The text below has been reproduced from VARIES deliverable D3.6 [Biot, 2015], section 8, and has been adapted for public dissemination.
When assessing the prospect of increasing variability for any product in any organization, it is important to look at the costs. As the variability paradox states, introducing variability should provide benefits, but also increases costs, see deliverable D3.1 [Hirvonen, 2013]. The relation between costs and variability also seems to be non-linear – if variability keeps increasing, complexity and the ensuing cost increases grow (see e.g. Strategies). When the company feels pressure to decrease costs, this cost pressure in itself becomes a variability driver (e.g. drivers companies to decrease variability).
The effect of complexity can also increase costs in unpredictable ways, create bottlenecks in critical resources and raise the base costs for production. This makes the cost driver a complex and important one, and it raises questions to be assessed; how much will it cost to increase variability in the product portfolio, and what do these costs consist of? Which types of costs are the most sensitive to variability and how do these costs formulate? What will be the probable resource bottlenecks, and how will these bottlenecks affect the time cost for operations? How will increasing variability in the product portfolio affect the resource needs and thus costs in time and money later in the lifecycle?
The current framework is an attempt to analyse the effects of variability on resource consumption when creating embedded systems in different life cycle phases independent of domain. This framework assesses the cumulative resource cost of variability in an organization that develops, produces and performs maintenance of products. The approach of the framework is identifying the types of resources, and the phases and tasks in the life cycle of a variant, that are most sensitive to the effects of variability.
It should be noted, that this approach observes resource cost effects of variability, not all costs or their effects on products. The reason for this is simply the complexity of handling all possible costs in all possible domains. Due to this approach this section is about the resource costs of variability and handling of those costs.
All activities in a company consume resources. These resources include time of employees, used facilities and materials, used services, subcontractors etc. Some of these resources generate costs directly when consumed, while some of them just replace the availability from other activities. In this framework we are interested in resources that are somehow related to variability of products. Thus, different types of resources and resource costs related to products are of interest in this section.
Normally a company has several different product variants that are in different stages of their life cycle. While some of these products or their variants are becoming obsolete, other variants might be in the maintenance-, production- or development- stage.
During different stages of a product life cycle different resource costs emerge and dominate the accrued resource costs of a product or a product variant. To understand which resource costs are most significant in which life cycle stage of a given product – resource costs in different stages of the product life cycle (for different kinds of products and product variants) need to be examined separately.
In the framework we (1) assess the resource costs of variability in different life cycle stages and the tasks included in those phases, and (2) assess which of these resources costs will potentially create bottle necks or snow ball effects when the level of variability changes, and (3) try to find the possible trade-offs for organizations to tackle the resource bottlenecks.
The life cycle model used is based on Blanchard [Blanchard, 2010]. The full life cycle with adjustments introduced in deliverable D3.1 [Hirvonen, 2013] includes the categories shown in Figure 1‑1 below.
In this subsection different approaches for analysis are explained, as well as the relevant cost types that are important in variability resource cost analysis.
The approach to identify the resource needs and associated costs impacted by changes in variability. These resource needs are categorized according to the variant life cycle and according to the tasks in that life cycle, both based on Blanchard [Blanchard, 2010]. The idea is to identify key resource costs that are impacted by adding new product variants, modifying existing variants, or eliminating variants. Several different resource costs are always affected, but the idea is to assess whether these resource costs create a choke point, cause delays, or create a snow ball effect to any resources or costs. These resource costs are the key resource costs.
To achieve this analysis, several known cost effects of variability are applied to the lifecycle. In the following these costs are explained.
According to Pohl [Pohl, 2005] there are costs caused by a high quantity of variants for different departments of a company. These are costs that typically increase as the number of variants increases. These kinds of costs are called flexibility costs and are described to accumulate for different departments of a company.
Another important, if more generic, cost type is opportunity costs that occur always when one variant is developed, produced or maintained in place of another variant.
The notion of opportunity cost plays a crucial part in ensuring that scarce resources are used efficiently. Thus, opportunity costs are not restricted to monetary or financial costs: the real cost of output forgone, lost time, or any other benefit that provides utility, should also be considered as opportunity costs [Green, 1894].
According to de Groote and Yücesan product variety increases logistics costs [deGroote, 2011]. When dealing with a higher product variety, the level of inventories and lead time is increasing. These respectively mean that the logistics costs and logistics time to deliver products increases. A company could choose to keep inventory costs low and not care about increases lead times, which would however lead to lower service levels and dissatisfied customers.
To assess the resource costs as impacts of variability decisions, the impact of different variability decision types is analysed for each costing category in the model. The purpose of this observation is to emphasize and to clarify the relationship between the variability decisions and the resource costs.
Linking all of the costing categories or tasks to all of the variability decision types would make this analysis massive and messy. Thus a more subtle and effective approach is needed. To do this, the two-dimensional classification of product differentiation versus product variety is utilized (D3.6, section 4.1, Figure 4 1 [Biot, 2015]).
There are several resource cost affecting impacts of variability decisions, which often entail a trade-off. Because the framework analyses resource costs and their impact, also these trade-offs need to be analysed, as many of them are done already when variability decisions are made and the resources are consumed. There are also several different ways in which variability decisions can impact a company (e.g. cost, revenue, time-to-market …) (see e.g. D3.6 chapter 4 and section 9.5 [Biot, 2015]). In addition, variability decisions often have both positive and negative consequences (i.e. there is often a trade-off between different decision consequences). Derived from these impacts, a group of trade-offs are presented in the framework and applied to the framework. These trade-offs include:
- Resource capabilities (manpower/skills/production equipment) versus investment/cost
- Variability to gain market share/revenue versus costs
- Commonality versus diversification: platform versus customisation cost
- Commonality/cost versus quality/product performance
Behaviour of different costs are analysed per task in a life cycle phase according to variability decisions in the framework, and trade-offs are discussed. This framework of resource cost behaviour then creates a base for determining resource cost impact for any company on a rough level.
|Biot, 2015||Biot, O., Bollen, M., Codenie, W., Hirvonen, H., Teppola, S., Van den Broeke, M., Vierimaa, M. (2015). Deliverable D3.6: Updated methods to capture product variability: drivers and variants.|
|Blanchard, 2010||Blanchard, B. S., & Fabrycky, W. J. (2010). Systems Engineering and Analysis. Prentice Hall.|
|Green, 1894||Green, D. I. (1894). Pain-Cost and Opportunity-Cost. The Quarterly Journal of Economics, Vol. 8, No. 2 (Jan., 1894), 218-229.|
|Hirvonen, 2013||Hirvonen, H., Mäntysaari, M., Pesonen, K., Haapaniemi, A., Biot, O., González-Deleito, N., . . . Jaring, P. (2013). Deliverable D3.1: Modeling and evaluation of variants in the product portfolio and roadmap|
|deGroote, 2011||de Groote, X., & Yücesan, E. (2011). The impact of product variety on logistics performance. Proceedings of the 2011 Winter Simulation Conference (pp. 2245-2254). IEEE Conference Publications.|
|Pohl, 2005||Pohl, K., G. Böckle, and F. van der Linden. 2005. Software Product Line Engineering: Foundations, Principles, and Techniques. Springer.|
|VARIES-TA||ARTEMIS Call 2011, ARTEMIS-2011-1, 295397 VARIES: VARiability In safety-critical Embedded Systems. Technical Annex.|