May 31, 2019

Methods Efficiency Engineering


Productivity Engineering - Principle of Industrial Engineering


Industrial engineering is concerned with redesign of engineering systems with a view to improve their productivity. Industrial engineers analyze productivity of each  resource used in engineering systems and redesign as necessary to improve productivity.

It has to be ensured that the increase in productivity due to the use of low-cost materials, processes and increasing speed of machines and men, should not lead to any decrease in quality of the output.

Similarly, operators should not feel any discomfort, not have any health problems or safety issues in the redesigned more productive processes.


Methods Efficiency Engineering - Method of Industrial Engineering



In industrial engineering, there is a branch popularized as methods engineering, method study or work study. The right term for this subject should be "Methods Efficiency Engineering". Methods Engineering is the process of coming out with methods to manufacture a component, a product or to perform a service. Methods engineering is expected to come out with effective and efficient method. Industrial engineering participates in the methods engineering activity to provide efficiency related services.

Industrial engineers use analysis to find inefficiencies in proposed methods or existing ways of work and then synthesize the new method having the most efficient components and then standardize the method. It includes training workmen also. Then they develop standard times for the installed standard times.

For improving methods efficiency, industrial engineers use process efficiency analysis techniques, operation efficiency analysis techniques and motion efficiency analysis techniques.

Process efficiency analysis questions the need for every step in the analysis and looks at the possibilities for changing the sequence of operations and for combining or splitting operations further to enhance the efficiency of the process.

Operation analysis looks at each operation and resources used in the operations. It looks at the equipment used, time the equipment is utilized, the tools used, jigs and fixtures used, energy consumption, material consumption, work place layout, material handing method used, and inventory.  Motion analysis examines the motions made by the operator.



More detailed articles on methods and techniques

Process Analysis - Questions/Check List
Method Study
Operation Analysis
MOTION STUDY

Method Study - Case Studies


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Casetudy: http://www.globalresearch.com.my/main/papers/icber/PAPER_107_ImpactTime.pdf

Time and Motion Studies in Libraries http://www.ideals.illinois.edu/bitstream/handle/2142/5533/librarytrendsv2i3F_opt.pdf


Originally posted in Knol

Updated 15 June 2014, 15 Dec 2011


Industrial Engineering Knowledge Revision Plan - One Year Plan


January - February - March - April - May - June



July - August - September - October - November - December


Updated on 1 June 2019, 15 June 2014

Selling Process - 10 Steps

Selling Skills - Process - Article - Series




Steps in selling process




1. Prospecting

2. Call planning

3. The visit – preliminaries

4. Presentation

5. Trial close

6. Listening to the objections

7. Objection handling

8. Trial close

9. Close

10. Follow-up and service





Description and explanation of each step - Knol References




Selling Process – Prospecting

1. Prospecting

Selling Process – Prospecting
http://nraomtr.blogspot.com/2011/11/selling-process-prospecting.html





2. Call planning

Sales Process – Call Planning

http://nraomtr.blogspot.com/2011/11/sales-process-call-planning.html



3. The visit – preliminaries

Approaching the Prospect
http://nraomtr.blogspot.com/2011/11/approaching-prospect.html



What should I wear for sales calls?

http://www.businesstown.com/sales/face-qa.asp

4. Presentation

http://nraomtr.blogspot.com/2011/11/interacting-with-prospect-customer.html

5. Trial close

http://nraomtr.blogspot.com/2011/11/trial-close.html

6. Listening to the objections

http://nraomtr.blogspot.com/2011/11/prospect-objections-during-sales.html

7. Objection handling


8. Trial close
http://nraomtr.blogspot.com/2011/11/trial-close.html

9. Close
http://nraomtr.blogspot.com/2011/11/sales-closing-techniques.html

10. Follow-up and service

http://nraomtr.blogspot.com/2011/11/service-to-customer-follow-up-after.html






Additional web references on Selling



Selling Skills: Strategies and Methods - Online Book
http://bbssob.blogspot.com/

10 greatest salesmen of all time
http://www.inc.com/ss/10-greatest-salespeople-of-all-time
Business Development Mindset:Small Business Sales Planning and Execution

http://knol.google.com/k/aline-gianfagna/business-development-mindset/2d21qdrhcu6v4/2#

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Popular Posts in Marketing Management


Marketing Communication: Channels and Promotion Tools


Marketing Strategy - Marketing Process - Kotler's Description 


Marketing Strategy - Differentiating and Positioning the Market Offering


The Marketing Concept - Kotler



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Updated on 2 June 2019, 26 November 2011

Industrial Engineering - Introduction



Industrial Engineering in Toyota Motors – Production System (TPS)


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Industrial Engineering - Introduction


There is a difference between industrial engineering and engineering management. Now both these programs are run by IE departments only in USA. IE is better described as engineering in response to industry data, economic theories, social science theories, and management requirements etc. Engineering has to be core of industrial engineering. It is done in response to industry generated data. Basic engineering is driven by scientific and technical development. Industrial engineering is response to industry data that is generated in using basic engineering output.  Cost data and human factor related data are two important data which find a significant role in industrial engineering. Work measurement and productivity measurement were developed within industrial engineering as useful measurements in industrial engineering design. Industrial engineering is very valuable. That is what Taiichi Ohno and Shigeo Shingo proved in Toyota after a period of IE successes in USA. Japanese practitioners of IE made significant contributions to industrial engineering.

Innovation is the daily activity of industrial engineers. They have to come out with redesigns and convince their colleagues as well as top managers to use them.  Ideas are to be identified or created  and their economic value has to be demonstrated. Solutions are to be implemented and customer satisfaction has to be ensured.

Industrial Engineering - Definitions



Industrial engineering directs the efficient conduct of manufacturing, construction, transportation, or even commercial enterprises of any undertaking, indeed in which human labor is directed to accomplishing any kind of work . Industrial engineering has drawn upon mechanical engineering, upon economics, sociology, psychology, philosophy, accountancy, to fuse from these older sciences a distinct body of science of its own . It is the inclusion of the economic and the human elements especially that differentiates industrial engineering from the older established branches of the profession (Going, 1911) [1].


“Industrial engineering is the engineering approach applied to all factors, including the human factor, involved in the production and distribution of products or services.” (Maynard, 1953) [2]


“Industrial engineering is the design of situations for the useful coordination of men, materials and machines in order to achieve desired results in an optimum manner. The unique characteristics of Industrial Engineering center about the consideration of the human factor as it is related to the technical aspects of a situation, and the integration of all factors that influence the overall situation.” (Lehrer, 1954) [3]

“Industrial engineering is concerned with the design, improvement, and installation of integrated systems of men, materials, and equipment. It draws upon specialized knowledge and skill in the mathematical, physical, and social sciences together with the principles and methods of engineering analysis and design, to specify, predict, and evaluate the results to be obtained from such systems.” (AIIE, 1955). [4]


"Industrial engineering may be defined as the art of utilizing scientific principles, psychological data, and physiological information for designing, improving, and integrating industrial, management, and human operating procedures." (Nadler, 1955) [5]


“Industrial engineering is that branch of engineering knowledge and practice which

1. Analyzes, measures, and improves the method of performing the tasks assigned to individuals,

2. Designs and installs better systems of integrating tasks assigned to a group,

3. Specifies, predicts, and evaluates the results obtained.

It does so by applying to materials, equipment and work specialized knowledge and skill in the mathematical and physical sciences and the principles and methods of engineering analysis and design. Since, however, work has to be carried out by people; engineering knowledge needs to be supplemented by knowledge derived from the biological and social sciences.” (Lyndall Urwick, 1963) [6]


"Industrial engineering is concerned with the design, improvement and installation of integrated systems of people, materials, information, equipment and energy. It draws upon specialized knowledge and skill in the mathematical, physical, and social sciences together with the principles and methods of engineering analysis and design, to specify, predict, and evaluate the results to be obtained from such systems." [7]

