Analytics Case Study

European Journal of Operational Research 281 (2020) 642–655

Contents lists available at ScienceDirect

European Journal of Operational Research

journal homepage: www.elsevier.com/locate/ejor

Actualizing business analytics for organizational transformation: A

case study of Rovio Entertainment

Yenni Tim a , ∗, Petri Hallikainen b , Shan L Pan c , Toomas Tamm d

a School of Information Systems and Technology Management, UNSW Business School, University of New South Wales (UNSW), Room 2085, West Wing,

Quadrangle, Sydney 2052, Australia b Business Information Systems, University of Sydney Business School, Rm 4073, Abercrombie Building (H70), NSW 2006, Sydney, Australia c School of Information Systems and Technology Management, UNSW Business School, University of New South Wales (UNSW), Room 2015, West Wing,

Quadrangle, Sydney 2052, Australia d School of Information Systems and Technology Management, UNSW Business School, University of New South Wales (UNSW), Room 2111, West Wing,

Quadrangle, Sydney 2052, Australia

a r t i c l e i n f o

Article history:

Received 5 February 2018

Accepted 29 November 2018

Available online 12 December 2018

Keywords:

Business analytics

Technology affordances

Effective use

Value creation

Organizational transformation

a b s t r a c t

Increased access to data and affordable technologies today has made business analytics within the reach

of most organizations. However, many organizations are unsure of how to translate their analytics use

into organizational value. While the area of business analytics value creation has become a popular point

of discussion amongst practitioners, much research is needed to provide insights into the effective use of

business analytics. The objective of this paper is to deepen understanding in the effective implementation

of analytics within organizations. Specifically, we performed an in-depth case study at Rovio Entertain-

ment to investigate how a pioneer in mobile games initiated an analytics-driven transformation. This

study contributes to the theory and practice of business analytics in two ways. First, drawing on the per-

spective of technology affordances, this study sheds light on the varying affordances of business analytics.

Second, this study presents empirically-informed insights on how these affordances could be effectively

actualized for an analytics-driven transformation in an organization. Collectively, this study opens up the

black-box of effective implementation of business analytics for organizational value creation.

© 2018 Elsevier B.V. All rights reserved.

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1. Introduction

Businesses today are becoming increasingly intrigued by the

possibilities of business analytics (hereafter BA) to create value

( Chen, Chiang, & Storey, 2012; Ransbotham, Kiron, & Prentice,

2015 ). While many organizations recognize the power of BA

( LaValle, Lesser, Shockley, Hopkins, & Kruschwitz, 2011 ), many are

overwhelmed by the far-reaching changes required to transform

into a data-driven organization ( Brydon & Gemino, 2008; Rans-

botham et al., 2015; Vidgen, Shaw, & Grant, 2017 ). To date, there

is insufficient empirical research about how organizations could

translate their BA use into organizational value ( Fink, Yogev, &

Even, 2017; Hindle & Vidgen, 2018; Vidgen et al., 2017 ). The ob-

jective of this paper is to improve the understanding of how BA

∗ Corresponding author. E-mail addresses: [email protected] (Y. Tim), [email protected].

au (P. Hallikainen), [email protected] (S.L. Pan), [email protected]

(T. Tamm).

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https://doi.org/10.1016/j.ejor.2018.11.074

0377-2217/© 2018 Elsevier B.V. All rights reserved.

an be effectively implemented and actioned in an organization for

alue creation.

We have performed an in-depth case study of Rovio Entertain-

ent to investigate an organization that has recently completed

BA-driven transformation. As with other industries, a wave of

A adoption is emerging in the gaming industry, driven by the

vailability of massive user data and analytics technologies, as well

s the rise of the freemium business model ( Voigt & Hinz, 2016 ).

n response to these environmental changes, Rovio Entertainment,

company that has seen incredible success with its Angry Birds

ame franchise, initiated a transformation towards becoming a

ore data-driven organization.

We adopt the technology affordances perspective ( Majchrzak

Markus, 2012 ) as our theoretical lens to uncover the underly-

ng mechanisms of Rovio’s successful implementation of BA. The

echnology affordances perspective serves as a lens for researchers

o identify the important potentials of a technology, and to the-

rize the actions required to effectively actualize those potentials

o achieve desirable outcomes ( Majchrzak & Markus, 2012; Strong

t al., 2014 ). By conducting an in-depth qualitative exploration

Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655 643

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sing this theoretical perspective, we are able to develop insights

n how the affordances of BA can be effectively actualized for

alue creation.

Collectively, our findings contribute to both the theory and

ractice of BA by revealing the mechanisms by which BA are actu-

lized for organizational value creation. Theoretically, our findings

pen up the black-box of effective implementation of BA through

dentifying the varying technological and organizational features

hat drive the actualization of BA affordances. This conceptualiza-

ion contributes insights to an emerging literature that aims to

nderstand analytics-driven value creation in organizations ( Fink

t al., 2017; Hindle & Vidgen, 2018; Vidgen et al., 2017 ). For prac-

itioners, our findings make explicit the goals, expertise and or-

anizational arrangements required to actualize the affordances of

A to create organizational value. These insights provide necessary

uidance for practitioners to derive value from their increasing in-

estment in BA ( Ransbotham et al., 2015; Ransbotham, Kiron, &

rentice, 2016; Vidgen et al., 2017 ).

The rest of this paper is organised as follows. In Section 2 ,

e present a review of the literature on BA use for organiza-

ional value creation. We then discuss the emerging use of BA in

he gaming industry to provide a foundation for this research. In

ection 3 , we discuss the theoretical underpinnings of this study

nd outline how the perspective of technology affordances is par-

icularly suited for our investigation. In Section 4 , we discuss our

esearch design. In Section 5 , we provide a case description of

ovio’s analytics-driven transformation. In Section 6 , we present

he rich description of our analysis, and in Section 7 , we dis-

uss our empirically-grounded findings. We conclude with a dis-

ussion of the theoretical and practical contributions of the paper

n Section 8 .

. Literature review: business analytics for organizational value

reation

In this section, we first present a review of the literature on BA-

nabled value creation. In this discussion, we outline the specific

pportunities and challenges faced by organizations in actualizing

alue from their uses of business analytics. Second, following from

he organizational context of our study, we present a review on BA

se in the gaming industry. We focus on a recent shift of the dom-

nant business model in this industry (from premium to freemium

ames) and discuss the role of BA in this transformation. Taken to-

ether, through this literature review, we have identified the need

or more empirical research on how BA can be effectively lever-

ged for organizational value creation. We present a summary of

his research gap at the end of this review section.

