December 31, 2017

MBA Core Management Knowledge - One Year Revision Schedule

The blog contains articles on all management subjects developed using the most popular book on the subject. You can read articles on the sybject of your choice or use the following schedule.

One Year MBA Knowledge Revision Plan

Revision Schedule

Current Month -  April  

January  - February  - March  - April  - May   -   June

July       - August     - September  - October  - November  - December

Subject Details of Each Month

January  (Principles of Management) - February (P.of M & Marketing Management from 23 Feb 2015 )
March (Mktg. Mgmt. & Operations Management from 17 March 2015)  -
April  (Supply Chain Management and Financial & Cost Accounting)

May  (Management Accounting & Organizational Behavior)  -
June (Innovation, Industrial Engineering and Economics)

July  (Economics, Engineering Economics, & Managerial Ethics)   - August    (Statistics, Quality and Six Sigma, OR & BRM)

September (HRM, Mentoring, Training, Maintenance, Energy & Environment Management)  -  October  (Information Technology and Management Information Systems, Logistics - Warehousing and Transport)

November (Strategic Management & Financial Management)  - December (Business Laws, Negotiation, Taxes and Government Relations)

Subject                                               Revision Period

Principles of Management                15 January   to   19 February

Marketing Management                    22 February to   16 March

Operations Management                   17 March     to    2 April

Supply Chain Management                 3 April       to  15 April

Financial & Cost Accounting            16 April       to  12 May

I am participating in April A to Z Blogging Challenge and I am writing on the theme Top Management Challenges.

Top Management Challenges.

Article 1: Awareness of Environment

Updated 1 April 2017.  22 February 2017,  10 December 2015

July 25, 2017

Leading and Managing Company Transformation

Transformation is  drastic change in the strategy and derived processes. How can you get the affirmative consent of the associates and do the change effectively. Certain problems are expected, but how do you recognize them early and solve them before they become major stumbling blocks for the transformation effort.

BCG has prepared a guidance book for you and sharing it with you through free download. Download it, read it and benefit from it.


Related Videos

Transformation of Organizations

5 ways to lead in an era of constant change

Jim Hemerling

Jim Hemerling is a senior partner and managing director in the firm’s San Francisco office. He is a leader of the People & Organization and Transformation practices and a BCG Fellow.



An imperative to transform
Lars Faeste
Lars F├Žste is a senior partner and managing director in the Copenhagen office of The Boston Consulting Group and the global leader of the Transformation practice.

Managers have to be paranoid.
Constantly question yourself - Is this good enough? Can I do more?



July 24, 2017


SAP IBP is the next generation technology enabler for supply chain planning.
It is developed on HANA and cloud platforms.
It supercedes SAP's MRP, ERP and APS

The key functional modules are:
IBP Demand
IBP Inventory
IBP Supply
IBP Control

Overview of SAP IBP


Gitacloud SAP IBP Workshop Information


SAP IBP workshop is a four day virtual event, conducted across two weekends. It is split into three parts:


Business Context: Maturity Models, S&OP evolution into IBP (why is IBP needed?)
IBP Business Processes & Key Capabilities
SAP IBP Platform Overview
Overview of SAP IBP Solutions (Demand, Inventory, Supply & Response, S&OP, Control Tower)

SAP IBP Model Configuration: mock implementation - build an IBP S&OP model from scratch against specific requirements
Model Activation, Data Load
Advanced Topics:
Statistical Forecasting / Demand Planning
Rough Cut Supply Planning
Planning Area Maintenance
Attribute Transformations
Planning Operators
Security & User Administration concepts

SAP IBP Implementation Considerations: Industry specific use cases, SAP IBP Model Design Best Practices, Implementation Methodology
Case Study: See how raw business requirements and data files from a customer are turned into a working prototype
Certification Exam



25 July 2017

Updated  26 July 2017,  17 June 2017, 5 June 2017

July 22, 2017

Application of Artificial Intelligence Based Agents, BBots and Systems in Business - 2017 State of Affairs

Application of Artificial Intelligence Based Agents, BBots and Systems in Business - 2017 State of Affairs

July 2017

Business bots (BBots) are now being used in businesses. Chatbots are the popular bots in this category. Chatbots are able to understand speech and reply in pronounced words and people are happy to have dialogue with them.

