Computer-oriented PICS – COPICS S – 1b; 2c; 4d; 6d; 7c; 10c; 13c; * 1.2c; 1.3b; 2.3b; 2.4b; 2.5d; 4.2c; 4.3b;4.4c; 4.5c Computer-oriented production information and control system COPIC
Trang 1can cause a fast machine to become the bottleneck from time to time, highvariance can cause the CONWIP line to become the bottleneck in the overallsystem
An analytical model (computed bottleneck, CBN) was developed forpredicting the mean and variance flow time The concept of a virtual bottle-neck machine was introduced that allowed the employment of analogiesbetween deterministic and stochastic systems This concept enables one tohandle migrating bottlenecks, an issue that is generally neglected The results
of simulation experiments show that the analytical model very accurately dicts the mean flow time, and is sufficiently accurate at predicting the stand-ard deviations of flow time Simulation experiments also show that theanalytical models are much quicker than simulations Since simulation does notconstrain the type of processing time distribution when developing models,the influence of machine breakdowns can also be considered by includingthem in the processing time distributions
pre-Since CONWIP systems can be viewed as closed queuing networks, onemay (mistakenly) view the system as a loop (having no beginning nor end) Thisallows one to ‘cut’ the line at any point in order to evaluate its performance.This approach, as recognized by the model, is valid for mean performancemeasures but very inaccurate for variance of performance measures
Bibliography
1 Burbidge, J., 1990: Production control: a universal conceptual framework,
Produc-tion Planning and Control, 1, 3–16
2 Duenyas, I and Hopp, W.J., 1990: Estimating variance of output from cyclic
expo-nential queuing systems, Queuing Systems, 7, 337–354
3 Duenyas, I., Hopp, W.J and Spearman, M.L., 1993: Characterizing the output
pro-cess of a CONWIP line with deterministic propro-cessing and random outages,
Man-agement Science, 39, 975–988
4 Duenyas, I and Hopp, W.J., 1992: CONWIP assembly with deterministic
process-ing and random outages, IIE Transactions, 24, 97–109
5 Hendricks, K and McClain, J., 1993: The output processes of serial production
lines of general machines with finite buffers, Management Science, 29, 1194–
1201
6 Hendricks, K., 1991: The output processes of simple serial production lines ing Paper, Georgia Institute of Technology, Atlanta, GA 30332
Work-7 Hendricks, K., 1992: The output processes of serial production lines of exponential
machines with finite buffers, Operations Research, 40, 1139–1147
8 Hopp, W.J., Spearman, M.L and Duenyas, I., 1993: Economic production quotas
for pull manufacturing systems, IIE Transactions, 25, 71–79
9 Hopp, W.J and Spearman, M.L., 1991: Throughput of a constant work in process
manufacturing line subject to failures, International Journal of Production
Research, 29, 635–655
10 Kanet, J., 1988: MRP 96: time to rethink manufacturing logic, Production and
Inventory Management Journal, 29, 57–61
Trang 211 Little, J., 1961: A proof of the queuing formula L = aW Operations Research,
9, 383–387
12 Miltenburg, G.J., 1987: Variance of the number of units produced on a transfer line
with buffer inventories during a period of length T Naval Research Logistics,
34, 811–822
13 Muckstadt, J and Tayur, S., 1995: A comparison of alternative kanban control
mechanisms, part 1, IIE Transactions, 27, 140–150
14 Reiser, M and Lavenberg, S., 1980: Mean-value analysis of closed multichain
queuing networks Journal of the Association for Computing Machinery, 27, 313–322
15 Spearman, M.L., Woodruff, D.L and Hopp, W.J., 1990: CONWIP: a pull
alter-native to kanban, International Journal of Production Research, 28, 879–894
16 Spearman, M.L and Zazanis, M.A., 1992: Push and pull production systems:
issues and comparisons, Operations Research, 40, 521–532
17 Tayur, S., 1992: Properties of serial kanban systems, Queuing Systems, 12, 297–
318
18 Tayur, S., 1993: Structural properties and a heuristic for kanban controlled serial
lines, Management Science, 39, 1347–1368
Cooperative manufacturing
P – 1b; 3c; 4b; 8c; 12d; 14d; 16d; * 1.3b; 1.4d; 2.4b; 3.3c; 3.5d; 3.6c; 4.2c; 4.5c Cooperative manufacturing is based on the view that it is difficult and expens-ive to anticipate disturbances and prepare meaningful programmed responses
to a specific situation The environment is perceived as inherently unstableand difficult to influence The following are ways to respond to disturbancesand variability
1 Make sure that the organization is closely linked to the environment, sothat information about disruptions is acquired quickly It is not limited toformal information from computer systems, but includes informal informa-tion such as gossip and body language
2 Ensure that people within the organization are inherently flexible and able
to respond to new situations through experience, education and training.Further, they should be able to create and work in teams to maximize theeffectiveness with which different skills and abilities are directed at devel-oping appropriate responses
