An activity decomposition methodology with theoretical foundation in the principles of activity control and stated focus of interest in the enterprise value-chain is presented. Characteristics of inputs and outputs are discussed, where a set of non-transformable inputs are defined and motivated. An integrated partial efficiency measure is formulated, compensating for some weaknesses of the Debreu-Farrell technical efficiency concept. Providing a coherent basis for productivity analysis, the IPE approach poses an alternative to e.g. DEA especially in the case of multi-level systems and sparse data. The method is easily communicable in terms of measurement and analysis, and may be extended to complement economic performance assessments and benchmarks.
A multi-criteria formulation for continuous and discrete-time dynamic systems is presented. The fundamental problem in the design of dynamic systems is the trade-off between response speed (e.g., the time to reach final value and the raise time) and response smoothness (e.g., the overshoot, the undershoot, and the transient dampening). Separate optimisation of criteria is impossible, thus the problem is inherently multiobjective. In a general dynamic system, this is accomplished by adjusting a number of technical parameters in accordance with some ad hoc practice. Previous multi-criteria approaches have been modelled as weighted sums of criteria, with shortcomings in terms of sensitivity analysis and preference articulation. The proposed framework enables the decision maker to design a most preferred system, with full knowledge of local trade-off ratios in terms of chosen criteria. Combining analytical techniques with simulation, the formulation makes the optimisation process transparent to the decision maker, working entirely in decision space. The framework is demonstrated on a dynamic production-inventory model.
Olika aspekter på samverkan har rönt stor uppmärksamhet under de senaste årtiondena men har endast i begränsad omfattning integrerats med centrala produktions- och logistikstrategiska beslutskategorier. Ett område som till stor del varit frånvarande i forskningen om kund/leverantörssamverkan är kopplingen till olika grader av kundorderstyrning. Sedan länge har graden av kundorderstyrning ansetts som ytterst central i utformningen av strategier för produktions- och logistiksystem men har trots detta sällan inkluderats i olika modeller för val av grad av samverkan mellan företag. Denna brist på samordning av två så viktiga kunskapsdomäner innebär att avgörande pusselbitar troligen saknas i kunskapen om hur konkurrenskraftig industriell verksamhet bedrivs i samverkan. Dessa två perspektiv har stor påverkan på utformning av både produkter och logistiksystem. Om man dessutom beaktar den snabba förändringstakten på dagens marknader och den dynamik som då skapas så finns det mycket starka motiv för att säkerställa att rätt grad av samverkan med andra parter i försörjningsnätverket etableras för att kunna hantera de osäkerheter som finns om marknadens behov.
Customization and customer-driven manufacturing are both explicitly based on end-customer relations and customer requirements. The impact of these aspects on internal operations is relatively well known and can be investigated using time phasing and decoupling points. These tools are however rarely used for analyzing purchased material. Based on the time phased product structure, items are categorized according to three criteria: driver, uniqueness, and make/buy. Purchased items can thus be identified using the last criteria and then driver and uniqueness are used as a point of departure for categorizing purchased material. The approach hence provides a platform for development of supplier relations based on the customer requirements which is the core theme of the method for customer-driven purchasing.
Under forskningsprojektet KOPeration visade sig grad av kundanpassning vara en viktig egenskap att beakta vid utformningen av lämplig grad av samverkan i leverantörsrelationen. Projektet omfattar sex svenska tillverkande företag från olika branscher och är inriktat på kundorderstyrning och leverantörsrelationer.
Projektet var inledningsvis inriktat på att undersöka i vilken utsträckning som kundorder är verksamhetsdrivande och hur det påverkar leverantörsrelationer. Under projektet visade det sig dock att ytterligare en komplicerande faktor i leverantörsrelationer identifierats, nämligen brist på överensstämmelse mellan det tillverkande företagets perspektiv och leverantörens perspektiv på grad av kundanpassning av en viss produkt. Inom ett företag finns en logisk sekvens av kundanpassningsgrad från standardartiklar, via kundunika artiklar till kundorderunika artiklar. Denna logiska sekvens gäller dock bara inom ett företag. En artikel som av leverantören uppfattas som kundunik kan ingå i standardsortimentet hos kunden, eller tvärt om, vilket kräver en mer nyanserad analys.
Denna brist på överensstämmelse mellan kundens och leverantörens syn på kundanpassningsgrad är viktig att identifiera eftersom spekulationsrisken i försörjningskedjan då kan fördelas på ett bättre sätt. Det innebär en låg risk att tillverka och lagerhålla standardartiklar på spekulation (mot prognos, innan en kundorder har mottagits), medan tillverkning och lagerhållning av kundunika, eller till och med kundorderunika, produkter innebär en hög risk om det utförs på spekulation. Mycket talar därför för att den aktör som upplever den lägsta graden av kundanpassning bör lagerhålla produkter när det finns olika uppfattning av grad av unikhet.