ERIK BRYNJOLFSSON & ANDREW MCAFEE authored an article "THE BUSINESS OF ARTIFICIAL INTELLIGENCE: What it can — and cannot — do for your organization" in HBR of July 2017 and explained the potential of artificial intelligence in business applications. There are good number of applications at this movement. But still their business and revenue impact is limited. The potential is very high. But business reimagination is needed to come out with a business concept using the AI that will have a significant revenue and business impact.

Important points made in the article

The term artificial intelligence was coined in 1955 by John McCarthy, a math professor at Dartmouth and he organized a  conference on the topic in 1956.

Up to the present time, the biggest advances have been made in two broad areas: perception and cognition. In the former category, voice recognition and image recognition are developed to become practical applications in Siri, Alexa, and Google Assistant. The driverless car uses image recognition in real life high risk practical application.

In the area of cognition  and problem solving, machines are beating human players in games like chess, poker and Go. Google’s DeepMind team has used ML systems to solve optimization problem and improve the cooling efficiency at data centers by more than 15%, after optimization efforts  by human experts.

Uniqueness of Machine Learning
Machine learning represents a fundamentally different approach to creating software. It does not use explicitly specified rules. Instead, the machine learns from examples. The learning when guided by successful answers is the most fruitful at the moment. Hence, most of the successes occurred in supervised learning systems, in which the machine is given lots of examples of the correct answer to a particular problem accompanied with lot of input data.

Another category of learning problems is emerging, reinforcement learning systems. In reinforcement learning systems the programmer specifies the current state of the system and the goal, lists allowable actions, and describes constraints. The system has to combine, the allowable actions, and the outcomes subject to constraints and  figure out how to get as close to the goal as possible.

Designing and implementing new combinations of technologies, human skills, and capital assets to meet customers’ needs requires large-scale creativity and planning. This is the task of entrepreneurs or  business managers employed to think like entrepreneurs. So the age of machine learning provides at the present moment, great rewarding opportunities entrepreneurs or  business managers.

Risks of employing machine learning systems include,  the machines' hidden biases, derived not from any intent of the designer but from the data provided to train the system.

The authors conclude that in their  view, artificial intelligence, especially machine learning, is the most important general-purpose technology of the present our era. The innovations developed using the new technology will be direct applications as well as complementary innovations.

If entrepreneurs and managers aren’t doing many experiments in the area of machine learning, they aren’t doing using their time devoted to strategic planning properly. Over the next decade, entrepreneurs and managers who understand and use AI effectively and efficiently will replace those who don’t.

If you are an entrepreneur or a business process/model manager register for a course of machine learning immediately if you have not done yet.


Andrew Ng: Artificial Intelligence is the New Electricity
Stanford Graduate School of Business



Davos WEF 2017 Panel Discussion on Artificial Intelligence

Published on 17 Jan 2017
As business opportunities for artificial intelligence multiply, how can industry leaders design the principles and technical standards into their products that benefit society as a whole?

- Ron Gutman, Founder and Chief Executive Officer, HealthTap, USA
- Joichi Ito, Director, Media Lab, Massachusetts Institute of Technology, USA
- Satya Nadella, Chief Executive Officer, Microsoft Corporation, USA
- Ginni Rometty, Chairman, President and Chief Executive Officer, IBM Corporation, USA

Moderated by
- Robert F. Smith, Chairman and Chief Executive Officer, Vista Equity Partners, USA



Davos WEF 2016 Panel Discussion on The State of Artificial Intelligence

How close are technologies to simulating or overtaking human intelligence and what are the implications for industry and society?

-Matthew Grob, Executive Vice-President and Chief Technology Officer, Qualcomm, USA.
-Andrew Moore, Dean, School of Computer Science, Carnegie Mellon University, USA.
-Stuart Russell, Professor of Computer Science, University of California, Berkeley, USA.
-Ya-Qin Zhang, President,, People's Republic of China.

Moderated by Connyoung Jennifer Moon, Chief Anchor and Editor-in-Chief, Arirang TV & Radio, Republic of Korea.





MIT Open courseware Lectures 2010 - Playlist


July 16, 2017

Value Engineering - Introduction

Product Industrial Engineering

We can use the term 'Product Industrial Engineering' to described the efficiency improvement carried out by industrial engineers in the product designs.