.1. BA and organizational value creation

In this paper, we adopt the widely-cited definition of business

nalytics as “the extensive use of data, statistical and quantita-

ive analysis, explanatory and predictive models, and fact-based

anagement to drive decisions and actions” ( Davenport & Harris,

007 , p. 7). Henceforth, we use the abbreviation “BA” and “ana-

ytics” interchangeably to refer to “business analytics” as per the

bove definition. This view of analytics focuses on what BA af-

ords, and how BA can be actualized to inform action and create

alue ( Davenport & Harris, 2007 ). In today’s business environment,

ata and BA tools have become more available and accessible for

rganizations ( Brydon & Gemino, 2008 ). The challenge in organi-

ational BA use however, relates to understanding how insights

erived from analytics can be translated into actions and organi-

ational value ( Fink et al., 2017; George, Haas, & Pentland, 2014;

ansbotham et al., 2015; Vidgen et al., 2017 ).

Several scholars have highlighted that in addition to having ac-

ess to BA tools, it is important to consider several organizational

spects that play a role in effective BA use ( Brydon & Gemino,

008; Hindle & Vidgen, 2018; Trieu, 2017; Vidgen et al., 2017 ).

aValle et al. (2011) highlighted that the biggest barriers to har-

ess value from analytics are often not technological, but manage-

ial and cultural. Davenport and Patil (2012) suggested that data

cientists are the “primary gating factor” in determining whether

A will be effective within an organization. Abbasi, Sarker, and Chi-

ng (2016) also pointed out how professionals in varying roles are

ncreasingly expected and required to make use of data and analyt-

cs to improve their work. A large-scale survey conducted by Kiron,

erguson, and Prentice (2013) further suggests that successful an-

lytical companies often have senior managers who embrace and

upport analytics, and possess a widely shared belief that BA is a

ore asset that enhances the organization’s competitive edge. Pape

2016) also pointed out that the success of an organization’s BA

trategy requires many considerations ranging from the selection

f data and the quantifying of the data items’ value. Collectively,

ultivating a data-oriented culture is found to be fundamental to

he effective use of analytics in organizations ( Kiron, Shockley, Kr-

schwitz, Finch, & Haydock, 2011 ).

Taken together, insights from existing research reiterate the

iew that “value is created only when the data is analyzed and

cted on” ( Watson, 2014 , p. 1252, emphasis added). However, to

ate, only a handful of research focuses on a concrete understand-

ng of how organizations can derive value from analytics. For ex-

mple, Vidgen et al. (2017) investigated the challenges faced by

anagers in leveraging BA to create value. Using a mixed method

pproach, Vidgen et al. (2017) have identified 31 challenges faced

y organizations in building the required analytics capabilities.

he authors then proposed recommendations and checklists to

uide managers through data-driven transformation. More recently,

indle and Vidgen (2018) proposed a business analytics methodol-

gy involving four activities to guide practitioners in drafting an-

lytics initiatives. The proposed methodology focuses on business

odel building and introduces several techniques for organizations

o develop a rich picture of their business practices.

.2. BA use in the gaming industry

In this paper, we investigate the mechanisms of BA-enabled

alue creation in the gaming industry. As with other industries, BA

as emerged as an important catalyst for competition and inno-

ation amongst companies in the gaming industry ( Watson, 2014 ).

pecifically, a few changes in the gaming landscape over the past

ecade have increased the importance of BA for gaming compa-

ies. First, the increasing use of mobile devices has resulted in the

xplosive growth of mobile games ( Chulis, 2012 ). Second, the pop-

larity of social media platforms has stimulated the growth of so-

ial games, which focus on interaction and competition between

layers ( Liu, Li, & Santhanam, 2013 ). Third, the proliferation of ca-

ual gaming, combined with changes in player demographics and

references, has led to a decline in “pay-to-play” console and com-

uter games and the rise of a freemium business model ( Chulis,

012; Kumar, 2014 ).

The freemium model has rapidly become the dominant pric-

ng model for social network applications and games in the recent

ecade ( Kumar, 2014; Voigt & Hinz, 2016 ). In the gaming industry,

reemium business model is also known as “free-to-play” (F2P). In

016, 97 percent of mobile gaming revenue came from free-to-play

ames ( Newzoo, 2017 ). The rise of F2P is significant as it signals

shift from the long-established, product-based business model

n the gaming industry towards a highly dynamic, service-based

odel. As with any new business model, there are challenges to

e addressed by gaming companies in this transition. For example,

644 Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655

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the monetization mechanisms between the two models are drasti-

cally different ( Chulis, 2012 ). Historically, games are developed as a

product and monetized through either a one-off payment or an on-

going subscription. In the F2P paradigm however, monetization re-

lies on in-game micro-purchases, such as the sale of virtual goods,

as well as in-game advertising. In other words, in the new model,

value is created by both developers and users through constant en-

gagement ( Oestreicher-Singer & Zalmanson, 2013 ). It is therefore

becoming increasingly important for freemium companies to better

understand player behavior in order to make strategic adjustments

to optimize profitability ( Voigt & Hinz, 2016 ).

Triggered by these shifting requirements, gaming companies

have started to adopt analytics to secure a stake in the fast-

growing gaming industry, which is estimated to reach $65 billion

in revenue by 2020 ( Newzoo, 2017 ). BA affords the opportunity to

analyze player data for effective marketing and data-driven mon-

etization ( Chulis, 2012 ), ultimately allowing gaming companies to

become more flexible when developing customer-driven products

and services ( Watson, 2014 ). Because BA use in the gaming indus-

try has only emerged recently, research on game analytics is still

in its initial phases, with related publications stemming from the

early 2010s, primarily in the form of conference papers and work-

shop proposals (e.g., Andersen, Liu, Snider, Szeto, & Popovi ́c, 2011;

Deterding, Björk, Nacke, Dixon, & Lawley, 2013; Nacke & Drachen,

2011 ). These studies, as well as two recent books on the topic (i.e.

El-Nasr, Drachen, & Canossa, 2016; Loh, Sheng, & Ifenthaler, 2015 ),

primarily focus on defining the technicalities related to how an-

alytics can be used to inform a better design of game features

and experience. These discussions have revealed several important

game-play and player metrics that could be used by game compa-

nies to measure the performance of their games.

However, there appears to have been little attention to date

on the organizational implementation of game analytics. This lack

of research might be attributed to a misconception that effective

implementation of analytics is simply about having access to ap-

propriate analytics technologies ( Vidgen et al., 2017 ). As recent re-

search has pointed out, value creation from BA is in fact a pro-

cess of complicated organizational changes, such as business model

alignment ( Hindle & Vidgen, 2018 ) and changes in organizational

processes and strategies ( Vidgen et al., 2017 ). Against this back-

drop, we argue that investigating the effective actualization of BA

in the gaming industry is important for two reasons. First, the

gaming industry is evolving rapidly today with a new focus on BA-

driven value creation. Many game companies have, or are in the

process of, adopting game analytics today but there is little in-

formation and guidance available for how gaming companies can

leverage BA for value creation. Second, and broadly, a study of

effective BA im plementation could provide valuable insights for

other organizations looking to embark on a BA-driven transfor-

mation in response to changing environment. An understanding

of BA-driven transformation is relevant and insightful for most of

today’s organizations; notwithstanding, lessons learned from the

gaming industry will be particularly relevant for organizations op-

erating in a similar industry environment, such as internet start-

ups offering digital products.

