How much of the change was probably random?.

Balanced scorecard

In 1992, Robert S. Kaplan and David Norton introduced the balanced scorecard, a concept for measuring a company's activities in terms of its vision and strategies, to give managers a comprehensive view of the performance of a business. The key new element is focusing not only on financial outcomes but also on the human issues that drive those outcomes, so that organizations focus on the future and act in their long-term best interest. The strategic management system forces managers to focus on the important performance metrics that drive success. It balances a financial perspective with customer, process, and employee perspectives. Measures are often indicators of future performance.

Implementing the scorecard typically includes four processes:

1. Translating the vision into operational goals;
2. Communicate the vision and link it to individual performance;
3. Business planning;
4. Feedback and learning and adjusting the strategy accordingly.

A comprehensive view of business performance
Balanced Scorecard is simply a concise report featuring a set of measures that relate to the performance of an organization. From the outset, the Balanced Scorecard has been promoted as a tool to help organizations monitor the implementation of organizational strategy.

The earliest Balanced Scorecards comprised simple tables broken into four sections - typically these 'perspectives' were labeled "Financial", "Customer", "Internal Business Processes", and "Learning & Growth".

Designing the Balanced Scorecard simply required picking five or six good measures for each perspective. Many writers have since suggested alternative headings for these perspectives, and also suggested using either additional or fewer perspectives: these suggestions being triggered by a recognition that different but equivalent headings will yield alternative sets of measures. The major design challenge faced with this type of Balanced Scorecard is justfiying the choice of measures made - "of all the measures you could have chosen why did you choose these...?" is a common question asked (and using this type of design process, hard to answer). If users are not confident that the measures within the Balanced Scorecard are well chosen, they will have less confidence in the information it provides. Although less common, these early style Balanced Scorecards are still designed and used today.

The early style Balanced Scorecards are hard to design in a way that builds confidence that they are well designed. Because of this, many are abandoned soon after completion.

In the mid 1990s an improved design method emerged. In the new method, selection of measures was based on a set of 'strategic objectives' plotted on a 'strategic linkage model' or 'strategy map'. With this modified approach, the strategic objectives are typically distributed across a similar set of 'perspectives' as is found in the earlier designs, but the design question becomes slightly more abstract. Managers have to identify the five or six goals they have within each of the perspectives, and then demonstrate some inter-linking between them by plotting causal links on the diagram. Having reached some consensus about the objectives and how they inter-relate, the Balanced Scorecard's measures are chosen by picking suitable measures for each objective.

Since the late 1990s, various improved versions of Balanced Scorecard design methods have emerged - examples being The Performance Prism, Results Based Management and Third Generation Balanced Scorecard for example. These more advanced design methods seek to solve some of the remaining design issues - in particular issues relating to the design of sets of Balanced Scorecards to use across an organization, and in setting targets for the measures selected.

Balanced Scorecard is a performance management tool: although it helps focus managers' attention on strategic issues and the management of the implementation of strategy, it is important to remember that Balanced Scorecard itself has no role in the formation of strategy. Balanced Scorecard can comfortably co-exist with strategic planning systems and other tools.

Actual usage of the balanced scorecard
Kaplan and Norton found that companies are using the scorecard to:

• Clarify and update budgets
• Identify and align strategic initiatives
• Conduct periodic performance reviews to learn about and improve strategy.

In 1997, Kurtzman found that 64 percent of the companies questioned were measuring performance from a number of perspectives in a similar way to the balanced scorecard.
Balanced scorecards have been implemented by government agencies, military units, corporate units and corporations as a whole, nonprofits, and schools; many sample scorecards can be found via Web searches, though adapting one organization's scorecard to another is generally not advised by theorists, who believe that much of the benefit of the scorecard comes from the implementation method.

Comparison to Applied Information Economics
A criticism of balanced scorecard is that the scores are not based on any proven economic or financial theory and have no basis in the decision sciences. The process is entirely subjective and makes no provision to assess quantities like risk and economic value in a way that is actuarially or economically well-founded. Positive responses from users of balanced scorecard may merely be a type of placebo effect. There are no empirical studies linking the use of balanced scorecard to better decision making or improved financial performance of companies.
Applied Information Economics (AIE) has been researched as an alternative to Balanced Scorecards. In 2000, the Federal CIO Council commissioned a study to compare the two methods by funding studies in side-by-side projects in two different agencies. The Dept. of Veterans Affairs used AIE and the US Dept. of Agriculture applied balanced scorecard. The resulting report found that while AIE was much more sophisticated, AIE actually took slightly less time to utilize. AIE was also more likely to generate findings that were newsworthy to the organization while the users of balanced scorecard felt it simply documented their inputs and offered no other particular insight. However, balanced scorecard is still much more widely used than AIE.

