Exploring entrepreneurial pivoting and the factors that trigger pivots by tech startups

Abstract

Technology entrepreneurship is an emerging domain in the field of entrepreneurship and the practice-oriented method called the Lean Startup approach (LSA) has made a big impact in this area. However, many technology startups continue to have survivability issues. This study focuses on understanding the theory of entrepreneurial pivoting and its associated factors. In this study, we have collected secondary data comprising 80 tech startups to validate the different types of pivots they pursued by the companies and the factors that triggered the pivoting. The most common pivots among these were found to be customer segment pivot and customer need pivot.

Full text

Exploring entrepreneurial pivoting and the factors that
trigger pivots by tech startups
Pavan Kumar Sala1, Simon P. Philbin1, Safia Barikzai1,2
1Nathu Puri Institute for Engineering and Enterprise, School of Engineering
2Computer Science and Informatics, School of Engineering
London South Bank Univeristy
London, United Kingdom
Email: salap@lsbu.ac.uk, philbins@lsbu.ac.uk, safia.barikzai@lsbu.ac.uk
Abstract—Technology entrepreneurship is an emerging
domain in the field of entrepreneurship and the practice-oriented
method called the Lean Startup approach (LSA) has made a big
impact in this area. However, many technology startups continue
to have survivability issues. This study focuses on understanding
the theory of entrepreneurial pivoting and its associated factors.
In this study, we have collected secondary data comprising 80 tech
startups to validate the different types of pivots they pursued by
the companies and the factors that triggered the pivoting. The
most common pivots among these were found to be customer
segment pivot and customer need pivot.
Keywords—Lean Startup approach; pivots and factors;
technology entrepreneurship.
I. INTRODUCTION
The Lean Startup approach (LSA) is considered as one of
the most popular practitioner-oriented approaches in the
entrepreneurship literature. This approach describes various
aspects including validated learning or customer development,
minimum viable product (MVP), market opportunity
navigation, perseverance and pivoting. Blank (2013), Ries
(2011), and Osterwalder & Pigneur (2010) are considered as
critical contributors to the LSA concept as their books on the
subject have been sold in the millions and the practices adopted
by countless entrepreneurs. However, in the field of
entrepreneurship there remains a gap between academic
research and practitioners. On the one hand, practitioners do not
necessarily pay much attention to research studies and on the
other hand, there is a need for research to fully characterise the
entrepreneurial process [1].
Technology advancement is considered a critical aspect of
economic growth as industries develop through innovating,
exploiting and commercialising emerging technologies.
Entrepreneurship has many domains, and one such domain is
technology entrepreneurship (TE), which is defined as
assembling resources, technical systems and the strategies by
an entrepreneur to pursue opportunities [2]. TE has also been
described in terms of digital entrepreneurship [3].
This exploratory research study focuses on understanding
the concept of technology entrepreneurship in the context of the
Lean Startup approach and entrepreneurial pivoting by startups.
The study seeks to validate the type of pivots pursued by tech
startups and the factors that trigger pivots.
II. LITERATURE REVIEW
A. Technology entrepreneurship
The universal definition of entrepreneurship is
the “creation of new enterprise” [4]. It can also be explained as
the process of extracting revenue from new and distinctive
amalgamations of resources in an uncertain environment.
Entrepreneurship is considered as a positive force that
contributes to the growth of both developed and developing
economies. Furthermore, entrepreneurship has played a
significant role in exploiting technological innovations [3]. It
can be observed that researchers in the field of entrepreneurship
seek to address questions such as the following: How do
entrepreneurs create value propositions? Why do some startups
fail to become sustainable in the long run? How does an
entrepreneur decide whether or not to persevere or pivot? [5],
[6]. Entrepreneurship has sub-branches and arguably
technology entrepreneurship is one of the essential fields.
Indeed, Spiegel and Marxt [2] defined “Formation” and
“Exploitation” as crucial phases of TE. The first phase is
formation, which involves the recognition of opportunities.
Exploitation is the second phase where strategies are developed
to exploit the recognised opportunities. TE has a third phase
known as “Renewal”. Moreover, Eliakis et al. [3] defined
technology entrepreneurship as developing innovative digital
technologies or using such technologies by forming new
startups and transforming existing businesses.
Technology entrepreneurship does not necessarily mean
just adopting digital technologies by technology startups; it acts
as an interface between innovation and entrepreneurship.
Innovation can be defined as a degree of newness by generating
ideas, processes, products, or services that enable a technology