3. Theoretical background: technology affordances and

actualization

In this study, we adopt the perspective of technology affor-

dances to theorize the organizational uses and implications of BA

in the game industry. The concept of affordances originates from

Gibson (1979) work in the field of ecological psychology. Gibson

(1979) first developed the concept of affordances to explain the

possibilities an object affords f or action. The concept of technology

affordances was then introduced by scholars in the recent decade

o capture the action potentials of technological objects ( Majchrzak

Markus, 2012; Majchrzak, Faraj, Kane, & Azad, 2013 ). Specifically,

echnology affordances refer to “what an individual or organization

ith a particular purpose can do with a technology” ( Majchrzak &

arkus, 2012 , p. 1).

Technology affordances is a relational concept ( Strong et al.,

014; Vaast, Safadi, Lapointe, & Negoita, 2017 ). It focuses not only

n technological features, but also takes into account how actors

erceive and interact with the technology ( Markus & Silver, 2008;

aast et al., 2017 ). Adopting this perspective is vital for schol-

rs in considering how organizational features, including “exper-

ise, organizational processes and procedures, controls, boundary-

panning approaches, and other social capacities present in the

rganization” ( Zammuto, Griffith, Majchrzak, Dougherty, & Faraj,

007 , p. 752) interact with features of a technology, and how this

nteraction influences the use of the technology ( Burton-Jones &

olkoff, 2017; Hasan, Henry Linger, Choy, & Schlagwein, 2016 ).

Scholars previously have adopted the perspective of technology

ffordances to identify action potentials of technological artifacts

n facilitating the attainment of organizational goals. Most of these

xisting studies focus on proposing higher-order categorization

or technological affordances or introduce different types of affor-

ances (see, for example, Leonardi, 2013; Treem & Leonardi, 2013 ).

evertheless, given the relational property of this concept, tech-

ology affordance is a “potentiality that only exists when leveraged

ithin a specific domain and set of actions” ( Majchrzak et al., 2013 ,

. 39). The same technology could then support different affor-

ances and lead to different organizational outcomes when lever-

ged within different domains and sets of actions ( Rice et al., 2017;

trong et al., 2014; Vaast et al., 2017 ).

Accordingly, scholars have begun to call for a theorization on

ffordance-actualization (see, f or example, Burton-Jones & Volkoff,

017; Strong et al., 2014 ; and Tim, Pan, Bahri, & Fauzi, 2018 ).

ffordance-actualization captures the process where actors realize

specific action potential afforded by a technological artifact to

acilitate a specific goal-oriented action ( Strong et al., 2014 ). Con-

eptualizing affordance-actualization allows scholars to capture the

rocess where a technological potentiality is discovered and articu-

ated to support a certain task, as well as aids their understanding

f the concrete outcomes of actualization ( Burton-Jones & Volkoff,

017 ). To date, a handful of existing research has provided con-

eptualizations for affordance-actualization to understand the vari-

us ways in which actors adopt and appropriate a technology, and

ow the actualization process leads to the achievement of certain

rganizational outcomes. Appendix A summarizes some of these

xisting studies. These studies have inspired our theorization as

hey provide an example into how attending to the importance

f affordance-actualization could lead to a better understanding of

igitally-enabled organizational change ( Anderson & Robey, 2017 ).

As such, we argue that the technology affordances perspective

s well-suited to address our research objective. Firstly, this per-

pective allows an investigation into how technological potentials

ould be actualized in a particular organizational context to facil-

tate a specific goal-oriented action ( Strong et al., 2014 ). Secondly,

his perspective not only describes the characteristics of a tech-

ology, but provides scholars with an opportunity to understand

ow organizational features play a part in leveraging technologi-

al potentials to enable a particular change or outcome ( Bygstad,

unkvold, & Volkoff, 2016; Strong et al., 2014; Zammuto et al.,

007 ). This perspective serves as an important sensitizing device

n this study because it is not obvious what effective organiza-

ional BA use involves. Using this perspective, we conceptualize the

ffective actualization of BA in organizations as an entanglement

f technology features, organizational processes and goals. A con-

eptualization of affordance-actualization allows us to answer the

uestion of how BA use could translate into organizational value.

Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655 645

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. Research method

.1. Research design and case selection

We started this research with an aim to understand how orga-

izations adopt BA to create value. Given the exploratory nature

f our research topic, we chose the qualitative case study ( Pan &

an, 2011; Walsham, 1995 ) and an interpretive approach ( Klein &

yers, 1999; Walsham, 1995 ) to develop a rich theoretical under-

tanding of the phenomenon and to answer our research question.

e provide a summary of our research design and key method-

logical considerations in Table 1 .

.2. Data collection

Interviews were our primary data source. Prior to our on-

ite visit, we collected and reviewed publicly available data from

ovio’s official channels, press releases, and news articles to de-

elop a basic understanding of the case organization and its trans-

ormation initiative. Our site visit and interviews took place in

une 2016 at Rovio’s headquarters located in Espoo, Finland. In to-

al, we conducted more than 12 hours of interviews with Rovio’s

mployees in a broad variety of roles and at different levels (see

ppendix B for a full list of interviewees). Our interviews were

emi-structured with a primary focus on open-ended questions.

e first asked our interviewees to provide an overview of Rovio’s

ransformation initiative, and then to elaborate in detail on the

elevant facts and key events (see Appendix C for the interview

uide). Questions were adapted along the way to gather more data,

epending on the interviewees’ role in the transformation. Our

nderstanding of prior research on BA adoption and affordance-

ctualization sensitized us to more questions to ask. Neverthe-

ess, we maintained flexibility during the interview process, hav-

ng non-leading conversations when necessary ( Myers & Newman,

007 ). We also cross-checked information gathered from intervie-

ees against publicly available materials to control for retrospec-

ive bias.

We complemented this data with a range of published materi-

ls surrounding the case to capture contextual complexity and for

riangulation. We first reviewed articles and reports available on

ovio’s official website to reconstruct details of its transformation

ourney. One of the key sources of published data that com-

lemented and confirmed our analysis was the official Offering

ircular document released by Rovio in line with its initial public

ffering ( Rovio, 2017 ). This 4 4 4-page official document provided

n unprecedented view of Rovio’s internal processes. It details

able 1

esearch design and key methodological consideration.