"Industrial engineering is an art for creating the most efficient system composed of people, matters, energy, and information, by which a specific goal in industrial, economic, or social activities will be achieved within predetermined probabilities and accuracy. The system may be for a small single work station, a group, a section, a department, an institution or for a whole business enterprise. It may be also be of a regional, national, international, or inter-planetary scope."(Sawada, 1977) [8]

“Industrial Engineering is Human Effort Engineering. It is an engineering discipline that deals with the design of human effort in all occupations: agricultural, manufacturing and service. The objectives of Industrial Engineering are optimization of productivity of work-systems and occupational comfort, health, safety and income of persons involved.” (Narayana Rao, 2006) [9]


"Industrial Engineering is Human Effort Engineering and System Efficiency Engineering. It is an engineering discipline that deals with the design of human effort and system efficiency in all occupations: agricultural, manufacturing and service. The objectives of Industrial Engineering are optimization of productivity of work-systems and occupational comfort, health, safety and income of persons involved."(Narayana Rao, 2009) [10]

Total Industrial Engineering is "a system of methods where the performance of labor is maximized by reducing Muri (unnatural operation), Mura (irregular operation) and Muda (non-value added operation), and then separating labor from machinery through the use of sensor techniques." (Yamashina)

( Source: http://wenku.baidu.com/view/a1cdf8ec4afe04a1b071de84.html)

"Industrial Engineering is Human Effort Engineering and System Efficiency Engineering. It is an engineering-based management staff-service discipline that deals with the design of human effort and system efficiency in all occupations: agricultural, manufacturing and service. The objectives of Industrial Engineering are optimization of productivity of work-systems and occupational comfort, health, safety and income of persons involved."(Narayana Rao, 2011) [Added to this knol (blog post) on 14.9.2011]

References

1. Going, Charles Buxton, Principles of Industrial Engineering, McGraw-Hill Book Company, New York, 1911, Pages 1,2,3

2. Maynard, H.B., “Industrial Engineering”, Encyclopedia Americana, Americana Corporation, Vol. 15, 1953

3. Lehrer, Robert N., “The Nature of Industrial Engineering,” The Journal of Industrial Engineering, vol.5, No.1, January 1954, Page 4

4. Maynard, H.B., Handbook of Industrial Engineering, 2nd Edition, McGraw Hill, New York, 1963.

5. Nadler, Gerald, Motion and Time Study", McGraw-Hill Book Company, Inc., New York, 1955

6. Urwick, Lyndall, F., “Development of Industrial Engineering”, Chapter 1 in Handbook of Industrial Engineering, H.B. Maynard (Ed.), 2nd Edition, McGraw Hill, New York, 1963.

7. http://www.iienet2.org/Details.aspx?id=282

8. Sawada, P.N., "A Concept of Industrial Engineering," International Journal of Production Research, Vol 15, No. 6, 1977, Pp. 511-22.
9. Narayana Rao, K.V.S.S., “Definition of Industrial Engineering: Suggested Modification.” Udyog Pragati, October-December 2006, Pp. 1-4.
10. Narayana Rao K.V.S.S., Industrial Engineering

Industrial engineering is based on science. It is based scientific theories developed by examining the work of machines and men in practical applications in delivering outputs using engineering processes.

Productivity Science - Principle of Industrial Engineering

Develop a science for each element of a man - machine system's work related to efficiency and productivity.

The productivity science developed is the foundation for industrial engineering in productivity engineering and productivity management phases.

Industrial Engineering is a Management Function



Industrial engineering (IE) discipline emerged out of the involvement of engineers in management of engineering departments. It is management function. Herny Towne in a 1886 paper, presented in ASME called for learning of economics, management, cost accounting and cost reduction by engineers. Frederick Taylor identified the short coming in the shop management that engineers really do not understand how operators are using machines or hand tools. It is not proper management of manufacturing activity. Taylor came with the theory that managers have to know how work is to be done by operators and must have the capability to train them. Managers have to specify standard operating procedures. Taylor used time study as the tool to identify the best practices or methods being used by operators at that point in time and based on them developed standard operating procedures that improved productivity. Along with it, Taylor developed theory of various work methods, conducted experiments and came out with improvements in man-machine system productivity. Gilbreth came with a different approach of developing micro motions used by operators to carry any activity. He developed optimal methods by removing certain non-value adding micro motions and specifying more optimal micro motions. Harrington Emerson, developed principles of efficiency for manufacturing organizations.

Within the management functions its present focus of industrial engineering is on the design of work done by operators and improvement of efficiency of systems and processes.

In certain companies, IE department was made a part of management services department which was appropriate. Management accounting, Management controls, Management audit, Industrial engineering and some more such similar functions can be organized under management services departments. Such a departmentation clearly recognizes that these sections or functions are functions of management assisting management in planning, organizing and directing resources.

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Explanation for the Words "Industrial" and "Engineering" in Industrial Engineering


Difference between Pure Engineering and  Industrial Engineering

Pure Engineering creates  technical products.

Industrial Engineering is engaged in evaluation and improvement of the technical product created by the pure engineers so that at the price offered by the customers to buy a specified quantity of production, profit is made by the firm through resource use minimization and through further iterations profit is further increased.

That is why Taiichi Ohno termed it Profit engineering
Target costing developed in Japan best explains the role of industrial engineering.


IE techniques are primarily used for improving technical processes and managerial processes of technical processes (planning, organizing, resourcing, executing and controlling of technical tasks and processes) for increasing productivity. All IE pioneers worked in engineering concerns. They improved technical processes as well as managerial methods and processes used to manage technical processes.

F.W. Taylor improved metal cutting, machines, and management of machine shop through his functional management scheme.

Gilbreth improved bricklaying process by making changes in techniques. Then he proceeded to make fatigue studies to decide the speed at which workers can function and also time.

As an augmented activity, IE is applied to business processes and managerial activities related to business processes.

The emphasis on engineering tasks is the engineering component of industrial engineering. Emphasis on making products profitable is the explanation for the term "industrial". Technical products are made commercial products or industrial products by IEs by reducing their costs below the prices quoted by potential consumers and still further reducing the costs by eliminating wastes so that profit is maximized through increase in sales (due to lower prices) as well as reduction in unit costs.

The basis for reduction of costs is better explained by value engineering. A potential customer quotes a price for a new product by the services it provides to him and by comparison to the prices that he is paying for current equipment that he is using. So for reducing the costs of a proposed product to bring it in line with customer's quote, industrial engineers have to study the architecture of the current products being used by potential customers. They need to get ideas for redesigning the proposed product by understanding how the required functions are being provided by the existing products being currently used at a lower cost. In investigating the product, the processes being used for producing them also come into investigation.

Productivity Engineering - Principle of Industrial Engineering

Industrial engineering is concerned with redesign of engineering systems with a view to improve their productivity. Industrial engineers analyze productivity of each  resource used in engineering systems and redesign as necessary to improve productivity.

It has to be ensured that the increase in productivity due to the use of low-cost materials, processes and increasing speed of machines and men, should not lead to any decrease in quality of the output.


1908 – The industrial engineering department at Penn State is founded by Hugo Diemer, a pioneer in the field. Diemer coined the term “industrial engineering” in 1900 to describe the fusion of engineering and business disciplines. Diemer is named the first head of the department.
http://www.ime.psu.edu/department/history.aspx

The fusion created by Taylor, Gilbreth, Emerson, Diemer and Going is the efficiency improvement of engineering systems to make projects viable and prosperous.

Functions and Focus Areas of Industrial Engineering

What is Industrial Engineering?

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Narayana Rao


Principles of Industrial Engineering - Taylor - Narayana Rao

Presentation by Narayana Rao on 23 May 2017 at IISE 2017 Annual Conference - Pittsburgh

Professor Narayana Rao developed Principles of Industrial Engineering in July 2016 and presented them in two conferences. The detailed set of principles were presented in the 2017 IISE Annual Conference held in Pittsburgh, USA. The paper is included in the proceedings of the conference.
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Narayana Rao


Basic Principles of Industrial Engineering - Narayana Rao

1. Develop science for each element of a man - machine system's work related to efficiency and productivity.
2. Engineer methods, processes and operations to use the laws related to the work of machines, man, materials and other resources.
3. Select or assign workmen based on predefined aptitudes for various types of man - machine work.
4. Train workmen, supervisors, and engineers in the new methods.
5. Incorporate suggestions of operators, supervisors and engineers in the methods redesign on a continuous basis.
6. Plan and manage productivity at system level.