Key performance indicators
According to each perspective of the balanced scorecard there are a number of KPIs.

Financial

• Cash Flow
• ROI
• Financial Result
• Return on capital employed
• Return on equity

Customer

• Delivery Performance to Customer - by Date
• Delivery Performance to Customer - by Quantity
• Customer satisfaction rate
• Customer retention

Internal Business Processes

• Number of Activities
• Opportunity Success Rate

Learning & Growth

• Investment Rate Illness rate

5 Whys

Determine The Root Cause: 5 Whys

Asking "Why?" may be a favorite technique of your three year old child in driving you crazy, but it could teach you a valuable Six Sigma quality lesson. The 5 Whys is a technique used in the Analyze phase of the Six Sigma DMAIC methodology. It's a great Six Sigma tool that doesn't involve data segmentatio, hypothesis testing, regression or other advanced statistical tool, and in many cases can be completed without a data collection plan. By repeatedly asking the question "Why" (five is a good rule of thumb), you can peel away the layers of symptoms which can lead to the root cause of a problem. Very often the ostensible reason for a problem will lead you to another question. Although this technique is called "5 Whys," you may find that you will need to ask the question fewer or more times than five before you find the issue related to a problem.

Benefits Of The 5 Whys

• When problems involve human factors or interactions
• In day-to-day business life; can be used within or without a Six Sigma project.

How To Complete The 5 Whys

1. Write down the specific problem. Writing the issue helps you formalize the problem and describe it completely. It also helps a team focus on the same problem.
   
2. Ask Why the problem happens and write the answer down below the problem.


3. If the answer you just provided doesn't identify the root cause of the problem that you wrote down in step 1, ask Why again and write that answer down.


4. Loop back to step 3 until the team is in agreement that the problem's root cause is identified. Again, this may take fewer or more times than five Whys.
   

5 Whys Examples

Problem Statement: Customers are unhappy because they are being shipped products that don't meet their specifications.

1. Why are customers being shipped bad products?
-Because manufacturing built the products to a specification that is different from what the customer and the sales person agreed to.

2. Why did manufacturing build the products to a different specification than that of sales?
- Because the sales person expedites work on the shop floor by calling the head of manufacturing directly to begin work. An error happened when the specifications were being communicated or written down.

3. Why does the sales person call the head of manufacturing directly to start work instead of following the procedure established in the company? - Because the "start work" form requires the sales director's approval before work can begin and slows the manufacturing process (or stops it when the director is out of the office)

4. Why does the form contain an approval for the sales director?
-Because the sales director needs to be continually updated on sales for discussions with the CEO.

Other example

Problem Statement: You are on your way home from work and your car stops in the middle of the road.

1. Why did your car stop?
- Because it ran out of gas.

2. Why did it run out of gas?
- Because I didn't buy any gas on my way to work.

3. Why didn't you buy any gas this morning?
- Because I didn't have any money.

4. Why didn't you have any money?
- Because I lost it all last night in a poker game.

5. Why did you lose your money in last night's poker game?
- Because I'm not very good at "bluffing" when I don't have a good hand.

As you can see, in both examples the final Why leads the team to a statement (root cause) that the team can take action upon. It is much quicker to come up with a system that keeps the sales director updated on recent sales or teach a person to "bluff" a hand than it is to try to directly solve the stated problems above without further investigation.

5 Whys And The Fishbone Diagram

The 5 Whys can be used individually or as a part of the fishbone (also known as the cause and effect or Ishikawa) diagram. The fishbone diagram helps you explore all potential or real causes that result in a single defect or failure. Once all inputs are established on the fishbone, you can use the 5 Whys technique to drill down to the root causes:

Six Sigma

Six Sigma is a set of practices originally developed by Motorola to systematically improve processes by eliminating defects. A defect is defined as nonconformity of a product or service to its specifications.While the particulars of the methodology were originally formulated by Bill Smith at Motorola in 1986, Six Sigma was heavily inspired by six preceding decades of quality improvement methodologies such as quality control, TQM, and Zero Defects. Like its predecessors, Six Sigma asserts the following: Continuous efforts to reduce variation in process outputs is key to business successManufacturing and business processes can be measured, analyzed, improved and controlled Succeeding at achieving sustained quality improvement requires commitment from the entire organization, particularly from top-level management The term "Six Sigma" refers to the ability of highly capable processes to produce output within specification. Six Sigma's implicit goal is to improve all processes to that level of quality or better.

