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A Learning Organisation Approach for Process Improvement in the Service Sector

Richard Messnarz, ISCN, Dublin, Ireland
Christine Stöckler, Bernhard Posch, APS, Austria
Gonzalo Velasco, Fueva, Spain
Gearoid O’Suilleabhain, CIT, Ireland
Miklos Biro & Tibor Remszö, Sztaki, Hungary
 

Introduction

This paper is based on the results from the EU Leonardo da Vinci project Bestregit. Bestregit focussed on general service organizations (general public services, European Union regional information nodes, and regional governmental divisions) which are non-profit, mostly state-funded, non-software and very human centered organizations.

In Bestregit the principles of process improvement were analyzed and tailored for the use in non-software general service industry, and tried out in three half-governmental institutions in Spain, Austria, and Ireland to improve their service capabilities.

The outcome is a framework for process improvement that could be beneficially applied in the general/public service sector to put a structure in place, with goals, and teamwork based processes, aiming at a learning organization architecture.

The paper describes characteristics of general service organizations, the Bestregit methodology, and presents parts of three case studies from the set of experiments tried out in the different countries.
 

The Approach

The target group in the first place were the technology transfer units (later they called themselves innovation transfer units) which are financed by the regional governments and the EU, and which are responsible for dissemination of programmes, support in the creation of transnational teams, and the multiplication of know how from the EU into the region and vice versa (see Figure 1).

At the beginning of Bestregit there were two different possible approaches to start with:

Trying to invent an ideal architecture of technology transfer and map each technology transfer unit onto this ideal model. (note: the typical assessment and benchmarking approach)

Trying to create a framework of process improvement steps through which each regional technology transfer unit runs and improves their knowledge multiplication ability.

The group for (a) was so ambitious to plan to establish a new technology transfer principle which could be sold to Brussels.

The group for (b) thought much more on a realistic level because:

A small team like Bestregit with regional representatives from a small subset of regions of Europe could not be in the power to influence the European Union level. Regional politics would create troubles, because even if we could manage 1. above, e.g. a regional Austrian unit cannot agree models with Brussels which influence the Austrian state, they would first have to agree on a state level.

There was an expectation of cultural differences so that work models for the same goal might look different in different regions.

Unlike in areas like software industry, electronics industry, etc. there is no international standard which describes the ideal architecture of innovation transfer organisations. There is the ISO 9000 standard with a guideline 9000-4 for service organisations, but this still is a quite general description.
 
 


Figure 1 : The Regional Multiplication Nodes

This formed the reason to follow the approach (b) and focus on an improvement of the dissemination and multiplication ability of regional transfer units, thus increasing the multiplication of EU strategies into the regions of Europe.

The project therefore aimed at a synergy between all involved parties. The Eu will have their information and results better promoted, the regional units increase their capability, ad the SMEs will receive a better service through defined teamwork, interfaces, and infrastructure.
 

What are the Characteristics of a General Service Organisation

The integrated business oriented approach followed in this section was first presented by Dr. Biro in chapter 1 of the book [1] edited by Messnarz, R., Tully, C, 1999, entitled Better Software Practice for Business Benefit – Principles and Experience written in the framework of the EU supported Leonardo PICO (Process Improvement Combined Approach) project.

Special characteristics of the addressed organizations and the BESTREGIT process improvement initiative

The organization we are addressing has the following special characteristics. It is: All of the above characteristics have deep implications for the motivations and approaches of managers in performing and improving their activities.

Service orientation as opposed to manufacturing means that direct contact with the customer is not restricted to the specially trained sales and marketing staff, but is the natural duty of the majority of the personnel. By consequent, technical knowledge is necessary but not sufficient. Special emphasis has to be put on human relationship skills especially when dealing with profit oriented enterprises which are keen on the most efficient use of their resources. This issue is directly addressed by the role based team work approach described in the process improvement guidelines.

‘Non-profit’ in our case means that the costs of the organization are covered by public sponsors in addition to private ones, which makes the requirement for both high level and impartial service quality of utmost importance.
 

Advantages and disadvantages of process improvement in non-profit service oriented organizations

One of the most pertinent questions the manager of a non-profit service organization can ask is the following "How can I best satisfy and allow to enhance my customers’ and sponsors’ expectations using and possibly increasing my available resources?" Managers with financial, operating, production, marketing, human behavioural, or other orientations will give a variety of answers to this question and will arduously argue for their valuable ideas. Here, we will outline a framework integrating and structuring several orientations.