(Principles developed by Narayana Rao based on principles of scientific management by F.W. Taylor on 4 July 2016.)

Detailed List of Principles - Presented at IISE 2017 Annual Conference at Pittsburgh on 23 May 2017.


1. Productivity science
2. Productivity engineering
3. Ind Engineering is applicable to all branches of engineering
4. Principles of machine utilization economy to be developed for all resources used in engineering systems.
5. Industrial engineering optimization
6. Industrial engineering economics
7. Implementation team membership and leadership
8. Human effort engineering for increasing productivity
9. Principles of motion economy to be used in all IE studies in the area of human effort engineering
10. Operator comfort and health are to be taken care of.
11. Work measurement
12. Selection of operators
13. Training of operators, supervisors and engineers
14. Productivity training and education to all
15. Employee involvement in continuous improvement of processes and products for productivity improvement.
16. Productivity incentives
17. Hearty cooperation
18. Productivity Management
19. System level focus for productivity
20. Productivity measurement
21. Cost measurement

June First Week - IE Knowledge Revision

http://nraoiekc.blogspot.com/2016/05/june-first-week-ie-knowledge-revision.html

Industrial Engineering in Various Functions of a Business/Industrial Organization



Product Design Industrial Engineering
http://nraoiekc.blogspot.com/2012/09/product-design-industrial-engineering.html

Maintenance System Industrial Engineering - Online Book
http://nraoiekc.blogspot.com/2012/09/maintenance-system-industrial.html

Information Systems Industrial Engineering - Online Book
http://nraoiekc.blogspot.com/2012/09/information-systems-industrial.html

Financial System Industrial Engineering - Online Book
http://nraoiekc.blogspot.com/2012/09/financial-system-industrial-engineering.html

Marketing System Industrial Engineering - Online Book
http://nraoiekc.blogspot.com/2012/09/marketing-system-industrial-engineering.html

Supply Chain Industrial Engineering - Online Book
http://nraoiekc.blogspot.com/2012/09/supply-chain-industrial-engineering.html

Manufacturing System Industrial Engineering - Online Book
http://nraoiekc.blogspot.com/2012/09/manufacturing-system-industrial.html

Total Cost Industrial Engineering - Industrial Engineering of Enterprise Cost
http://nraoiekc.blogspot.com/2012/09/total-cost-industrial-engineering.html

Quality System Industrial Engineering
http://nraoiekc.blogspot.com/2012/10/quality-system-industrial-engineering.html
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Updated 1 June 2019, 25 May 2019,   4 June 2017,  27 May 2016,  16 Dec 2011

Work Measurement



Work measurement is to be used to identify best way of doing an element of work. After a task is designed combining various elements the total time taken can be specified by summing up the time estimate for each element. Now predetermined time systems, the most popular being Most use this method.

Stop watch time study can be used on average trained operator to observe the time taken for each elements and from these observations standard times can be prescribed.

Measured calculated standard times of various tasks can be used to set daily task for operators.

Task based incentives can be set based on the standard time which is an output of work measurement.



Purpose of Work Measurement in Today's Industrial Situation.


Efficient methods are selected with the help of work measurement techniques when time is the most important parameter for deciding the efficiency of a method. Even if cost is the decision variable, we have to know the manpower time and machine times to calculate the cost of a method.

Optimization of plans and management decisions are done with work measurement results.


Work Measurement in Taylor's Time


One Reason was understanding the output that can be produced by a man. Taylor improved the working method, and gave rest breaks that would result in maximum output per day. But he used work measurement to find the minimum time in which a first class workman is able to do a given element of work.

F.W. Taylor came out with stop watch time technique that measured time taken for each element of an operation and systematized the work measurement procedures. Based on these time studies standard times of various work pieces were determined and fair job for the day of the worker was established using these standard times. Incentive systems were put in place to provide scope and income opportunity for production above the standard rate and also to provide motivation to reach the standard and exceed the standard.

Work Measurement - More Detail - Nadler

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Industrial Engineering Knowledge Revision Plan - One Year Plan


January - February - March - April - May - June



July - August - September - October - November - December



Updated 1 June 2019,   4 June 2016, 16 Dec 2011

Marketing Management Subject Update




Marketing Management Revision Article Series



2019

Why B2B Buying Cycles Are So Long
http://b2bmarketingdirections.blogspot.com/2019/05/why-b2b-buying-cycles-are-so-long.html

What Abraham Maslow Can Teach Us About Customer Experience
http://b2bmarketingdirections.blogspot.com/2018/07/what-abraham-maslow-can-teach-us-about.html

Marketing Communication Plan
Communication for pull. Communication for push Communication for profile.
https://neilsbrandingblog.blogspot.com/2018/10/marketing-communication-plan.html

Marketing 4.0


“Marketing 4.0: When Online Meets Offline, Style Meets Substance, and Machine-to-Machine Meets Human-to-Human” – Philip Kotler, Hermawan Kartajaya, Iwan Setiawan
May 5, 2018

Marketing 4.0 is about balancing machine-to-machine (M2M) with human-to-human (H2H).

New Ideas in Marketing 4.0

‘Segmentation and Targeting’ to ‘Customer Community Confirmation’
‘Selling the 4P’s’to ‘Commercializing the 4C’s’
‘Customer Service Processes’ to ‘Collaborative Customer Care’
‘Brand Positioning and Differentiation’ to ‘Brand Characters and Codes’
‘Segmentation and Targeting’ to ‘Customer Community Confirmation’
http://www.marketingjournal.org/marketing-4-0-when-online-meets-offline-style-meets-substance-and-machine-to-machine-meets-human-to-human-philip-kotler-hermawan-kartajaya-iwan-setiawan/


Why Great Innovation Needs Great Marketing
Denise Lee Yohn
FEBRUARY 20, 2019

Strategic, upstream marketing that is incorporated into the innovation development process can clearly define who to sell the new offering to and how to sell it.
Decide 4Ps of marketing using marketing expertise.

 Innovation alone may be enough to initiate the adoption life cycle, but marketing remains the bridge necessary to cross the chasm between early adopters to the wider group of people who will form a viable, valuable customer base.
https://hbr.org/2019/02/why-great-innovation-needs-great-marketing

4 Ways to Improve Your Content Marketing
Frank V. CespedesRuss Heddleston
APRIL 19, 2018
The average viewing time for content is 2 minutes and 27 seconds.
Frank Cespedes is a Senior Lecturer at Harvard Business School and author of Aligning Strategy and Sales (Harvard Business Review Press).
https://hbr.org/2018/04/4-ways-to-improve-your-content-marketing

Why Marketing Analytics Hasn’t Lived Up to Its Promise
Carl F. MelaChristine Moorman
MAY 30, 2018

Communication theory tells us that the transmitter and receiver of information must share a common domain of knowledge for information to be transmitted. This means analysts need to understand what the firm’s managers can understand.
 it is critical for analysts to connect externally with customers and internally with the managers using their work.
Carl F. Mela is the T. Austin Finch Foundation Professor of Marketing at Duke University’s Fuqua School of Business and the Executive Director at the Marketing Science Institute.
https://hbr.org/2018/05/why-marketing-analytics-hasnt-lived-up-to-its-promise



2017

5 Ways Words Can Destroy Your Marketing Messages (And How to Fix Them)
Use these copywriting tips to improve your marketing messages and ensure you don't lose sales or money on your marketing investments.
https://www.entrepreneur.com/article/298766



There is No Luck. Only Good Marketing.