Methodological consideration

Case study approach and case selection

• Research aim was to investigate the effective actualization of BA for organizational value creation

• Theoretical sampling to select a revelatory case to study this phenomenon of interest

Interviews as primary data source • Snowballing technique ( Myers & Newman, 2007 ) to recruit suitable

interviewees • Principles of openness, flexibility and improvisation to make necessary

adjustments during the data collection process ( Myers & Newman, 2007 )

Multiple data sources for triangulation

• A rich set of data sources (see Table X) for triangulation to add breadth and depth to our analysis ( Flick, von Kardoff, & Steinke, 2004 )

ow analytics provides Rovio with a strong competitive advantage

n the market. This emphasis signals the importance of analytics

t Rovio, which confirms the significance of the focus of this

tudy. The specific analytics examples provided in the document

re also consistent with our interview data and analysis, which

eaffirms the reliability of our findings. We also reviewed all

fficial social media channels of Rovio and captured all relevant

nformation to complement our interviews. Overall, data collected

rom different sources enabled a triangulated understanding of

ovio’s BA-enabled transformation. Our data sources and their role

n the data analysis is summarized in Table 2 .

.3. Data analysis

We approached our analysis from an interpretive perspective

nd adopted the theoretical lens of technology affordances as our

sensitizing device” ( Klein & Myers, 1999 , p. 75) to guide our

ense-making of the rich data. In interpretive research, data anal-

sis is started as soon as data collection commences. In the first

hase of our data analysis, we focused on developing narratives

o delineate the transformation journey at Rovio. At this stage, we

ade use of data from a variety of sources to reconstruct the key

tages and events of the transformation. This initial understand-

ng allowed us to organize detailed stories from our data into four

tages of transformation (i.e., Establish, Enhance, Engage, and Em-

race, as illustrated in our theoretical framework) to account for

he different types of activities and BA use over time. This narra-

ive serves as the main source of our analysis.

The next step of our data analysis involved working back and

orth between our data, literature and emerging insights to con-

truct a deeper understanding of the phenomenon. At this stage,

e mapped out our data into broad thematic categories to present

he different types of BA use. The theoretical lens of technology

ffordances provided us with the theoretical sensitivity to perform

his mapping. Following guidance from existing studies (e.g., Tim

t al., 2018; Volkoff & Strong, 2013 ), we asked questions such as

what did BA enable Rovio to do?” and “what did Rovio use BA

or?” when analyzing our data. This process allowed us to identify

our affordances (i.e., foundational, functional, formative and for-

alizing affordances) as salient affordances that emerged as core

o the attainment of Rovio’s transformation goals.

As is typical for interpretive research, we analyze our data, the

iterature and the emerging insights to construct and refine our

nderstanding of the phenomenon. Upon identification of the af-

ordances of BA, we cross-checked this with the data to identify

tatements describing different actions relating to each affordance.

Outcome

The case of Rovio was selected because the company has recently undergone a

hugely successful analytics-driven transformation • Rovio embraced BA to transform from a premium pay-to-play model to a

free-to-play model • The use of BA has enabled value creation at Rovio, as evident from the

developed capabilities including in-house analytics and a proven user

acquisition process, expertise in game development and monetization,

substantial cross-promotion capability ( Rovio, 2017 , p. 145)

• The interviews at Rovio provided a deep understanding of the transformation process, especially the use of BA in supporting the process

• The insights gained allowed us to establish meaningful understanding of the underlying mechanisms and also to capture the contextual richness

• Rovio provided us with an unprecedented view of specific analytics metrics and measures used internally in the organization to guide decision making

• A range of published data used as supporting pieces of evidence for triangulation

646 Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655

Table 2

Description of data sources and their role in analysis.

Data sources Description Role in analysis

Onsite, semi-structured

interviews

12 hours and 15 minutes of interview recordings Insights into key events related to the transformation journey

Deep understanding of meaningful and contextual richness behind

the process

Analytics metrics and

measures

Specific analytics metrics and measures used by Rovio, including a

snapshot of analytics dashboard, specific measures and illustrative

examples

Insights into the exact use of analytics

Deep understanding of the changes enabled by analytical insights

Official channels Offering Circular document, articles, posts and reports published

on Rovio’s website and official social media channels (Facebook,

LinkedIn, Instagram and Twitter)

Insights into timeline and detailed information of key events and

decision points

Understanding of the key events and developments from the

company’s perspective

Published materials Publicly available reports, articles and case studies Insights into key events and developments

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This allowed us to better appreciate the importance of organiza-

tional arrangements in enabling effective actualization of the af-

fordances. Multiple readings of the data and the literature fur-

ther affirmed that an effective actualization of affordances depends

upon a combination of technological features and organizational

arrangements. For example, our interviewees repeatedly noted that

having access to BA does not immediately generate value for the

organization. In many cases, multiple rounds of adjustments in

processes and structures were needed to effectively realize the

value potential of BA.

Further consultation of the literature and our emerging in-

terpretations (for example, by asking questions such as: How

were the affordances of BA actualized? What are the enablers

of affordance-actualization? What are the outcomes?) allowed us

to conceptualize the mechanisms of affordance-actualization, and

how these actualizations lead to the attainment of varying organi-

zational goals (i.e., different value created). When performing these

analyses, our rich data allowed us to verify salience of the emerg-

ing concepts and to refine our interpretations. We also retained “a

considerable degree of openness to the field data, and a willing-

ness to modify initial assumptions and theories” ( Walsham, 1995 ,

p. 76), and remained open to identifying additional new concepts

from our data. As we continued to analyze the emerging concep-

tualization, data and related literature, we were able to map the

various mechanisms of affordance-actualization to different trans-

formation stages. This final step resulted in a deep conceptual in-

terpretation of the phenomenon, which we organized into a theo-

retical framework discussed later in the paper. During the analysis

process, we also cross-checked our interpretations and theoretical

framework with our interviewees at Rovio. Involving our intervie-

wees in the analysis process enabled a critical reflection that adds

to the validity of our interpretations ( Flick, 1998 ).

5. Case description: envisioning a BA-enabled transformation

at Rovio Entertainment corporation

Rovio Entertainment is a Finnish entertainment company

founded in 2003 as a mobile game development studio by three

students – Niklas Hed, Jarno Väkeväinen, and Kim Dikert. In the 15

years since, Rovio has grown to more than 430 employees, close to

€200 million in annual revenue, and created some of the most suc- cessful mobile games of all time. The company is best known for

its Angry Birds game franchise. The original title in the series, re-

leased as Rovio’s 52nd game in 2009, has been downloaded more

than 3 billion times and led the paid iOS app rankings for longer

than any other game.