The key concept of the approach is the notion of lever. Levers are means used by a firm to increase its resource generating ability, just as a mechanical lever is used for increasing the force applied to an object. The analogy goes even further. Just as a force can be applied in many different ways to the object resulting in a similar displacement, the use of the different levers can increase the resource generating ability of the firm resulting in similar benefits. Finally, the resources of a non-profit organization are used to increase the assets of the firm and to reward employees.

Let us analyse the ways process improvement can provide leverage to a non-profit service organization from the financial, operating, production, marketing, and human behavioural perspectives.
 

Financial leverage

Financial leverage means borrowing funds and investing them with a return higher than the cost of the debt. If a company is able to exploit financial leverage, it can make money on funds it does not own. This is by definition a type of leverage a non-profit organization can never exploit. This issue is nonetheless very relevant in our case.

The type of non-profit service organization we are addressing is partly sponsored from public funds which means that there is in fact a public investment whose return can only be accounted for indirectly. This means that the return on investment (ROI) must be realized partly by the public through the intermediary of both the non-profit organization and its client profit oriented organization.

It goes without saying that an exact quantitative return is usually not identifiable in such cases, but a qualitative return statement confirmed by the profit oriented customers and possibly public representatives serves clearly the interests of the non-profit service organization.

We claim that process improvement results in a return definitely making the necessary investment worthwhile only if the addressed organization is fully committed and able to immediately exploit its benefits. Everybody must be aware however that process improvement is not a silver bullet. Commitment and hard work is necessary to obtain the expected results so that the leverages discussed in this section can be taken advantage of.

Operating Leverage

Operating leverage is related to the cost structure, that is the repartition between the fixed costs and variable costs.

Process improvement clearly means an increase in fixed costs, which include training, consulting fees, equipment, improvements in office conditions, etc... However, the question is whether the company is really able to use it for decreasing its variable costs. Measuring the variable costs of a non-profit service organization is not a straightforward issue.

If, due to process improvement, the firm is able to deliver the same quantity and better quality of service using less person months than earlier, then it will have the potential to take advantage of operating leverage.

Learning Leverage

It is an empirical fact that unit costs decline exponentially when experiences are accumulated and the steady reuse of these experiences is well managed by the firm. This is called production leverage in the manufacturing industry, while learning leverage is a better expression in the service sector.

The graph of the unit costs in function of the cumulative quantity of service provided or product produced is called the experience or learning curve which is exponentially decreasing. Its existence is essentially due to economies of scale, learning, improvements, and reuse.

Learning, the accumulation of experiences and the management of their steady reuse is clearly one of the primary objectives of process improvement and it is in the primary focus of the BESTREGIT methodology.

Marketing Leverage

Process improvement, maturity achievement, ISO 9000 certification have an important impact on the perceived capability of the company and on the perceived value of its products or services, which contributes to improved customer satisfaction.

Quality and process improvement are part of a differentiation strategy in which the company delivers and is perceived to deliver a superior product or service. Taking advantage of this marketing leverage towards the public and its customers is clearly the interest of a non-profit service organization.

Human Leverage

It is widely known that employee motivation (empowerment) can be significantly influenced by immaterial means like management styles and organizational structures. Huge individual energies can be released for example in an appropriate teamwork environment where team members are simply given the responsibility to do their jobs as well as they can, instead of exerting close surveillance over them. This means that the same employees can perform more work and even in better quality than otherwise. Nevertheless, attention must be paid at the differences in the collective mental programming of people in different national cultures [57].

The exploitation of human leverage is particularly important in service organizations since they are directly dependent on the enthusiasm of their employees. This issue is largely addressed by the BESTREGIT methodology.
 

An Overview of the Methodology
The methodology has been adapted from a set of methodologies from the information technology industry and has been field tested in innovation transfer organizations in Austria, Ireland, and Spain.