3 Provide flexible manufacturing facilities This does not usually imply aflexible manufacturing system, but rather machines and people that can beeasily adapted to a variety of production tasks either simultaneously or oneafter another
4 Link the manufacturing organization with other people and organizationsfor knowledgeable support and advice The organization may subcontractsupport activities that are not central to its mission and use internal andexternal consultants to address challenging and complex problems
Trang 3The cooperative organization relies on speed and variety of response to dealwith disruptions Implementation of cooperative manufacturing usually requiresthat there be product focus to keep market problems in one product groupfrom affecting other product groups Production is organized around cells andteams, with the team being largely self-managing Support is largely directed
by the work team to ensure that it is aimed at meeting team goals Much munication is informal and the role of computers is primarily as a decision aidfor specific individuals and team Team size is limited to a critical size, andmanufacturing activities may be organized around a loosely linked network ofsmall units, where different units may be under different ownership
com-Cooperative manufacturing is most appreciated when bringing a new uct to market and product innovation is the key factor of success Quality ofdesign is created by the experience and expertise of the team and its ability,because of its close link to the environment, to understand the real needs ofcustomers
prod-Bibliography
1 Ashby, W.R., 1957: An Introduction to Cybernetics Chapman & Hall
2 Devenport, T.H., 1993: Process Innovation: Reengineering Work Through
Informa-tion Technology Harvard Business School Press, Cambridge, MA
3 Duimering, P.R., Safayeni, F and Purdy, L., 1993: Integrated manufacturing:
redesign the organization before implementing flexible technology, Sloan
Manufac-turing Review, 34, 47–56
4 Hammer, M and Champy, J., 1993: Reengineering the Corporation: a manifesto for
Business Revolution Harper Business, New York
5 Stalk, G and Hout, T.M., 1990: Competing Against Time Free Press
6 Salvendy, G and Seymour, W.D., 1973: Prediction and Development of Industrial
Work Performance John Wiley, New-York
7 Kristensen, P.H., 1990: Technical projects and organizational changes: Flexible
specialization in Denmark In M Warneer, W Wobbe and P Broudner (eds), New
Technology and Manufacturing Management John Wiley & Sons, pp 159–189
Computer-oriented PICS – COPICS
S – 1b; 2c; 4d; 6d; 7c; 10c; 13c; * 1.2c; 1.3b; 2.3b; 2.4b; 2.5d; 4.2c; 4.3b;4.4c; 4.5c
Computer-oriented production information and control system (COPICS) is asystematic method of performing the technological disciplines of the enterprise,which consist of the following stages:
• Master production planning
• Material requirement / Resource planning
• Capacity planning
Trang 4• Shop floor control
• Inventory management and control
COPICS objectives are exactly as those of PICS, the difference is in themethod of collecting feedback information: COPICS uses electronic datacollection terminals instead of manual forms Therefore, it is more accurateand allows work online
Master production planning transforms the manufacturing objectives ofquantity and delivery dates for the final product, which are assigned by mar-keting or sales, into an engineering production plan The decisions in thisstage depend either on forecast or confirmed orders, and the optimizationcriteria are meeting delivery dates, minimum level of work-in-process, andplant load balance These criteria are subject to the constraint of plant capacityand to the constraints set by the routing stage
The master production schedule is a long-range plan Decisions concerninglot size, make or buy, addition of resources, overtime work and shifts, andconfirm or change promised delivery dates are made until the objectives can
be met
Material requirement planning (MRP – see separate item) – The purpose of
MRP is to plan the manufacturing and purchasing activities necessary in order
to meet the targets set forth by the master production schedule The number ofproduction batches, their quantity and delivery date are set for each part of thefinal product Decisions at this stage are confined to the demands of the mas-ter production schedule, and the optimization criteria are meeting due dates,minimum level of inventory and work-in-process, and department load bal-ance The parameters are on-hand inventory, in-process orders and on-orderquantities
Capacity planning transforms the manufacturing requirements, as set forth
at the MRP stage, into a detailed machine-loading plan for each machine orgroup of machines in the plant It is a scheduling and sequencing task Thedecisions at this stage are confined to the demands of the MRP stage, and theoptimization criteria are capacity balancing, meeting due dates, minimumlevel of work-in-process and manufacturing lead time The parameters areplant available capacity, tooling, on-hand material and employees