Methodology

Six Sigma has two key methodologies: DMAIC and DMADV:

• DMAIC is used to improve an existing business process;


• DMADV is used to create new product or process designs for predictable, defect-free performance.

DMAIC

Basic methodology consists of the following five steps:

• D - Define the process improvement goals that are consistent with customer demands and enterprise strategy.


• M - Measure the current process and collect relevant data for future comparison.


• A - Analyze to verify relationship and causality of factors. Determine what the relationship is, and attempt to ensure that all factors have been considered.


• I - Improve or optimize the process based upon the analysis using techniques like Design of Experiments.


• C - Control to ensure that any variances are corrected before they result in defects. Set up pilot runs to establish process capability, transition to production and thereafter continuously measure the process and institute control mechanisms.

DMADV
Basic methodology consists of the following five steps:

• D - Define the goals of the design activity that are consistent with customer demands and enterprise strategy.


• M - Measure and identify CTQs (critical to qualities), product capabilities, production process capability, and risk assessments.


• A - Analyze to develop and design alternatives, create high-level design and evaluate design capability to select the best design.


• D - Design details, optimize the design, and plan for design verification. This phase may require simulations.


• V - Verify the design, set up pilot runs, implement production process and handover to process owners.

Other Design for Six Sigma methodologies:

DMADOV (Define, Measure, Analyze, Design, Optimize and Verify) General Electric

DMEDI (Define, Measure, Explore, Develop and Implement) PricewaterhouseCoopers

Kaizen

Kaizen (改善, Japanese for "change for the better" or "improvement"; the English translation is "continuous improvement" or "continual improvement").

Kaizen aims to eliminate waste (defined as "activities that add cost but do not add value"). It is often the case that this means "to take it apart and put back together in a better way." This is then followed by standardization of this 'better way' with others, through standardized work.

Introduction
Kaizen is a daily activity whose purpose goes beyond improvement. It is also a process that, when done correctly, humanizes the workplace, eliminates overly hard work (both mental and physical), and teaches people how to perform experiments using the scientific method and how to learn to spot and eliminate waste in business processes.

Kaizen must operate with three principles in place: process and results (not results-only); systemic thinking (i.e. big picture, not solely the narrow view); and non-judgmental, non-blaming (because blaming is wasteful).

People at all levels of an organization participate in kaizen, from the CEO down, as well as external stakeholders when applicable. The format for kaizen can be individual, suggestion system, small group, or large group. In Toyota it is usually a local improvement within a workstation or local area and involves a small group in improving their own work environment and productivity.

The "zen" in Kaizen emphasizes the learn-by-doing aspect of improving production. This philosophy differs from the "command-and-control" improvement programs of the mid-twentieth century. Kaizen methodology includes making changes and monitoring results, then adjusting. Large-scale pre-planning and extensive project scheduling are replaced by smaller experiments, which can be rapidly adapted as new improvements are suggested.

Kaizen: Meaning and Translation:
The original kanji characters for this word are: In Japanese this is pronounced 'kaizen'.

• 改 ('kai') means 'change' or 'the action to correct'


• 善 ('zen') means 'good'.

Implementation
The cycle of kaizen activity can be defined as: standardize an operation -> measure the standardized operation (find cycle time and amount of in-process inventory) -> gauge measurements against requirements -> innovate to meet requirements and increase productivity -> standardize the new, improved operations -> continue cycle ad infinitum.

5S - methodology

What is 5S?
The key targets of 5S are workplace morale and efficiency. As a result, it is often executed in tandem with standard work which standardizes the processes in which the items organized in 5S are used.

The 5S's are:

• Seiri (整理): tidiness, organization. Refers to the practice of sorting through all the tools, materials, etc., in the work area and keeping only essential items. Everything else is stored or discarded. This leads to fewer hazards and less clutter to interfere with productive work.