The methodology works in the following major phases :

Start and First Investment of Resources
Analysis of Current Situation

Goal Analysis
Teamwork Analysis
Experimentation and Measurement
Selection of Experiment
Initiation of Experiment
Experiment Performance
Multiplication of Lessons Learned

The methodology itself helps general service organizations to


 


Figure 2 : The Building Blocks of the Methodology


Figure 3 : The Learning Framework of the Methodology

From a people point of view (as mentioned before people are the most important resource in service organisations) the following levels of learning are run through:

Level 0 : Initiation (see Figure 3)

At the start:

Our processes are that complex that we do not believe that they can be modelled and shared ? It is just the skills of some heroes fighting for innovation transfer success.

Later: A continuous restart to work on further needs.

Level 1 : Awareness (see Figure 3)

A goal analysis helps to put a structure (with goals) in place for the organisation and makes a common understanding possible.

At this level the visions, goals, and structures can be shared and understood. It is the first time that the hero culture changes into a team with a shared vision. Please note that through a structure (documented and understandable for all) all can contribute and share the goals from that point onwards.

Level 2 : A Team View (see Figure 3)

An information flow and process analysis helps to identify team roles, information flows, work results, and required resources for different work scenarios in the organisation.

At this level people who work in a team start to separate responsibilities, make information flows clear, and agree on work results. This leads to defined team-work structures for different business cases of the service enterprise.

From that point onwards people know their roles, know how to work in a team and how to exchange information to jointly reach a certain service goal.

This level usually ends with an enthusiastic feeling of the people involved. But ….

Level 3 : The Level of Criticism/Feedback (see Figure 3)

No learning environment works without criticism and feedback loops to further build on the goals and the team-work scenarios.

An experiment and try-out shows if the models and goals are right or have to be adapted. This has to be based on measurement of data (objective evaluation).

This usually leads first to a pessimistic phase (after the enthusiastic one) until people realise that the continuous industrial change will always require adaptation and further refinement of the models and goals.

Level 4 : A Change Driven Learning Organisation (see Figure 3)

People understand that change is a natural requirement and that change can be managed (avoiding level 0) as long as there is a structure in place which allows to share goals, work processes, and knowledge.

Change is not a single-person activity it is a change of the shared goal, vision and work force of the entire team following an adapted structure for the organization into the future.
 

Experiences Gathered per Step

The project created a guideline based on the feedback from practical case studies in regional innovation transfer organisations in Spain, Ireland, and Austria. The guideline is too big to present all underlying work procedures and support tools here.

Below you only find a short list of lessons learned per step

Step 1 : Installation of a Process Improvement Manager (Team)

This improvement manager is responsible for

Goal Analysis

Mission. A mission is a strategic goal of the organization. It is usually defined by the director and the board of owners, has a long term view, and is defined in a way that it clearly represents the organization and allows that all current business fields fit into it. Especially in innovation transfer it is usually aligned with some technology transfer political visions.

You can see that a mission is right if (in spite of the rapidly changing requirements) it had to be changed only every 4-5 years.

Business Field Goals. This is a goal that is important to be achieved to satisfy the mission. To reach such a business field goal it is required to create a work force whose task it is to perform projects which contribute to the achievement of that business goal. Such goals usually are defined in cooperation between the director and the department heads (managers) of the organization.

A goal for a certain business field is right if (in spite of the rapidly changing requirements) it had to be changed only every 2-3 years.

Work Specific Goals. This is the most concrete level of a goal. Work specific goals contribute to the achievement of business field goals. Here concrete work performance indicators can be measured and conclusions are made if the project was successful or not.

Such goals usually are defined in cooperation between the department heads (managers) and project leaders of the organisation.

A goal for a certain project is right if it clearly contributes to the business field goal and if it is short term (maximum 1.5 years) and can be measured to have an objective basis to decide about success, failure, and required adaptations.

Goal Tree. A goal tree defines an architecture in which the mission, the business field goals, and the work specific goals are represented. A goal tree (in its ideal structure) should provide forward and backward trace-ability. Forward trace-ability means that it is clear which business fields belong to the mission, and which work specific goals contribute to which business field goal. Backward trace-ability means that quantitative performance indicators are used for measuring the achievement of the work specific goals, and that these indicators help to evaluate a business field indicator, which in turn can be used to measure the mission’s success. Backward trace-ability builds the feedback loop into the goal structure, and usually it requires data collection and evaluation.