Shop floor control occurs where the actual manufacturing takes place In allprevious stages, personnel dealt with documents, information, and paper Atthis stage workers deal with material and produce products Shop floor control
is responsible for the quantity and quality of items produced and for keepingthe workers busy
Inventory management and control is responsible for keeping track of thequantity of material and number of items that should be and that are present ininventory at any given moment; it also supplies data required by the otherstages of the manufacturing cycle and links manufacturing to costing, book-keeping, and general management
Trang 5The COPICS method must have data from several sources such as customerorders, available inventory, status of purchasing orders, status of items on theshop floor, status of items produced by subcontractors, status of items in thequality assurance department, etc The data from all sources must be synchron-ized to the instant that the COPICS programs are updated For example,because of new jobs and shop floor interruptions, capacity planning must beupdated at short intervals COPICS introduces data collection station terminalsfor shop floor data collection, and terminals in store rooms and productionplanning and control departments
Bibliography
1 Baker, K.R., 1974: Introduction to Sequencing and Scheduling, John Wiley &
Sons, New York
2 Barash, M.M et al., 1975: The optimal planning of computerized manufacturing
systems, NSG GRANT No APR74 15256, Report No 1, November
3 Berry, W.L., 1972: Priority scheduling and inventory control in job lot
manu-facturing system, AIIE Transactions, 4(4), 267–276
4 Buffa, E.S., 1966: Models for Production and Operation Management John Wiley
& Sons
5 Coffman, E.G., Bruno, J.L., Graham, R.L et al., 1976: Computer and Job-shop
Scheduling Theory John Wiley & Sons, New York
6 Hanna, W.L., 1985: Shop floor communication – MAP, 22nd Annual Meeting &
Technical Conference Proceedings AIM Tech, May, pp 294–300
7 Harding, J., Gentry, D and Parker, J., 1969: Job shop scheduling against due dates,
Industrial Engineering, 1(6), 17–29
8 Harrington, J., 1985: Why computer integrated manufacturing, 22nd Annual
Meet-ing & Technical Conference ProceedMeet-ings AIM Tech, May, pp 27–28
9 Halevi, G., 1980: The Role of Computers in Manufacturing Processes John Wiley
& Sons
10 Halevi, G., 1992: The magic matrix as a smart scheduler, manufacturing in the era
of concurrent engineering, North-Holland IFIP
11 Hubner, H and Paterson, I (eds), 1983: Production Management Systems,
Many manufacturing executives are facing the dilemma of where do theyposition their firms in the ‘value chain’ – the entire series of activities that
Trang 6begins with the processing of raw materials and ends when a finished product
in the hands of the end user
Frequently, facing this challenge starts with an examination of the pany’s core competencies, the things it does best in creating value for custom-ers Corporations organize around business units and business units organizearound products – not the other way around Without defined products, it isimpossible to rationalize corporate assets efficiently; it is impossible to have amarket It is essential to go through the incremental processes of discoveringwhat their core competencies are and fiercely concentrating on them Oftenthe result is to become less vertically integrated – to outsource production orlogistics or other functions
com-Outsourcing can result in loss of control of key capabilities, which, in turn,can affect a company’s ability to introduce changes in response to shifts in themarket place or simply to improve its efficiency in serving customers Conse-quently, there has been a growing impetus to find ways to manage the
‘extended enterprise’ – to build collaborative relationships and improve boththe flow of materials and information throughout the value-creating pipeline.The scope of the challenge extends beyond traditional supply-chain manage-ment, although that is a key element
For manufacturers, one distinction is that the value chain extends in bothdirections and encompasses trading partners ranging from the supplier’s sup-plier to the customer’s customer Another is the increasing focus on workingwith trading partners to collectively increase speed, pare costs, and enhancethe end customer’s perception of value Shaping a strategy that reflects thereality of the downstream marketplace often leads to new approaches toupstream supplier management
When a decision to change factory operations is made, one may find that itcouldn’t be done because it wasn’t totally within company control It might bewithin the control of the suppliers To change the business it is necessary thatthe suppliers change their businesses The extended-enterprise-managementapproach called for the supply-chain partners to behave almost as though they arepart of a single organization In deciding where to focus supplier-developmentinitiatives, the emphasis is on manufacturing cycle time If the cycle time islong, it means that there is a lot of opportunity for cost reduction, and for qualityimprovement it is important to synchronize the activities between multiplelinks in the value chain In some organizations the terms ‘supply chain’ and