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TEDx Talks

Article in HBR on Organization of Marketing Department
https://hbr.org/2014/07/the-ultimate-marketing-machine

Developing a marketing plan  (interesting information is in the article)
http://canadabusiness.ca/managing-your-business/marketing-and-sales/marketing-basics/developing-a-marketing-plan/

Key competencies for general sales effectiveness
By Amir Qureshi
12 December 2016
https://www.thomasinternational.net/en-gb/blog/december-2016/key-competencies-for-general-sales-effectiveness/


Dec 2016

https://medium.com/context/tagged/best-of-2016


March 2016

Marketing Managers' Salary Guide for USA - 2016
https://www.ama.org/career/Pages/2016-Marketers-Salary-Guide.aspx

https://hbr.org/topic/marketing

http://knowledge.wharton.upenn.edu/article/imagine-theres-no-marketing-its-easy-if-you-try/

http://knowledge.wharton.upenn.edu/article/six-digital-marketing-traps-that-cmos-should-avoid/

http://knowledge.wharton.upenn.edu/article/small-data-new-big-data/

http://knowledge.wharton.upenn.edu/article/recommended-for-you-how-well-does-personalized-marketing-work/


https://www.ted.com/talks/seth_godin_on_the_tribes_we_lead

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TED


May 2015

Negotiation: What Makes the Right Business Deal
http://www.forbes.com/sites/ianaltman/2015/05/05/negotiation-what-makes-the-right-business-deal/


Macromarketing
I searched for this topic today in my interest to write an article on the topic marketing support for Make in India Campaign. I found that there a huge literature in the area of macromarketing. The reference I came across today are:

Marketing Theory: Philosophy of Science Perspectives
https://books.google.co.in/books?id=W4phEfAbHBQC


http://en.wikipedia.org/wiki/Macromarketing


April 2015

Marketing communication messages have to be different when you announce a product and build buying intention for it. The communication has to change when the product is actually made available in the market for purchase.  Read the summary of a recent research paper on adoption of products.
http://nraomtr.blogspot.com/2015/04/adoption-of-new-products-and-processes.html


February 2015
Planned Revision schedule for marketing chapters is in February and March

January 2015

Why Your Customers’ Social Identities Matter.

By: Champniss, Guy; Wilson, Hugh N.; Macdonald, Emma K. Harvard Business Review. Jan/Feb2015, Vol. 93 Issue 1/2, p88-96.

People are highly social animals. Most of us belong to many social groups, each with its own identity.

For five years the authors have been studying how social identity affects customer behavior in a wide range of industries. They have seen that companies can trigger more-favorable reactions in customers by subtly influencing which identities they tap into. This is something firms should take into account when doing market research or designing experiences.

The first step is to surface the range of  a customer's  possible identities. If a customer's identity encourages targeted behaviors, marketers can help reinforce it.  Marketers can also work to add a desired behavior to those that customers associate with an identity, prime different identities in customers, and even create new identities that deepen relationships with existing customers and attract new ones.




2014's top The Gunn Reports' Cases For Creativity

1. 1. IBM's 'A Boy And His Atom' Ogilvy & Mat her, USA
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IBM upload
http://economictimes.indiatimes.com/magazines/brand-equity/2014s-top-the-gunn-reports-cases-for-creativity/articleshow/45952325.cms


2. Evian Baby & Me
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EvianBabies
99,261,360 views 29 Jan 2015


"Contagious: Why Things Catch on" by Jonah Berger was named the best book of Marketing of 2014
Talk by Jonah Berger
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Talks at Google upload
http://google.co.in/books?id=J2l7pgwTiW4C  (For previewing the book)

Marketing News - 15 January Issue
http://publications.ama.org/Marketing_News/MN-jan15/index.html

Why Uniqlo Is Winning
By: David Aaker
Uniqlo is Japanese clothing retailer now in top 5 and plans to beat Zara.
https://www.ama.org/publications/MarketingNews/Pages/why-uniqlo-is-winning.aspx


Updated 1 June 2019. Dec 2015


Give your suggestions for adding any articles to the collection.

May 30, 2019

Digital Transformation of Business and Industrial Organizations - Subject Update


What is Management? A New Look:

Management Definition – Narayana Rao


Management of an organization is the process of establishing objectives and goals of the organization periodically, designing the work system and the organization structure, and maintaining an environment in which individuals, working together in groups, accomplish their aims and objectives and goals of the organization effectively and efficiently. (3rd December 2008)

Implications of the  Definition:

(i) Management is a process.
(ii) Management applies to every kind of organization, government, profit making, or nonprofit making.
(iii) It applies to managers at all levels in the organization.
(iv) Management is concerned with effectiveness and efficiency.

Video Explanation of  the  Definition

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2019

Top 10 influencers in digital transformation you should follow in 2019

Dez Blanchfield – Chief Data Scientist, Gara Guru
Ken Bonifay – North America Sales Leader – Financial Services Market, IBM
Sally Eaves – Member, Forbes Technology Council
Antonio Grasso – Founder & CEO, Digital Business Innovation Srl
Dr. Robin Kiera – Speaker, Thought Leader, Storyteller, DigitalScouting.de
Joe McKendrick – Analyst and Contributor, CBS Interactive, Forbes, Information Today
Mike Quindazzi – Managing Director US Digital Alliances, PwC
Jacqui Shawley – Global Market and Offering Manager, IBM Z
Ronald van Loon – Director, Adversitement
Helen Yu – Founder & CEO, Tigon Advisory Corp.
https://www.ibm.com/blogs/systems/top-10-people-digital-transformation-2019/

2018

January

Digital Transformation - Principles, Strategies and Rules


Advice and Suggestion from Jeff Immelt -
Leaders must act as Systems Thinkers in Digital Transformation.


Leaders have to understand how cyber - physical systems in combination deliver value to customers.

Marketing chain and Supply Chain are to be integrated and cyber - physical systems exist in both the chains. Digital and Physical systems and people have to work in combination and deliver value to customers. Leaders and managers have to first visualize and design the work system.


https://www.linkedin.com/pulse/leaders-must-act-systems-thinkers-digital-jeff-immelt

Transform Your Business to Compete in the Digital Age

Columbia Business School
uploaded 19 January 2018
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#207: Digital Transformation and disruption in the Insurance Industry, with UNIQA Insurance Group



2017

KPMG declared leader in digital transformation consulting
Jul 12, 2017

KPMG was recently named a leader in the IDC MarketScape awards titled “Worldwide Digital Transformation Consulting and Systems Integration Services 2017 Vendor Assessment”. The award process noted that under times of turbulent change and economic challenges many firms around the world were calling upon KPMG to help them through the process challenges. KPMG have been identified for their strength in aiding organizations to begin the transformation process, and the disruptions this can bring, while maintaining their place within a competitive market.
http://www.digitaljournal.com/business/kpmg-declared-as-a-leader-in-digital-transformation-consulting/article/497459


Evolve Or Die: Why Digital Transformation Is More Important Than Ever
Four areas of focus for Digital transformation
http://www.brandquarterly.com/evolve-die-digital-transformation-important-ever

Davos 2017 - Preparing for the Fourth Industrial Revolution

World Economic Forum
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Published on 19 Jan 2017
http://www.weforum.org/
What is needed from the public and private sectors to ensure that the Fourth Industrial Revolution benefits all of humanity?

- Mukesh D. Ambani, Chairman and Managing Director, Reliance Industries, India
- Mary Barra, Chairman and Chief Executive Officer, General Motors Company, USA
- Marc R. Benioff, Chairman and Chief Executive Officer, Salesforce, USA; Young Global Leader Alumnus
- Shu Yinbiao, Chairman, State Grid Corporation of China, People's Republic of China
- Vishal Sikka, Chief Executive Officer, Infosys, USA

Chaired by
- Ngaire Woods, Dean, Blavatnik School of Government, University of Oxford, United Kingdom



Davos 2017 - Press Conference: The Digital Transformation of Industries

__________________

__________________
World Economic Forum,  Published on 19 Jan 2017
http://www.weforum.org/

The World Economic Forum launched the multi-year Digital Transformation of Industries Project in 2015 in partnership with Accenture. The project looks at how digital technologies like machine learning, cloud computing, and the internet of things are changing existing industries and creating entirely new ones. It makes recommendations to incumbents on how they can thrive in the new digital environment.