Step 2: Identification of the Mission, Business Field Goals, and Project Goals

Lessons Learned

Step 3: Setting Priorities Before Further Effort Investment

While in Bestregit the three organizations got funding to model all work scenarios, in a real business case this approach would not be applicable. Business and service demands lead to

It means significant effort to run at least one improvement, and to achieve return on investment you have to invest your improvement resources properly and carefully.

Therefore

Lessons Learned

Teamwork Analysis


Work Scenario. Each organization consists of a set of work scenarios. E.g. Customer handling, service delivery, workshop organization, etc. A work scenario is therefore a description of the best way to conduct a certain business case in the organization.

Work scenarios in Betregit are described with two complementary views:

Role Models. Role centered models base on roles which are played by individuals. One person can play many roles as well as many persons could play just one role. Roles exchange information and work results. This information flow between the roles forms the role model.

Work Flow Models. Work flow models consist of a network of work steps. Work steps produce results that can be used by other work steps. Each work step requires resources (e.g. a certain effort, tools to be used, etc.).

Bestregit uses an integration of both these views:

First role models are analysed and designed. Secondly the role models are transformed into work-flow views. Thirdly, both models are integrated so that a work scenario according to Bestregit can be defined as follows:

A Work Scenario According to Bestregit. People are assigned to roles, roles are assigned to activities, activities are part of a network of work-steps, activities produce results, and roles use resources to perform the activities. These relationships are then defined for a certain business case of the organization to have a description of the best way to perform the business case.

Step 4: Identify the Roles and Design a Role Model

Lessons Learned:

Step 5: Identify the work-steps and create a work-flow

Lessons Learned:

Step 5 can result in the identification of a number of inconsistencies, such as

An elegant approach for ensuring consistency is to transform role models into work-flow views. The Bestregit guideline contains a procedure for how to manage this.

Step 6: Identify the Results Produced by the Work-Steps

After performing the previous steps 1 – 5 the organization is understood as a defined network of work steps, performed by roles, with a number of results to be produced in a team. However, so far the results are just a graphical element in a work-flow chart or the name of an arrow in a role model.

The question is "how can we evaluate if a work-flow model or a role model is right"? Here the Bestregit methodology takes into account different perspectives:

Quality. The degree to which a system, component, process, or service meets customer or user needs or expectations. [IEEE-Software Engineering Standards]

Customer´s Quality Perception. A customer would not look into how the processes were used to develop a service or product, he would just evaluate the quality of the delivery. (how his/her expectations are met).

Manager’s Quality Perception. A manager who coordinates work and delivers products or services to a customer evaluates the quality of his work on how well structured his work processes are to ensure that he can deliver quality to customers.

Bestregit’s Perception of Quality. Quality of an end product / service (on which the customer perception bases) is the sum of the quality of the intermediate results of the work steps in the work flow (what the manager can review and control).

Therefore the Bestregit methodology assumes that

Experimentation

Metric. A quantitative measure of the degree to which a system, component, process, or service possesses a given attribute. [IEEE-Software Engineering Standards]

Measurement. The activity of assigning numbers using a defined counting or evaluation process (a metric) on the characteristics of a product or activities.

Experiment. An experiment is a practical try-out of the previously established models and results. It must be based on a feedback mechanism that allows to measure the impact of the experiment at the start and after performance of it. Both measures are then used to make conclusions about success/failure of the experiment and required refinements.

An experiment is the first step to create a learning/feedback loop around ideal models established by the managers’ quality perceptions.

Three types of experiments were tried out in Bestregit –
 

Type 1 - Work Scenario Optimisation

One selected work-flow is chosen for a try-out. The required duration times and efforts for the roles are set at the beginning either based on previous experience or assumptions (if no past data are there). People are assigned to the roles and the work-flow is initiated.

Deviations, problems, and improvement wishes are documented throughout the experiment controlled by the process improvement manager.

This includes

The experiment results in a refined work model, with adapted duration and effort times. This is like running through a set of learning cycles, and the more cycles you run, the more realistic and professional the processes become.
 

Type 2 – Infrastructure and Work Process Optimisation


The Bestregit methodology analyzed all required ingredients to build a computer supported work environment (Intranet) in the steps 4 to 6.
 