• Seiton (整頓): orderliness. Focuses on the need for an orderly workplace. "Orderly" in this sense means arranging the tools and equipment in an order that promotes work flow. Tools and equipment should be kept where they will be used, and the process should be ordered in a manner that eliminates extra motion.


• Seiso (清掃): systemized cleanliness. Indicates the need to keep the workplace clean as well as neat. Cleaning in Japanese companies is a daily activity. At the end of each shift, the work area is cleaned up and everything is restored to its place. The key point is that maintaining cleanliness should be part of the daily work - not an occasional activity initiated when things get too messy.


• Seiketsu (清潔): standards. This refers to standardized work practices. It refers to more than standardized cleanliness (otherwise this would mean essentially the same as "systemized cleanliness"). This means operating in a consistent and standardized fashion. Everyone knows exactly what his or her responsibilities are.


• Shitsuke (躾): sustaining discipline. Refers to maintaining standards. Once the previous 4S's have been established they become the new way to operate. Maintain the focus on this new way of operating, and do not allow a gradual decline back to the old ways of operating.
  

5S in a business context

The 5S methodology has been adopted into a variety of organizations from small business to Fortune 500 companies. All implement the 5S's in the hope to improve productivity and performance. Such organizations and their achievements include:

• Improved levels of quality communication.


• Increased levels of product quality


• Improved productivity


• Improved value morale


• Improved safety

Lean manufacturing

Lean manufacturing is a generic process management philosophy derived mostly from the Toyota Production System (TPS), but also from other sources. It is renowned for its focus on reduction of the original Toyota 'seven wastes' in order to improve overall customer value. Lean is often linked with Six Sigma because of that methodology's emphasis on reduction of process variation (or its converse smoothness). Toyota's steady growth from a small player to the most valuable and the biggest car company in the world has focused attention upon how it has achieved this, making "Lean" a hot topic in management science in the first decade of the 21st century.

For many, Lean is the set of TPS 'tools' that assist in the identification and steady elimination of waste (muda), the improvement of quality, and production time and cost reduction. To solve the problem of waste, Lean Manufacturing has several 'tools' at its disposal. These include continuous process improvement (kaizen), the "5 Whys" and mistake-proofing (poka-yoke). In this way it can be seen as taking a very similar approach to other improvement methodologies.
There is a second approach to Lean Manufacturing which is promoted by Toyota in which the focus is upon implementing the 'flow' or smoothness of work (opposite of mura, unevenness) through the system and not upon 'waste reduction' per se. Techniques to improve flow include production levelling, "pull" production (by means of kanban) and the Heijunka box.
The difference between these two approaches is not the goal but the prime approach to achieving it. The implementation of smooth flow exposes quality problems which always existed and thus waste reduction naturally happens as a consequence. The advantage claimed for this approach is that it naturally takes a system-wide perspective whereas a 'waste' focus has this perspective assumed. Some Toyota staff have expressed some surprise at the 'tool' based approach as they see the tools as work-arounds made necessary where flow could not be fully implemented and not as aims in themselves.

Overview

Both Lean and TPS can be seen as a loosely connected set of potentially competing principles whose goal is cost reduction by the elimination of waste. These principles include:

• Pull processing: products are pulled from the consumer end (demand) just-in-time to be used, not pushed from the production end (Supply)
  Perfect first-time quality - quest for zero defects, revealing & solving problems at the source
• Waste minimization – eliminating all activities that do not add value & or are safety nets, maximize use of scarce resources (capital, people and land)
• Continuous improvement – reducing costs, improving quality, increasing productivity and information sharing
• Flexibility – producing different mixes or greater diversity of products quickly, without sacrificing efficiency at lower volumes of production
• Building and maintaining a long term relationship with suppliers through collaborative risk sharing, cost sharing and information sharing arrangements
• Autonomation - if an abnormal situation arises then a machine or person must stop production in order to avoid defective products and other waste
• Load levelling and Production flow - fluctuations in product flow increase waste because process capacity must always be prepared for peak production
• Visual control - where the actual progress of work in comparison to daily production plans is clearly visible.

