Appendices
Improving the delivery reliability and quality performance of a Make-To-Order SME
Danny Sprietsma
Email:
D.Sprietsma@student.rug.nlStudent number: S2005719
University of Groningen Faculty Economics and Business Master of Science Technology Management
Company: Ventura Systems B.V. Bolsward Company Supervisor: M. Bruinsma University Supervisor: Drs. Ing. H.L. Faber University Co-assessor: Prof. Dr. R.H. Teunter
August 2013
Final version
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Appendices
Appendix I: Improvements within Ventura Systems ... 3
Appendix II: Problem analysis... 4
Functional or Instrumental analysis ... 4
System definition... 5
Goal, Reality and Perception analysis ... 6
Appendix III: Literature study ... 7
Small to Medium Enterprises and Business Process Maturity ... 7
Strategy deployment, goal setting and performance measurement ... 9
Delivery reliability in the supply chain ... 11
Quality in the value chain ... 12
Appendix IV: Customer satisfaction research ... 13
Appendix V: Performance measurement recommendations ... 16
Appendix VI: PM development framework ... 17
Appendix VII: PM analysis Ventura Systems ... 18
Appendix VIII: Supplier delivery performance ... 21
Appendix IX: NCR form ... 23
Appendix X: NCR analysis ... 24
Appendix XI: Supplier development steps and possible pitfalls ... 26
Appendix XII: The main characteristics of a PMS ... 29
Appendix: XIII: Collection of performance measurements ... 30
Appendix: XIV: PMS-IRIS Methodology ... 32
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Appendix I: Improvements within Ventura Systems
4 weeks supplier lead time 1 day: printing PO’s1 day: Order picking3 days: Assembly1 day: Shipping
Suppliers Receiving products
Microsoft Dynamics Nav Order picking
Printing Production orders
Logistics AssemblyShipping
Customer Short term rescheduling
Log. & Prod. Supervisor
PurchasingSales Engineering Quality assurance 1
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4 2 7
1. Delivery reliability and quality from suppliers 2. Supplier management/development and tracking incoming goods 3. Production planning based on knowledge/skills 4. Limited information for order acceptance / due date setting 5. Transparency within the Engineering department (performance) 6. Quality control within the current process 7. Transparancy within the system and reactive fire-fighting mentality 6
7 7
Short term improvements Medium term improvements Long term improvements
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Appendix II: Problem analysis
Functional or Instrumental analysis
The original problem in a company can be related to the output of a system (functional) or related to the characteristics of the system itself (instrumental). From the perspective that the system itself is
“only” a method or tool to reach a certain goal, it would mean that the shortcomings of the system (instrumental problems) are not useful to use as a starting point of the diagnostic phase. However, the instrumental problems can lead to insightful information related to the output of the system (De Leeuw, 2002).
The original problems voiced by the initiators of the project are that the 97% delivery reliability and the 3% or less defects goals are not being met by Ventura Systems. This is a functional problem as described by management of Ventura Systems, as it focuses on the output of the total supply chain.
Strategic management has set these goals to gain a competitive edge on other suppliers and to be able to offer their products for their current prices. Strategic management knows these performance measurements are very important to the customers because of their years of experience and furthermore by customer satisfaction research, which will be discussed later on in this research.
After exploring the problem further by conducting preliminary interviews with the problem owners, it becomes clear that there are certain other problems which according to them could result in the output problem. These are instrumental problems which could be a cause of the original problem stated by the initiators. These are related to the performance measurements done by the company itself, the delivery reliability and quality measurements which will be discussed in a later stage.
Further analysis into the problem if it is a functional problem and related to the output of the system is done by the triptych of Haselhoff (Haselhoff, 1977). Haselhoff states that organisations must fulfil three assessment criteria, these are: be effective (hitting the goal), be efficient (shortest route possible), and keeping the employees motivated. Functional problems should therefore always be defined as problems related to the output of a system based on these three assessment criteria. By judging the system by these assessment criteria, it can be stated that the system, order acceptance till shipping of the products, can be seen as an ineffective system. This is because the goal that has been set by strategic management is not accomplished currently.