Figure 4 : Intranet Work Environment Using Bestregit Like Results

A typical measurement at the start would be different satisfaction evaluations:

Type 3 - Human Resource Capability Optimisation

In the past skills were largely defined on a single-person level. However, the systems and services in industry become that complex, that sometimes one person would work for her/his life-time or more to complete the task. So team work is growing in its importance and in the new education and skills white paper of the European Union inter-personal and communication skills are emphasised. This is also the focus of the Bestregit methodology which creates frameworks (role models) that allow people to identify themselves with roles, know their interfaces to other team members, and through a feedback cycle can build on the team work structure.

The assumption is that if you try out a Bestregit role model in staff training and integration that the time to be integrated and effective for organisations decreases. The staff integration time is reflected by the effort of the person which introduces the person to the environment. The less additional effort is needed to become a new effective employee, the smoother the integration works. This tutoring effort can be used as an indicator.
 

Lessons Learned

Step 8: Assign your Personnel to the Roles

Step 9: Select and Prioritise Experiments

Step 10: Measure (Define, Collect, Evaluate Data)

Step 11: Learn and Disseminate

Here we describe some example results from the field test organisations. Each field test report is prepared as a case study and comprises about 60 pages. Thus we only can extract small parts for this paper.
 

Example E: Spanish Organisation – Sample Types 2 & 3 Experiments


The Spanish filed test partner is a non for making profit organisation created by the Valladolid Chamber of Commerce and Valladolid University in 1986 in order to link interests coming from both institutions.

They have a large background in the management of Regional, National and European projects. They are mainly specialised in Training and Human Resources Projects, and in Innovation projects and Technology Transfer.


Figure 5 : The Spanish Partner Structure and Identified Work scenarios

Figure 6 : The Spanish Partner Top level Goals


Figure 7a : Goals and Measurements


Figure 7b : A Small Part A of the The R&D Management Role Model

The experiment focussed on the design, development and implementation of a documentation system, which allows everybody to manage information/documentation of the rest of colleagues from the same department without having problems to find any document.

To measure, in quantitative and qualitative way, all improvements made through the comparison between the current and future situation.


Figure 8 : A Small Part B of the The R&D Management Role Model

The Bestregit analysis results included all ingredients to build such a system

So the Spanish partner built up an indexing system through a database which stores information and resource allocators of project results.

Results:


 

References

[1] Messnarz R. Tully C., Better Software Practice for Business Benefit – Principles and Experience, IEEE Computer Society Press, Brussels, Washington, Tokio, 1999, ISBN : 0-7695-0049-8.
 

Goal Analysis

[2] Basili, V., Rombach, H.: The TAME Project: Towards Improvement-Oriented Software Environments, IEEE Transactions on Software Engineering, Vol 14, Number 6, June 1988.

[3] Card D.: Understanding process improvement, IEEE software, July 1991.

[4] Debou C.: ami a new paradigm for software process improvement, In: Proceedings of the first ISCN Seminar, Dublin, May 1994

[5] Debou C., M. Kuntzmann-Combelles A: From Business Goals to Improvement Planning,: Practical Use of ami In: Proceedings of the SPI96/ISCN96 conference, Brighton, December 1996

[6] Debou C., Stainer S.: Improving the maintenance process: a quantitative approach, In: Proceedings of the 6th international conference on software engineering and its application, Paris, Nov 1993.

[7] Debou C., Fuchs N., Haux M.: ami: a Taylorable Framework for Software Process Improvement, In: Proceedings of the second ISCN Seminar, Vienna, September 1995

[8] Debou C., Kuntzmann-Combelles A., Rowe A.: A quantitative approach to software process, In: Proceedings of the 2nd international symposium on software metrics, London, Oct 1994.

[9] Dion R.: Process Improvement and the corporate balance sheet, IEEE Software, July 1993.

[10] Debou C., Lipták J., Shippers H.: Decision making for software process improvement: a quantitative approach, In: Proceedings of the 2nd international conference on "achieving quality in software" ACQUIS 93, Venice (Italy), pp 363-377, Oct 1993.

Also In: The Journal of Systems and Software, 1994; 26:43-52, Elsevier Science Inc.

[11] Esprit II 5494 ami:ami Handbook, Published version, March 1992.

[12] Mc Garry F. and al.: Software process Improvement in the NASA Software Engineering Laboratory, CMU/SEI-94-TR22, December 1994.