Product Design Efficiency Engineering - Component of Industrial Engineering

Value Analysis and Value Engineering - Miles Way (L.D. Miles)

Value engineering has for its purpose the efficient identification and elimination of unnecessary cost. First article on the topic was written by L.D. Miles in 1949. Link available in this article.

What is Value Engineering?

Value engineering has for its purpose the efficient identification of unnecessary cost, i.e., cost which provides neither quality nor use nor life nor appearance nor customer features. It focuses the attention of engineering, manufacturing, and purchasing on one objective – equivalent performance for lower cost. It results in the orderly utilization of low cost alternative materials, low cost alternative processes including new processes, and abilities of specialized suppliers to procure items at lower costs.
Lawrence D. Miles is the pioneer of this technique. He wrote the book - Techniques of Value Analysis and Engineering - in 1961. His designation at that time was Manager, Value Service, General Electric Company. He published the first article on value analysis in 1949 in American Machinist.

Functional design is not tampered:
Inherent in the philosophy of value engineering is the full retention for the customer of the usefulness and esteem features of the product. Miles argued emphatically right at the beginning of his book, “Techniques of Value Analysis and Engineering” that identifying and removing unnecessary cost, and thus improving the value, must be done without reducing in the slightest degree quality, safety, life, reliability, dependability, and the features and attractiveness that the customer wants.

What is Value?

Miles described  four types of value.

1. Use value: The properties and qualities which accomplish a use, work, or service.
2. Esteem value: The properties, features, or attractiveness which cause us to want to own it.
3. Cost value: The sum of labor, material, and various other costs required to produce it.
4. Exchange value: Its properties or qualities which enable us to exchange it for something else we want.

Even though Miles did not describe it that way, I feel value analysis or engineering is concerned with cost value without in anyway decreasing the use value, esteem value and exchange value

Value Analysis Techniques

Miles provided 13 ideas as value analysis techniques.
  1. Avoid generalities
  2. Get all available costs
  3. Use information from the best source
  4. Blast create and refine
  5. Use real creativity
  6. Identify and overcome roadblocks
  7. Use industry experts to extend specialized knowledge
  8. Get a dollar sign on key tolerances
  9. Utilize vendors’ available functional products
  10. Utilize and pay for vendors’ skills and knowledge
  11. Utilize specialty processes
  12. Utilize applicable standards
  13. Use the criterion, “would I spend my money this way?”
The list can be reorganized in this way to show their role in value engineering

At the start of the value engineering exercise some people will object to the project with some general statements.
    1. Avoid generalities  - Don't accept general statements. Try to find out the real objection and confirm whether it is a valid objection.

        Information Phase

        During information phase get information relevant to the product under evaluation
          2. Get all available costs
          3. Use information from the best source
          4. Get a dollar sign on key tolerances - Part of analysis, but it can be treated as information phase as routine information collection activity.

          Searching for low cost alternative materials, standard products and processes. 
          To reduce product through design changes, low cost alternative materials, components and production processes are to be identified.
            5. Utilize vendors’ available functional products
              6. Utilize specialty processes
                7. Utilize applicable standards

                After searching and identifying low cost alternatives which may be of use in redesign, redesign will start.
                  8. Use the criterion, “would I spend my money this way?”  - This idea refers to certain components that are having high costs. This gives rise to the feeling money is being wasted and forces the VE team to look for alternatives in more focused manner.
                    9. Blast,  create and refine - Blasting the current design by identifying a possible low cost alternative. Create is technically showing that the new alternative is a feasible. Refine is commercial design of the new alternative to go into the product

                    10. Use industry experts to extend specialized knowledge - The value engineering team has to approach industry experts to use new materials and new processes appropriately. 

                    11. Utilize and pay for vendors’ skills and knowledge - Vendors who can offer new process capabilities must be supported for developing the solution needed by the VE team.
                      12. Use real creativity - Creativity is required to identify the solution to the value engineering problem. A value engineer knows the function that he has to provide and he must be able to pick the relevant material, component or process from the collection of the information that he has gathered.

                      During presentation of the solution, a value engineer is likely to face objections. He must be prepared for these objections and answer them so that objection is answered adequately and the questioner is satisfied that the new solution is a suitable redesign.
                        13. Identify and overcome roadblocks

                        More detailed description of techniques

                        The Right Way to use the Techniques
                        Choose appropriate techniques to value engineer the specific product.

                        Arrange the techniques in best order for the particular job.

                        Use each technique imaginatively and effectively.