breakthrough. Furthermore, entrepreneurship is inferred as
exploring and exploiting business opportunities to create a
value proposition. The domain of TE can be characterised
through the following: a) science and technology policies; b)
exploration and fostering of new technologies across various
industries; c) government support to science and technology to
stimulate new technologies; and d) market regulations that
govern the entrepreneurial initiatives [7]. Technology
entrepreneurship has gained both academic and policymakers’
interest over the last two decades. Leading entrepreneurs such
as those that founded major tech companies in the Silicon
Valley area in California (USA) were able to succeed due to
identifying and evaluating opportunities to create value
propositions enabled through emerging technologies. However,
researchers like Sobel and Clark [8] argue that even though TE
is widely recognised, it still lacks a unified framework [9].
Furthermore, TE has evolved further and broadened through
assimilation and evolution of new topics in the literature on
entrepreneurship. One such new topic is product or service
development based on customer feedback, which has been
considered as the need to "probe and learn the process" [10].
B. Entrepreneurial pivoting
During the inception and launch phases, a tech startup
undergoes frequent changes in the business model and the
value-capturing technique due to resource scarcity and external
market conditions. In this regard, startup companies can adopt
the Lean Startup approach. The global manufacturing industry
adopted the principles of lean philosophy over the last several
decades. The five principles of lean are as follows: a) creating
value to the customers; b) identifying the value stream; c)
creating a process flow to prevent breakdowns, re-entrant loops,
low-quality products or services; d) producing high-quality
products that are efficient and valuable for the customers; e)
identifying and eliminating excess engineering hours in order
to be cost-effective [11].
Startups are defined as a group of talented people trying to
seize an opportunity by turning an idea into a product [12]. An
entrepreneur may encounter a question, i.e., whether to
persevere or pivot while commercializing their idea to develop
a competitive product or service. Eric Ries author of The Lean
Startup and an entrepreneur defined the pivot as a "structural
course of correction designed to test a new fundamental
hypothesis" [13]. He says entrepreneurs should pivot from time
to time to learn the customers' needs, problems, and preferences
to develop a market-fit product or service [14]. The LSA model
emphasises experimental entrepreneurship to explore
opportunities, which can be viewed as an active search and
iterative design solution. In such a case, companies such as GE,
Motorola, Searle and Corning are some of the examples that
have followed the probe and learn process [15]. For any
organization, continuous innovation will help develop new
ideas, products, and organizational structure to support long-
term goals. Those strategies help to further build the success of
companies. It has been reported that Facebook and Twitter are
two classic examples of pivoting [13].
A total of fourteen pivots have been identified from the
literature [12, 13, 16] that are further categorized into four
levels, which are as follows: Product level pivots are those that
lead to a change in the products/services offered by the
company (1). Market level pivots focus on customers and the
market in which a company operates (2). Strategy level pivots
focus on the way to generate more value for the company (3).
People level pivots are associated with resources in a startup
(4). Table I illustrates all the pivots categorized under the above
four levels.
TABLE I. TYPES OF PIVOTS. SOURCE: [12, 13, 16]
S. No
Level
Name of pivot
Source
I
Product
level pivot
Zoom
-
in pivot
Ries [1
3
]
Zoom
-
out pivot
Technology pivot
Platform pivot
II
Market level
pivot
Customer segment pivot
Ries [1
3
]
Customer need pivot
Channel pivot
Market segment pivot
a
Bajwa [1
6
]
III
Strategy
level pivot
Value capture pivot
Ries [1
3
]
Business architecture
pivot
Engine of growth pivot
Complete pivot
Bajwa [1
6
]
Side project pivot
Bajwa [1
6
]
IV
People level
pivot
Social pivot
Hirvikoski [1
2
]
a. Name changed from zoom-in pivot to market segment pivot
The market segment pivot (name changed from zoom-in
pivot to avoid confusion), complete pivot and side-project pivot
were identified by Bajwa [16]. The social pivot was identified
by Hirvikoski [12], and the remaining ten pivots were identified
by Ries [13]. Furthermore, Bajwa [16] identified eleven factors
may trigger a startup to change its direction (pivot). Table 2
illustrates all of these factors.
TABLE II. FACTORS THAT TRIGGER PIVOTS. SOURCE: [16]
S. No Factors
I Customer feedback (positive and negative feedback)
II Technology challenges
III Competition
IV Unscalable business
V Wrong timing
VI Market conditions
VII Influence of investor, partner or founder
VIII Legal issues

