High-Level Strategies for Addressing the Variability Paradox

1     High-Level Strategies for Addressing the Variability Paradox

The text below has been reproduced from VARIES deliverable [D3.1], section 2.3, and has been adapted for public dissemination.

1.1     Product Variability

Product variability is defined as the art of managing the creation, evolution and maintenance of different ‘versions’ (variants) of a product [VARIES-TA]. This definition encompasses the creation of new products in the portfolio, the sequential incremental updates of a product (i.e., evolution) as well as the creation of derived products (i.e., customization and configuration). We follow the definitions given in [Codenie, 2009]: “the term customization is used to refer to the activity of changing a (generic) product into a solution satisfying the specific needs of a customer. Changing could be adding new functionality, and changing or removing existing functionality. In essence, customization creates a new product variant that not existed before. Configuration is choosing among a predefined set of product variants (e.g. by filling in configuration parameters).”

1.2     The Variability Paradox

Figure 1 below illustrates the typical course of value (turnover, profit) and cost curves related to the product variety:

  • A number of reasons for creating product variants are market segmentation and keeping up with evolving market trends and requirements. Typically, the turnover will increase by creating variants tailored to these new market segments or that provide an answer to upcoming market needs. However, adding more variety will eventually provide fewer yields: the turnover curve (green) evolves almost logarithmically as variety increases [Schuh, 2005]. This is consistent with the typical market segmentation story.
  • By adding more variety, initially the engineering of the first variants can benefit significantly from acquired product expertise, domain knowledge and reuse & adaptation of existing engineering artefacts. However, by adding more variety in the portfolio, the incremental cost for creating one extra variant starts growing exponentially (red curve), since product engineering will have to manage the overhead caused by interdependencies between different product variants. This is exacerbated when dealing with multidisciplinary and multi-technology products having a life expectancy exceeding the lifecycles of the technologies used.
  • As a result, the incremental profit (margin) curve (blue) will show a maximum and will gradually evolve to a point where added variety will have negative yield (red zone).

On this graph there appears to be an optimum (in the green zone) where variety contributes most to the yield. To the left of this optimum, yield can effectively be increased by adding more variety (e.g., via market segmentation). To the right of this optimum, yield can still increase by adding more variety, however the extra variants will contribute less and less to the overall profit. Eventually the yield of extra variety will no longer outweigh the penalty of the increased complexity of managing the extra variability (red zone).


Figure 1. Incremental cost and value of variants

The graph in Figure 1 leads us to the “variability paradox”:

How can the benefits offered by introducing variability into embedded systems
outweigh the increased product complexity caused by variability?

A first challenge is to try identifying the optimal level of variety. Mathematically it’s where the blue margin curve’s first derivative is zero. However, in practice, this curve depends on many more, often intricately interdependent parameters than variety and cost alone, hence finding this optimum is difficult.

A second challenge is that the situation evolves over time. For instance, a once profitable market segmentation and assorted offering may no longer be profitable because of competition leading to cheaper products that lower the green curve and consequently reduce the margin, sometimes even to the point of generating losses (see Figure 2 below).


Figure 2. Reduced profit due to competition

This reasoning is well described in literature.

1.3     Strategies for Addressing the Variability Paradox

Based on Figure 1, a number of high level strategies can be proposed to address the ‘variability paradox’:

  • Strategies that do not affect the cost and value curves
    • (1.3.1) Add more variants
    • (1.3.2) Eliminate unprofitable variants
  • Strategies that affect the cost curve
    • (1.3.3) Reduce costs of variability
    • (1.3.4) Manage variability
  • Strategies that affect the value curve
    • (1.3.5) Make better products

1.3.1     Add more variants

A first strategy is to add more variety in the product portfolio. This can be applied in cases where the benefits of the extra product variety outweigh the engineering & management effort for making and maintaining these new variants. A typical scenario is the identification of a significant market segment in an already served market for which the current product offering does not satisfactorily meet the needs. In another scenario a promising market niche has been identified, for which it is understood how to adapt existing products and engineering artefacts to build products adapted to that segment’s needs.

To assess the feasibility and yield of this strategy, often a business case is developed.

Figure 3 illustrates how this strategy moves along the existing curves in the direction of increased variability, with the intention to remain in the green area of positive yield of variability.


Figure 3. Strategy 1: add more variants

The following examples illustrate how this strategy may be implemented (this is context dependent):

  • Apply market segmentation. By identifying criteria for segmenting your market, you may gain insight in potential variants that better support a segment’s particular weighed set of needs (certain features may be more or less relevant for different segments).
  • Identify customers with similar needs.

1.3.2     Eliminate unprofitable variants

In some cases, there is too much diversity in the product portfolio. Some variants cost more to develop and maintain than they contribute to the profit margin. Several scenarios can be proposed in which this case applies. A product variant developed for a specific market segment in the past may incur high maintenance costs due to technology obsolescence; in addition the profit margin may have been put under pressure by competitors. In other cases there may be a motivation to become a dominant player by offering a product for several existing market segments; where initially this made sense and did realize added profit, eventually the market needs changed, competition may have offered a hard to beat alternative and the added complexity of managing all existing variants is further eroding the profit margins.

A first strategy to apply in these scenarios is pruning the product portfolio from the less profitable or loss inducing variants. In Figure 4 this is achieved by moving leftward on the profit curve towards less variety.


