Typologies of Variability Decisions

1 Typologies of variability decisions

This section reproduces chapter 4 of VARIES deliverable D3.6 (Biot, et al., 2015).

There are many ways to categorize variability decisions. A number of relevant typologies are presented in this section. They are by no means an exhaustive set.

1.1 Product differentiation versus product variety

Variability decisions can be classified on a two-dimensional plane representing the impact on product differentiation (internal product variety) and on product variety (external product variety), see deliverable [D3.5], section 4.3.3 (Van den Broeke, et al., 2015). This is represented in Figure 1‑1:

Figure 1 1. Impact of variability decision types on product variety and product differentiation

Figure 1 1. Impact of variability decision types on product variety and product differentiation

Product similarity and differentiation refers to similarities and dissimilarities between products. When the product differentiation is low, the products have mainly small differences in features (more overlap), functionality etc. When the differentiation is high, the products share relatively fewer features and functionality (less overlap).

1.2 Consequences on the product portfolio

In deliverable [D3.3], a set of 11 generic variability decision types were introduced. After revisiting the data collected, this set of decision types rather reflects the consequence of a variability decision on the product portfolio on 3 levels (product, market and maintenance).

Table 1‑1 is based on Table 5–2 from deliverable [D3.3], section 5.3.5 (Biot, et al., 2014). It shows the different consequences a variability decision can have on the product portfolio.

Table 1‑1. Consequences of variability decisions on the product portfolio

Dimension Consequence of decision on product portfolio Explanation
Product D0 A new product line has been created New product creation or derive new product line from existing product variant
Product D1 A product has been updated Create a new ‘sequential’ version (release, product evolution)
Product D2 A new variant has been derived from an existing product Create a new ‘parallel’ version (branching, increase portfolio diversity)
Product D3 Changes from different product variants have been incorporated into a new product version that may replace / supersede the former variants Reduce portfolio complexity (merger from parallel branches, decrease portfolio diversity)
Market D4 A product variant has been exposed to the market Make a variant visible and available on the market (make internal variant external / exposed / visible)
Market D5 A product variant has been retracted from the market The product is no longer available on the market.
Maintenance D6 Maintenance has been started on a product variant The product variant is under maintenance.
Maintenance D7 Maintenance has been terminated on a product variant The product variant is no longer under maintenance.
Product D8 A product variant has been removed / eliminated from the portfolio All economic activity relating to this particular variant has been halted (R&D, sales, maintenance).
Product D9 A set of product variants has been eliminated (abandoned) from the portfolio All economic activity relating to this branch of variants has been halted (R&D, sales, maintenance).
Product D10 A product line (including all its branches) has been eliminated (abandoned) from the portfolio All economic activity in the product line has been halted (R&D, sales, maintenance).

 

1.3 Internal versus external visibility

Not all variability decisions will have an outcome that has the same level of visibility. Some decisions will only introduce small modifications that otherwise don’t adversely affect the product functionality or its performance. The results of such decisions are often hidden to most stakeholders. Other decisions have a more profound impact and result in higher visibility, up to the creation of a new product portfolio.

Decisions can be categorized on the level of impact on and visibility in the product portfolio, see deliverable [D3.5], section 4.3.3 (Van den Broeke, et al., 2015). The impact can be at the level of one single product, or at the level of (parts of) the product line, or even across product lines. It can also be either internal (invisible to the market) or external (visible to the market), see for instance Figure 1‑2.

Figure 1 2. Visibility and impact level of variability decisions (source: [D3.3])

Figure 1 2. Visibility and impact level of variability decisions (source: [D3.3])

1.4 Disciplines and stakeholders affected

Variability decisions can also be categorized depending on the engineering disciplines affected. Typically one discipline is dominantly affected by the decision, but sometimes several disciplines are comparably affected. When more than one engineering discipline is affected, typically this is also reflected in a higher number of stakeholders affected by the decision, and a higher impact of the decision on the product (it can require more change due to complex interactions across disciplines and stakeholders).

1.5 Impact on resources and profitability

Variability decisions can also be categorized according to the impact of the decision on resources and on profitability. The distinction should be made between the impact on the investment required to implement the decision, as well as on the impact after having the decision implemented (yield).

For some impact factors, an increase is a positive effect (e.g. revenue), while it can also convey a negative effect to others (e.g., time to market). This is illustrated in Figure 1‑3, where a number of example impact factors are represented (e.g., revenue with positive effect, and lead time with negative effect).

Figure 1 3. Impact of variability decisions on resources and profitability, from investment and yield perspective

Figure 1 3. Impact of variability decisions on resources and profitability, from investment and yield perspective

2 References

Biot, O., Bollen, M., Codenie, W., Hirvonen, H., Vierimaa, M., Teppola, S., & Van den Broeke, M. (2015). VARIES deliverable D3.6: Updated methods to capture variability: drivers and variants.

Biot, O., Hirvonen, H., Bollen, M., González-Deleito, N., Drissen, T., Codenie, W., . . . Vierimaa, M. (2014). VARIES deliverable D3.3: Variability drivers.

Van den Broeke, M., Vierimaa, M., Hirvonen, H., Bollen, M., Biot, O., & Teppola, S. (2015). VARIES deliverable D3.5: Identifying and shaping variability in the product portfolio.