S. No Factors
IX Flawed business model
X Side project success
XI Business financials
III. RESEARCH APPROACH
The objective for this research study is to validate the type
of pivots pursued by startup companies and the factors that
trigger such pivots. In order to address this objective, we
collected secondary data from various academic journals and
company websites. Secondary data is a dataset that a researcher
does not collect by him/herself but instead analyses existing
data [17]. The benefits of using secondary data are eliminating
financial and logistical obstacles while collecting primary data
[18]. However, certain precautions must be taken. A researcher
should elucidate the limitations using secondary data and
explain the actions taken to use the original data set for the new
research gap. The secondary data should be conscientiously
interpreted to generate a hypothesis and not to prove hypothesis
[17], [18].
As part of the secondary data collection, we reviewed
academic articles [16, 19, 20] that discuss different types of
pivots and possible factors behind pursuing those pivots. At the
same time, we have searched the internet to identify technology
startups/companies that have pivoted. Examples of the search
keywords used in the internet search are as follows: “business
pivots”, “pivots by startups”, “famous business pivots” and
“pivots”. While looking for data, we focussed only on tech
startup companies to understand what type of pivots they have
pursued. The intention behind collecting the secondary data is
to understand what type of pivots have been pursued by
technology startup companies. The secondary data was
collected from multiple sources (academic articles and different
websites), out of which 60% was collected from Bajwa et al.,
[14], 30% was from the internet (different websites searched in
google) and the remaining 10% was from Comberg et al. [19],
Terho et al. [20] and Hirvikoski [12]. We collected data of
startup companies from across the globe and this includes
startups from Canada, Finland, France, Germany, India,
Ireland, Israel, Japan, Mexico, Republic of Tunisia, Spain, UK
and USA.
The secondary data study shows what type of pivots pursued
by tech startups/companies and how successful they are after
pivoting. Tech companies such as Twitter and Facebook are
international examples that pivoted at a very early stage of their
journey [12]. During data collection, we came across websites
that illustrated the startup companies that pivoted to face
pandemic situation caused due by COVID-19. We studied the
types of pivots those tech startups pursed and labelled their
factor as market condition (due to pandemic).
Table III provides the details of companies that pursued
pivots and the factors that trigger pivots. We have anonymized
the company names.
TABLE III. COMPANIES WITH PIVOTS THEY PURSUED AND FACTORS
ASSOCIATED WITH THOSE PIVOTS. SOURCES: [12, 16, 19-34]
Company Factor (s) Pivot (s)
Company-1 Influence of investor,
partner or founder
Platform pivot
Company-2 Customer feedback
(positive)
Platform pivot
Company-3 Market conditions
(due to pandemic)
Platform pivot
Company-4 Market conditions
(due to pandemic)
Value capture pivot
Company-5 Customer feedback
(negative)
Zoom-in pivot
Company-6 Unscalable business Customer need pivot
Company-7 Flawed business model Zoom-out pivot
Company-8
Influence of investor,
partner or founder, flawed
business model, market
conditions, business
financials and technology
challenges
Customer segment
pivot, business
architecture pivot,
value capture pivot
and engine of growth
pivot
Company-9 Customer feedback
(negative)
Customer need pivot
Company-10 Unscalable business Customer need pivot
Company-11 Legal issue Complete pivot
Company-12 Wrong timing and
unscalable business
Customer need pivot
Company-13 Flawed business model Customer segment
pivot
Company-14
Influence of investor,
partner or founder, flawed
business model, market
conditions, business
financials and technology
challenges
Customer segment
pivot, channel pivot,
engine of growth pivot
and value capture
pivot
Company-15 Unscalable business Zoom-out pivot
Company-16 Market conditions
(due to pandemic)
Value capture pivot
Company-17 Market conditions
(due to pandemic)
Complete pivot
Company-18
Customer feedback
(negative) and flawed
business model
Complete pivot
Company-19 Customer feedback
(positive)
Customer segment
pivot
Company-20 Market conditions
(due to pandemic)
Customer segment
pivot
Company-21 Customer feedback
(positive)
Zoom-in pivot
Company-22 Market conditions
(due to pandemic)
Complete pivot and
business architecture
pivot
Company-23 Competition Zoom-in pivot
Company-24 Side project success Side project pivot
Company-25 Market conditions
(due to pandemic)
Platform pivot
Company-26
Customer feedback
(negative) and flawed
business model
Customer need pivot
and customer segment
pivot
Company-27 Side project success Side project pivot
Company-28 Market conditions
(due to pandemic)
Market segment pivot
Company-29 Unscalable business Customer need pivot
Company-30 Market conditions
(due to pandemic)
Business architecture
pivot
Company-31
Flawed business model,
technology challenges and
unscalable business
Zoom-out pivot,
platform pivot,
customer segment
pivot, channel pivot
and business
architecture pivot