The disconnected nature of some of these principles perhaps springs from the fact that the TPS has grown pragmatically as it responded to the problems it saw within its own production facilities. The TPS has been under development since about 1948 and continues to develop today. Thus what one sees today is the result of a 'need' driven learning to improve where each step has built on previous ideas and not something based upon a theoretical framework. Toyota's view is that the methodology is not the tools but the method of application of muda, mura, muri to expose the things the tools can address. Thus the 'tools' are adapted to different situations which explains any apparent incoherence of the 'principles' above.
Lean production, alternatively gaining distinction as the Toyota Product Development System (TPDS), is aimed at defining value, creating flow, and eliminating waste in every area and stage of work including customer relations, product design, supplier networks and factory management. Its goal is to incorporate less low-value human effort, less inventory, less time to develop products, and less space to become highly responsive to customer demand while producing top quality, error-proofed products in the most efficient and economical manner possible.'
The TPS has two pillar concepts: JIT (flow) and autonomation (smart automation).[3] Adherents of the Toyota approach would say that 'flow' delivery of 'value' does all these improvements as a side-effect. If production 'flows' perfectly then there is no inventory, if customer valued features are the only ones produced then product design is simplified and effort is only expended on features the customer values. The other of the two TPS pillars is the very human aspect of 'autonomation' whereby automation is achieved with a human touch.[4] This aims to give the machines enough 'intelligence' to recognise when they are working abnormally and flag this for human attention. Thus humans do not have to monitor normal production and only have to focus on abnormal, or fault, conditions. A reduction in human workload that is probably much desired by all involved.
Lean is focused on getting the right things, to the right place, at the right time, in the right quantity to achieve perfect work flow while minimizing waste and being flexible and able to change. These concepts of flexibility and change are principally required to allow production levelling, using tools like SMED, but have their analogues in other processes such as R&D. The flexibility and ability to change are not open-ended, and therefore often expensive, capability requirements. More importantly, all of these concepts have to be understood, appreciated, and embraced by the actual employees who build the products and therefore own the processes. The cultural and managerial aspects of lean are just as important as the actual tools or methodologies of production itself. There are many examples of Lean tool implementation without sustained benefit and these are often blamed on weak understanding of Lean in the organisation. Lean aims to make the work simple enough to understand, to do and to manage. To achieve these three at once there is a belief held by some that Toyota's mentoring process (loosely called Senpai and Kohai relationship), so strongly supported in Japan, is one of the best ways to foster Lean Thinking up and down the organizational structure. The closest equivalent to Toyota's mentoring process is the concept of Lean Sensei, which encourages companies, organizations, and teams to seek out outside, third-party "Sensei" that can provide unbiased advice and coaching, (see Womack et al, Lean Thinking, 1998).

Lean implementation

System engineering
Lean is about more than just cutting costs in the factory. One crucial insight is that most costs are assigned when a product is designed, (see Genichi Taguchi). Often an engineer will specify familiar, safe materials and processes rather than inexpensive, efficient ones. This reduces project risk, that is, the cost to the engineer, while increasing financial risks, and decreasing profits. Good organizations develop and review checklists to review product designs.
Companies must often look beyond the shop-floor to find opportunities for improving overall company cost and performance. At the system engineering level, requirements are reviewed with marketing and customer representatives to eliminate costly requirements. Shared modules may be developed, such as multipurpose power-supplies or shared mechanical components or fasteners. Requirements are assigned to the cheapest discipline. For example, adjustments may be moved into software, and measurements away from a mechanical solution to an electronic solution. Another approach is to choose connection or power-transport methods that are cheap or that used standardized components that become available in a competitive market.

A summary, An Example program:

With a muda or tools based approach

• Senior management to agree and discuss their lean vision
• Management brainstorm to identify project leader and set objectives
• Communicate plan and vision to the workforce
• Ask for volunteers to form the Lean Implementation team (5-7 works best, all from different departments)
• Appoint members of the Lean Manufacturing Implementation Team
• Train the Implementation Team in the various lean tools - make a point of trying to visit other non competing businesses which have implemented lean
• Select a Pilot Project – 5S is a good place to start
• Run the pilot for 2-3 months - evaluate, review and learn from your mistakes
• Roll out pilot to other factory areas
• Evaluate results, encourage feedback
• Stabilize the positive results by teaching supervisors how to train the new standards you've developed with TWI methodology (Training Within Industry)
• Once you are satisfied that you have a habitual program, consider introducing the next lean tool. Select the one which will give you the biggest return for your business.