‘value chain’ are used almost interchangeably Yet, quite commonly, tives think of supply chains as the flow of incoming materials – not the out-bound links to the end customer And often their attention is limited to a singleconnection – with either an immediate supplier or a direct customer
execu-A fundamental question in value-chain management is: How is value ated? If improved efficiency lowers the cost to the end customer, does thatincrease the perception of value? If so, then strategies such as lean manufac-turing, which reduces inventory-carrying costs, have a role to play Lean
Trang 7cre-thinkers would ask: ‘How can I add value to the product and at the same timereduce lead time?’ In short, how do you eliminate non-value-adding activity? For a value chain to function well and have little waste, it is important thatsuppliers deliver in smaller batches and deliver more frequently The suppliermust be able to respond quickly to the needs – but without maintaining a hugeinventory upstream of the value chain In many industries, vendor-managedinventory is becoming a popular value added service – one that not onlyimproves inventory control, but also greatly reduces administrative transac-tions such as purchase orders
For many online retailers, keeping fulfilment operations in-house givesthem a rare opportunity to link directly with their customers Such firmsbelieve that in-house fulfilment means better quality control and increasedflexibility to master the rapidly changing e-commerce environment Formany of these companies, direct to-consumer selling is synonymous withmaintaining core competencies in warehousing and fulfilment, and they arescrambling to expand their own facilities in hopes of avoiding e-commercebacklogs
Bibliography
1 Blackburn, J.D., 1991: Time-Based Competition: The Next Battleground in
Amer-ican Manufacturing Business One-Irwin, Homewood IL
2 Chrisman, J.J., Hofer, C.W and Boulton, W.R., 1988: Toward a system for
classi-fying business strategies, Academy of Management Review, 13, 413–28
3 Gabel, H.L., 1991: Competitive Strategies for Product Standards McGraw Hill,
London
4 Huber, G.P., 1990: A theory of the effects of advanced information technologies
on organizational design, intelligence, and decision making, Academy of
Manage-ment Review, 15, 47–71
5 Keen, 1986: Competing in Time: Using Telecommunications for Competitive
Advantage Ballinger, Cambridge, MA
6 Lacity, M and Hirschheim, R., 1993: Information Systems Outsourcing.
Wiley
7 Mannion, D., 1995: Vendor accreditation at ICL: competitive versus collaborative
procurement strategies In R Lamming and A Cox (eds), Strategic Procurement
Management in the 1990s Earlsgate, Winteringham
8 Miller, J.G and Roth, A.V., 1994: A taxonomy of manufacturing strategies,
Man-agement Science, 40, 285–304
9 Peters, T and Waterman, R., 1982: In Search of Excellence: Lessons from
Amer-ica’s Best-Run Companies Harper & Row, New York
10 Prahalad, C.K and Hamel, G., 1990: The core competence of the corporation,
Harvard Business Review, 68(3), 79–91
11 Tayeb, M.H., 1996: The Management of a Multicultural Workforce John Wiley &
Sons, Chichester
12 Teece, D.J., Pisano, G and Shuen, A., 1997: Dynamic capabilities and strategic
management, Strategic Management Journal, 18, 509–533
Trang 8Cost estimation
M – 2b; 4d; 11d; * 1.2b; 3.2b; 4.2d; 4.4c
Cost estimation is an activity undertaken to calculate and predict the costs of aset of activities before they are actually performed In the particular domain ofmanufacturing of mechanical parts, cost estimation can be seen as the predic-tion of costs of the machining operations and other associated activities neces-sary for the complete manufacture of a mechanical part
For process planning purposes, we may distinguish four types of cost:
1 the pure machining cost;
2 the cost of moving a part from one machine to another;
3 the cost of a setup change on a machine; and
4 the cost of a tool change on a machine
The pure machining cost depends mainly on the time a machine is used for aparticular machining operation
Cost estimating calculations are particularly useful at the early design phase
of a product where 70% of its cost is determined The importance of costestimation based on process plans is outlined in a manufacturability analysissurvey and research in this domain is quite recent and growing together withresearch in feature-based manufacturing
Two main types of cost estimation models may be distinguished: the variantmodel based on machining statistics available in the company; and the generat-ive model, based on analysis of the design of the part The generative modelrequires detailed information in order to produce a process plan that deter-mines the costs of the manufacturing of the part This approach offers the pos-sibility to consider various alternatives in the design and processing andcompare the resulting costs
