=Paper=
{{Paper
|id=Vol-1829/iStar17_paper_4
|storemode=property
|title=A Proposed Textual Model for i-Star
|pdfUrl=https://ceur-ws.org/Vol-1829/iStar17_paper_4.pdf
|volume=Vol-1829
|authors=Vik Pant,Eric Yu,Albert Tai
|dblpUrl=https://dblp.org/rec/conf/istar/PantYT17
}}
==A Proposed Textual Model for i-Star==
https://ceur-ws.org/Vol-1829/iStar17_paper_4.pdf
Towards Reasoning About Pivoting In Startups With i*
Vik Pant1, Eric Yu1, 2, and Albert Tai1
1Faculty of Information, University of Toronto, Toronto, Canada
2Department of Computer Science, University of Toronto, Toronto, Canada
vik.pant@mail.utoronto.ca
eric.yu@utoronto.ca
albert.tai@mail.utoronto.ca
Abstract. Software start-ups have embedded themselves in the economic zeit-
geist as drivers of innovation and growth. ‘Unicorns’, such as Facebook, Uber,
Pinterest, Dropbox, and Palantir, have ably demonstrated the market disrupting
and industry transforming potential of upstarts that ‘punch above their weight
class’. These successful businesses began as start-ups and matured into enter-
prises with multi-billion dollar valuations even though most start-ups fail or are
abandoned within a few years of founding. A notable reason for the failure or
abandonment of many start-ups is erroneous logic and faulty assumptions un-
derpinning their products, business models, and engines of growth. The lean
start-up approach encourages decision makers to test their fundamental hypoth-
eses and effect strategic pivots to identify new and superior fundamental hy-
potheses. This paper outlines exploratory research into the modeling of strategic
pivoting using i*. It discusses the key concepts that are relevant for developing
a framework for analyzing strategic pivoting in a structured and systematic
manner using i*. Such a framework can support decision-makers in start-ups to
test the fundamental hypotheses underlying their products, business models, and
engines of growth.
Keywords: Startup. Entrepreneurship. Design. Modeling. Review.
1 Introduction
Ries [1] promotes the notion of Lean Startup which encourages decision-makers at startup
companies to pivot their products, business models, or engines of growth if tests disprove their
fundamental hypotheses. Changes to a startup’s product, business model, or engine of growth
that are catalyzed by disproving of their fundamental hypotheses are referred to as pivots [2].
Pivoting is useful for effecting strategic redirection in many situations such as when new com-
petitors enter the market; novel substitute products are launched; key suppliers exit the market;
technologies disrupt an industry; as well as when laws and regulations are changed. Pivots are
also crucial for staving off bankruptcy if a startup is operating on unsound assumptions and
incorrect logic since many startups typically operate with limited financial resources which can
be wasted through mistakes. In this paper, we share our vision for a framework that supports
the analysis of pivoting in a systematic and structured manner using i*.
2 Pivoting In Startups
Ries [1] argues that a start-up may need to pivot multiple times and may also need to execute
multiple pivots quickly. Pivoting affects a startup in significant ways because it establishes new
fundamental hypotheses for its products, business model, and engines of growth [1]. Thus, the
stakes are high if a startup executes an incorrect pivot or executes a required pivot incorrectly.
Therefore, a structured and systematic framework for analyzing pivots can be valuable for
decision-makers in a start-up. Ries [1] proposes a catalog of ten types of pivots which are de-
scribed in Table 1. Decision-makers can benefit by analyzing the feasibility, viability, and
desirability of these pivots in their start-ups in a coherent and methodical manner.
Pivot Meaning
Zoom-in Functionality that was formerly a single feature becomes the whole product.
Zoom-out All the functionality in a product is considered insufficient for meeting the require-
ments of a customer segment and thus it is assimilated into another product
whereby the original product becomes a feature in the larger product.
Customer The functionality in a product meets the needs of a certain customer segment that
Segment is different from the customer segment that it was targeted to and thus that prod-
uct is positioned to a customer segment whose needs its satisfies.
Customer The original need of a customer segment that a product is designed to meet is
Need recognized to be less important than another need for that customer segment and
thus the product is changed to meet the other more important need of that cus-
tomer segment.