Not being able to realise the desired delivery reliability or quality is related to the output of the
system and related to effectiveness. The functional problem is therefore not being able to realise the
goals, which are a delivery reliability of 97% and the desired 3% or less defects.
5 System definition
The relevant system for this research is the entire process that has an influence on the delivery reliability and the quality of the door systems produced by Ventura Systems.
This process starts at the Sales department by accepting an order from the customer depending on what type of order, at the engineering department. The first process step that influences the delivery reliability is the delivery date that has been agreed on between the sales department and the customer, which is based on a certain quota for a period of time. When a customer is in need of an earlier delivery while a certain period’s quota is full, there will be a meeting between multiple departments of Ventura Systems (Sales, Purchasing, Production & Logistics) to see if it is possible to deliver in time. When the order has been accepted and a delivery date has been set by the sales department in cooperation with the customer, they release the customer order. This is a sign for the operational purchasing team to purchase all of the necessary goods to be able to produce the ordered door systems. During this process, the operational purchasing department will send a purchasing order and receive confirmation.
The next step is logistics i.e. the warehouse within Ventura Systems where the goods that have been ordered by the purchasing department will be received. All of the parts are expected to be delivered to Ventura Systems six days in advance of the production schedule which is the time when the order is released for production by the logistics department. Subsequently, when the order is released the order can be picked in the warehouse. Specific parts for an order are directly placed on an order picking cart after delivery to Ventura Systems, and other smaller parts which are in stock are picked for the order. While some other parts, i.e. screws etc. are in a Kanban system on the work floor.
If everything is going according to schedule, the order cart is delivered to the assembly line as planned and assembled in approximately three days. The last steps of the process of Ventura Systems are within Expedition. These steps are the preparation of the orders for shipping, planning the transportation and lastly, loading and shipping the products to the customer. The Quality Assurance activities are incorporated within multiple places of the entire chain.
The processes that lead to the unwanted output can be seen in figure 1.
Sales Administration
Expedition Production
Warehouse Logistics and warehouse
Sales
Tactical purchasing Engineering Operational purchasing
Suppliers
Quality complaint
Customer inquiry Non conformance
report
Pre-sales engineering
Supplier selection Formulate
proposal Order
Production engineering Release
customer order
Planning order based
on targets Making
purchaseorder Release
purchaseorder
Confirmation
Receiving goods
Billing
Customers
Intake / Store
Quality control
Goods in stock
Register and checking
invoice
Releasing production
order
Picking
goods Assembly
Organising transportation Preparing
for
shipping Loading and shipping
Figure 1: Process overview of Ventura
6 Goal, Reality and Perception analysis
It is necessary to give an answer whether the problem is a goal, reality or perception problem according to De Leeuw (2002). This is necessary to analyse whether the problem the organisation expresses to have is possible to research. It could be possible that the goal Ventura Systems has set is an impossible goal or a goal where costs would be way too high for it to be worth it. Or could the problem expressed by management be a perception problem? For example, is it really a problem that Ventura Systems cannot deliver 97% of their products on schedule to the customer or deliver products with 3% or less defects? Has the company received complaints or requests to do this? If it is neither a goal nor a perception problem, the problem can be seen as a reality, thus possible to research.
After talking with the initiators of the problem, the problem owners, it seems that there is a real problem within Ventura Systems. The goal that has been set by Ventura Systems has been set because of signs from the market and the need to differentiate themselves from other suppliers, mainly because of their prices. Furthermore, it has become clear according to recent measurements that the company can perform better than it is currently doing. The delivery reliability and quality has been higher in the past and the performance is varying over time. Ventura Systems is according to their customers doing fairly well when it comes to delivery reliability but receiving complaints from some customers related to the quality of their products. So there is certainly room for improvement.
So it can be seen as a reality problem.
However, it has also become clear that Ventura Systems is not entirely sure if their current measurement methods are right. This could mean that they are performing even worse than they think, or might be performing better than they think.
Their does seem to be a problem within Ventura Systems, however how critical this problem is will
be discussed during a later stage of the research, whether for example the goal that has been set is
realistic or not.