Despite the phenomenal success of Angry Birds, Rovio has al-

ready had to reinvent itself in response to disruptive industry

forces. By 2012, the “pay-to-play” (also referred to as “premium”)

games business model underpinning Rovio’s original Angry Birds

success was becoming unviable. The more profitable titles in the

aming industry, such as the Candy Crush Saga and Clash of Clans,

ere moving to a “free-to-play” (F2P) business model. As the name

uggests, this new model allowed customers to download a game

nd access a significant part of its functionality for free. The F2P

odel is dependent on keeping users continuously engaged in the

ame, and earning revenue from in-game micro-transactions that

ither enrich or simplify the user experience. The rise of F2P games

as signalled a shift in the gaming industry towards a highly acces-

ible, connected and dynamic gaming model:

[The move to F2P business] has been the biggest transformation,

not only for Rovio, but for the whole games industry…I would ac-

tually argue that the biggest changes in the whole games indus-

try are related to … App Store and Android markets opening to

us…and the F2P business being enabled by the fact that those app

stores actually allowed in-app purchases… In 2015 just the mobile

gaming market was 34 billion (USD)… that’s huge…[it’s] a really

crowded place…200 new iOS games per day. Head of Studio

Rovio’s management team soon realized that they could not af-

ord to ignore the F2P business model as F2P games have become

he dominant revenue model in the market:

With the proliferation of the free-to-play model, barriers to down-

loading games have decreased, and an increasing share of the pop-

ulation and of mobile phone users are playing mobile games. In

the United States, 69% of mobile phone users played mobile games

at least once per month in 2016, and it is estimated that this per-

centage will increase to 77% by 2020. ( Rovio, 2017 , p. 8 )

In responding to the shift in the environment, Rovio embarked

n its first F2P game project in the summer of 2012. Initially,

ome of the premium games were converted to F2P games but this

as considered only partially successful as fundamental changes in

ame design were still needed to fully embrace the F2P model. As

uch, Rovio decided to solely focus on F2P games going forward:

One of the biggest decision points was actually the company come

out and say that we are only doing free to play games. That was

a big change because before that if there was even a chance that

someone could do premium games they would like to grab that

chance. But when it was explicitly said that no, we don’t do pre-

mium games any more at all, that was a big, big change. Senior

Product Manager

However, Rovio was also well aware that the transformation re-

uired to adopt this new business model was complicated. There

ere several challenges which Rovio needed to overcome. First,

2P games have historically been of low quality compared to pre-

ium games. As Rovio’s staff prided themselves on creating top

uality products, this stereotype presented an initial hurdle in their

ursuit of the F2P model. Second, creating a successful F2P game

equired a deep understanding of players’ preferences and the use

f behavioral economics. While Rovio had one of the strongest

Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655 647

Table 3

Actualizing BA for organizational transformation.

Organizational goal Technological features Organizational features Affordance-Actualization (AA) Organizational outcomes

Improved understanding • Aggregation of user behavioral data, public feedback and

comments

• Analysts with expertise in analyzing big data

AA1 : Curate relevant data • Comprehensive data awareness (where it is, what

we need and how we use it) • Dashboards and reports • Designers tasked to review

analytical insights

AA2 : Perform basic analysis • Improved understanding of the potential of analytics in

enabling transition to new

model

Improved core operational

processes

• Customizable data acquisition (e.g., return on paid user

acquisition investment, retention

and monetization rate)

• Individuals with optimism towards analytics

AA3 : Incorporate analytics into

existing processes

• Increased strategic use of analytics

• Analysts tasked to provide constant guidance

AA4 : Use analytics to make

constant adjustments to

products

• Formulation of more concrete analytics strategies and plans

Integrated use of analytics • Real-time, integrated dashboard • Individuals with confidence in the potential of analytics

AA5 : Set visible statements

about the importance and

expected use of analytics

• A change in organizational structure and individual

responsibilities in enacting

analytics • Easily accessible reports and ad hoc analytics queries

• Managers with clear expectations about the use of

analytics

AA6 : A hybrid team structure

to promote the use of BA

• Broadened use of analytics in different areas

Analytics-driven culture • Real-time, integrated dashboards • Individuals with trust in analytics

AA7 : Formalize analytics as an

essential part of the

organization

• Tolerance for trial and error and an openness to

data-driven orientation • Regular feedback, consolidated

analysis and interim reports

• A culture that respects reliance on data and

analytics

AA8 : Proactively enact

analytics to maximize impact

and value

• Appreciation of the power of analytics as a source of

competitive advantage for

the organization

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ools of premium game talent, there was very little know-how

ithin the company on how to create successful F2P games.

BA was identified as a key enabler for this transformation.

irstly, BA afforded several new possibilities for Rovio to create

ustomer-centric games to compete in the F2P market. For exam-

le, data about players’ in-game behaviors and the economic per-

ormance of a game could be analyzed to generate insights into

layer preferences. These data improved the games’ retention and

onetization, which are the key performance indicators (KPIs) for

2P games. Secondly, Rovio embedded analytics in many of its op-

rations, and introduced a change in organizational structure to ac-

ommodate for more effective BA use. This BA adoption enabled

ovio to transform into a data-driven organization, as summarized

uccinctly by a Head of Studio:

Now everybody is somehow exposed to the data. When I joined

Rovio the only data we basically had and we were looking at were

the app store downloads. Now we have a lot of data. We look at

how the players actually play the game, where are the pain points

possibly, where are the opportunities…The usage of data has ba-

sically entered every area, even the work of artists. They see that

if I do this kind of icon, we can immediately see that ok, when

the possible customers go to the app store page this icon actually

works this much better in actually converting people to download

the game. All the disciplines now are using the data in their work.

Today, Rovio is thriving in the industry as a customer-driven,

ervice-based entertainment company. “By 2016, the Company’s

ames were almost fully transformed to the free-to-play model as

pposed to 2011, when 63% of the Company’s Games gross book-

ngs was generated from paid apps.” ( Rovio, 2017 , p. 139) This

ransformation journey of Rovio serves as a revelatory case to in-

estigate the actualization of BA for value creation. We present

ur analysis of this analytics-driven transformation in the follow-

ng section.

. Case analysis

Based on the technology affordances perspective, we uncovered

our salient affordances of BA that were core to the attainment of

ovio’s transformation goals: (1) foundational affordances for im-

roved understanding, (2) functional affordances to improve core

perational processes, (3) formative affordances to foster an in-

egrated use of BA, and (4) formalizing affordances to cultivate a

ata-driven culture. For each affordance, our analysis unveiled the

pecific technological features of BA, as well as the organizational

rrangements that are essential for organizational actors to actual-

ze the affordance. We then described the organizational outcomes

chieved through affordance-actualization. These findings are sum-

arized in Table 3 and discussed in detail in this section.