I detta papper definieras teorigapet gällande brist på överenstämmelse av kundens och leverantörens perspektiv på grad av kundanpassning. Därefter belyses det praktiska problemet, dvs. vikten av att identifiera situationer med ett ”ologiskt” flöde av kundanpassningsgrad. Potentiella fördelar med att vara medveten om dessa ”ologiska” flöden exemplifieras med hjälp av en fallstudie hos Parker Hannifin i Trollhättan.
Purpose
The purpose of the paper is to describe ambidextrous learning in organizations within the customer order-based context (COBC), here based on a dynamic view of work processes. The study focuses on how organizations can learn while working with customer orders, considering learning in organizations as both a process and an outcome.
Design/methodology/approach
This conceptual article focuses on learning in the COBC, where the individual customer requirements represent a key input into the organization’s work processes, thus limiting the possibilities to plan and standardize. The COBC brings about challenges and potentials for learning in organizations where task variety and complexity are high and in which the contradictory interplay between efficiency and responsiveness is apparent not only at a strategic level but also at an operative level in the customer order fulfillment processes. Depending on the variations in tasks and parallel complex work processes between different units in the organization, the ambidextrous learning dynamic can appear in the COBC.
Findings
Five propositions were made from the analysis: Proposition 1: Learning in the COBC can occur both in real-time but also in retrospect and with sporadic and recurrent interventions. Proposition 2: Learning in the COBC can occur for, as well as from, customer order processes. Proposition 3: Learning in the COBC varies and will depend on the delivery strategy. Proposition 4: Learning can be stimulated by the variation in priorities among customer orders in the COBC because the work characteristics for the back office and front office differ between customer order fulfillment processes. Proposition 5: Learning in the COBC can occur both within the back office and front office but also between these organizational units. The paper discusses the importance of building learning infrastructure in COBC and how that can be supported by a suggested learning office.
Originality/value
The present study demonstrates the importance of functions being able to act both as back office and front office in relation to delivery strategy. It also shows the ambidextrous learning process for the sake of improving both the internal efficiency and external effectiveness across the organization.
The human perspective and the flow perspective of businesses represent two areas of competence that study similar systems but with different frame of references. The human perspective involves ambidextrous learning that concerns how knowledge is developed and used for different purposes by individuals or groups of individuals. The development of knowledge for new situations is referred to as ‘exploration’, while ‘exploitation’ refers to execution in known and stable contexts. Furthermore, decoupling thinking is important from a flow perspective and concerns how a value-delivery package is created. This type of thinking decouples the flow perspective into segments with different characteristics that are significant for process management. The examples presented in this paper are distinctive drivers of flow in terms of speculation or commitment, and the level of customisation. By combining these two perspectives, a set of 15 scenarios is identified for further research on ambidextrous learning in a decoupling thinking context.
In this article we model standard inventory ordering rules in terms of control systems theory. A differential equation is designed describing the development of a system in which an input signal reaching a predefined level triggers an output. The reorder point of inventory control systems may be interpreted as such a level triggering a replenishment. Systems using this kind of control are frequent in a variety of applications. Apart from inventory, domestic heat and pressure control are but two examples.
The view on safety buffers is fragmented in the current literature; some researchers argue that a safety buffer is only waste, while others see them as prerequisites to absorb variations and secure a competitive delivery capability. This study conceptualises various safety buffer types in terms of materials, capacity and lead time to mitigate the negative effects of short-term stochastic variations in supply and demand. The identified safety buffers are categorised based on a material flow perspective as inbound, process and outbound buffers. In total, seven safety buffer sub-types are identified and investigated in terms of their utilization in four manufacturing companies. The experiences from eleven respondents highlight the utilization purposes in their selection of safety buffers. The empirical investigation also indicates several concerns through four propositions that highlight the significance of decision support, providing a more holistic perspective on different types and sub-types of safety buffers and their application in practice. Finally, a conceptual framework is proposed to facilitate the selection of safety buffers in practice.
Metodstödet för kapacitetsdimensionering är i dagsläget svagt, trots att det är en viktig utmaning i de flesta typer av verksamheter. Hur en kapacitetsnivå ska fastställas kommer in i flera sammanhang såsom tillverka-/köpabeslut, maskin-investering, planering och styrning samt bemanning. Denna studie är utformad för att skapa en bättre förståelse för hur industriella verksamheter arbetar med kapacitetsdimensionering i dagsläget, samt vilka faktorer och utmaningar som påverkar och är centrala i beslutsprocessen. Det har visat sig att kapacitetsdimensioneringen har interna såväl som externa påverkansfaktorer och utmaningar. I denna studie identifieras budget, investeringskostnader, konkurrensförmåga, ledningsbeslut samt grad av komplexitet och integration i försörjningskedjan som centrala påverkansfaktorer. Vidare identifieras prognoser, kommunikation, suboptimering samt bristande systemsupport i beslutsfattandet som utmaningar i beslutsprocessen.