There are now hundreds of startups attacking traditional markets as a result of the democratization of technology, increased access to funds and a rising entrepreneurial culture. Start-ups are achieving scale far quicker than analogue companies ever did. Average Fortune 500 companies took 20 years to reach a market cap of $1 billion, Google managed it in eight years, and the likes of Uber, Snapchat and Xiaomi in three years or less. 88% of Fortune 500 companies from 1955 – 2015 no longer exist. Digital disruption has been a major driver of this, consequently Fortune 500 companies must use their considerable resources to fight off the attacks of leaner challengers and remain relevant in a digital age.

- Bruce Weinelt, Head of Digital Transformation, World Economic Forum
- Peter Lacy, Global Managing Director, Strategy and Sustainability, Accenture
- Stephanie Linnartz, Global Chief Commercial Officer, Marriott International Inc.
- Jean Philbert Nsengimana, Minister of Youth and Information Communication Technology,        Ministry of Youth and Information and Communication Technology of Rwanda

Moderated by
- Alem Tedeneke, Media Specialist, World Economic Forum LLC

2016


3 Industries That Will Be Transformed By AI, Machine Learning And Big Data In The Next Decade
Bernard Marr
SEP 27, 2016
Healthcare - Finance - Insurance

https://www.forbes.com/sites/bernardmarr/2016/09/27/3-industries-that-will-be-transformed-by-ai-machine-learning-and-big-data-in-the-next-decade/#2104a850183e


Acting on the Digital Imperative - BCG

SEPTEMBER 12, 2016
By Ralf Dreischmeier , Karalee Close , Thomas Gumsheimer , Peter Hildebrandt , and Adal Zamudio
https://www.bcg.com/publications/2016/technology-digital-strategy-acting-on-digital-imperative.aspx

Digital Transformation Playbook

Prof. David Rogers, Columbia Business School
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_________________
June 2016, Columbia Business School

https://cup.columbia.edu/book/the-digital-transformation-playbook/9780231175449



The Digital Imperative  - Article by BCG

By Ralf Dreischmeier , Karalee Close , and Philippe Trichet
MARCH 2, 2015
https://www.bcg.com/publications/2015/digital-imperative.aspx



Updated on 2019  31 May 2019

2018 - 3 February 2018,   25 January,  19 January


 25 November 2017,  26 August 2017,   22 August 2017, 7 June 2017, 14 April 2017

What is Data Science? - Evolution of Data Science

Excerpts from Global Data Science Forum What is Data Science?
By Paco Nathan posted Mon March 04, 2019
https://community.ibm.com/community/user/datascience/blogs/paco-nathan/2019/03/04/what-is-data-science

What is Data Science?

A popular 2012 tweet by Josh Wills:

Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.

Data Science gained traction in industry circa 2008, just as tooling for big data was on the rise, and as business use cases for machine learning (ML) became popularized. Those three grew together in contrast to an earlier era of business intelligence (BI), which was initially popularized by Gartner analyst Howard Dresner. Most of BI was defined atop data warehouse (DW) practices, based on work by Barry Devlin and Paul Murphy, Ralph Kimball, Bill Inmon, et al. BI and DW were both introduced in the late 1980s, then became widespread practices throughout the 1990s.

Data science emerged in response to demand for more advanced techniques and larger scale-out than what the best practices from the prior decade could provide. Cloud resources were becoming popular, and crucial insights could be obtained more quickly and more cost-effectively due to popular open source tools such as Hadoop, Spark, plus a whole range of Python libraries.

In 1962, a Bell Labs mathematician named John Tukey wrote a paper called “The Future of Data Analysis”.  Tukey urged a provocative new stance for applied mathematics which he called data analysis. The interesting section headings are:

“We should seek out wholly new questions to be answered.”
“We need to tackle old problems in more realistic frameworks.”
“We should seek out unfamiliar summaries of observational material, and establish their useful properties.”
“And still more novelty can come from finding, and evading, still deeper lying constraints.”

In the  books on visualizing data by Ed Tufte, references to Tukey show up throughout most all of books.

A generation later, another Bell Labs researcher named William Cleveland coined the term data science in a 2001 paper citing Tukey among others,  “Data science: An action plan for expanding the technical areas of the field of statistics”. Cleveland proposed an outline for a multi-disciplinary curriculum:

(25%) Multidisciplinary Investigations: data analysis collaborations in a collection of subject matter areas.
(20%) Models and Methods for Data: statistical models; methods of model building; methods of estimation and distribution based on probabilistic inference.
(15%) Computing with Data: hardware systems; software systems; computational algorithms.
(15%) Pedagogy: curriculum planning and approaches to teaching for elementary school, secondary school, college, graduate school, continuing education, and corporate training.
(5%) Tool Evaluation: surveys of tools in use in practice, surveys of perceived needs for new tools, and studies of the processes for developing new tools.
(20%) Theory: foundations of data science; general approaches to models and methods, to computing with data, to teaching, and to tool evaluation; mathematical investigations of models and methods, of computing with data, of teaching, and of evaluation.

This curriculum indicates what Cleveland thought the field required, namely that data science is a space in which statistics and computing needed to interact, to provide the necessary resources and scale.

That same year, a UC Berkeley professor named Leo Breiman wrote “Statistical Modeling: The Two Cultures”. One culature is of the previous era which he called data modeling and a new trend emerging which he called algorithmic modeling. That culture of data modeling was what Tukey had argued against.  The newer culture embraced much larger data rates and more computation and also leveraged machine learning algorithms to help automate decisions at scale.

The current heyday of data science began when some of these applications which required more data started to become tractable, reliable, and cost-effective (in that order).

Check out these histories by lead architects at those firms – roughly centered on Q3 1997, which turned out to be a key inflection point for the Dot Com Boom:

“Early Amazon: Splitting the website”, Greg Linden, Amazon
“eBay Architecture”, Randy Shoup, eBay
“Inktomi’s Wild Ride”, Erik Brewer, Yahoo! Search (0:05:31 ff)
“Underneath the Covers at Google”, Jeff Dean, Google (0:06:54 ff)

The timing for those projects was during the peak of data warehouses and business intelligence adoption. However, a common theme among those four architects’ reflections is that they recognized how they’d need to scale ecommerce applications but could not do so with available tooling. Instead they turned to open source tools (such as Linux) for early data science work on proto clouds, leveraging ML at scale for ecommerce. Their timing was impeccable, particularly for Amazon: just in time to monetize the first big wave of ecommerce in the holiday season of Q4 1997. The rest is history.

The gist is that ecommerce firms split their web apps using a principle of horizontal scale out, i.e., proto cloud work on server farms. Those many servers generated lots of log files (proto Big Data), which in turn were analyzed using machine learning algorithms, which in turn provided predictive analytics that improved customer experience in the web apps. A virtuous cycle emerge, with data as a product.

However, after Q4 1997 the world of data changed, predictive analytics loomed large. Breiman described that sea change quite succinctly:

A new research community using these tools sprang up. Their goal was predictive accuracy. The community consisted of young computer scientists, physicists and engineers plus a few aging statisticians. They began using the new tools in working on complex prediction problems where it was obvious that data models were not applicable: speech recognition, image recognition, nonlinear time series prediction, handwriting recognition, prediction in financial markets.

Plenty of other people also helped further the cause of “data science” and deserve credit, such as Jeff Wu who likely coined the phrase (in its contemporary usage) during his U Michigan appointment lecture “Statistics = Data Science?”

The main takeaway from this article:

Looking at decades of history, data science found its place by applying increasingly advanced mathematics for novel business cases, in response to surges in data rates and compute resources.

In the latest wave of AI applications in industry, we have the term ABC emerging to describe a winning combo of “AI”, “Big Data”, and “Cloud Computing” – as the latest embodiment of that takeaway described above.

Beyond the well-known roles of data scientist and data engineer, there’s another important role emerging which has not yet been named. We found that 23% of the enterprise organizations attempting to leverage data science, machine learning, artificial intelligence, etc., cite recognize business use case as a critically missing skill within their teams. What would you call that role? Where and how does a person learn to perform it?