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Appendix III: Literature study
The first part of the literature study is focused on the difference between larger companies and SMEs and the maturity of a company to assess whether there are differences between the two and whether the maturity of a company needs to be taken into account. Moreover an analysis focused on the strategy deployment and performance measurements. Other subjects discussed are the delivery reliability and quality specifically and related possible causes according to literature.
Small to Medium Enterprises and Business Process Maturity
The research discussed in this report takes place in an SME context as described earlier. Therefore, during the research within Ventura Systems the fact that it is an SME should be kept in mind if there are differences between SMEs and larger companies, which can have an impact on realising performance improvements, strategy and so on. Furthermore, possible improvements suggested during the redesign might have to be designed with these possible differences in mind as well.
Theoretical research done by Hudson et al. (2001a) suggests that SMEs do have characteristics that differentiate them from larger companies. These have been generally described in different researches; a collection of these different characteristics of SMEs are listed below (Hudson et al., 2001a, p. 1105):
Personalised management, with little devolution of authority;
Severe resource limitations in terms of management and manpower, as well as finance;
Reliance on small number of customers, and operating in limited markets;
Flat, flexible structures;
High innovatory potential;
Reactive, fire-fighting mentality;
Informal, dynamic strategy
The significant differences that have been found between larger companies and SMEs indicate that it is necessary to keep these differences in mind according to Hudson et al. (2001a) while developing new processes or managing existing processes effectively. Different research by Wong and Aspinwall (2004) characterised SMEs in terms of Total Quality Management (TQM) aspects and their advantages and disadvantages compared to larger companies. What can be formulated as different characteristics compared to larger companies of which some of the different characteristics can have a positive influence on making improvements within the company, while other characteristics might make it harder to achieve improvements. The following has been described by Wong and Aspinwall (2004):
Ownership and management: High management visibility, closeness to point of delivery and easier to permeate new change initiatives (Yusof and Aspinwall, 2000a). However, owners might not delegate tasks but try to control every aspect of business, suppressing teamwork and involvement (Yusof, 2000). Management team frequently deals with day-to-day crises as discussed earlier by Hudson et al., (2001a).
Structure: A flat structure and short decision making process allows shorter and faster information flows, improving communication (Yusof and Aspinwall, 2000a).
Culture and behaviour: Its unified culture provides a good foundation for change, for
example, the adoption of TQM and the high incidence of innovativeness can nurture a
continuous improvement culture; reduced bureaucracy helps improve the chances of success
for new initiatives (Yusof and Aspinwall, 2000a). However, decisions are restricted by
financiers, customers, legislation and the organisation’s owners (Hudson, 2003; Hudson et al.,
2001b).
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Systems, processes and procedures: A low degree of specialisation results in having a broader perspective of issues and problems rather than narrow specialists’ functional views; better in providing improvement ideas (Yusof and Aspinwall, 2000a). However, improper and inadequate systems and procedures can affect efficiency and will result in dissatisfaction from employees (Yusof, 2000); SMEs are using less advanced manufacturing technologies than larger organisations (Kennedy and Hyland, 2003). Lack of financial resources which can affect investment in new products and processes (Yusof, 2000).
Human resources: Training and staff development being ad hoc and small scale can hinder the improvement effort (Yusof, 2000).
Customers and markets: Easily suppressed/dictated to by larger multinationals (if they are customers).
A study with entrepreneurs by Deakins and Freel (1998) discuss how companies in their early years grow very fast and then the growth levels off: It “has revealed that the learning process in SMEs is a crucial part of the evolution of SMEs. The entrepreneur, through experience, acquires the ability to learn. Rarely is this learning process planned; rather it is the result of a series of reactions to critical events in which the entrepreneur learns to process information,. Adjust strategy and take decisions (Deakins and Freel, 1998, p.146). The study revealed that strategic development and change occurred more by learning and as a reaction to critical events. Other relevant literature discusses the Business Process Maturity (BPM) of companies.
Literature related to BPM models, describe how companies can improve their strategy realisation (i.e. deployment). One of these models by Persse (2001) has a level in line with the research by Hudson et al. (2001a) who mentions reactive fire-fighting behaviour as a characteristic within SMEs.