A new method is proposed for the cost estimation of machining a mechanicalpart given its feature-based description and the associated alternative manu-facturing operations for each manufacturing feature together with the requiredresources (machines, setups and tools), and is capable of representing:
1 manufacturing knowledge, which has the form of precedence constraints;
2 alternative solutions for the machining of manufacturing features;
3 cost factors influencing the cost of a particular process plan
Besides normal machine operation costs, costs caused by machine setup andtool changing are taken into account
Some modelling and cost estimation techniques are based on Petri nets Thepotential for extending Petri nets or the matrix method to process planningmodelling allows the calculation of costs The process planning cost systemcombines net structure with explicit modelling of resources
Trang 9Two techniques for the dynamic modelling of process plans for the ing of mechanical parts are proposed
machin-• The first technique uses specific and independent nets that are then grated into a common net model for machine, setup and tool changing oper-ations The various costs (operation cost and machine, setup and toolchanging costs) are modelled as cost values of transition in the model andthe optimal process plan, i.e a process plan of minimal cost is given by aminimal weighted path from the initial to final node of the correspondingprocess planning cost system
inte-• In the second technique, instead of using separate cost values (depending onprocess batch size) for machine, setup and tool changing, there costs are anintegral part of the process planning task, and affect routing selection Thisyields a compact representation of an operation together with the machine,setup and tool associated with this operation A minimal weighted path algo-rithm is used to search for a path in the generalized process planning thatrepresents a process plan with minimal cost
Bibliography
1 Aho, A.V., Hocroft, J.E and Ullman, J.D., 1983: Data Structures and Algorithms.
Addison-Wesley
2 Alting, L and Zhang, H., 1989: Computer aided process planning: the
state-of-the-art survey, International Journal of Production Research, 27(4), 553–585
3 Anand, S and Quo, P.C., 1996: CAD directed on line cost estimation using
activ-ity based costing, Proceedings of the 5th Industrial Engineering Research
Confer-ence, Minneapolis, pp 781–786
4 Cecil, J.A., Srihari, K and Emerson, C.R., 1992: A review of Petri net applications
in process planning, The International Journal of Advanced Manufacturing
Tech-nology, 7, 168–177
5 Desrochers, A and Al-Jaar, 1995: Applications of Petri Nets in Manufacturing
Systems IEEE Press, New York
6 DiCesare, F., Harhalakis, G., Proth, J.M., Silva, M and Vernadat, F.B., 1993:
Practice of Petri Nets in Manufacturing, Chapman & Hall, London
7 Eversheim, W., Gupta, C and Kümper, R., 1994: Methods and tools for cost
estimation in mechanical manufacturing (METACOST), Production Engineering,
I(2), 201–204
8 Feng, C.-X., Kusiak, A and Huang, C.-C., 1996: Cost evaluation in design with
form features, Computer-Aided Design, 28(11), 879–885
9 Gunther, C., 1998: Batch Delivery Time Calculations Using INA, EPFL report
10 Gupta, S.K., Nau, D.S., Regli, W.C and Zhang, G., 1994: A methodology for tematic generation and evaluation of alternative operation plans In J.J Shah,
sys-M Mantÿla and D.S Nau (eds), Advances in Feature Based Manufacturing
Else-vier Science B.V., pp 161–184
11 Gupta, S.K., Regli, W.C., Das, D and Nau, D.S., 1995: Automated bility analysis: a survey Report ISR-TR-95-14, University of Maryland
Trang 10manufactura-12 Ham, I and Lu, S.C.-U., 1988: Computer-aided process planning: the present and
the future, Annals of the CIRP, 37(2), 591–601
13 Kiritsis, D and Porchet, M., 1996: A generic Petri net model for dynamic process
planning and sequence optimisation, Advances in Engineering Software, 25(1),
61–71
14 Kiritsis, D and Xirouchakis, P., 1996: A software prototype for cost estimation of
process plans of machined parts, ISATA’96, Florence
15 Kruth, J.P and Detand, J., 1992: A CAPP system for nonlinear process plans,
Annals of the CIRP, 41(1), 489–492
16 Lee, D.Y and DiCesare, F., 1992: FMS scheduling using Petri nets and heuristic
search, Proceedings of the 1992 IEEE International Conference on Robotics and
Automation, IEEE, pp 1057–1062
17 Liebers, A and Kals, H.J.J., 1997: Cost decision support in product design, Annals
of the CIRP, 46(1), 107–112
18 Liebers, A., 1996: Integrated cost estimation for assembled products, CIRP
Sem-inar on Manufacturing Systems, available at: http://www.pt.wb.utwente.nl/staff/ arthur/papers.html, Johannesburg
19 Neuendorf, K.-P., Kiritsis, D., Kis, T and Xirouchakis, P., 1997: Two-levelPetri net modeling for integrated process and job shop production planning,
ICAPTN’97, Proceedings of the workshop Manufacturing and Petri Nets,
Tou-louse, pp 135–150
20 Ou-Yang, C and Lin, T.S., 1997: Developing an integrated framework for
feature-based early manufacturing cost estimation, The International Journal of Advanced
Manufacturing Technology, 13, 618–629
21 Srihari, K and Emerson, C.R., 1990: Petri nets in dynamic process planning,