[13] Kuntzmann-Combelles A., from assessment to improvement actions: compared experiences with CMM and SPICE, In: Proceedings of the 5th European conference on software quality, Dublin, Sept 1996.

[14] Perez I., P. Ferrer, A. Fernandez: Application of Metrics in Industry In: Proceedings of the 3rd European conference on software quality, Madrid, November 1992.

[15] Pulford K., Kuntzmann-Combelles A., Shirlaw S.: A Quantitative Approach to Software management, ISBN 0201877465, Addison Wesley, 1995

[16] Rombach, D.: New Institute for Applied Software Engineering Research, In: Software Process Newsletter, No 7, IEEE Computer Society TCSE, Fall 1996

[17] SEL, NASA Goddard Space Flight Center, Software Engineering Laboratory Relationships, models and management rules, SEL-91-001, February 1991
 

Process Definition and Teamwork Analysis

[18] Chroust G., Computer Integrated Work Management, in (ed.) Mittermeir R., Shifting Paradigms in Software Engineering, pp. 4 -13, Springer Verlag, Wien, New York, Sept. 1992

[19] Curtis B., M. Kellner, J. Over: Process modelling, In: Communication of the ACM, September 92, vol 35, No 9.

[20] ESA Board for Standardisation and Control, ESA PSS 05 Software Engineering Standards, European Space Agency, Paris, 1991

[21] German Interior Ministry, German V-Model, Bonn, August 1992

[22] Haase V., Messnarz R., Koch G., Kugler H., Decrinis P: Bootstrap: Fine-Tuning Process Assessment, In: IEEE Software pp25-35, July 1994

[23] Haase V., Messnarz R., Cachia R.M., Software Process Improvement by Measurement, in (ed.) Mittermeir R., Shifting Paradigms in Software Engineering, pp. 32 - 41, Springer Verlag, Wien, New York, Sept. 1992

[24] Haase V., Messnarz R., A Survey Study on Approaches in Technology Transfer, Software Management and Organisation, Report 305, Institutes for Information Processing Graz, June 1991

[25] J. Herbsleb, A. Carleton, J. Rozum, J. Siegel, and D. Zubrow: "Benefits of CMM- based Software Process Improvement: Initial Results". Technical Report, CMU-SEI-94-TR-13, Software Engineering Institute, 1994.

[26] Humphrey W.: Managing the Software Process, Addison-Wesley, Reading, Mass., 1989.

[27] Humphrey W.S., Sweet W.L.: A Method for Assessing the Software Engineering Capability of Contractors, Software Engineering Institute, Sept 1987

[28] ISO 9000-3. Quality management and quality assurance standards. International Standard. Part 3: Guidelines for the Application of ISO 9001 to the Development, Supply and Maintenance of Software. ISO (1990).

[29] ISO 9001. Quality Systems. Model for Quality Assurance in Design/Development, Production, Installation and Servicing. International Organisation for Standardisation, Geneva (1987)

[30] ISO 9126, Information Technology - Software Product Evaluation - Quality Characteristics and Guidelines for Their Use, 1991

[31] ISO/IEC 12207, Information technology - Software life cycle processes, first edition Aug. 95.

[32] Messnarz R., Kugler H.J., BOOTSTRAP and ISO 9000: From the Software Process to Software Quality, in: Proceedings of the APSEC´94 Conference, Comput. Soc. Press of the IEEE, Tokyo, Japan 1994

[33] Messnarz R., Practical Experience with the Establishment of Improvement Plans, in: Proceedings of the ISCN´96/SP’96 Conference on Practical Improvement of Software Processes and Products, ISCN LTD, Brighton, UK, 1996

[34] Messnarz R., Scherzer H., The Evolution of a Quantitative Process Analysis - the BOOTSTRAP - Approach, in: (eds.) G. Chroust, P. Doucek, Interdisciplinary Informational Management Talks, Oldenbourg, Vienna, Munich, 1995

[35] Messnarz R., Stubenrauch R., Melcher M., Bernhard R., Network based teamwork and Quality Assurance (NQA), in: Proceedings of the 6th European Conference on Software Quality, Vienna, April 1999

[36] Paulk M. C., Curtis B., Chrissis M. B.: Capability Maturity Model for Software, version 1.1, CMU/SEI-93-TR-24, February 1993.