Systematic and stochastic variations, both endogenous and exogenous to companies, are a constant challenge for decision makers struggling to maintain a competitive advantage for the business. In response the decision maker introduces buffers to absorb variations but this does not target the source of the problem. The first step should instead be to focus on how to reduce variations and then to handle the remnant variations. In summary the first step should be to perform variation management and then as the second step buffer management should be applied. The combination of these two subprocesses represent service performance management and within this context is buffer dimensioning a key challenge. Input data, decision maker and process logic are identified as three key aspects of buffer dimensioning which are integrated and resulting in six scenarios. These scenarios unravel different conditions for performing buffer dimensioning and facilitate an awareness of a match or mismatch between current and desired situation.
Buffer management is not of a great concern when there is a perfect match between demand and supply. Demand represents the requirement for resources, and supply represents the collective capability of the resources to fulfill the requirements. A perfect match would then represent that supply can fulfill demand without any buffers involved, such as materials prepared in advance or capacity not being fully loaded. Such a perfect match is usually not possible to achieve since demand is frequently difficult to predict and the agility of the supply is limited. As a consequence, supply cannot perfectly match demand which may result in insufficient delivery performance. Different types of buffers may be employed to improve performance but they should only be used when the contribution of a buffer is greater than the cost of it. Hence, management of buffers is an important part of manufacturing planning and control (MPC) in order to mitigate such imbalances in pursuit of a competitive supply. The purpose here is therefore to define a framework for MPC that reflects the significance of buffers. To actually establish competitive supply is a complex challenge and four management perspectives are identified to support the balancing of supply with demand. Buffer management is here defined based on the intersection of these four management perspectives related to the transformation flow: the resources employed in the flow, the risk involved in the flow, the decision making related to the flow, and finally the planning and control to balance the flow.
Customization in different flavors have been identified as an important differentiator if low-cost competitiveness is not viable. To provide a customer unique solution is however not the same as providing a solution that is designed and individualized for a particular delivery to a customer. These two cases are illustrations of how customer requirements may be fulfilled differently depending on the match between stated requirements and the solution offered. The range of solutions that can be offered is represented by a solution space consisting of either predefined or postdefined solutions. Predefined refers to solutions that are defined before commitment to a customer and postdefined refers to solutions that are defined after commitment to a customer. Both cases are constrained by a boundary of possible solutions but the postdefined solutions provide opportunities for bounded innovation beyond what the predefined solutions can provide. Combining the properties of the different solution spaces provides not only an operational definition of customization but also supports in identifying strategic opportunities for extending the solutions and types of customizations a business provides.
Användning av planerade ledtider är en förutsättning för att effektivt kunna styra materialflöden och kapacitetsutnyttjande. I tillverkande företag krävs de exempelvis för att med hjälp av ledtidsförskjutningar beräkna starttidpunkter för tillverkningsorder från önskade färdigtidpunkter. Detta är exempelvis fallet vid användning av materialbehovsplanering och för bestämning av beställningspunkter i beställningspunktssystem. Planerade ledtider krävs också för att kunna använda fasta leveranstider vid tillverkning mot kundorder. Av de komponenter som ledtider består av anses kötiden vara den mest svårbestämbara och dessutom den som ofta utgör den största delen av ledtiden. De i företag vanligaste sätten att bestämma planerade ledtider är att antingen direktuppskatta den totala ledtiden baserat på erfarenhet eller att uppskatta var och en av de ingående komponenterna, exempelvis kötiderna, och sedan addera dem till en total ledtid. Det finns ett antal nackdelar med detta tillvägagångssätt, bland andra att kötiderna inte blir en funktion av kötidspåverkande faktorer som önskad utnyttjningsgrad och variationer i tider mellan ankomster och i operationstider. I en behovsstyrd planeringsmiljö där utgångspunkten är att kunna leverera när behov av att fylla på lager uppstår eller kund önskar få levererat inträffar önskade färdigtidpunkter slumpmässigt över tid. Via ledtidsförskjutningen inträffar följaktligen även planerade starttidpunkter slumpmässigt. Dessa starttidpunkter kan därmed betraktas som slumpmässiga ankomster av tillverkningsorder. Det ligger då nära tillhands att använda ett köteoretiskt angreppssätt för att beräkna kötider som ett alternativ till att basera dem på erfarenhetsuppskattningar. Vid tillämpning av köteoretiska beräkningsmodeller i det här sammanhanget föreligger två principiella problem som måste hanteras för att kunna åstadkomma trovärdiga resultat. Det ena problemet gäller de antaganden om exponentialfördelade ankomsttider mellan order och exponentialfördelade operationstider som förekommer i traditionella köteoretiska modeller. För att få någorlunda realistiska beräkningar behöver dessa beräkningsmodeller anpassas så att de bygger på mer realistiska och i praktiken förekommande fördelningar. Det andra problemet är att de kötider som beräknas med de teoretiska modellerna är medelkötider. Kötider är stokastiska variabler vilket innebär att kötiderna för enskilda tillverkningsorder varierar och som konsekvens att vissa order levereras för tidigt medan andra kommer att bli leveransförsenade och därmed påverka servicenivån, exempelvis i form andel order som kan levereras i tid. En modell för att beräkna kötider i den kontext det är fråga om här, måste följaktligen inte endast beakta önskade utnyttjningsgrader utan även kunna ta hänsyn till önskade servicenivåer. I den här studien har en sådan beräkningsmodell utvecklats. Modellens användbarhet och tillförlitlighet har också testats med hjälp av simulering.