Com-puters Industrial Engineering, 19, 447–451
22 Starke, P and Roch, S., 1998: Integrated Net Analyzer: INA, free available from
internet, http://www.informatik.hu-berlin.de/lehrstuehle/automaten/ina/, 1998
23 Tönshoff, U., Beckendorff, U and Anders, N., 1989: FLEXPLAN-A Concept for
Intelligent Process Planning and Scheduling, CIRP International Workshop on
Computer Aided Process Planning, Hannover University, pp 87–106
24 Valk R., 1995: Petri nets as dynamical objects 1st Workshop on Object-Oriented
Programming and Models of Concurrency, 27 June, Turin, Italy
25 Xirouchakis, P., Kiritsis, D and Persson, J.G., 1998: A Petri Net Technique forProcess Planning
Cross-functional leadership
P – 2c; 3c; 8b; 9c; 12b; 13c; 14c; * 1.1b; 1.2b; 1.3c; 3.1c; 3.2c; 4.2c; 4.5b;4.6c
Cross-functional work teams came into prominence as a direct result of sizing, rightsizing, and other staff-reduction efforts Cross-functional teamshave enormous capacity for introducing substantive process improvements Cross-functional special interest teams have many names and can occur in avariety of forms In some firms, they are well organized and widely publicized
down-In other places, they’re informal and not well understood They typically
Trang 11focus on broad subjects of interest to the enterprise as a whole, such as quality,cost control, waste reduction, contingency planning, strategic sourcing, and soforth The characteristics of cross-functional leadership are:
1 Create commitment outside of authority
2 Use the customer as the authority
3 Ask questions as a means of focusing on problems
4 Allow anyone to offer an answer
5 Continually raise the bar to improve performance
6 Create and maintain continual membership
7 Set time limits to solve a given problem
In other words, regard anyone as a partner in company problems and theirsolution Construct a business culture that fosters open communication andmutually beneficial relationships in a supportive environment built on trust Apartnering relationship stimulates continuous quality improvement Thismight mean moving from numerous suppliers for goods or services to few orone, or increasing information exchange from as little as possible to as much
as possible Some of the principles of this methodology are:
1 Develop relationships before you need the cooperation
2 When encountering differences, seek a win/win breakthrough rather thanlose/lose conflict
3 Most of us enter into agreements to exchange money, services or goods –and then try to get the best of the exchange Partners also commit to treat-ing the relationship as more important than any single exchange
4 To envy another’s prosperity is to wish for limited prosperity Partnerscelebrate other’s prosperity thus promoting opportunity for all
Flexible technology has begun to change the ground on which the assumptionsunderlying the emerging organizational paradigm have been built Applicationareas have moved beyond the linear flows of factory floor and clerical office tothe nonlinear, interactive, mutually interdependent domains of managers andengineers and other professionals, e.g design to manufacture As a con-sequence, the complexity of the design task for both technical and organizationdesigners has increased significantly, and the challenge for designing socio-technical systems that incorporate these two changing domains has increasedeven more In particular, it has outstripped most of the methodology that aroseunder conditions of linear technical systems and sequential work flows Therules and procedures that guided decisions have had to be augmented withprocesses that are open to the flexible possibilities of new technologies Team-based organizational arrangements have arisen not only where teamscross organizational and physical locations, but also straddle global, cultural,and ethnic differences
Trang 12The need for contemporary organizations to use teams to perform all levels
of work and management tasks is well documented Management educatorsacknowledge the challenge to create exercises and simulations to providelaboratory opportunities to experience these new forms of organization Fortun-ately, the experiential learning literature offers many exercises that allow awide range of organizational and interpersonal dynamics to surface for debrief-ing and classroom study However, many of these classic exercises weredesigned with an understanding of yesterday’s hierarchical organizationalconfigurations
Attention to single-person leadership often excludes lessons about thedifferences made by all other participants in team effectiveness In addition,exercises with only one leadership role encourage the perpetuation of genderand ethnic role stereotypes and discourage the active participation of all teammembers as leaders