This level is called the Initial stage: “there is fire-fighting management. Success depends on the competence and heroics of individuals and not on the use of proven processes” (Weber et al. 2008;
cited by Röglinger et al. 2012). The Capability Maturity Model by Persse (2001) is shown in figure 2 displayed below:
The Capability Maturity Model displays different stages of BPM; according to literature companies should strive to achieve the highest level of maturity. As McCormack et al. (2009) states “Higher process maturity in any business process result in:
Better control of results;
Improved forecasting of goals, costs, and performance;
Greater effectiveness in reaching defined goals;
Improving managements’ ability to propose new and higher targets for performance”
Figure 2: Capability Maturity Model (Persse, 2001)
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Strategy deployment, goal setting and performance measurement
According to Neely et al. (1997) traditional performance measures are used to analyse whether certain actions are efficient and effective. Flapper et al. (1996) for example, state that: “A good manager keeps track of the performance of the system he or she is responsible for by means of performance measurement. His/her staff carrying responsibility for certain activities within the system, need performance measurement to see how well they are performing their tasks. This also holds for the employees actually executing the various process steps. So performance indicators are important for everyone inside an organisation, as they tell what has to be measured and what are the control limits the actual performance should be within.” The performance within Ventura Systems is in this research an important aspect in relation to the strategy and the goals that have been set by management. Since these different aspects are all interrelated, the literature will be reviewed to view what is important regarding these three.
When it comes to customer requirements, effectiveness is how well customer requirements are met by a company, and the efficiency how the resources are used to meet the desired customer satisfaction by a company. In order to quantify these two, performance measurements are chosen, implemented and monitored within companies. Several researches state (Fortuin, 1988; Neely et al., 1997) that performance measures are the metrics that should be used to quantify efficiency and/or effectiveness of actions within a process (or parts of the process) or of an entire system in relation to the goals. Performance measures should capture the most important aspects i.e. Critical Success Factors (CSF) within a company, the essence of a company to be able to exist/survive (Gunasekaran et al., 2004).
Authors like Lynch and Cross (1991), Dixon et al. (1990), Kaplan and Norton (1992, 1996) also emphasise the link between performance measurements and the strategy of a company. In order to realise a strategy, certain key performance indicators (KPI) should be in place regarding the aspects the company wants or thinks they need to excel at, which can be seen as Critical Success Factors (CSF). Furthermore the way a measure is designed according to Globerson (1985) is also related to specific, stretching, but achievable goals (targets). Performance measures are essential for strategic planning, strategic control cycles (Neely et al., 1997), evaluating strategy (Globerson 1985) and evaluating whether certain objectives have been met (Goold and Quinn, 1990).
Not only should performance measures be linked to strategy, it should be linked to all hierarchical levels of the organisation, i.e. Strategic, Tactical and Operational (Braz et al., 2011). Furthermore, performance measurements can be linked to the decision-making processes and provide control over the lowest levels of the company (Gunasekaran et al., 2004).
Feedback Measurement Frequency
(Short term plans) Organization
Mission/Vision
Stakeholder requirements
Requirement and Capability
Identify Critical Success Factors
(CSFs)
Define Key Performance Indicators (KPIs)
Performance Management and
Appraisal
Develop Responsibility
Action Plans:
Reward and Recognise Performance
Measure Performance vs
KPIs
Implement Action Plans
Feedback (Long term plans)
Figure 3: Strategy development and goal deployment (Chang, 2006)
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A framework for strategy deployment and goal deployment has been developed by Chang (2006) which can be seen in figure 3. Key steps for strategy development are shown; Chang (2006) summarized the following steps:
1. An organisation mission statement based on recognizing the needs of all organisation stakeholders.
2. Identification of Critical Success Factors (CSF) for the achievement of the organisation’s requirements and capabilities.
3. Definition of performance measures for each Key Performance Indicator (KPI), including:
sources of data and methods used for analysis, measurement process and frequency, targets for customer requirements and competitor performance.