Data Science - More explanations


What is Data Science?


 In a 2009 McKinsey&Company article, Hal Varian, Google's chief economist and UC Berkeley professor of information sciences, business, and economics, predicted the importance of adapting to technology’s influence and reconfiguration of different industries. 2

“The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades.”
https://datascience.berkeley.edu/about/what-is-data-science/

Chapter 1. Introduction: What Is Data Science?
Doing Data Science by Rachel Schutt, Cathy O'Neil
https://www.oreilly.com/library/view/doing-data-science/9781449363871/ch01.html

Data Science vs. Big Data vs. Data Analytics
By Shivam Arora
Jan 4, 2019
https://www.simplilearn.com/data-science-vs-big-data-vs-data-analytics-article

Oracle Artificial Intelligence (AI)—What Is Data Science?
An elaborate article giving many details of data science and related issues.


Earlier Articles

What is Data Science? - An Introduction to Data Science

Data Science - Online Study Notes and Video Courses - Free Also

Data Analytics and Data Mining - Difference Explained


Updated on 31 May 2019, 26 May 2019

Peter Drucker on Scientific Management - Industrial Engineering

"Scientific management is our most widely practised personnel management concept" said Peter Drucker in his book The Practice of Management. The concepts of scientific management underlie the actual management of worker and work in American Industry.

"Scientific management is our most widely practised personnel management concept" said Peter Drucker in his book The Practice of Management. The concepts of scientific management underlie the actual management of worker and work in American Industry. The core of scientific management is the organized study of work, the analysis of work into its simplest elements and the systematic improvement or design of each of these elements. Drucker emphasized that scientific management has both basic concepts and easily applicable tools and techniques to carry out it intended job. Its contribution is visible in the form of higher readily measurable output.

Scientific management is a systematic philosophy of worker and work. As long as industrial society endures, we will not forget the insight that human work can be studied systematically, can be analyzed, can be improved by work on its elementary parts. Scientific management was a great liberating and pioneering insight. Without it a real study of human beings at work would not have been possible. Scientific management or industrial engineering has penetrated the entire world. Yet is has been stagnant for a long time. From 1890 to 1920 Scientific Management produced one brilliant insight after the other and creative thinkers like Taylor, Gantt and Gilbreths. During the last thirty years, it has given us little. There are exceptions like Mrs Lillian Gilbreth and the Late Harry Hopf.

According to Drucker, the lack of progress is due to two blind spots. One was the thinking that each element has to be done by one worker. Taylor saw the need to integrate and Harry Hopf certainly advocated it. According to Drucker, IE has not provided good integration tools or concepts, both individual elements and the special qualities of each man.

The second blind spot according to Drucker is insistence on divorce of planning and doing.

Drucker concluded his discussion of the topic with the statement, 'We must preserve the fundamental insights of Scientific Management - just as we must preserve those of Human Relations. But we must go beyond the traditional application of Scientific Management, must learn to see where it has been blind. And the coming of the new technology makes this task doubly urgent."


Functions and Focus Areas of Industrial Engineering formulated from a fresh statement of principles of industrial engineering. The fundamental insights of scientific management and human relations approaches are integrated by Narayana Rao.

References

Peter Drucker in his book The Practice of Management, First Edition, 1955, Current Print 2006, Butterworth Heinemann, .pp.273-281


Industrial Engineering Knowledge Revision Plan - One Year Plan


January - February - March - April - May - June



July - August - September - October - November - December

Updated on 31 May 2019, 2 May 2019

Orlicky's Material Requirements Planning, Third Edition by: Carol Ptak, Chad Smith - Book Information




Orlicky's Material Requirements Planning, Third Edition

by: Carol Ptak, Chad Smith

Preview the book in Google Books https://books.google.com/books?id=lRsULeiVTroC

A fully revised and updated edition of the landmark work on material requirements planning (MRP), Orlicky's Material Requirements Planning, Third Edition focuses on the new rules required to effectively support a manufacturing operation using MRP systems in the twenty-first century. This authoritative resource offers proven solutions that help you gain the competitive edge through strategic lead time reductions, substantial reductions in total inventory investment, and significant increases in service levels.

Building on the pioneering work of Joseph Orlicky, this new edition of the classic text on material requirements planning (MRP) reveals the next evolutionary step for materials and supply chain synchronization in the modern manufacturing landscape.

Orlicky's Material Requirements Planning, Third Edition  explains an alternative pull structure for planning and controlling materials flow, and presents results from actual implementations. This thoroughly updated edition offers comprehensive coverage of MRP, describes the current state of the MRP application, and identifies the fundamental changes required to achieve sustainable success given the current global circumstances and technology options. This state-of-the art guide articulates the next generation of MRP logic—demand driven MRP (DDMRP)—and provides a roadmap for the near and distant future for this critical manufacturing management tool.



Table of Contents

A. About the Authors
B. Foreword
C. Preface
1. Overview
2. MRP in the Modern World
3. The Four Critical Questions Answered
4. Inventory in a Manufacturing Environment
5. Principles of Materials Requirements Planning
6. The Material Requirements Planning System
7. Processing Logic
8. Lot Sizing
9. System Records and Files
10. A New Way of Looking at Things
11. Product Definition
12. Master Production Schedule
13. More Than an Inventory Control System
14. System Effectiveness: A Function of Design and Use
15. Industry Effect on MRP
16. Project Manufacturing
17. Remanufacturing
18. Process Industry Application
19. Repetitive Manufacturing Application
20. Sales and Operations Planning
21. Historical Context
22. Blueprint for the Future: Demand-Driven MRP Logic
23. Strategic Inventory Positioning
24. Buffer Profiles and Level Determination
25. Dynamic Buffers
26. Demand-Driven Planning
27. Highly Visible and Collaborative Execution
28. Demand-Driven Material Requirements Planning (DDMRP) Performance Reporting and Analytics
29. DDMRP Future
A. Joseph Orlicky's Contributions to Material Requirements Planning
B. Definitions: APICS Terms and Their Place in DDMRP
C. New Terms in Demand-Driven Material Requirements Planning
D. To My Best Recollection: The Eras of Material Requirements Planning with Packaged Software
Tools & Media
figure (283)
table (12)
graph (2)



Expanded Table of Contents

A. About the Authors
B. Foreword
C. Preface
SCOPE FOR THIS EDITION
ABOUT THE COLLABORATION
1. Overview
ORLICKY'S VISION
FOCUS AND ORGANIZATION OF THIS BOOK
BIBLIOGRAPHY

2. MRP in the Modern World
KEY QUESTIONS FOR PLANNING AND FLEXIBILITY
DEALING WITH VARIABILITY
MATERIALS OR CAPACITY: WHERE TO FOCUS FIRST?

3. The Four Critical Questions Answered
QUESTION 1: RELEVANCE OF MRP
QUESTION 2: MRP—FLAWED APPROACH OR POORLY APPLIED?
QUESTION 3: THE MRP CONFLICT WITH LEAN OR PULL
QUESTION 4: MRP PROGRESS IN THE LAST 30 YEARS?