In the 1970s, group exercises focused on contingent styles of the singleformal leader in influencing functional groups The 1980s saw the addition ofleadership exercises focused on teams operating across functions to solveproblems in quality and productivity However, teamwork was still per-formed within pyramidal lines of authority, often ad hoc and in parallel to theso-called regular ways of doing business In contrast, many businesses todayare trying fundamentally different organizational designs that allow greaterflexibility, rapid redeployment of resources, closer interaction with custom-ers and suppliers, and unremitting innovation The focus is on acceleratinglearning to make the timely, continuous improvements demanded by custom-ers who can now shop worldwide Teams are often the fundamental buildingblocks in these designs, but understanding team leadership opens unchartedground
Many large project design activities now incorporate customers as well assuppliers within the project team and/or via focus groups Strategic alliancesand network organizations explicitly cross traditional organizational frontiers.Concurrent or simultaneous engineering teams cross functional boundarieswithin companies to include members who can reduce the time needed todesign and produce products Unlike project management arrangements thattraditionally incorporated these functions in sequence, these arrangementsemphasize the simultaneity of the activity More often than not, it is the exist-ence of shared manufacturing and product design databases, accessed throughinformation technology, that is facilitating and fostering the redesign of theseconceptually new integrative approaches
Bibliography
1 Beckhard, R and Prichard, W., 1992: Changing the Essence: The Art of Creating
and Leading Fundamental Change in Organizations Jossey-Bass, San Francisco
2 Blake, R and Mouton, J., 1974: The Managerial Grid Prentice Hall, Englewood
Cliffs, NJ
Trang 133 Burack, E., 1993 Corporate Resurgence and the New Employee Relationships:
After the Reckoning Quorum Books, New York
4 Byrne, J.A., 1993: The horizontal corporation Business Week, 3351(6), 76–81
5 Cohen, A and Bradford, D., 1991: Influence Without Authority John Wiley, New
York
6 Fiedler, E., 1972: A Contingency Theory of Leadership Effectiveness Prentice
Hall, Englewood Cliffs, NJ
7 Hoberman, S and Mailick, S., 1995: Experiential Management Development.
Quorum Books, New York
8 Juran, J., 1989: Juran on Leadership for Quality Free Press, New York
9 Kolb, D., Rubin, I and McIntyre, J., 1971: Organizational Psychology Prentice
Hall, Englewood Cliffs, NJ
10 Kouzes, J and Posner, B., 1995: Challenge: How to Get Extraordinary Things
Done in Business Jossey-Bass, San Francisco
11 Manz, C and Sims, H., 1990: Self-leadership Berkeley Books, Berkeley, CA
12 Vaill, P., 1988: Managing as a Performing Art: New Ideas for a World of Chaotic
Change Jossey-Bass, San Francisco
13 Vance, C.M., 1993: Mastering Management Education Sage, Newbury Park, CA
14 Vroom, V and Yago, A., 1988: The New Leadership Prentice Hall, Englewood
Cliffs, NJ
15 Whetten, D and Cameron, K., 1995: Developing Management Skills
Harper-Collins, New York
Customer relationship management – CRM
S – 7c; 9b; 10b; 11c; 13c; 16b; * 1.1b; 1.2c; 1.3b; 1.5b; 1.6b; 3.3c; 3.4c;4.1c; 4.2c; 4.3c; 4.4c
Customer relationship management is defined as any strategy for managingcustomers and customer relationships, by developing a network of ‘touch points’with customers that establish, cultivate and maintain long-lasting relationships.This goes beyond implementing technologies such as a customer informationdatabase and data analysis tools CRM extends into areas such as strategicdecisions regarding delivery channels, customer service approach and evenorganizational structure
Customer relationship management means the responsible acquisition anddeployment of knowledge about customers to sell more of a company’s prod-ucts and services more efficiently CRM will advance notions about integratedmarketing, so agencies will be better able to boost their clients’ bottom linesthrough technologically advanced, but personal, methods of cross-selling andup-selling to existing customers
While traditional advertising and sales channels could make prospectivebuyers aware of the offerings, CRM would allow the marketer to target theprospects most likely to buy, and with offers relevant to their situations CRM relies on a robust database Data comes in from numerous paths or, asCRM practitioners call them, touch points These touch points include the obvi-
Trang 14ous channels in the integrated marketing mixture – advertising, direct marketing,public relations, interactive – but also include additional touch points, includingsales calls, billing records, service orders, customer inquiries, satisfaction sur-veys to provide a complete picture of how customers interact with a brand The fundamental assumption of CRM is that a company that can integratefront-office applications with back-office applications would have a highervalue for customers by being able to view both customer and supplier needs.One more benefit to integrating CRM with other applications is the ability tomore easily conduct data mining and draw business intelligence from the datawithin applications
The convergence of e-commerce with existing supply-chain channels is cing companies to find better ways to serve customers The need to improvethose interfaces while integrating information technology into readily avail-able access points is driving the market for customer relationship managementsolutions