[37] Paulk M. C., Weber C. V., Garcia S. M., Chrissis M : Key practices of the Capability Maturity Model, version 1.1, CMU/SEI-93-TR-25, February 1993.

[38] Axel Völker, Sortware Process Assessments at Siemens as a Basis for Process Improvement in Industry, Proceedings of the ISCN'94 Conference, ISCN Ltd., Dublin, Ireland
 

Measurement and Experimentation

[39] Boegh J., SCOPE - A Guide for Software Product Quality Evaluation, in: Proceedings of the ISCN´94 Conference on Practical Improvement of Software Processes and Products, ISCN Ltd., Dublin, Ireland, 1994

[40] Briand L., El Eman K., Melo W.: AINSI: an Inductive Method for Software Process Improvement: concrete Steps and Guidelines, In: Proceedings of the second ISCN Seminar, Vienna, September 1995

[41] Briand L., Differding C., Rombach D.: Practical Guidelines for Measurement-based Process Improvement, Technical Report of the International Software Engineering Network, ISERN-96-05, 1996

[42] L.C. Briand, C.M. Differding, H.D. Rombach, Practical guidelines for Measurement Based Process Improvement, Proceeding of SP-ISCN 96 Conference, Brighton, December 1996

[43] Brooks F.P., The Mythical Man-Month, in: Datamation, Addison Wesley Publishing Company, Massachusetts, December 1973

[44] DeMarco T., Controlling Software Projects, Yourdon Press Computing Series, Prentice Hall, Englewood Cliffs, London, Sydney, Tokyo 1982

[45] R.B. Grady, D.L. Caswell, Software metrics: establishing a company-wide program, Prentice-Hall, 1987

[46] R.B. Grady, Practical software metrics for project management and process improvement, Prentice-Hall, 1992

[47]  G. Bazzana, P. Caliman, D. Gandini, R. Lancellotti, P. Marino, Software management-by-metrics: experiences in Italy, Invited paper - Proceedings of CSR 10th Annual Conference, Amsterdam, October 1993.

[48] G. Bazzana, R. Brigliadori, O. Andersen, T. Jokela, ISO 9000 and ISO 9126: friends or foes, Proceedings of IEEE Software Engineering Standards Symposium, Brighton, September 1993

[49]  B. Hetzel , The sorry state of the art of software measurement, in: N. Fenton, R. Whitty, Y. Iizuka, Software Quality Assurance and Measurement - A worldwide perspective, Thomson Computer Press, 1995

[50] Mehner T., Siemens Process Improvement Approach. In Practical improvement of software processes and products: Proceedings of the ESI–ISCN 95 Conference on Measurement and Training Based Process Improvement, Vienna, September 1995.

[51] METKIT Consortium and BRAMEUR Ltd., METKIT Industrial Package, 1994

[52] Pyramid Consortium, Quantitative management: get a grip on software!, Technical Reference: EP-5425 Y 91100-4, December 1991

[53] E. Trodd, A Minimum Set of Metrics for Effective Process Management, Proceeding of SP-ISCN 96 Conference, Brighton, December 1996

[54] E.F. Weller, Using Metrics to manage Software Projects, IEEE Computer, Vol. 27, No. 9, September 1994

[55] G. Stark, R.C. Durst, C.W. Vowell, Using metrics in management decision making, IEEE Computer, Vol. 27, No. 9, September 1994
 
 

Business and Leveraging Models

[56] Capers Jones, The Pragmatics of Software Process Improvement. Software Process Newsletter. No.5, Winter 1996, pp.1-4.

[57] Geert Hofstede, Motivation, Leadership, and Organization: Do American Theories Apply Abroad? Organizational Dynamics. Summer 1980, pp.42-63.

[58] Herbsleb,J; Carleton,A; Rozum,J; Siegel,J; Zubrow,D. Benefits of CMM-Based Software Process Improvement: Initial Results. Software Engineering Institute, Carnegie Mellon University, Technical Report CMU/SEI-94-TR-13.


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Editors
ISCN LTD, ISCN GesmbH, Schieszstattgasse 4/24, 8010 Graz, and Coordination Office, Florence House, 1 Florence Villas, Bray, Ireland, office@iscn.at, office@iscn.com, office@iscn.ie, Editing Done: 19.7.2002