4. Development of (and assignment of responsibility for) action plans at the organisational level for achievement of desired performance against KPI targets.
5. Measurement of performance against organisational KPIs, and comparison with targets.
Communicate performance and proposed actions throughout the organisation.
6. Reward and recognize superior organisational performance.
Part of the mission of Ventura Systems is as stated before “to become the best door systems manufacturer in the eyes of the customer”, the strategy to accomplish this within Ventura Systems is by excelling at other aspects instead of price. Therefore, carrying a higher price compared to other competitors has to be justified in terms of for example quality. How this should be done is by first assessing Critical Success Factors (e.g. excelling at quality and delivery reliability), followed by Key Performance Indicators to monitor this over the whole organisation. The strategic alignment pyramid gives a short overview, see figure 4.
Figure 4: Strategic Alignment Pyramid (Bauer, 2004)
11 Delivery reliability in the supply chain
In order to identify possible causes of low delivery reliability literature is analysed based on this subject. Jahnukainen et al. (1999) discuss the need to pay attention to the total performance of the supply chain. According to Jahnukainen et al. (1999) most of the problems of MTO supply chains exists between the different parts of the chain. Streamlining the different operations by linking them in processes should therefore help. Common problems according to Jahnukainen et al. (1999) can be seen in figure 5.
Figure 5: The problems of the delivery process (originally from Luhtala et al., 1994 adopted by Jahnukainen et al., 1999)
Others discuss the importance of Production Planning and Control (PPC) decisions within MTO companies as seen in the overview in figure 6, by Land and Gaalman (1996), the different input and output controls. The process of order acceptance and delivery date promising is the first input control followed by order release and priority dispatching. Output control is usually in the form of capacity changes during the main processes to realize the orders. Soepenberg et al. (2012) have, in relation to these control decisions, made a distinction between the processes underlying the delivery reliability performance. The relevant processes are the process of promising the delivery time and the realisation process. The last one can be sub-divided into pre-shop floor processes and shop-floor processes.
Figure 6: Input and output control decisions by Land and Gaalman (1996)
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In short; the starting point that can be the reason why delivery reliability performance cannot be achieved according to literature, is the first decision making process within the supply chain. This is the order acceptance and delivery date setting stage which could be the cause by setting wrong or unreliable delivery dates mainly because of the lack of relevant information. Furthermore, the pre- shop floor process could be the cause, for example complications during product design due to lack of information etc., the purchasing department or head of production and logistics due to incorrect planning. Another option could be mistakes or delays during the realisation process itself, in Ventura Systems their case Logistics and Production or the suppliers. Missing or non-conform parts can be seen as a factor of Logistics and Production, especially in an assembly process, where the procurement of parts is a very important aspect.
Quality in the value chain
More literature has been analysed in order to identify possible causes of insufficient quality leading to Non-Conformity Reports (NCRs). Because NCRs can also be caused by complaints from the customer it is important to discuss the term quality. Customers complain when a certain product does not have the desired quality, raising the question how customers perceive quality. Quality can be defined in several ways, Reeves and Bednar (1994) have found several definitions, and some of these definitions are:
Quality is excellence (Pirsig, 1992; p.73);
Quality is value; “When price tags are attached to ideas or services or products, it is the best bargain that wins.” (Abbott, 1955; p.108);
Quality is Conformance to Specifications (Juran, 1974);
Quality is Meeting and/or Exceeding Customers' Expectations (Buzzell & Gale, 1987).
Each of these definitions describes a different view or use of the term quality. These different terms of quality show that quality can be interpreted in different ways and that meeting the desired quality of a customer depends on their expectations. Whether a customer decides to file a complaint therefore also depends on their definition of quality. An important part of quality within Ventura Systems is therefore knowledge of how a customer perceives their product and which aspects of a door system require extra attention.
Some researchers have placed the causes of quality in different categories, for example the categories by Rooney and Hopen (2005, p.17), 4M and PIE: Machinery, Methods, Materials, Measurements, People, Information and Environment. Since some of these categories are almost non-existent within an assembly process with a lot of manual labour, which is the case at Ventura Systems (i.e. no complex machines), a different approach to categorize quality can be taken. The causes of insufficient quality due to processing steps within the assembly are not that complex to locate, it is more valuable in this case to locate where these issues are caused the most in the value chain.