for-Companies are using CRM applications to enhance their competitive tion and boost revenue by identifying and maintaining customers, integratingwith back-end enterprise resource planning (ERP) systems to create a singlecustomer contact point, and more efficiently managing business coming in viathe Web
posi-Customers and suppliers could use this information to show a prospectiveclient how its usage costs compare with others in its industry, or to prepare apersonalized savings forecast for the upcoming year based on the efficiency ofnew equipment, including how quickly the equipment will pay for itself.Perhaps this prospect has asked its sales representative to contact a differentindividual about related services If this information were stored in the market-ing database, CRM would dictate a specific, well-informed strategy for theaccount Rather than calling the main contact, the CRM agency could contact
an alternative buyer, leverage the success of the original relationship anddemonstrate bottom-line savings based on individual-level data
Companies are now developing business plans with CRM strategies nated as the key to revenue-enhancement opportunities and customer retention.CRM applications, along with e-commerce systems, address these criticalissues and are becoming the hub of many companies’ marketing strategies With so much emphasis being placed on integrating enterprise-wide sys-tems, the trend is to extend the family methods of customer relationship, supplychain management, and enterprise resource planning to overlap each other or tocombine them Suppliers of these packages extend their offering either throughnew products or by acquiring and integration with others As customers recog-nize the power of systems that use information from all parts of the enterpriseand automate processes along organizational boundaries, stand-alone CRMapplications will find it harder to retain market share
desig-As information sources proliferate, it becomes harder and harder to getcustomers to pay attention to your marketing message, especially when they
Trang 15are constantly receiving messages through multiple channels As customerattention becomes a scarcer resource, cataloguers must attract and maintaincustomer attention by meeting their needs for information, entertainment andcommunity Not only is it more difficult to keep customers’ attention, but alsothere are fewer barriers keeping them from buying a competitor’s product orservice All a customer has to do to change loyalty is to simply type www.yourcompetitor.com
To keep your customers’ attention, retain and create more interactivity withyour customers, implement customer relationship management (CRM) strat-egies This may mean doing business in a different way This may mean thatyou must offer more convenience by selling via the Web, keep track of thestage of the relationship with your customer to better anticipate behaviour,measure success in terms of lifetime value/profitability and identify customercommunication preferences
CRM strategies need to identify and address value, from both the customerand business perspectives As a business person analysing your customers, youmust put the emphasis on them rather than the product portfolio So it is essen-tial to understand who your customers are, what and how they buy, why theybuy and their value to your organization Value is typically represented by howmuch they have spent with your company Furthermore, the wealth of informa-tion gathered from CRM strategies becomes the foundation for prospect model-ling – creating what are known as look-alike models – that can be leveraged tomaximize the rate of new customer acquisition The cost of acquiring customers
is substantial and will probably increase, so you want to ensure that you are ting the most for your money Existing customers are responsible for near-termprofits, but new customers will contribute in the future
get-Customers, on the other hand, must identify what value your companybrings to them if you are to keep their attention Your value could be as simple
as offering convenience, or excellent customer service, or a brand that the tomer perceives as valuable In short, any way to meet a customer’s need willcreate value Creating value for customers yields loyalty, which in turn yieldsgrowth, profits and more value Customer loyalty delivers huge bottom-linebusiness impact because loyal customers spend more money, stay longer, costless to service and refer more new customers
cus-Bibliography
1 Blackburn, J.D., 1991: Time-Based Competition: The Next Battleground in
Amer-ican Manufacturing, Business One, Irwin, Homewood IL
2 Chrisman, J.J., Hofer C.W and Boulton, W.R., 1988: Towards a system for
classify-ing business strategies, Academy of Management Review, 13, 413–428
3 Gabel, H.L., 1991: Competitive Strategies for Product Standards, McGraw Hill,
London
4 Christopher, M., Harrison, A and Van Hoek, R., 1999: Creating the agile supply
chain: issues and challenges In Proceedings of the 4th ISL, Florence, Italy, 1999