Value Cap- A company changes the way by which it captures value from its product such as
ture by monetizing features individually or commercializing functionality holistically.
Engine of The company changes its growth strategy by focusing on different ways of grow-
Growth ing market share, increasing revenues, and boosting margins.
Platform A product is turned into a platform where other companies can also offer their
products or conversely a platform on which other companies offer their products is
changed into a product.
Business A company changes from a margin business to a volume business or conversely
Architecture from a volume business to a margin business.
Channel A company changes its sales distribution channel as well as process to take its
products to market more effectively.
Technology A company changes the technology underlying an existing solution in order to
benefit from better price or performance.
Table 1. Catalog of ten types of pivots (Source: Reis [1])
Feasibility pertains to the ability of a start-up to initiate a pivot. Some pivot types, though at-
tractive, may not be possible because the start-up is not capable to start them. Desirability refers
to a start-up’s interest in undertaking a specific type of pivot. While a start-up may be capable
of undertaking a type of pivot– it may not regard that type of a pivot as being suitable for it at
that time. Viability refers to the ability of a start-up to successfully complete an on-going pivot.
A start-up may commence a pivot but may not be able to finish it properly due to mismanage-
ment. If adequate caution is not exercised in planning or implementing pivots then it can have
deleterious impact on that start-up.
3 Towards Modeling Pivoting In Startups With i*
There are certain general characteristics of i* that make it useful for expressing and evaluating
pivoting in startups. These include means-ends reasoning; refinement and elaboration; strategic
dependencies between actors; distinction between actors, agents, roles, positions; and actor
associations. Additionally, the semantics and notation of i* are helpful for articulating and
analyzing pivoting techniques that are listed in table 1. Features of i* that are especially rele-
vant for each type of pivot are discussed below. i* Strategic Rationale (SR) diagrams represent-
ing abstract patterns for four types of pivots are included below. Similar abstract patterns for
remaining pivot types could not be included in this paper due to space constraints. The follow-
ing diagrams only depict unidirectional dependencies (i.e., from customer to vendor) to simpli-
fy visual presentation. We have also omitted some goals and tasks within each actor or role for
brevity and have shown this via a break in dependency links.
• Zoom-in/Zoom-out: i* supports the portrayal of decomposition and refinement as well as
contribution and dependency links. Figure 1 presents an abstract i* model of Zoom-
in/Zoom-out pivots. A focal actor’s (i.e., start-up) product (PrdX) features (FtrX) can be
represented as softgoals that can be chained in a hierarchy such that the topmost softgoal
represents a product. The objectives of a customer (RqtX), which is represented as another
actor, can be expressed as softgoals which can be related to the focal actor’s product via
dependency links. These dependency links can be to the product as a whole or to constitu-
ent features of that product. This information about the dependency of particular user re-
quirements on specific product features can be used to inform the analysis of the start-up’s
impact of offering distinct features as discrete products (zoom-in) as well as of combining
multiple features into a consolidated product (zoom-out). In figure 1, solid (blue) down-
ward arrows depict examples of zoom-in pivoting while dashed (red) upward arrows rep-
resent examples of zoom-out pivoting. Arrows depict examples of pivots among products.
Prd1
Vendor Customer
Ftr1 Prd1a Rqt1
Prd1b
Ftr1a Ftr1b Rqt1a Rqt1b
Prd1a1
Ftr1a1 Ftr1b1 Rqt1a1 Rqt1b1
Prd1b1
Ftr1a2 Ftr1b2 Rqt1a2 Rqt1b2
Prd1a2
Prd1b2
Legend
Goal Softgoal Task Resource
Actor
Means-End Link
Goal Softgoal Task Resource
Actor Actor Boundary
Help Contribution Hurt Contribution Satisficed Denied Is part of Link
Link Link
Role
Make Contribution Break Contribution Weakly Weakly
Link Link Satisficed Denied Role
Figure 1. Abstract i* model of Zoom-in/Zoom-out pivots
• Customer Segment: i* supports the representation of goals and softgoals within the indi-
vidual scopes of various actors. This allows an analyst to group customers by their needs
where customers with identical needs are represented as a segment. The support for actor
associations (e.g., ISA, Plays, etc.) also make it possible to represent sub-segments of cus-
tomers where customers share certain needs in common while maintaining their unique
identities. Figure 2 presents an abstract i* model of Customer Segment pivot. This infor-
mation can be used to reason about the requirements (RqtX) that different groups of cus-
tomers have for a product and to build customer value propositions (VPrX) based on prod-
uct offers (OfrX) that are relevant to meet those requirements. In figure 2, arrows portray
examples of pivoting amongst customer segments.