A useful approach is therefore quality in relation to the value chain as described by De Toni et al.
(1995):
Inbound quality
o Vendor quality performance
Internal quality
o Product design quality o Process engineering quality o Manufacturing quality
Outbound quality
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Appendix IV: Customer satisfaction research
Source: Customer satisfaction research by B. De Nooijer, Ventura Systems (April, 2012)
1 Kennis
Hoe beoordeelt U:
1.1 De branchekennis van Ventura Systems van uw bedrijfstak?
1.2 Vaktechnische kennis van Ventura Systems?
1.3 Het innovatief vermogen van Ventura Systems?
1.4 Het kennisniveau van Ventura Systems ten opzichte van de concurrentie?
2 Prijs
Hoe beoordeelt U:
2.1 De prijs kwaliteitverhouding die Ventura Systems levert?
2.2 De helderheid van prijsstelling die Ventura Systems hanteert?
2.3 De helderheid en juistheid van facturering van Ventura Systems?
2.4 Het prijsniveau van Ventura Systems ten opzichte van de concurrentie?
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3 Communicatie
Hoe beoordeelt U:
3.1 De duidelijkheid met betrekking de tot functies van uw verschillende aanspreekpunten binnen Ventura Systems?
3.2 De communicatie en betrouwbaarheid van uw contactpersonen met betrekking tot het nakomen van gemaakte afspraken?
3.3 De responstijden van Ventura Systems?
3.4 De communicatie met Ventura ten opzichte van de concurrentie?
4 Dienstverlening Hoe beoordeelt U:
4.1 De mate waarin de dienstverlening voldoet aan uw verwachtingen?
4.2 De mate waarin u zich als klant gewaardeerd voelt door Ventura?
4.3 De acceptatie door Ventura Systems van door u gedane suggesties en adviezen?
4.4 De kwaliteit van de dienstverlening van Ventura Systems ten opzichte van de concurrentie?
15 5 Kwaliteit
Hoe beoordeelt U:
5.1 De kwaliteit van de producten van Ventura Systems?
5.2 De duurzaamheid en de storingsgevoeligheid van de producten van Ventura Systems?
5.3 Het installeren van de producten van de Ventura Systems?
5.4 De kwaliteit van de producten van Ventura Systems ten opzichte van de concurrentie?
6 Algemeen
Hoe beoordeelt U:
6.1 De leverbetrouwbaarheid van Ventura Systems?
6.2 De klantgerichtheid van Ventura Systems?
6.3 De toegevoegde waarde van Ventura Systems voor uw organisatie?
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Appendix V: Performance measurement recommendations
(Neely et al., 1997, P.1137)
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Appendix VI: PM development framework
(Neely et al., 1997, P.1151)
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Appendix VII: PM analysis Ventura Systems Review of the current delivery performance measurement
1. Title: Delivery reliability
2. Purpose: To enable Ventura Systems to track their performance of delivery
reliability and track improvements.
3. Relates to: Business objective: “Becoming the best supplier of door systems in the eyes of the customer, by being reliable and delivering high quality goods”. By achieving 99% delivery reliability and 1% quality defects.
4. Target: Delivering 99% of the orders as promised.
5.
Formula:
6. Frequency of measure: Weekly
7. Frequency of review: Weekly
8. Who measures? Operational director
9. Source of data: Data from the Sales and Service departments in the ERP system. The Sales and Service departments assess if the order has been delivered in time according to the first promised delivery date, if this is not the case they will determine who or what caused it. Either the customer or Ventura, and for the latter which department caused it.
10. Who owns the measure? Operational director
11. What do they do? Operational director analyses all of the collected data from a certain period by using a tool implemented in the ERP system.
12. Who acts on the data? Operational director
13. What do they do? The Operational director gives feedback by reporting the overall performance of the company during a certain period to motivate
people to improve.