Company Factor (s) Pivot (s)
Company-32 Customer feedback
(positive)
Market segment pivot
Company-33 Market conditions
(due to pandemic)
Customer need pivot
Company-34 Customer feedback
(positive)
Zoom-in pivot
Company-35 Customer feedback
(negative)
Customer need pivot
Company-36 Market conditions
(due to pandemic)
Market segment pivot
Company-37 Customer feedback
(negative)
Customer segment
pivot
Company-38 Market conditions
(due to pandemic)
Customer need pivot
Company-39 Market conditions
(due to pandemic)
Side project pivot
Company-40 Side project success Side project pivot
Company-41
Influence of investor,
partner or founder, flawed
business model, market
conditions and technology
challenges
Technology pivot,
channel pivot, engine
of growth pivot and
value capture pivot
Company-42 Market conditions
(due to pandemic)
Business architecture
pivot
Company-43 Unscalable business and
technology challenges
Zoom-in pivot, Zoom-
out pivot and
technology pivot
Company-44
Unscalable business and
customer feedback
(positive)
Complete pivot and
customer need pivot
Company-45 Technology challenges Technology pivot
Company-46 Flawed business model Customer need pivot
Company-47 Unscalable business Complete pivot
Company-48 Influence of investor,
partner or founder
Complete pivot
Company-49
Influence of investor,
partner or founder and side
project success
Side project pivot
Company-50 Influence of investor,
partner or founder
Customer need pivot
Company-51 Market conditions
(due to pandemic)
Platform pivot
Company-52
Customer feedback
(positive) and wrong
timing
Zoom-in pivot
Company-53
Customer feedback
(negative), unscalable
business and competition
Complete pivot
Company-54 Customer feedback
(negative)
Complete pivot
Company-55 Customer feedback
(positive)
Zoom-in pivot
Company-56 Competition Customer need pivot
Company-57
Customer feedback
(negative) and influence of
investor, partner or founder
Channel pivot
Company-58 Customer feedback
(negative)
Zoom-in pivot
Company-59 Customer feedback
(positive)
Customer segment
pivot
Company-60
Influence of investor,
partner or founder, flawed
business model and
business financials
Customer segment
pivot, value capture
pivot and engine of
growth pivot
Company-61 Influence of investor,
partner or founder
Complete pivot
Company-62 Unscalable business Platform pivot
Company-63 Technology challenges Platform pivot
Company Factor (s) Pivot (s)
Company-64
Flawed business model,
business financials and
marker conditions
Zoom-in pivot, Zoom-
out pivot, customer
segment pivot and
business architecture
pivot
Company-65
Unscalable business and
customer feedback
(positive)
Customer need pivot
Company-66 Influence of investors,
partners or founders
Side project pivot
Company-67 Unscalable business Complete pivot
Company-68 Competition Complete pivot
Company-69 Customer feedback Customer need pivot
Company-70 Customer feedback
(positive)
Zoom-in pivot
Company-71 Market conditions
(due to pandemic)
Side project pivot
Company-72 Market conditions Value capture pivot
Company-73 Technology challenges Technology pivot and
customer need pivot
Company-74 Customer feedback
(positive)
Complete pivot
Company-75 Technology challenges Technology pivot and
customer need pivot
Company-76 Customer feedback
(positive)
Customer need pivot
Company-77 Market conditions
(due to pandemic)
Value capture pivot
Company-78 Market conditions
(due to pandemic)
Platform pivot
Company-79
Customer feedback
(negative) and wrong
timing
Customer need pivot
Company-80 Side project success
Side project pivot and
customer segment
pivot
IV. RESULTS
The objective behind studying the 80 technology startup
companies through collecting secondary data was to secure a
more in-depth understanding of pivoting and its associated
factors. While analysing the secondary data, we calculated
across the 80 companies the number of times (and percentage)
a pivot was pursued and number of times a factor triggered
pivoting, which is provided in Table IV and V respectively. The
bar charts (Fig. 1 and 2) are graphical representations of these
tables. For example, the factor customer feedback was a driver
for selecting a pivot by twenty-seven different startups. Of these
twenty-seven startups, seven of them used zoom-in pivot; four
startups pursued customer segment pivot; eight startups
pursued customer need pivot; five startups pursued complete
pivot while three startups pursued platform pivot, channel pivot
or a market segment pivot.
TABLE IV. FREQUENCY OF PIVOTS PURSUED BY THE TECH STARTUPS
Type of pivots No. of times pursued Percentage
Social pivot 0 0%
Market segment pivot 2 1%
Complete pivot 8 4%
Technology pivot 9 5%