VPr1 Customer
Vendor
Segment 1
Ofr1 Vpr2 Rqt1 Customer
1
Ofr2 Ofr3 Vpr3
Rqt2 Rqt3
Ofr4 Customer
2
Ofr5 Ofr6 Vpr4 Customer
Rqt4 Segment 2
Vpr5
Customer
3
Vpr6 Rqt5 Rqt5
Figure 2. Abstract i* model of Customer Segment pivot
• Customer Need: i* supports the depiction of goals and softgoals within the scope of each
actor. It also supports the representation of contribution links between various types of en-
tities. This allows an analyst to identify the needs of a focal customer (including those that
are currently being met) as well as the connections between those needs. Figure 3 presents
an Abstract i* model of customer need pivot. This information can be used to analyze
whether it is beneficial to transition to serving different customer needs (RqtX) than those
that are currently being catered to. Alternatively, it can be used to reason about whether it
is advantageous to continue serving currently targeted needs while also catering to addi-
tional needs. Each of these scenarios might require the vendor to offer different products
(PrdX) to the customer. These products may be developed and delivered via different of-
fers (OfrX) that align differently with the focal actor’s primary targets (TgtPrX) and sec-
ondary targets (TgtScX). While products are represented as physical or informational enti-
ties that satisfy customer requirements – offers are represented as tasks because they en-
capsulate specific ways of meeting customer requirements. A focal actor’s decision to ex-
ecute a customer need pivot must consider the impact of that pivot on its own targets and
not be motivated merely by a desire to meet additional or different customer requirements.
Vendor Customer
TgtPr1
Prd1 Rqt1
TgtSc1 TgtSc2
Prd2
Ofr1 Rqt2 Rqt3
Ofr2 Prd3
Ofr3
Figure 3. Abstract i* model of Customer Need pivot
• Value Capture: i* supports the portrayal of decomposition and refinement as well as
contribution links. A product’s features as well as their respective value inputs to the reve-
nue stream can be represented as softgoals. These features and value inputs can be related
to each other via contribution links. Equally importantly, the impact of features on value
inputs of other features can also be related via contribution links. This information can be
used to compare groups of features to evaluate the optimal bundles of features for achiev-
ing the value capture goals of the business.
• Engine of Growth: i* supports the expression of goals and softgoals as well as means-
ends and contribution links. Objectives of the business (such as growing market share, in-
creasing revenues, and boosting margins) can be represented as goals and softgoals. The
alternatives for achieving those objectives (e.g., paid, viral, sticky engines of growth) can
be expressed as tasks. The impact of these alternatives can be portrayed via means-ends
and contribution links. This information can be used to compare the impact of different al-
ternatives on the current and future objectives. Moreover, as tasks can be decomposed it is
possible to explore their strategic, tactical, and operational details to design blended en-
gines of growth.
• Platform: i* supports the articulation of strategic dependencies between any kind of ac-
tors such as customers, brokers, resellers, co-sellers, etc. In the case of a product, the rela-
tionship between the focal actor (i.e., business) and the customer can be shown via de-
pendencies. Here, the customer depends on the business directly to meet its product needs
while the business depends on the customer directly to meet its economic needs. However,
in the case of a platform, customer and the partners only have direct dependency relation-
ships with the business which is the platform operator. Here, the customer depends on the
other actors (i.e., partners) indirectly to meet its product needs while the partners also de-
pend on the customer indirectly to meet their economic needs. This information can be
used to analyze whether more of its own objectives are served when it functions as a prod-
uct vendor or as a platform operator.