Notes and comments:
As discussed by Neely et al. (1997) the title should be clear and so should the purpose be,
furthermore the measure needs to relate to the business objective. These elements of the delivery
reliability measure are in line with literature. The fourth element however, the target should include
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a time scale according to Neely et al. (1997) to achieve the explicit target and the target should be based on competitors. The fifth element, the formula, is described as being the most challenging one. This seems to be the case for Ventura Systems as well, which is also related to the source of the data. The Sales or Service department can in this case for example promise long delivery dates to be on the safe side. Furthermore, the Sales or Service department can manipulate data by not assigning the right or any reason code (1, 2 or none) simply to avoid conflict with the responsible party. The frequency of the measure is weekly, which can be valuable to motivate people by showing the overall performance. But this requires that all of the data has been filled for each of these orders for this week because of the limited amount of orders. Furthermore, the current way of data gathering and analysis does not provide an accurate analysis to gain more detailed information related to performance or reasons of late delivery because the company does not deliver many orders each week. The most important element is what action is taken based on the performance that has been analysed: “…because it makes explicit the fact that unless the management loop is closed, there is no point in having the measure” (Neely et al. 1997). Within Ventura, the overall performance is shown on a weekly basis on a board for everyone to motivate their employees.
Review of the current quality performance measure
1. Title: Quality
2. Purpose: To enable Ventura to track their performance of quality
and track improvements.
3. Relates to: Business objective: “Becoming the best supplier of door systems in the eyes of the customer, by being reliable and delivering high quality goods”. By achieving 99% delivery reliability and 1% quality defects.
4. Target: Only receive 1% quality complaints.
5. Formula: Quality = (Internal & supplier quality + Customer complaints)/ 2
6. Frequency of measure: Monthly
7. Frequency of review: Monthly
8. Who measures? Head of quality assurance
9. Source of data: The data is collected by quality assurance by entering all of the
received NCRs into an excel file.
20 10. Who owns the measure? Head of quality assurance
11. What do they do? Head of quality assurance analyses collected data from a certain period to assess the overall quality performance.
12. Who acts on the data? Head of quality assurance
13. What do they do? Head of quality provides a monthly dashboard by reporting the overall performance of the company during a certain period to motivate and make people aware of the current quality within the
company with the goal to improve.
Notes and comments:
The first three elements are simple to understand and logical in relation to the business objective.
However, the fourth one, just like the delivery reliability measure does not include a time scale and therefore it will be unclear of the company is improving fast enough to keep up with competitors.
The fifth element for the quality measure, the formula, is the biggest issue here. The global quality performance measure basically consists out of different formulas. Internal and external quality combined together and divided by two to get an overall percentage of quality within Ventura Systems. The internal quality and supplier formula is based on written and open NCRs caused or reported internally. The amount of these NCRs is divided by the amount of purchase orders. Dividing it by the amount of purchase orders can cause a distorted view on the internal quality. Not only because of varying amounts of parts that can be bought as one purchase order, but also because purchase orders are made for service and production orders, which means that the suppliers can cause it to be really low while it seems that both cause low quality. The other measurement, the quality based on customer complaints generates a distorted view because of the amount of door systems sold that are used. Customer complaints are received as NCRs after products have been delivered to the customer. So it is possible that NCRs from customers are received weeks after a door system has been produced. When there are a lot of NCRs coming in during a month where production is very low, from last month or even earlier when production was running on full capacity, the measurement will not be reliable at all.
Another issue with the quality measure is the source of data. The source of data for quality is the NCRs written internally and received by customers. It is possible to set strict rules or classifications when to write an NCR for internal or supplier non conformities. However, the customer can have illegitimate claims or have caused some quality defects themselves. When an NCR is accepted or should be rejected is hard to determine, which makes it less easy to control.
Last important part of the quality performance measure is what is done with the quality
measurements. Head of quality owns the measure and should act on the measure. The current
performance measure is mainly used to report to employees within the company how the global
quality performance is to motivate and create awareness amongst the employees. Recurring
problems are solved by the quality assurance department.