Alla tillverkande företag i försörjningskedjor är utsatta för variationer av olika slag. Det kan vara fråga om variationer i efterfrågan på produkter, variationer i tillgång på kapacitet i de värdeförädlande processerna och variationer i tillgång på material att förädla. Sådana variationer påverkar effektiviteten negativt, både i materialflöden och i kapacitetsutnyttjande, och bör genom olika typer av åtgärder reduceras så längt som det är ekonomiskt försvarbart. De variationer som återstår och som inte kan reduceras ytterligare bör istället absorberas med hjälp av olika slag av säkerhetsbuffertar. Det kan exempelvis vara frågan om materialbuffertar av typ säkerhetslager, kapacitetsbuffertar av typ säkerhetskapacitet och tidsbuffertar av typ kötider och säkerhetsledtider.
Storleken på de olika buffertar som används påverkar både intäkter, kostnader och kapitalbindning. De måste därför positioneras i flödet och dimensioneras så effektivt som möjligt. Buffertar kan dimensioneras baserat på erfarenhetsmässiga bedömningar alternativt med hjälp av olika beräkningsmetoder. Med bedömningsmetoder måste buffertstorlekarna sättas på detaljerad nivå och det är i huvudsak endast personal som är involverad i den detaljerade operativa verksamheten som har rimliga förutsättningar att göra bra värderingar och fatta beslut. Det kan innebära att beslut som påverkar så för företaget avgörande framgångsfaktorer som leveransförmåga, kapacitetsutnyttjande och kapitalbindning till stor del måste fattas av enskilda medarbetare på ”golvnivå”.
Med beräkningsmetoder blir buffertstorlekar en funktion av en beslutsparameter och indata på en eller flera buffertstorlekspåverkande variabler. De möjliggör att dimensionering i större utsträckning kan göras på en mer grupperad nivå och med mer managementbaserade beslut. Med beräkningsmetoder kommer dessutom buffertstorlekar att kunna relateras till faktorer som påverkar hur stora de bör vara, exempelvis att efterfrågevariationer påverkar ett säkerhetslagers storlek. I många förekommande beräkningsmetoder är beslutsparametrarna inte identiska med resultatvariablerna. Detta försvårar möjligheterna att sätta lämpliga värden. Metoderna utgår också vanligtvis från ett begränsat antal buffertpåverkande variabler och de teoretiska beräkningsmodeller som ingår i metoderna bygger oftast på förenklande antaganden.
För att komma tillrätta med dessa svagheter med beräkningsmetoder och de osäkerheter som är förknippade med bedömningsmetoder är det väsentligt att tillämpa dem inom ramen för ett adaptivt tillvägagångsätt. Det innebär att mål sätts för önskade värden på varje resultatvariabel, så kallade ”bör-värden”, och att periodiskt och rutinmässigt genom resultatmätning få information om de verkliga utfallen, så kallade ”är-värden”. Är skillnaden mellan ett är- och ett bör-värde inte acceptabel anpassas värdet på beslutsparametern. I den här artikeln redovisas synpunkter på användning av bedömningsmetoder vs beräkningsmetoder, ett koncept för adaptiv styrning av säkerhetsbuffertar och en sammanställning av ett antal alternativa resultatvariabler som kan användas för att definiera ”bör-värden” och mäta ”är-värden” för respektive buffert.