4. Inventory in a Manufacturing Environment
MANUFACTURING INVENTORIES
DISTRIBUTION INVENTORY
THE LOGIC OF MANUFACTURING
ORDER-POINT VERSUS MRP SYSTEMS
THE PARADOX OF INVENTORY MANAGEMENT
A DISTRIBUTION POSITIONING EXAMPLE
SUMMARY
BIBLIOGRAPHY

5. Principles of Materials Requirements Planning
TIME PHASING
INVENTORY SYSTEM CATEGORIES
PREREQUISITES AND ASSUMPTIONS OF MRP
PART NUMBERS
BILLS OF MATERIAL (BOMS)
APPLICABILITY OF MRP METHODS
BIBLIOGRAPHY

6. The Material Requirements Planning System
OBJECTIVES OF THE SYSTEM
THE PURPOSE OF THE SYSTEM
SYSTEM INPUTS AND OUTPUTS
FACTORS AFFECTING THE COMPUTATION OF REQUIREMENTS

7. Processing Logic
INVENTORY STATUS
TECHNIQUES OF TIME PHASING
GROSS AND NET REQUIREMENTS
COVERAGE OF NET REQUIREMENTS
EXPLOSION OF REQUIREMENTS
TIME-PHASED ORDER POINT
ENTRY OF EXTERNAL-ITEM DEMAND
SYSTEM NERVOUSNESS
BIBLIOGRAPHY

8. Lot Sizing
COSTS IN LOT SIZING
LOT-SIZING TECHNIQUES
LOT-SIZE ADJUSTMENTS
EVALUATING LOT-SIZING TECHNIQUES
BIBLIOGRAPHY

9. System Records and Files
THE TIME-PHASED RECORD
UPDATING INVENTORY RECORDS
THE DATABASE
INPUT-DATA INTEGRITY
BIBLIOGRAPHY

10. A New Way of Looking at Things
PLANNED VERSUS ACTUAL MANUFACTURING LEAD TIME
SAFETY STOCK IN A NEW LIGHT
A FRESH LOOK AT QUEUES
WORK-IN-PROCESS REVISITED
TOTAL PLANNING HIERARCHY
BIBLIOGRAPHY

11. Product Definition
ASSIGNMENT OF IDENTITIES TO INVENTORY ITEMS
PRODUCT MODEL DESIGNATIONS
MODULAR BILLS OF MATERIAL
PSEUDO-BOMS
INTERFACE TO ORDER ENTRY
BIBLIOGRAPHY

12. Master Production Schedule
MASTER PRODUCTION SCHEDULING CONCEPTS
THE FINAL ASSEMBLY SCHEDULE
FUNCTIONS OF MASTER PRODUCTION SCHEDULING
MPS DEVELOPMENT
CLOSING THE LOOP
MANAGEMENT AND ORGANIZATIONAL ASPECTS
BIBLIOGRAPHY

13. More Than an Inventory Control System
USE OF SYSTEM OUTPUTS
AN INVENTORY PLANNING AND CONTROL SYSTEM
A PRIORITY PLANNING SYSTEM
DETERMINING CAPACITY REQUIREMENTS

14. System Effectiveness: A Function of Design and Use
CRITICAL SYSTEM DESIGN FEATURES
THE SYSTEM AND THE INVENTORY PLANNER

15. Industry Effect on MRP
PROJECT MANUFACTURING COMPANY
MAKE TO STOCK
MAKE TO ORDER
ASSEMBLE TO ORDER
MAKE TO STOCK/ASSEMBLE TO ORDER

16. Project Manufacturing
PROJECT LIFE CYCLES
PROJECTS IN MRP
CAPACITY DEPLOYMENT
MATERIAL ALLOCATION
SUMMARY
PROJECT MANAGEMENT RESOURCES

17. Remanufacturing
REMANUFACTURING SIMILARITIES AND DIFFERENCES
MANAGING REMANUFACTURING MATERIAL
REMANUFACTURING BILLS OF MATERIALS
REMANUFACTURING ROUTINGS
REMANUFACTURING INVENTORY MANAGEMENT
TERMS RELATED TO THE REMANUFACTURING INDUSTRY1

18. Process Industry Application
PROCESS INDUSTRY OVERVIEW
PROCESS-FLOW SCHEDULING
MRP SYSTEM REQUIREMENTS
SUMMARY

19. Repetitive Manufacturing Application
GENERAL REPETITIVE APPLICATION
KANBAN
RATE-BASED SCHEDULING
PRODUCTION-SALES-INVENTORY ANALYSIS
BACKFLUSH
PERIOD COSTING
HIGH-VOLUME MIXED-MODEL MANUFACTURING
CONFIGURATORS
SUMMARY

20. Sales and Operations Planning
WHAT'S IN A NAME?
TRADITIONAL SALES AND OPERATIONS PLANNING
S&OP, THE UNIFIER—TRADITIONAL S&OP CHALLENGED
S&OP, THE RECONCILER AND INTEGRATOR
KNOWLEDGE AND KNOW-HOW VERSUS DROWNING IN DATA
UNCERTAINTY VERSUS A SINGLE SET OF NUMBERS
S&OP AS THE ALIGNER TO SUCCESS AND FUTURE SUSTAINABILITY
DISCOVERIES LEADING TO BREAKTHROUGH S&OP
APPLICATION OF S&OP TO VARIOUS ENVIRONMENTS
SUMMARY
ABOUT THE AUTHORS
BIBLIOGRAPHY

21. Historical Context
PRE-MRP INVENTORY CONTROL
THE STORY OF MRP
EVOLUTION OF THE ART
EVOLUTION OF MRP AND PLANNING SYSTEMS
PLANNING, EXECUTION, AND CONTROL

22. Blueprint for the Future: Demand-Driven MRP Logic
THE MRP CONFLICT
DEMAND-DRIVEN MRP INTRODUCTION
THE FIVE PRIMARY COMPONENTS OF DEMAND-DRIVEN MRP

23. Strategic Inventory Positioning
ASR LEAD TIME: A NEW TYPE OF LEAD TIME
ASRLT AND MATRIX BOMS
24. Buffer Profiles and Level Determination
INVENTORY: ASSET OR LIABILITY REVISITED
BUFFER PROFILES
BUFFER ZONES
CALCULATING BUFFER LEVELS
BUFFER LEVEL SUMMARY
SUMMARY
25. Dynamic Buffers
RECALCULATED ADJUSTMENTS
PLANNED ADJUSTMENTS
MANUAL ADJUSTMENTS
26. Demand-Driven Planning
PART PLANNING DESIGNATIONS
THE DDMRP PROCESS
SUPPLY GENERATION FOR STOCKED ITEMS
SUPPLY GENERATION FOR NONSTOCKED ITEMS
DECOUPLED EXPLOSION
27. Highly Visible and Collaborative Execution
CHALLENGING PRIORITY BY DUE DATE
BUFFER STATUS ALERTS
SYNCHRONIZATION ALERTS
EXECUTION COLLABORATION
28. Demand-Driven Material Requirements Planning (DDMRP) Performance Reporting and Analytics
OREGON FREEZE DRY RESULTS
LETOURNEAU TECHNOLOGIES RESULTS
29. DDMRP Future
RESEARCH OPPORTUNITIES
PREDICTION OF THE FUTURE
SUCCESS LEVERAGING TECHNOLOGY
A. Joseph Orlicky's Contributions to Material Requirements Planning
B. Definitions: APICS Terms and Their Place in DDMRP
C. New Terms in Demand-Driven Material Requirements Planning
D. To My Best Recollection: The Eras of Material Requirements Planning with Packaged Software
Book Details
Title: Orlicky's Material Requirements Planning, Third Edition

Publisher: McGraw-Hill Education: New York, Chicago, San Francisco, Lisbon, London, Madrid, Mexico City, Milan, New Delhi, San Juan, Seoul, Singapore, Sydney, Toronto

Copyright / Pub. Date: 2011 McGraw-Hill Education, LLC

ISBN: 9780071755634

Authors:

Carol Ptak is currently a partner with the Demand Driven Institute, and was most recently at Pacific Lutheran University as Visiting Professor and Distinguished Executive in Residence. Previously, she was vice president and global industry executive for manufacturing and distribution industries at PeopleSoft where she developed the concept of demand driven manufacturing (DDM). Ms. Ptak spent four years at IBM Corporation culminating in the position of global SMB segment executive.

Chad Smith is cofounder and managing partner of Constraints Management Group, a services and technology company specializing in pull-based manufacturing, materials, and project management systems for mid-range and large manufacturers. He has been at the forefront of developing and articulating demand driven MRP and is also an internationally recognized expert on the theory of constraints (TOC) Carol and Chad founded the Demand Driven Institute, an organization devoted to the proliferation and further development of demand driven strategies and tactics in industry.