                        Use the techniques iteratively until useful information is developed to the extent that direction for decision and action is available.

                        To use the techniques an analyst requires special knowledge.
                        Value engineer is not a functional designer. He will have access to functional designers as needed in his value work. Hence his knowledge is not specialized to particular areas like mechanical engineering, electrical engineering, automobile engineering, or aerospace engineering. Knowledge required for high-grade value work is extremely broad.
                        The specialized knowledge required in value improvement work consists of information on materials, processes, functional products, sources of functional knowledge, approaches to function performance, and practical ideas for economical function performance.
                        It is important that the value engineer’s library of special knowledge contains a comprehensive volume of trade knowledge backed by efficient means for a quick recall of needed information. Value engineer also needs well-organized references to a maximum number of persons of special skills that may be consulted in connection with each problem.
                        Value engineers need develop a database having the association between properties of materials and costs apart from material and its cost. Similarly a database that shows the relationship between the properties of products produced by various processes and the cost of each process, including the material used is also valuable.

                        This topic will be discussed in more detail in a separate article 'Knowledge Required for Value Engineering'.

                        Job Plan for Value Engineering
                        Phase 1. Orientation: Understand the customers’ needs and wants. Understand the functions performed by the product and the contribution of each part and each feature of the part and the complete product to the functions to be performed by the product.
                        Value engineer has to make sure that he does not diminish the contribution of the product to the customers' needs and wants.
                        Phase 2. Information: Collection of information on quantities, vendors, drawings, materials, manufacturing methods, and costs.
                        Techniques to be used:

                        Get all available costs
                        Get a dollar sign on key tolerances

                        Phase 3. Speculation: Using all the techniques of value analysis to come out with alternative low cost materials and methods to produce components and the product. Creativity is to be employed here. Value engineer has to involve experts from various disciplines to help with ideas.
                        Techniques to be used:

                        Blast, create and refine

                        For each function to be performed by a product or a component, find alternative products, materials or processes that serve the function to a great extent but at a less cost. These alternative ideas do not satisfy the specified or required function completely but they do to a significant extent. Identify they function they perform and the cost involved,

                        During the blast activity use these techniques.
                        Utilize vendors’ available functional products

                      1. Utilize and pay for vendors’ skills and knowledge
                      2. Utilize specialty processes
                      3. Utilize applicable standards
                      4. Use the criterion, “would I spend my money this way?”

                      5. All the five techniques have the potential to suggest lower cost alternatives


                        In create phase, the technique of "Use real creativity" needs to be employed to come out with ways by which the low cost alternatives identified during the blast stage can be modified to accomplish the specified function to a much greater extent with pertinent increase in cost. During this stage also the improvement in function and the increase in cost are to be clearly identified.


                        In this step, much more creativity is used and also the techniques "Use industry experts to extend specialized knowledge" and  "Utilize and pay for vendors’ skills and knowledge" are used to refine the ideas developed during the create step to come out with a refined alternative that fully accomplishes the specified function at a lower cost. During refine step, some more functionality is added as well as some additional cost.

                        Phase 4. Analysis:  Technical and cost analysis of the alternative proposed.

                        The techniques to keep in mind and use during this stage are:

                        Avoid generalities

                        Use information from the best source

                        Identify and overcome roadblocks

                        Phase 5. Program planning: Approach the specialists to further refine the selected alternatives. Inform the specialists the accepted suggestions and give mandate to them to take steps to implement the suggestions.
                        Phase 6. Program execution: Pursue regularly the specialists and vendors to get their inputs on various tasks assigned to them. The output of this phase is a detailed design, successful trail  pilot  run of a manufacturing process or  a confirmed estimate from a vendor for supplying a component, material or sub assembly.
                        Phase 7. Status summary and conclusion. The results of the value engineering study are to be presented to decision makers. The reports needs to have a summary sheet as well as the full supporting documentation.  The value engineering project is concluded when the product is manufactured and distributed at the lowered cost as per the value engineering study.

                        Special Knowledge Required

                        In practically all fields, the operator used special tools and special or field specific knowledge. Value analysis and engineering is no exception.

                        Reach of knowlege: For value analysis, the knowledge required is extremely broad.
                        Nature of knowledge: Information on materials, processes,  and functional products.
                        Form and Constitution of Knowledge Fund: Handbooks, catalogues, charts, price lists, product and process descriptions, tables etc.
                        Listing of specialized Competence: Value analysis requires consulting specialists and specialized sources. So a list of consultants as well as special publication is required for various materials, processes and components.