Senior managers when solving problems commonly use analogical reasoning, allowing a current ‘target problem’ situation to be compared to a valid previous experienced ‘source problem’ from which a potential set of ‘candidate solutions’ may be identified. We use a single-echelon of the often-quoted Forrester (1961) production-distribution system as a case ‘target model’ of a complex production and inventory control system that exhibits bullwhip. Initial analogical reasoning based on ‘surface similarity’ would presuppose a classic control engineering ‘source model’ consisting of a phase-lag feedback system for which it is difficult to derive the transfer function. Simulation alone would have to be relied on to mitigate the bullwhip effect. By using z-transform block diagram manipulation, the model for a single-echelon, consisting of 17 difference equations with five feedback loops is shown to have exact analogy to Burns and Sivazlian's (1978) second order system that has no feedback. Therefore, this more appropriate ‘source model’ is based on a deeper understanding of the ‘behavioral similarities’ which indicates that the bullwhip effect is not in the case of the ‘target model’ due to feedback control but due to a first-order derivative, ‘phase advance’, term in the feed forward numerator path. Hence a more appropriate ‘candidate solution’ can be found via the use of a ‘recovery’ filter. An interdisciplinary framework for exploiting control engineering block diagram manipulation, utilizing analogical reasoning, in a practical setting is presented, as is an example in a contemporary supply chain situation.
This paper shows the impact of using the net present value (NPV) on parameter selection in the ordering policy of a production planning and control system. Using a well understood and documented model, the net present value is used as an objective function to determine the discounted future variance costs resulting from the model's dynamics. The NPV of the variance (NPVv) is defined and applied to the model under make-to-order and make-to-stock conditions. We show that the cost structure of the manufacturing system defines the NPVv and hence aids in identifying the most appropriate control strategy to apply.
One of Forrester’s (1958) original intentions of presenting a production-distribution system model was to highlight that “feedback theory explains how decisions, delays, and predictions can produce either good control or dramatically unstable operation”. Using system simplification techniques on Laplace block diagrams, the model for a single echelon, consisting of 17 difference equations with five feedback loops is shown to actually contain no linear system state feedback in the ordering rule. Here we replicate the simplification study using the z-transform, allowing us to identify the resultant transfer function as directly mimicking Burns and Sivazlian’s (1978) model used to show the impact of the ‘false order’ wherein the order placed by an echelon is a combination of ‘real’ plus ‘safety’ orders to account for delays leading to inventory depletions. Hence Forrester’s original model, rather than showing the impact of feedback on decision making, is in fact a pre-existing case of the ‘false order’ effect. Therefore the so called ‘Forrester effect’, in which orders are amplified from sink to source, is not in this case due to linear feedback control but due to a first-order derivative term in the feedforward numerator path. In hardware control engineering terms this generates the well-known “phase advance”, or predictive, component. This paper indicates the value of the system simplification approach in system design. Without the simplification approach opportunities for drawing analogue with a system archetype with known solutions, such as the use of a ‘recovery’ filter, would have been missed. The approach is consistent with the “Power of Analogy” paradigm.
Efficient long-term capacity management is vital to any manufacturing firm. It has implications on competitive performance in terms of cost, delivery speed, dependability and flexibility. In a manufacturing strategy, capacity is a structural decision category, dealing with dynamic capacity expansion and reduction relative to the long-term changes in demand levels. Sales and operations planning (S&OP) is the long-term planning of production levels relative to sales within the framework of a manufacturing planning and control system. Within the S&OP, resource planning is used for determining the appropriate capacity levels in order to support the production plan. Manufacturing strategy and sales and operations planning provide two perspectives on long-term capacity management, raising and treating different issues. In this paper, we compare and link them in a framework for long-term capacity management.
All value chains are not designed the same way. A major determinant is the type of product that is to be supplied through the chain or network, calling for different types of value chains. An interesting model for this selection is the one developed by Fisher, arguing that products can be characterised as being either functional or innovative, and that supply chains are either physically efficient or market-responsive. Certain combinations of products and supply chains are assumed to provide matches whereas other combinations lead to mismatches. This paper combines this approach with the concept of a customer order decoupling point. We distinguish between a product supply decoupling point and a demand mediation decoupling point. A decoupling point divides the value chain into two distinct parts; one upstream with certain characteristics and one downstream with distinctly different characteristics. In this paper we specifically explore how the Fisher model can be used to characterise the role and features of upstream versus downstream value chain operations relative to the product supply decoupling point and the demand mediation decoupling point.