May 29, 2019

Philip Kotler's Lectures, Presentations and Interviews on Marketing



“Leadership and the Public Good” – An Interview with Philip Kotler
January 15, 2019

Sep 12, 2018
Northwestern Professor Philip Kotler On What's Next For Marketing

“Marketing 4.0” – A Podcast Interview with Philip Kotler

December 13, 2016
http://www.marketingjournal.org/marketing-4-0-a-podcast-interview-with-phil-kotler/


Philip Kotler: Future of business is doing good (and the four Ps are safe)

_______________

_______________
Marketing Magazine
Uploaded 22 Feb 2015

Marketing 1.0  -Rational appeal to consumers.
Marketing 2.0 - Emotional appeal to consumers
Marketing 3.0 - Think of consumer segment who cannot buy your present product. Think of cost reduction of the product and serve those sections out of philanthrophic feelings.


The Thinker Interview with Philip Kotler, the Father of Marketing

With the rise of the internet and the advent of new concepts like social media, e-commerce and digital marketing, critics started questioning the relevance of the classic Four Ps model of marketing. Yet Kotler chooses to staunchly defend the concept
BY NEELIMA MAHAJAN
Jan 29, 2014
http://www.forbesindia.com/article/ckgsb/the-thinker-interview-with-philip-kotler-the-father-of-marketing/36951/1

The Larger Context for Social Marketing
Marketing for Planned Social Change
________________

________________
World Social Marketing upload
2013




The Larger Context for Social Marketing

Social marketing is one of six social change strategies. To be maximally effective, social marketers must work with other social change strategies. Social marketers must tie their work to new technologies that become available and also tie their work to current and emerging
social movements. The addition of upstream and mid-stream social marketing thinking is enriching the power of social marketers to more effectively bring about behavioral change, its main objective.


Updated on 30 May 2019, 17 February 2016

Marketing Strategy - Differentiating and Positioning the Market Offering





Marketing Strategy

 
Philip Kotler discussed five issues of marketing strategy in his Marketing Management

Differentiating and Positioning the Market Offering


Managing Life cycle Strategies

Designing marketing Strategies for Market Leaders, Challengers, Followers, and Niches



   
These issues are covered in different articles  by me in  Management Theory Revision


This article  describes differentiating and positioning. 
 
Differentiating and Positioning the Market Offering



The issues discussed in the area of differentiating and Positioning the market offering are:

  • Tools for Competitive Differentiation
  • Developing a Positioning Strategy
  • Communicating the Company’s Positioning

Tools for Competitive Differentiation

Differentiation - Definition: is the act of designing a set of meaningful differences to distinguish the company's offering from competitor's offerings.



Boston Consulting Group's differentiation opportunities matrix: Actually it is a competitive advantage matrix applicable to differentiation opportunities. 

Four types of industries identified by BCG matrix are:



Volume industry: only a few but very large competitive advantages are possible. The benefit of the advantage is proportional with company size and market share. Example given - construction industry.



Stalemated industry: in this type there are only few opportunities and the benefit from each is small. The benefit is also not proportional to the size or market share.


Example: Steel industry - It is hard to differentiate the product or decrease its manufacturing cost.


Fragmented industry: in this type, there are many opportunities, but the benefit of each of them is small. Benefit does not depend on size or market share.

Specialized industry: in this type, the opportunities are more and benefit of each opportunity is high. The benefit is not related to size or market share.

Kotler mentions, Milind Lele's observation that companies differ in their potential maneuverability along five dimensions: their target market, product, place (channels), promotion, and price. The freedom of maneuver is affected by the industry structure and the firm's position in the industry. For each potential competitive opportunity or option limited by the maneuverability, the company needs to estimate the return. Those opportunities that promise the highest return define the company's strategic leverage. The concept of maneuverability brings out the fact that a strategic option that worked very well in one industry may not work equally well in the other industry because of low maneuverability of that option in the different industry and by the firm in consideration.

Five Dimensions of Differentiation



Regarding the tools of differentiation, five dimensions can be utilized to provide differentiation.



Product

Services that accompany marketing, sales and after sales services.

Personnel that interact with the customer

Channel

Image

 
Differentiating a Product


Features


Quality:  performance and conformance

Performance - the performance of the prototype or the exhibited sample,
Conformance - The performance of every item made by the company under the same specification

Durability

Reliability

Repairability

Style

Design


Services differentiation



Ordering ease

Delivery

Installation

Customer training

Customer consulting

Miscellaneous services


Personnel Differentiation

Competence

Courtesy

Credibility
Reliability
Responsiveness
Communication

Channel differentiation
Coverage
Expertise of the channel managers
Performance of the channel in ease of ordering, and service, and personnel

Image differentiation
First distinction between Identity and Image - Identity is designed by the company and through its various actions company tries to make it known to the market.
Image is the understanding and view of the market about the company.
An effective image does three things for a product or company.
1. It establishes the product's planned character and value proposition.
2. It distinguishes the product from competing products.
3. It delivers emotional power and stirs the hearts as well as the minds of buyers.
The identity of the company or product is communicated to the market by
Symbols
Written and audiovisual media
Atmosphere of the physical place with which customer comes into contact
Events organized or sponsored by the company.
 

Developing a Positioning Strategy

Levitt and others have pointed out dozens of ways to differentiate an offering(Theodore Levitt: "Marketing success through differentiation-of anything", Harvard Business Review, Jan-Feb, 1980)


While a company can create many differences, each difference created has a cost as well as consumer benefit. A difference is worth establishing when the benefit exceeds the cost. More generally, a difference is worth establishing to the extent that it satisfies the following criteria.

  
Important: The difference delivers a highly valued benefit to a sufficient number of buyers.


Distinctive: The difference either isn't offered by others or is offered in a more distinctive way by the company.


Superior: The difference is superior to the ways of obtaining the same benefit.


Communicable: The difference is communicable and visible to the buyers.


Preemptive: The difference cannot be easily copied by competitors.


Affordable: The buyer can afford to pay the higher price


Profitable: The Company will make profit by introducing the difference.



Positioning  
Positioning is the result of differentiation decisions. It is the act of designing the company's offering and identity (that will create a planned image) so that they occupy a meaningful and distinct competitive position in the target customer's minds.

The end result of positioning is the creation of a market-focused value proposition, a simple clear statement of why the target market should buy the product.


Example:

Volvo (station wagon)
Target customer-Safety conscious upscale families,
Benefit - Durability and Safety,
Price - 20% premium,
Value proposition - The safest, most durable wagon in which your family can ride.



How many differences to promote?

Many marketers advocate promoting only one benefit in the market (Your market offering may have many differentiators, actually should have many differentiators in product, service, personnel, channel, and image).


Kotler mentions that double benefit promotion may be necessary, if some more firms claim to be best on the same attribute. Kotler gives the example of Volvo, which says and "safest" and "durable".


Four major positioning errors
1. Underpositioning: Market only has a vague idea of the product.

2. Overpositioning: Only a narrow group of customers identify with the product.

3. Confused positioning: Buyers have a confused image of the product as it claims too many benefits or it changes the claim too often.

4. Doubtful positioning: Buyers find it difficult to believe the brand’s claims in view of the product’s features, price, or manufacturer.


Different positioning strategies or themes
1. Attribute positioning: The message highlights one or two of the attributes of the product.

2. Benefit positioning:  The message highlights one or two of the benefits to the customer.

3. Use/application positioning: Claim the product as best for some application.

4. User positioning: Claim the product as best for a group of users. - Children, women, working women etc.

5. Competitor positioning: Claim that the product is better than a competitor.

6. Product category positioning: Claim as the best in a product category Ex: Mutual fund ranks – Lipper.

7. Quality/Price positioning: Claim best value for price

Which differences to promote:



This issue is related to the discussion of worthwhile differences to incorporate into the market offering done earlier. But now competitors positioning also needs to be considered to highlight one or two exclusive benefits offered by the product under consideration.



 
Communicating the Company’s Positioning


Once the company has developed a clear positioning strategy, the company must choose various signs and cues that buyers use to confirm that the product delivers the promise made by the company.

References

Philip Kotler - Marketing Management



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Updated 30 May 2019, 26 November 2011