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Appendix VIII: Supplier delivery performance
Supplier delivery performance of production orders 2012 (O-orders)
Requested date <
Total Delivered on desired day? Delivered on promised day? min. Start data Arrival for order
Days delivered late Orders Desired 1+ day 4+ days Promised 1+ day 4+ days True Untrue and same day On time Later % 3 days left Metaal 2000 BV 13371 38,4% 61,6% 21,1% 39,1% 60,9% 19,6% 87,0% 8,0% 96,3% 90,0% 10,02% 5,75%
Aludex bv 7402 63,5% 36,5% 2,5% 62,8% 37,2% 0,9% 90,3% 9,7% 98,2% 96,8% 3,24% 1,92%
Essit Assemblage 5803 70,8% 29,2% 4,5% 71,8% 28,2% 3,1% 89,4% 10,6% 98,7% 96,0% 3,96% 2,41%
Aluprof Processing B.V. 4897 5,8% 94,2% 8,8% 12,4% 87,6% 1,7% 92,1% 7,9% 97,4% 89,7% 10,31% 6,37%
Droste Bejah bv 3309 35,1% 64,9% 4,4% 39,1% 60,9% 1,0% 81,5% 18,5% 93,8% 90,8% 9,25% 2,81%
Segla 3010 38,0% 62,0% 4,1% 38,2% 61,8% 3,1% 88,1% 11,9% 97,6% 93,4% 6,64% 3,02%
Gogo Metaal B.V. 2345 21,7% 78,3% 2,3% 21,9% 78,1% 1,7% 93,2% 6,8% 96,2% 95,4% 4,56% 3,58%
Gummi-Welz GmbH 1722 18,4% 81,6% 25,1% 20,7% 79,3% 22,2% 88,9% 11,1% 94,4% 93,4% 6,56% 5,69%
Metaalplus BV 1746 36,8% 63,2% 22,5% 36,9% 63,1% 22,3% 65,4% 34,6% 83,8% 72,7% 27,26% 16,61%
HPR Techniek 1043 78,4% 21,6% 0,4% 75,4% 24,6% 0,0% 90,0% 10,0% 98,8% 96,9% 3,07% 0,96%
VDM B.V. 832 63,7% 36,3% 7,9% 63,7% 36,3% 4,7% 87,5% 12,5% 92,4% 91,8% 8,17% 4,93%
VDL Postma bv 744 44,5% 55,5% 6,6% 44,8% 55,2% 5,6% 90,3% 9,7% 96,8% 92,2% 7,80% 3,90%
SMI Plaatwerk BV 800 42,5% 57,5% 20,6% 47,4% 52,6% 19,0% 75,6% 24,4% 96,5% 89,5% 10,50% 7,88%
Captron Electronic GmbH 537 91,6% 8,4% 5,4% 93,3% 6,7% 3,0% 95,0% 5,0% 99,4% 98,3% 1,68% 1,68%
Parker 286 78,0% 22,0% 3,5% 82,9% 17,1% 1,4% 94,1% 5,9% 97,2% 94,8% 5,24% 3,50%
National Gummi 249 77,5% 22,5% 6,0% 79,1% 20,9% 2,0% 88,4% 11,6% 89,2% 86,7% 13,25% 4,42%
Betech Kunststoffen bv 193 69,4% 30,6% 16,1% 63,2% 36,8% 22,3% 86,0% 14,0% 98,4% 87,6% 12,44% 11,92%
Camozzi Benelux B.V. 190 76,3% 23,7% 1,1% 76,8% 23,2% 0,5% 95,3% 4,7% 97,4% 96,3% 3,68% 1,58%
MNAC Electricm. Industrial Lda 113 77,0% 23,0% 4,4% 77,9% 22,1% 3,5% 92,0% 8,0% 96,5% 95,6% 4,42% 3,54%
EAO Benelux bv 111 82,9% 17,1% 11,7% 91,9% 8,1% 4,5% 77,5% 22,5% 94,6% 91,9% 8,11% 4,50%
Total # orders and percentage 48872 43,8% 55,9% 10,7% 45,1% 54,6% 8,6% 87,4% 10,9% 96,0% 91,8% 7,90% 4,56%