Master scheduling is gaining recognition as the major planning process for manufacturing firms, where the appropriate trade-offs can be made among e.g. customer service, manufacturing efficiency and inventory investment, involving both market and manufacturing insights. Master scheduling has traditionally been treated as a material-based planning tool, e.g. in the MRP II (manufacturing resource planning) approach to master scheduling. Capacity issues are then treated in a secondary way, as a capacity check of material plans. However, in, for example, process type industries the main focus is rather on capacity. Taking into account the positions of bottlenecks, order penetration points, and material profiles, the integration of material and capacity plans becomes necessary in many manufacturing environments. This paper presents a framework for the structuring of material and capacity integration taking the factors above into consideration. A matrix is presented where three material based characteristics meet four capacity based characteristics, and the resulting twelve situations depict possible manufacturing settings. In this context, issues such as material and capacity integration, planning and scheduling approaches and multi-level master scheduling are discussed.
Det finns många olika modeller och metoder tillgängliga för produktionslogistik och material- och produktionsstyrning (MPS). Antalet verktyg växer hela tiden liksom verktygens komplexitetsgrad. För det specifika producerande foretaget är det inte trivialt att hitta, välja eller utforma den mest lämpliga uppsättningen verktyg. På senare tid har dock forståelsen för kopplingen mellan verktyg och lämpliga produktionsmiljöer och för hur verktygen skall användas ökat. Syftet rned denna artikel är att ge några perspektiv på olika verktyg såsom modeller och metoder liksom trender inom området.
There are numerous tools available to be used for production planning and control purposes. The number of tools is ever increasing, and so are the levels of sophistication as well as complexity. For the specific manufacturing firm, the task of selecting the most appropriate set of tools is not trivial. However, in recent years, the understanding of the relationship between tools and manufacturing environments for which they are suitable has increased. The purpose of this paper is to provide an overview of production planning and control tools available today, as well as new trends, issues and ideas.
In recent years the customer order decoupling point (CODP) has gained increased acceptance as an important concept when organizing value-adding activities in production and logistics. The CODP, which is defined as the point in the value-adding material flow that separates decisions made under uncertainty from decisions made under certainty concerning customer demand, is however normally only used for production- and distribution- related activities. Here we adjust the typical CODP typology and show how the engineering resources can be integrated with the production process so as to take the features of mass customization environments into account. This paper also examines existing mass customization frameworks and offers a more thorough and nuanced typology for classifying various levels of mass customization. Finally, the adjusted CODP typology is used as a foundation for developing a reliable order promise process for mass customizers.
Operations management, as any type of management, is basically concerned with making decisions. Many of these decisions are related to customer demand and an important concept for understanding the underlying complexity is the customer order decoupling point (CODP). The CODP separates decisions made under certainty from those made under uncertainty about customer demand. Here, a brief background to the concept is presented and the CODP is defined. The paper also shows how the CODP can be used in a number of situations and applications; in the formulation of a manufacturing strategy, in the design of supply chains, and the use in a business processes context. In particular we investigate the application to settings where production and engineering activities are interlaced.
To be competitive, it is important for companies to create a breeding ground for innovation without jeopardizing productivity. The challenge posed by industrial companies and the innovation research community is how to promote innovation while achieving efficient execution. The ability to balance execution and innovation is referred to as organizational ambidexterity (OA), which includes several dimensions, concepts and approaches where a central task can be identified. The purpose of this paper is to investigate what consequences result from different dimensions of a task in relation to the types of its actions, and their effects on OA. The focus of the task is firstly investigated, followed by the development of nine scenarios via combining the designers’ and the performers’ perspectives of the task. A brief analysis of the scenarios indicates that there is no single optimal scenario; rather, the scenarios represent different states that are appropriate for certain conditions, and dynamic adaptation should be encouraged in relation to the changing conditions. This type of dynamics is particularly expected to prevail in small and medium-sized enterprises (SME) because the roles that are responsible for tasks in these organizations are less specialized. Therefore, SMEs must define tasks that include both explorative and exploitative parts, either simultaneously or sequentially, to stimulate employees to work ambidextrously and thereby develop the concept of task-based ambidexterity.
There is no consensus on the supply chain management definition of resilience. To aid in evaluating thedynamic behaviour of such systems we need to establish clearly elucidated performance criteria thatencapsulate the attributes of resilience. A literature review establishes the latter as readiness, responsivenessand recovery. We also identify robustness as a necessary condition that would complement resilience. We findthat the Integral of the Time Absolute Error (ITAE) is an appropriate control engineering measure ofresilience when it is applied to inventory levels and shipment rates. We use the ITAE to evaluate an often usedbenchmark model of make-to-stock supply chains consisting of three decision parameters. We use both linearand nonlinear forms of the model in our evaluation. Our findings suggest that optimum solutions for resiliencedo not yield a system that is robust to uncertainties in lead-time. Hence supply chains will experience drasticchanges in their resilience performance when lead-time changes.