• Business Architecture: i* supports the expression of goals and softgoals as well as
means-ends and contribution links. The objectives of a business architecture (e.g., maxim-
ize quantity, maximize price) can be represented as goals as well as softgoals the impact of
different alternatives for achieving those objectives can be compared using means-ends
and contribution links. This information can be used to analyze the impact that each alter-
native has on the currently selected objective and the prospective candidate objective. The
current alternative may be equally suitable for serving both the present and future objec-
tives or it may only be suitable for either of these in which case other alternatives may
need to be considered.
• Channel: i* supports the articulation of strategic dependencies between any kind of actors
such as customers, brokers, resellers, co-sellers, etc. A channel can be depicted as the
chain of dependencies from a focal actor (i.e., business) to a customer. Dependencies be-
tween the business and its customers without any intermediary actors can be thought of to
constitute a direct channel. Whereas, if the business and its customers have dependencies
with mutual intermediaries but not each other – then these can be regarded as constituting
an indirect channel. This information can be used to reason about whether the benefits of
using intermediaries (e.g., business softgoals of revenue scaling, market penetration, etc.)
are outweighed by the vulnerabilities of a hold up problem.
• Technology: i* supports the portrayal of softgoals, tasks, and contribution links. Technol-
ogy alternatives can be represented as tasks and product features can be depicted as soft-
goals. The impacts of alternate technologies on product features can be shown via contri-
bution links. Substitutive technologies (i.e., those that can be used to do the same thing)
can be identified by finding tasks with similar contribution links to common softgoals. The
impacts of different technologies on the overall bundle of features can be used to select the
future technology. The additional softgoals that are supported by the future technology
compared to the past technology can be regarded as sustaining innovation.
4 Conclusion
Section 3 offered possible methods applying i* to express and evaluate strategic pivoting by
startups. There can be other approaches by which i* can be used to represent and reason about
pivoting. While many aspects of i* make it an attractive modeling language for articulating and
analyzing pivoting – it is also limited in three main respects in its ability to support such an
endeavor. These include lack of support for temporal, sequential, and quantitative reasoning.
Our future work is concerned with addressing these limitations as well as further developing
the ideas discussed in section 3 prior to testing and validating them.
i* does not support the notion of relative or absolute time but both concepts can be relevant in
analyzing pivoting. One condition that necessitates pivoting is when the burn rate of a startup
(i.e., the speed with which it is spending its financial resources) exceeds its income and invest-
ments. If a startup does not pivot quickly enough then it can go bankrupt. So, time is an im-
portant dimension for reasoning about pivoting because it can be used to analyze whether or not
pivoting is a necessary option for a startup. Moreover, the amount of time that a startup has to
be able to pivot can determine which type of a pivot it can execute. For example, a product
pivot may take more or less time for a startup than a customer segment pivot. Without being
able to represent the time dimension in i* means that it is difficult to identify which of these
pivots are viable.
i* does not support the notion of precedence or subsequence but both concepts can be relevant
in analyzing pivoting. A startup may only be able to execute a pivot after certain conditions are
met. Similarly, it may only be able to perform other actions after it has pivoted. Without being
able to show the sequential preconditions for pivoting it can be difficult to fully understand the
feasibility of pivoting. Moreover, a start-up may need to execute a combination of pivots albeit
in a certain order. For example, a start-up may first need to implement a zoom out pivot in
order to implement a customer need pivot. Without being able to represent the sequence dimen-
sion in i* means that it is difficult to show one pivot as a prerequisite for another pivot.
i* does not support quantitative reasoning but it can be relevant in analyzing pivoting. Reason-
ing about certain types of pivots is especially dependent on the concept of economic value.
These include business architecture pivot, value capture pivot, and engine of growth pivot. In
each of these pivots, different economic objectives are evaluated in quantitative terms. For
example, they may need to exactly measure the attainment of numerical targets (e.g., revenue,
margin, market share). While the attainment of these metrics can be represented in i* in binary
terms (i.e., as goals), their partial attainment cannot be depicted practically. Without being able
to reason about quantitative aspects of pivoting in i* means that it is difficult to analyze the
economic impact of certain types of pivots in a precise manner.
5 References
1. Ries, E. (2011). The Lean Startup: How today’s entrepreneurs use continuous innovation to
create radically successful businesses. New York: Crown Publishing Group.
2. Blank, S., 2013. Why the lean start-up changes everything. Harvard Business Review 91 (5),
64–68.