                        Qualifications and Training for Value Analysts and Engineers

                        Qualifications: Logic, creativity, ability to make rapid searches, recall, ability to quickly sort out useful information,  synthesis of solutions, selection of promising alternatives.

                        Knowledge: Understanding of the properties of materials, and of manufacturing processes, their potentialities, and their limitations.

                        Traits required: Imagination, initiative, self-organization, cooperative attitude,
                        Attitude: belief in the importance of value

                        Training: Three weeks class room followed by six months of practical work.
                        Another round of three weeks class room followed six months of practical work
                        Another round of three weeks.

                        For further study:

                        First article by L.D. Miles in 1949 download the file 35.5 pdf from this page.

                        Lawrence D. Miles, Techniques of Value Analysis and Engineering, McGraw-Hill Book Company, New York 1961.

                        Note on Value Engineering

                        Especially gives Juran's and Clawson's comments on value engineering

                        Value Engineering - NPC, Chennai (77 page Document. Available online)
                        History of Value Engineering

                        1.17 minutes


                        Related Knols

                        Related Web Pages

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                        Value Engineering -  Case Studies



                        Originally posted at
               - Knol Number 4

                        Industrial Engineering Knowledge Revision Plan - One Year Plan

                        January - February - March - April - May - June

                        Updated  17 July 2017,   27 June 2015
                        First Published on blog  15 December 2011

                        July 15, 2017

                        Product Management in Digital World - Recent Trends

                        The one-stop product management guide

                        Down the Book - Strategic Role of Product Management

                        The evolving role of product management
                        What product management is and why it’s so relevant today.
                        By Martin ErikssonRichard BanfieldNate Walkingshaw June 22, 2017
                        Excerpt from Chapter 1 of “Product Leadership.

                        “The job of a product manager is to discover a product that is valuable, usable, and feasible.”
                        Product management is the intersection between business, user experience, and technology

                        Product managers for the digital world
                        By Chandra Gnanasambandam, Martin Harrysson, Shivam Srivastava, and Yun Wu
                        May 2017

                        Product managers connect many functions related to  a product— market research, design, engineering,  marketing, sales, marketing, operations, finance, legal, and more. They are involved in the decisions about what gets built but also influence every aspect of how it gets built and launched.

                        The product manager of today is increasingly given the role of  the mini-CEO of the product.

                        16 Killer Videos on Product Management Essentials
                        June 9, 2016

                        A Panel Discussion on Product Management
                        12 March 2010
                        Stanford Graduate School of Business
                        Features executives formerly at Apple Computer, Hewlett-Packard, PeopleSoft, and Sybase:
                        Rita Iorfida, VP Products, Liquid Engines;
                        Rich Mironov, former VP Product Marketing, AirMagnet;
                        Tiffany Riley, VP Marketing at Nextance;
                        David Straus, SVP Worldwide Sales and Marketing, Corticon.


                        Product Management At Google

                        July 14, 2017

                        Manufacturing Policy - Review and Modification

                        Business strategy changes and manufacturing policy and strategy have to change. Wickham Skinner advocated the concept of focused factory. Focused factories reflect the business strategy of the organization. So when business strategy changes what happens to the focused factory. It can change and it has to change, asserts Prof. Wickham Skinner in a recent paper published in the journal, Production and Operations Management (October 2015). The paper describes the experience of  Hewlett Packard's plant for computer servers in Germany. It successfully changed its focus in line with the change in environment and the consequent business strategy.

                        Hendrik Brumme, Daniel Simonovich, Wickham Skinner, and Luk Van Wassenhove present new ideas and understandings about review and modification of focused production operations developed from insights derived from an historical analysis of the evolution of Hewlett-Packard’s (HP) award winning plant for computer servers in Germany. The plant was restructured from an innovation factory to an operational excellence factory and  then  to a solutions factory. The brings out the right timing of focus changes and discusses the critical structural and infrastructural changes required during the focus transitions as well as cross-functional coordination and leadership challenge. The production and related operations constitute a system and even as a focused factory or production system, it can adapt to disruptive change.  The article also lists out seven myths regarding focused factories and rebuts them.

                        The content is the paper is also reflected in this Knowledge @ Insead post.