Time, or elements of time, are frequently considered a core competitive advantage and affecting the financial situation of a company. However, the connection between lead-time and financial measures is not always obvious. Therefore, in this paper the conceptual relations between the strategic lead-times and the financial measure return on assets (ROA) are empirically investigated. The results from this research will help increase the understanding of lead-time as a critical resource and reduce the literature gap between strategic lead-times and financial measures. Furthermore, the result could be used by practitioners in evaluating supply chain design and prioritize alternatives based on profitability.
Tid och ledtid betraktas ofta som en konkurrensfördel samt påverkar ett företags ekonomiska situation. Sambandet mellan ledtid och finansiella nyckeltal är dock inte alltid självklart. I denna studie undersöktes därför empiriskt relationen mellan strategiska ledtider och det finansiella nyckeltalet ROA. Resultaten från denna studie bidrar till att öka förståelsen för ledtid som en kritisk egenskap samt minska det teoretiska gapet gällande sambandet mellan ledtid och finansiella nyckeltal. Resultaten kan vidare användas av företag vid utvärdering och prioritering av olika alternativ i försörjningskedjan.
Since its introduction, postponement as a supply chain strategy has received a lot of attention in the operations management and the supply chain management literature. Nevertheless, there are still mixed answers about the meaning of postponement and as such, about its operational benefits. For instance, while some scholars argue that postponement results in a shorter delivery lead time, others claim the contrary. To reconcile these apparently conflicting findings, the purpose of this study is to establish a typology that highlights the three key properties of displacement, which is a collective term for preponement and postponement. By breaking down postponement into the three dimensions of form, place, and time, as well as introducing its antithesis preponement, a typology for displacement is presented and illustrated using a well-known postponement case.
Balancing efficiency and responsiveness has been identified as an overall challenge for decision makers in supply chain management. The literature offers several strategies for managing this balance challenge. From a decision-making perspective this is a significant contribution but in combination the strategies also result in complexity related to the different alternatives offered. This study does, however, show that the strategies share a common foundation in terms of content related to decoupling thinking, which is based on flow discontinuities. Using the strategies’ individual strengths, a process is outlined that takes advantage of these strengths through a four-phase ongoing process.
Purpose – The purpose of the study is to describe the implications of strategic lead times (SLTs) for return oninvestment (ROI).
Design/methodology/approach – This study was part of an interactive research project and is based on thelogic of theory application leading to theory building. It uses a multiple case study with five holistic singlecases. Empirical data (ED) have mainly been collected from interviews and focus groups.
Findings – The length of and uncertainty in SLTs have implications for companies’ financial performance.These implications vary in strength and can be either direct or indirect. These findings are incorporated into aframework on SLTs’ implications for ROI.
Research limitations/implications – The presented array of SLTs’ implications for ROI could be furtherinvestigated, focussing on their strength. Additionally, it would be interesting to substantiate the findings inthe context of environmental and social sustainability (i.e. the triple bottom line).
Practical implications – The findings offer practitioners a rich description and understanding of SLTs’actual implications for financial performance in terms of ROI. This knowledge can support practitioners inanalysing supply chain designs based on financial performance.
Originality/value – Using a combination of a relative financial performance measure (ROI) and a set of SLTs(systems perspective), this study focuses on SLTs’ actual implications for ROI. The findings provide evidencethat different sections of a supply chain can have different implications for revenue, cost and investment (i.e. thethree absolute measures related to ROI).
Reviews the dynamic operation of supply chains and reaches some simple conclusions for reducing demand amplification, which consequently attenuates swings in both production rates and stock levels. The results are based on one particular supply chain, for which the use of systems simplification techniques has generated valuable insight into supply chain design. Although different strategies are compared for reducing demand amplification as witnessed by one particular supply chain model, the conclusions are nevertheless thought to have wide application and, indeed, implication. Comments in depth on the significance of the simulation results for the demand chain as a whole, and for the role of an individual business within the chain. In the first instance, supply chain integration, and in particular free exchange of information, is a prerequisite for progress. In the second case, shows that reduction in lead times throughout the supply chain via JIT is similarly beneficial. Clearly pinpoints the limitation to supply chain improvement which can be obtained as a result of using JIT alone. This can be an expensive and ongoing process of improvement with many spin-off benefits. Nevertheless, shows that the improvement possible by JIT operation of an individual business can be negated by the failure to design and manage the supply chain dynamics as a total system. The message for an individual business is thus quite specific. Not only must lead times be reduced via JIT, but also the business must seek to be part of the right supply chain, if it is to remain competitive and stable.