Figure 4. Strategy 2: eliminate unprofitable variants

The following examples illustrate how this strategy may be implemented (this is context dependent):

  • Identify legacy products that tend to waste resources in engineering and production merely to support aging, low margin and low volume products. These resources could be reassigned to work on the future products in the portfolio.
  • Make or refine the business plan for problematic products
  • Remove product features that are no longer relevant. This can happen for several reasons, e.g. due to technology obsolescence, new market trends, removing product features that are no longer in use, no longer supported or no longer relevant.
  • Re-segment the market. The criteria used in market segmentation may have evolved to the point where they became irrelevant. This can affect the number of variants to offer.
  • Evaluate how the product variants are actually used

1.3.3     Reduce costs of variability

Instead of walking the existing curves, one can also attempt at manipulating the curves. This leads to the following set of strategies.

Figure 5 illustrates a first strategy in which the cost curve is pushed downward. The goal of this strategy is to produce the same variety at a lower cost. The net effect of pursuing this strategy is to increase the profit margin. Indirectly the green profit zone also grows to the right.


Figure 5. Strategy 3: reduce costs of variability

The following examples illustrate how this strategy may be implemented (this is context dependent):

  • Deploy configuration management in the product development organization
  • Identification and management of reusable assets
  • Optimize the economic return of reuse versus customer specific customization. Reuse comes with a cost, it is important to evaluate whether the reuse will ever recoup this cost.
  • Deploy instruments and processes to better support the management of the variants
  • Deploy a test automation framework

Reduction of costs of variants may occur in several ways [Pohl, 2005]:

  • Upgrading products by standard integration of formerly supplementary features. Reducing complexity, which is caused by supplementary features, reduces production costs.
  • Modular structure. A modular structure allows high diversity of variants under the condition of low increase of complexity.
  • Product platforms. The usage of platforms and non-variable parts lowers the diversity of parts and the production complexity.

1.3.4     Manage variability

The next strategy consists of offering more variety without incurring any cost penalty. Figure 6 illustrates this strategy as the red cost curve being pushed rightward. The net effect is to grow the green profit zone rightward too. Indirectly, the profit curve will grow thanks to the variability management.

Figure 6. Strategy 4: manage variability

Figure 6. Strategy 4: manage variability

The following examples illustrate how this strategy may be implemented (this is context dependent):

  • Deploy configuration management in the product development organization
  • Use technologies that support product configuration
  • Deploy instruments and processes to better support the management of the variants
  • Adding a layer of abstraction (divide and conquer)
  • Optimize the definition of subsystem boundaries (e.g., to facilitate up-scaling of the engineering activities for creating more variants)

1.3.5     Make better products

Lastly, the turnover curve can be pushed upward by creating products that bring more value to the customers. As a consequence, such products can be sold at a higher price. A direct consequence is that the profit curve will grow upward (Figure 7). Indirectly the green profit zone will expand rightward thanks to the turnover contributing more substantially to the profit margin.

Figure 7. Strategy 5: make better products

Figure 7. Strategy 5: make better products

The following examples illustrate how this strategy may be implemented (this is context dependent):

  • Build products that better meet the customer needs and wishes. If your offering more closely matches the customer’s needs than other offerings, yours brings more value; hence you may decide to ask a higher price for your offering.
  • Create products that better support the users in their tasks and activities. Again, these products may offer more value to their users, hence may be a reason for asking a higher price.
  • Value innovation. In this approach [Kim, 2005], you try to define a unique value proposition based on an existing offering in an existing market. By identifying value elements that differentiate your offer from competing offerings, you can bring uniqueness in your value proposition.
  • Market segmentation. In some cases, the same product can be sold at a higher price to a specific market segment (e.g. vanity products, ODM/OEM rebranding).
  • Identification of new market niches. By exploring the relevance of your offering in related and distant market niches, you may end up offering high value by building a product that is targeted at that niche.

Aforementioned high-level strategies serve different purposes and are sufficiently generic to be broadly applicable. The exercise of choosing which strategy to apply heavily depends on the context of the company, which is impacted by the variability drivers at play.

2     References

Author, Year Authors; Title; Publication data (document reference)
Codenie, 2009 Codenie, W., González-Deleito, N., Deleu, J., Blagojević, V., Kuvaja, P., Similä, J. (2009). Managing Flexibility and Variability: a Road to Competitive Advantage. In Applied Software Product Line Engineering, Chapter 12, pages 269–313. Taylor and Francis, December 2009
Kim, 2005 W. Chan Kim, Renee Mauborgne. Blue Ocean Strategy: How to Create Uncontested Market Space and Make Competition Irrelevant. Harvard Business Press, 01 Feb 2005
Pohl, 2005 Pohl, K., G. Böckle, and F. van der Linden. 2005. Software Product Line Engineering: Foundations, Principles, and Techniques. Springer.
Schuh, 2005 Schuh, G., Schwenck, U. (2005). Produktkomplexität Managen: Strategien – Methoden – Tools, Carl Hanser Verlag Fachbuch, ISBN 3-446-40043-5.
VARIES-TA ARTEMIS Call 2011, ARTEMIS-2011-1, 295397 VARIES: VARiability In safety-critical Embedded Systems. Technical Annex.
D3.1 ARTEMIS Call 2011, ARTEMIS-2011-1, 295397 VARIES: VARiability In safety-critical Embedded Systems. Deliverable D3.1: Modeling and evaluation of variants in the product portfolio and roadmap.