Type of pivots No. of times pursued Percentage
Zoom-out pivot 10 5%
Platform pivot 11 6%
Zoom-in pivot 13 7%
Channel pivot 14 7%
Business architecture pivot 14 7%
Engine of growth pivot 17 9%
Side project pivot 17 9%
Value capture pivot 21 11%
Customer need pivot 23 12%
Customer segment pivot 28 15%
Grand Total 187 100%
The bar chart in Fig. 1 represents the frequency of each
pivot pursued by a tech startup. For instance, customer segment
pivot was the highest pursued pivot (N=28, 15%). Customer
need pivot is the second most pursued pivot among the 80
startup companies (N=23, 12%) followed by value capture
pivot (N=21, 11%). Market segment pivot is the least pursued
pivot (N=2, 1%). We could not identify a single tech startup
that pursued social pivots in order to validate.
Fig. 1. Frequency of pivots pursued by the tech startups
TABLE V. FREQUENCY OF FACTORS THAT TRIGGERED PIVOTS
Factors No. of times occurred Percentage
Legal issues 1 1%
Wrong timing 3 2%
Competition 4 2%
Side project success 5 3%
Business financials 15 8%
Market conditions 17 9%
MC-Pandemic 19 10%
Unscalable business 20 11%
Influence of investor,
partner or founder 22 12%
Factors No. of times occurred Percentage
Technology challenges 24 13%
Customer feedback 27 14%
Flawed business model 30 16%
Grand Total 187 100%
Fig. 2 illustrates the frequency of each factor that has
triggered a tech startup company to pivot. For example, the bar
chart shows that the flawed business model was the most
triggered factor (N=30, 16%), followed by customer feedback
(N=27, 14%) and technology challenges (N=24, 13%).
Whereas competition (N=4, 2%), wrong timing (N=3, 2%) and
legal issues (N=1, 1%) are the least triggered factors. Therefore,
the customer segment, customer need, and value capture pivots
are the most pursued pivots. Similarly, the flawed business
model, customer feedback and technology challenges are the
most triggering factors.
Fig. 2. Frequency of each factor that triggered the pivot
V. CONCLUSION
This exploratory research study focuses on understanding
the concept of technology entrepreneurship through examining
the lean startup approach, pivots and the factors that trigger
such pivots. Technology entrepreneurship is a critical field that
can enhance economic growth and create new technology-
driven market opportunities [3]. Therefore, the question arises:
How can a technology startup company survive in the long run?
One way to address the question is by implementing LSA. As
the Lean Startup approach (LSA) encourages startups to
interact with customers and promotes them to test new
fundamental hypotheses to improve the product/service based
on the feedback [35]. From the secondary data analysis, we
observed that the most frequently pursued pivots are customer-
oriented types of pivots i.e., customer segment pivot (15%) and
customer need pivot (12%) followed by the value capture pivot
(11%). However, we could not identify any examples for the
social pivot which was proposed by Hirvikoski [12].
Pivoting is defined as changing the course of direction by a
tech startup. Product, market, strategy and people level pivots
are the four categories out of which a startup can opt a single
pivot or multiple pivots to test their new hypothesis. However,
0
2
8
9
10
11
13
14
14
17
17
21
23
28
0 5 10 1 5 20 25 3 0
Social pivot
Market Segment Pivot
Complete pivot
Technology pivot
Zoom-out pivot
Platform pivot
Zoom-in pivot
Channel pivot
Business architecture pivot
Engine of growth pivot
Side project pivot
Value capture pivot
Customer need pivot
Customer segment pivot
No. of times pursued
1
3
4
5
15
17
19
20
22
24
27
30
0 5 10 15 20 2 5 30 3 5
Legal issues
Wrong timing
Competition
Side project success
Business financials
Market conditions
MC-Pandemic
Unscalable business
Influence of investor, partner or founder
Technology challenges
Customer feedback
Flawed business model
No. of times triggered

the following aspects are yet to be explored: How many times
a tech startup has to pivot to identify a market fit product? Does
a pivot lead to another pivot (i.e., a domino effect)? Whether
there is a correlation between pivots and the factors? Therefore,
future research should focus on collecting primary data to
identify new pivots and factors, determine the domino effect,
and the influence of pivoting on the value proposition.
ACKNOWLEDGMENT
This research study is funded by The Puri Foundation and
their support is gratefully acknowledged.
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