Competing through goods only has turned out to be increasingly difficult unless efficiency and low-cost manufacturing are at the core of the business. Extending the offering by introducing customisation in combination with services has improved the effectiveness capability. Still, much remains to understand how these servitised businesses can be managed in an integrated fashion. Service operations management and manufacturing operations management have evolved along separate paths but are beginning to align, and by focusing on value adding processes some fundamental principles can be identified. Using a value driven and process-based approach the value offering is defined as provided by initial capabilities and adapting capabilities of the provider. From a supply chain perspective this is shown to be identical to the established approach of balancing efficiency and responsiveness (also referred to as leagility) based on the customer order decoupling point. As a consequence focus on efficiency is at the core of goods-based supply and focus on responsiveness is at the core of service-based supply.
De integrerade affärssystemens förmåga att hantera stora mängder data och dela information till både kunder och leverantörer över stora geografiska avstånd, ger dem en given plats om man vill få ut mesta möjliga av lean produktion.
Continuous flow is the guiding star for lean thinking and considered the ideal state for value streams. Despite this objective, it is seldom possible to obtain a state of continuous flow in a wider context. Decision makers face dynamic environments, and variable internal preconditions require a flow-thinking approach that provides support in response to these challenges. In the present study, the underlying logic of flow thinking is first identified as the key management layer, and thereafter the effectiveness of flow is targeted. The vision of continuous flow is challenged by different exogenous requirements that result in flow discontinuities. Flow thinking is then used to identify 10 decision categories based on these discontinuities, each related to a type of decoupling point and classified as time-based (exogenous) or conversion-based (endogenous). The flow-thinking approach is finally applied in three different contexts: a time-phased product structure, a modularized approach for planning and control, and a mixed-model value stream.
Purpose – To provide an overview of how a number of frequently used smoothing-based forecasting techniques can be modelled for use in dynamic analysis of production-inventory systems.
Design/methodology/approach – The smoothing techniques are modelled using transfer functions and state space representation. Basic control theory is used for analysing the dynamic properties.
Findings – A set of expressions are derived for the smoothing techniques and dynamic properties are identified.
Practical implications – Dynamic properties are important in many applications. It is shown that the different smoothing techniques can have very different influences on the dynamic behaviour and therefore should be considered as a factor when smoothing parameters are decided on.
Originality/value – Dynamic behaviour of production-inventory systems can be analysed using control theory based on, e.g. transfer functions or state space models. In this paper a set of models for five common smoothing techniques are analysed and their respective dynamic properties are highlighted.
Dynamic modelling of production-inventory systems usually involves lead time models since this is one of the most important aspects of these systems. Many different models are possible and this paper presents an overview and some ideas for how the models may be interpreted. Three different approaches to continuous-time dynamic modelling of variable lead times based on Control Theory are discussed. Two of the models can easily be incorporated into linear models based on the Laplace transform. The models are shown to be three instances of a generic delay model, which by careful selection of two parameters can be adapted to a wide variety of systems. Also the relation between waiting line theory concepts and the generic delay model is analysed, establishing an interpretation of the models as generating the concept of expected dynamic behaviour.
Purpose – A production-inventory system based on a model proposed by Axsäter is examined with the purpose of understanding the dynamic properties of the model.
Design/methodology/approach – The information flow concept is discussed and a dynamic analysis using a system simplification approach is carried out to achieve an understanding of the dynamic behaviour of the system. Finally, the information flow is examined and analysed from a hierarchical perspective.
Findings – The model is extended to include an order decision rule and a production unit and it is shown that the extended model has the capability to represent the dynamics of a number of different system management principles. The three different model instances of base stock, kanban and material requirements planning character are analysed.
Originality/value – Dynamic modelling of production-inventory and supply chain models are usually analysed at an aggregate level not involving any complex relations of materials or capacities. In this paper, this line of research is merged with an approach based on multiple information channels using matrix representation and it is shown how a system simplification approach can be used for this purpose.
The basic production distribution system presented by Forrester in his book "Industrial Dynamics" is analysed. Although many subsequent authors have quoted the original simulation results, especially when referring to supply chain behaviour, a complete analysis of the model has yet to be published. This dissertation fills this gap. As the starting point the Dynamo program representing the system is transformed to a block diagram representation commonly used in control theory. A general model for one echelon of the system is then devised and analysed. Simulations are used to cross check the analysis and to compare the behaviour of sub-systems based on varying degrees of simplification. This general model is then put into the context of the full system and further analysis and simulation is performed to gain a deeper understanding for the dynamics than is obtained from the Forrester results alone. Five different approaches are then used to improve the system.
- Tuning the policy parameters.
- Reduction of delays in the system.
- Removal of the distributor echelon.
- Improvement of the decision rules.
- Improvement via better use of information in the system.
Finally two or more of these alternative approaches are combined to find a new design that behaves better than the original Forrester model.