.1. Actualizing foundational affordances for improved understanding

Rovio first adopted BA to better understand its new business

odel as well as its current performance and opportunities in an

merging market. At this stage, Rovio actualized several founda-

ional affordances of BA, including accessibility and visibility, to es-

ablish a strong foundation for its analytics-driven transformation.

.1.1. Curate relevant data (AA1)

BA was first adopted by Rovio as an experimental move to

ain a greater understanding of the F2P model. Moving from a

remium-game business model to a F2P model was a significant

ransformation for Rovio. F2P games need to be designed in a way

hat keeps users continuously engaged and willing to make pur-

hases within the game. This is fundamentally different from the

remium game model, as highlighted by a Head of Studio at Rovio:

This is what has fundamentally changed with the F2P busi-

ness…you need to be able to think where does the monetization

of the game sit…things like target audience size as well as things

like long term retention .

Rovio knew that it needed to have an in-depth understanding of

he F2P model to develop successful games in this new space. BA

as adopted to achieve this purpose. At this stage, BA was utilized

ainly to inform Rovio’s understanding on the current trends of

he F2P mobile gaming market, and subsequently on users’ needs

nd behaviors:

Data on the mobile gaming market, competitors and users is uti-

lized more strongly in generating, designing and prototyping new

648 Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655

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game ideas whereas quantitative user data is utilized to a larger

extent when games are opened for wider distribution. – ( Rovio,

2017 , p. 162)

As Rovio developed an initial understanding of the changes

required, they set out to hire people with expertise in game ana-

lytics and the F2P model. A handpicked transformation leadership

team – CorePM was established to lead Rovio in harnessing BA

in the transformation. The team consisted of four people - Senior

Vice President, Games, a Head of Studio and two Senior Product

Managers with strong expertise in F2P. This team was in charge of

coaching and familiarizing existing employees with the F2P design

logic and the uses of BA in the process. For example, they would

run one-day workshops that involved a competitor’s successful

premium game as a point of discussion and working through what

is needed to be done in order to transform it into a successful

F2P game. BA played an essential role in these workshops as it

afforded visibility into the progress of all activities involved, and

allowed the team to stay on the right track:

At some point we were getting more money from the in-app pur-

chases than from the paid downloads, so that’s already one place

when we knew that ok, we are on the right track. Vice President,

Game Development

6.1.2. Perform basic analysis (AA2)

Based on this understanding of the F2P model and support from

analytics experts, Rovio started to develop its first F2P game from

the ground-up. The use of BA grew considerably starting from this

trial:

When we had our first real free to play games…that was the

place when we started really digging into that, what happens

when players spend money, when do they spend money, in which

things they spend money, is it energy, is it power ups, is it speed-

ing up things. Also, the journey—what happens before they spend

and what happens after they spend. And do they spend multiple

times, how much do they spend in one go. We started testing that

ok if you offer let’s say this starter bundle with this price point,

that price point or this price point, which of these performs better

money-wise, which brings the most revenue. Vice President, Game

Development

At the time, the F2P mobile gaming market was highly com-

petitive. The cost of user acquisition was high and only a small

portion of F2P mobile games could reach significant scale. As a

new entrant in this market, Rovio employs analytics to understand

content and the campaigns that work best, often combined with

embedded A/B content testing and refinement. ( Rovio, 2017 , p. 163) .

As highlighted by the Senior Product Manager, the use of BA

has provided a detailed view of user expectations and game

performance, something which has been historically unattainable:

Everything can be measured since it’s a service-based thing and

that’s a huge change. You don’t rely on your gut or your think-

ing, but rather rely on numbers, which is quite a drastic change of

thinking.

This visibility has reassured Rovio that their transition to F2P

model was necessary and possible. This improved awareness and

allowed Rovio to establish a strong foundation and momentum for

its analytics-driven transformation.

6.2. Actualizing functional affordances to improve core operational

processes

Having established an understanding of the power of analyt-

ics and the F2P model, Rovio began to expand their BA use to

improve existing processes and to guide its transition to the F2P

odel. Several functional affordances of BA have been actualized

t this stage to improve existing business and game development

rocesses, as well as to inform new products and services design.

.2.1. Incorporating analytics into existing processes (AA3)

The F2P market is highly dynamic and requires companies to

ontinually anticipate and respond to changing trends and de-

and. Rovio’s use of BA has afforded visibility into market changes

nd crucially, allowed informed decisions to be made in response

o these changes. One specific example of this is how Rovio incor-

orated BA in its game development process. As part of the trans-

ormation into a F2P model, Rovio has introduced a game devel-

pment process called “Flightpath”. This process takes game ideas

hrough the phases of (1) Idea and Concepting, (2) Market Re-

earch and Prototyping, (3) Pre-production, (4) Production and Soft

aunch. BA is used in all phases of a game’s Flightpath to achieve

nformed decision-making. For example, BA was used to identify

otential new game designs in the Idea and Concepting phase:

Rovio has accumulated significant understanding of user behavior,

and Rovio uses this knowledge to develop its games based on data-

driven analysis and user feedback. ( Rovio, 2017 , p. 141)

The Senior Vice President, Games has provided a specific exam-

le of how BA was used to identify a need for adjustments to a

ame prototype (see also Fig. 1 ):

A game team working on a new game prototype noticed from an-

alytics that players were not using their free boosters as expected

in the very early part of the game. Especially the share of play-

ers using zero free boosters per level was alarmingly high (70%).

Using free boosters will give better feeling of control to the player

and make the experience more fun, so those that do not use free

boosters are more likely to churn out from the game .

After gaining this insight, the team has spent two days imple-

enting a series of User Experience (UX) improvements to remind

layers to use their free boosters. With BA, the team was able to

ontinuously monitor the impact of changes and make any neces-

ary adjustments.

To ensure highly available and reliable BA services, Rovio has

lso invested extensively in an in-house cloud-based platform to

ollect data and perform analytics on all Rovio games. This plat-

orm allows everyone at Rovio to have full visibility and control

ver user data and analytics services. Currently [in 2017], Rovio’s

4/7 platform handles up to 4 billion analytics events on a daily basis

nd on peak times more than 45,0 0 0 API requests per second ( Rovio,

017 , p. 161). Rovio has provided us with an unprecedented look of

he platform. Fig. 2 shows one of the dashboards which describes

everal measurement areas of a game that were actively used by

ame developers at Rovio. As explained by the Senior Vice Pres-

dent, Games, there are altogether 55 dashboards. All of them are

sed actively by developers. The platform has various graphical and

preadsheet data and it’s possible to export data e.g., to Excel for fur-

her analysis . This in-house analytics platform has been repeatedly

ighlighted by Rovio as one of the key support for its transition

nto the new model:

Rovio relies on its network infrastructure, including the cloud-

based services, to manage its operations, to develop its games and

to provide Rovio with the data needed to analyze the performance

of its business and to accurately report its operational and finan-

cial performance . ( Rovio, 2017 , p. 90)

.2.2. Use analytics to make constant adjustments to products (AA4)

The use of BA has enabled an unparalleled understanding on

he performance of each games. As elaborated by the Vice Presi-

ent, Game Development, back in the premium times we didn’t re-

Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 6 42–655 64 9

Fig. 1. Analytics used by Rovio team to monitor the use of free boosters and improvements once changes were made to the game’s UX design (confidential information

including the game’s name have been removed).