With a muri or flow based approach

• Sort out as many of the visible quality problems as you can, as well as downtime and other instability problems, and get the internal scrap acknowledged and its management started.
• make the flow of parts through the system/process as continuous as possible using workcells and market locations where necessary and avoiding variations in the operators work cycle
• introduce standard work and stabilise the work pace through the system
• start pulling work through the system, look at the production scheduling and move towards daily orders with kanban cards
• even out the production flow by reducing batch sizes, increase delivery frequency internally and if possible externally, level internal demand
• improve exposed quality issues using the tools remove some people and make it all work again
  
  

Toyota Production System

The Toyota Production System
(TPS, トヨタ生産方式) is the philosophy which organizes manufacturing and logistics at Toyota, including the interaction with suppliers and customers. The TPS is a major part of the more generic "Lean manufacturing". It was largely created by the founder of Toyota, Sakichi Toyoda, his son Kiichiro Toyoda, and the engineer Taiichi Ohno; they drew heavily on the work of W. Edwards Deming and the writings of Henry Ford. When these men came to the United States to observe the assembly line and mass production that had made Ford rich, they were unimpressed. While shopping in a supermarket they observed the simple idea of an automatic drink resupplier; when the customer wants a drink, he takes one, and another replaces it. The main goals of the TPS are to design out overburden (muri), smooth production (mura) and eliminate waste (muda). There are 7 kinds of muda targeted in the TPS:

1. over-production


2. motion (of operator or machine)


3. waiting (of operator or machine)


4. conveyance


5. processing itself


6. inventory (raw material)


7. correction (rework and scrap)

Toyota was able to greatly reduce leadtime and cost using the TPS, while improving quality at the same time. This enabled it to become one of the ten largest companies in the world. It is currently as profitable as all the other car companies combined and became the largest car manufacturer in 2007. It has been proposed that the TPS is the most prominent example of the 'correlation', or middle, stage in a science, with material requirements planning and other data gathering systems representing the 'classification' or first stage. A science in this stage can see correlations between events and can propose some procedures that allow some predictions of the future. Due to this stellar success of the production philosophy's predictions many of these methods have been copied by other manufacturing companies.

Origins and philosophies behind the Toyota Production System

Toyota has long been recognized as a leader in the automotive manufacturing and production industry.This system, more than any other part of the company, is responsible for having made Toyota the company it is today. It may be surprising that Toyota received their inspiration for the production system in the United States, but not from its automotive production process. This occurred when a delegation from Toyota visited the United States to study its commercial enterprises. They first visited several Ford Motor Company automotive plants in Michigan, but despite Ford being the industry leader at that time, found the methods in use to be unappealing. They were mainly appalled by the large amounts of inventory on site and by how the amount of work being performed in various departments within the factory was uneven on most days. However, on their visit to a Piggly Wiggly, an American supermarket, the delegation was inspired by how the supermarket only reordered and restocked goods once they’d been bought by customers.

Toyota applied the lesson from Piggly Wiggly by reducing the amount of inventory they would hold only to a level that its employees would need for a small period of time, and then subsequently reorder. This is highly representative of a Just-in-Time (JIT) inventory system. While low inventory levels are a key outcome of the Toyota Production System, an important element of the philosophy behind its system is to work intelligently and eliminate waste so that inventory is no longer needed. Many American businesses, having observed Toyota's factories, set out to attack high inventory levels directly without understanding what made these reductions possible.The act of imitating without understanding the underlying concept or motivation may have led to the failure of those projects.

The Toyota Way, the underlying principles are outlined as follows:

Long-term philosophy

Base your management decisions on a long-term philosophy, even at the expense of short-term financial goals.