Fig. 2. A high level view of a dashboard showing several measurement areas of a game, which are reviewed actively by game developers. (Non-public information on the

original dashboard has been removed).

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lly care about KPIs, we didn’t have retention KPIs, no one was talk-

ng about that . The use of BA has now enabled the teams to keep

rack of multiple Key Performance Indicators (KPIs) of F2P games,

ncluding:

We have retention, we have average revenue per daily active

user… how many views there are per daily active users, what’s

the average revenue per paying user over a certain period of time,

your activity how many minutes per day you are playing and how

many sessions per day you are playing. Those are the main KPIs.

This visibility enables Rovio to continuously improve on its

ame design. For example, Fig. 3 shows a screenshot of specific

nalytics for one of Rovio’s games. The development team uses the

ata on Level Funnel (i.e. how many players who have started play-

ng the game are still left on a level x ) and the Fail Rate (i.e. the

umber of failed attempts at each level) to identify which levels of

he game are either too easy or too challenging for its players.

With this insight into how each game performs, the develop-

ent team was able to continuously make improvements to the

ame to maximize user experience. As highlighted by the Product

ead at Rovio, basically there are a lot of things that hour-by-hour

ou are able to change in the game . Rovio has also made sure to de-

ign their games in a way that made accumulation of meaningful

ata points possible:

The game is responsible for actually sending the data events to our

system and then the big data system crunches that data and makes

it available both for the data analysts, but also in the form of dif-

ferent dashboards and reports to everybody who is working with

the games. – Head of Studio

Beyond improving the games, incorporation of BA also aided

ovio in optimizing the game development process. As discussed

bove, BA was used to monitor a game’s performance in each

lightpath. Games with retention issues can be abandoned early in

he Pre-production phase. This allowed Rovio to focus its resources

n games that were more likely to generate revenue, which is dif-

cult to do in the past:

People were previously not willing to publish unfinished, or not

unfinished, but not optimal game. Now we can go soft launch with

not quite the full game and get initial learning and develop based

on the feedback or the results. That was unheard of in the pre-

mium era when we just wanted to make a superpolished game.

That’s a huge design thinking change . Senior Product Manager

A Senior Producer has provided a detailed description on how

A was integrated to inform various decisions in the game devel-

pment process:

650 Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655

Fig. 3. Dashboard to keep track of level funnel and fail rate of a game.

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It is much more data-driven and the loop-back of getting feedback

and reacting to changes is much faster… You have to think how

you can analyze all of this when the game is live. So, you have

to put all the analytics events in and to make sure that the an-

alytics pipeline is there, so that you can get the events, you can

aggregate them, you can analyze. And then you need to have some

dashboards, some analytics tools, all of that. So, there’s a big shift

[from] having a premium game to free to play—similar to boxed

software .

When discussing how BA often unveils surprising insights into

users’ preferences, a Senior Game Artist also highlighted an inter-

esting example:

Since our game is called Angry Birds, we long thought that we

have to picture them always angry…but then we noticed through

this data that it works best if they are, for example, smiling and

really happy…this doesn’t really perfectly fit our title [Angry Birds]

but it just looks best for the people.

6.3. Actualizing formative affordances to foster an integrated use of

BA

The positive impact of BA cultivated an optimism towards

Rovio’s transition into the F2P model. With increased experience

in analytics, “Rovio aims to connect the data, insights and knowl-

edge gained from its analytics and monetization techniques to every

element of its business – from marketing to merchandizing ” ( Rovio,

2017 , p. 162). To foster a more integrated use of BA, Rovio started

to define clear expectations about BA use and introduced changes

to the organizational structure to accommodate these expectations.

6.3.1. Set visible statements about the importance and expected use

of analytics (AA5)

To better harness the affordances of BA, Rovio has started to

embrace BA as part of its strategic priorities. For Rovio, this trans-

formation was at times challenging because it involved both a

change of processes and a shift in mindset and organizational

structure to accommodate the changes. Based on our analysis, we

found that the positive uses of BA have played a part in culti-

vating a much-needed confidence towards the transformation. Ini-

tially, some employees at Rovio were unsure of the potentials of

2P games and were intimidated by the need to transform the old

remium model. These concerns were soon addressed as the use

f BA afforded transparency in the process. Employees were able

o monitor the status of all ongoing activities, including their per-

ormance and the company’s transformation progress. The use of

A has also allowed better communication internally and fostered

ontinuous improvement of processes and products. For example,

he Senior Vice President, Games explained how BA enabled trans-

arency into the progression of different teams. This insight allows

ertain changes to be made to foster collaboration:

If you use a lot of market data, you can find a lot earlier that hey,

there seems to be a studio that has something much better than

anyone else in that area, and something that you need .

The transparency of BA was also actualized to foster commu-

ication and exchanges of ideas. The Vice President, Game Devel-

pment highlighted that the open sharing of analytical evidence

parked new conversations and stimulated healthy competition:

We have all kinds of QlikView dashboards that pretty much any-

one can access about all the KPIs of the games. Then we have

a weekly report that is sent out to every single employee in the

games unit. That shows weekly KPIs, weekly statistics, it has a

ranking of games, which games are performing the best at the mo-

ment, so some kind of internal competition about that.

As the use of BA continues to cultivate transparency, Rovio has

hifted towards a more open culture. This is demonstrated through

ovio making its games analytics reports available to all employ-

es. Where previously in the premium model era, only managers

ad the access to the analytics. Now, the use of BA has become

ore widespread and well-acknowledged, employees have been

iven access to key data and reports. This seemingly small change

as deemed essential to foster a sense of openness and collec-

ive learning. As elaborated by a Senior Game Artist, the company’s

ew priority in transparency was very different from the old model

here individuals worked in silos:

Our common goal now is to share information. I would say that’s

the keyword here. For example, we have this new event once a

month where we have to share what we have been doing in this

Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655 651

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game for everybody who is interested. We have to present and

have this presentation ready to show efficiently what is different in

the game and what we are going to push forward. That’s a thing

which we were not accustomed to before, because we were just

working privately and doing our everyday stuff.