The right process will produce the right results

1. Create continuous process flow to bring problems to the surface


2. Use the "pull" system to avoid overproduction


3. Level out the workload (heijunka). (Work like the tortoise, not the hare.)


4. Build a culture of stopping to fix problems, to get quality right the first time


5. Standardized tasks are the foundation for continuous improvement and employee empowerment


6. Use visual control so no problems are hidden


7. Use only reliable, thoroughly tested technology that serves your people and processes.

Add value to the organization by developing your people and partners

1. Grow leaders who thoroughly understand the work, live the philosophy, and teach it to others.


2. Develop exceptional people and teams who follow your company's philosophy


3. Respect your extended network of partners and suppliers by challenging them and helping them improve.

Continuously solving root problems drives organizational learning

1. Go and see for yourself to thoroughly understand the situation (Genchi Genbutsu)


2. Make decisions slowly by consensus, thoroughly considering all options; implement decisions rapidly


3. Become a learning organization through relentless reflection (Hansei, 反省) and continuous improvement (Kaizen)

The Toyota production system has been compared to squeezing water from a dry towel. What this means is that it is a system for thorough waste elimination. Here, waste refers to anything which does not advance the process, everything that does not increase added value. Many people settle for eliminating the waste that everyone recognises as waste. But much remains that simply has not yet been recognised as waste or that people are willing to tolerate.
People had resigned themselves to certain problems, had become hostage to routine and abandoned the practice of problem-solving. This going back to basics, exposing the real significance of problems and then making fundamental improvements, can be witnessed throughout the Toyota Production System

Commonly used terminology in TPS:
Just In Time (ジャストインタイム) (JIT)
Jidoka (自働化) (English: Autonomation - automation with human intelligence)
Heijunka (平準化) (English: Production Smoothing)
Kaizen (改善) (English: Continuous Improvement)
Poka-yoke (ポカヨケ) (English: fail-safing - to avoid (yokeru) inadvertent errors (poka))
Kanban (看板, also かんばん) (English: Sign, Index Card)
Andon (アンドン) (English: Signboard)
Muri (無理) (English: Overburden)
Mura (斑 or ムラ) (English: Unevenness)
Muda (無駄, also ムダ) (English: Waste)
Genchi Genbutsu (現地現物) (English: Go and see for yourself)
Manufacturing supermarket where all components are available to be withdrawn by a process

Fordism - Assembly line

Abstract. Fordism refers to the system of mass production and consumption characteristic of highly developed economies during the 1940s-1960s. Under Fordism, mass consumption combined with mass production to produce sustained economic growth and widespread material advancement.

Ford's main contributions to mass production/consumption were in the realm of process engineering. The the hallmark of his system was standardization -- standardized components, standardized manufacturing processes, and a simple, easy to manufacture (and repair) standard product. Standardization required nearly perfect interchangeability of parts. To achieve interchangeability, Ford exploited advances in machine tools and gauging systems. These innovations made possible the moving, or continuous, assembly line, in which each assembler performed a single, repetitive task. Ford was also one of the first to realize the potential of the electic motor to reconfigure work flow. Machines that were previously arrayed about a central power source could now be placed on the assembly line, thereby dramatically increasing throughput

Scientific management

Scientific management

Is a method in management theory which determines changes to improve labour productivity. The idea was first coined by Frederick Winslow Taylor in The Principles of Scientific Management. Taylor believed that decisions based upon tradition and rules of thumb should be replaced by precise procedures developed after careful study of an individual at work.

Taylor's scientific management consisted of four principles:

1. Replace rule-of-thumb work methods with methods based on a scientific study of the tasks.



2. Scientifically select, train, and develop each employee rather than passively leaving them to train themselves.



3. "Detailed instruction and supervision of each worker in the performance of that worker's discrete task"



4. Divide work nearly equally between managers and workers, so that the managers apply scientific management principles to planning the work and the workers actually perform the tasks

Conclusion:
Approach to business management and process improvement;
Balance and compensation for performance. There are the importance of Planning and study of tasks and jobs and selection and training.

Industrial Revolution

A Summary - First and Second Industrial Revolution

Process of change from an agrarian, handicraft economy to one dominated by industry and machine manufacture.

It began in England in the 18th century. Technological changes included the use of iron and steel, new energy sources, invention of new machines that increased production, development of the factory system, and important developments in transportation and communication (including the steam engine and telegraph). Other changes included agricultural improvements, a wider distribution of wealth, political changes reflecting the shift in economic power, and sweeping social changes.

The Industrial Revolution was largely confined to Britain from 1760 to 1830, then spread to Belgium and France. Other nations lagged behind, but once Germany, the U.S., and Japan achieved industrial power they outstripped Britain's initial successes. Eastern European countries lagged into the 20th century, and not until the mid-20th century did the Industrial Revolution spread to such countries as China and India. Many analysts saw evidence of a second, or new, industrial revolution in the later 20th century, with the use of new materials and energy sources, automated factories.

Conclusion: The evolution, the technology and the increase of industrial productivity, they were provided by scientific studies, influences social economical, for it analyzes of processes, production cycle and improvement continues.