.3.2. A hybrid team structure to promote the use of BA (AA6)

With an increased confidence in BA, management at Rovio has

tarted to initiate changes to the organizational structure. A sig-

ificant move involved the integration of analytics experts into

ovio’s game studios (i.e. game development teams). Analytics ex-

erts used to work in separate units and served the game devel-

pment teams only when the need arose. From our case study, we

an see how Rovio creatively assigned analytics and technology ex-

erts to work closely with artists, designers and developers. With

his structural change, Rovio transitioned from a centralized model,

o a hybrid model, that we are part of BA, but ‘rented’ to the game

eams so to speak (Senior Data Analyst). Analysts and game experts

ere now empowered to work together to make the best use of

ata and insights:

Rovio develops and produces its own titles using a development

process in which a group of creative, production, and techni-

cal professionals – including designers, producers, programmers,

artists, and sound engineers – in cooperation with marketing, fi-

nance, analytics, sales, and other professionals – collaborate in an

agile ( i.e. iterative and incremental) manner ( Rovio, 2017 , p. 156)

.4. Actualizing formalizing affordances to cultivate a data-driven

ulture

Lastly, Rovio actualized the formalizing affordances of BA to cul-

ivate a data-driven culture. At this stage, BA has been integrated

nto Rovio’s new model and processes, and teams at Rovio have

tarted to proactively adopt BA in their day-to-day operations.

.4.1. Formalizing analytics as an essential part of the organization

AA7)

Fundamentally, the positive impacts generated from BA use

ave led to a strong reliance on data and analytics at Rovio. As

A became a part of the company’s DNA, most key decisions made

t Rovio are now data-driven. For example, Rovio now develop[s] its

ames based on data-driven analysis and user feedback ( Rovio, 2017 ,

. 141), prioritizes games based on the ROI they deliver ( Rovio, 2017 ,

. 158), and improve[s] its monetization through data-driven feature

evelopment ( Rovio, 2017 , p. 142).

The persistence affordance of BA also plays a crucial role at this

tage. BA technologies allowed all communication, decisions and

rogress to be stored and remain accessible over time. This persis-

ence allowed teams at Rovio to keep track of all analytics activ-

ties and review the progress and learning when any needs arise.

ogether, the transparency and persistence of BA were actualized

o support constant reflection and improvement. As summarized

y the Vice President, Game Development, these features are vital

n promoting a data-driven mindset:

If you wanted to have everyone to be interested about the money

and about making a business we had to change that mindset. That

everyone can access the data. That everyone can see that how your

game did yesterday. Did the change that we made actually have

an impact on KPIs of the game? That was a big thing, we had to

convince the whole company that yes, we can share data of every

game to every employee

.4.2. Proactively enact analytics to maximize impact and value

AA8)

Once a majority of employees recognized the value of analyt-

cs and made it a high priority, it triggered a shift in the funda-

ental attitudes and culture within Rovio. The continuing BA use

timulated and reinforced a trial-and-error mindset and a commit-

ent to data-driven decision-making. An analytical culture thrives

hrough a company-wide change in attitudes and value. A Senior

roduct Manager provided an example of this mindset shift:

[ The design process] has changed so much more into this model of

systematic thinking and definitely data-based decisions. Everything

can be measured as it’s a service-based thing and that’s a huge

step change. That don’t rely on your gut or your creative thinking,

but rather rely on the numbers, which is quite a drastic change of

thinking .

As employees were now well equipped with skills and confi-

ence to embrace analytics in their work, BA use has become nor-

alized in all areas of work at Rovio. Employees are now proac-

ively embracing analytics to improve their work. A Senior Product

anager summarized the proactiveness succinctly:

The whole analytic mentality has definitely come through the com-

pany. It’s a very big win. Level designers are posting results of how

did their level perform and why. […] Rather than someone telling

them to do that, they actually want to share .

.5. Actualizing the affordances of BA for organizational

ransformation

In 2015, Rovio launched Angry Birds 2, the first sequel to the

riginal Angry Birds game. Angry Birds 2 is an interactive F2P game

ith a focus on engagement, social interactions and monetization.

reating F2P games allows Rovio to add more flexibility and depth

nto the games. In Angry Birds 2, for example, Rovio introduced

aily reward mechanics that make use of player behavior analysis

see Appendix D for illustrations), and deploy dynamic, content en-

ancements to maximize user retention. The game was launched

n July 2015 and has reached 10 million downloads within just

he first three days of launch. The success of Angry Birds 2 was

strong encouragement and an acknowledgment of Rovio’s transi-

ion into the F2P model. As described by the Lead Game Designer

f Angry Birds 2, F2P games are no longer seen as “shallow games”,

ut meaningful games that can be more scalable and engaging as

ong as a solid support system is in place:

When you’re creating your game, you should design for it to live

for years, that means you have to have smart systems in place that

can scale and engage players for a long time. In support of that I

would not look too much in the past way of making casual games

where the core game was 90% of the experience . ( Tandom, 2017 )

Today, Rovio’s titles have been downloaded 4 billion times

Rovio, 2018 ). Rovio’s original Angry Birds’ premium game now

as several F2P spinoffs, all of which have been highly success-

ul and ranked among the most downloaded games. The revenue

f Rovio’s gaming business has increased by 40% year-to-year, with

ost of this increase attributable to the improved monetization of

he company’s top F2P games ( Rovio, 2017 ). These improvements

ave clearly demonstrated the organizational value created by BA

nd served as valuable data points for analysis and discussion.

. Discussion

We developed Fig. 4 as a synthesis of our analysis to illustrate

ow affordances of BA were actualized to enable value creation.

his model proposes four categories of affordances, organized into

our stages of analytics-driven transformation. For each affordance,

he model highlights three salient dimensions (i.e., technologi-

al potentials, organizational actors, and specific organizational

rrangements) that are key to effective affordance-actualization.

652 Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655

Fig. 4. Actualizing the affordances of BA for organizational value creation.

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The purpose of conceptualizing affordance-actualization is to pro-

vide a practical understanding for organizations to derive value

from BA. Overall, our findings suggest that the same action po-

tential when leveraged within different contexts and sets of ac-

tions would lead to different organizational outcomes. For exam-

ple, the visibility affordance of BA was actualized to establish

awareness and understanding in the initial stage of Rovio’s trans-

formation, but was also actualized in later stages to communicate a

sense of progress of the transformation. Conceptualizing the vary-

ing affordance-actualization mechanisms is therefore important to

allow organizations to consider the nuances involved in effective

use of BA for value creation. We now discuss in further detail how

the different affordances of BA can be actualized to obtain four

main analytics-driven transformation goals.

7.1. Establish an initial understanding

In Stage 1, several foundational affordances of BA were ac-

tualized to establish an initial understanding. Today, many firms

are approaching BA-related transformation with little prior knowl-

edge and expertise ( Ransbotham et al., 2015 ). Similarly, in our case

study, Rovio ventured into the analytics space following a shift in

the gaming industry, with little understanding of how data and an-

alytics would translate into practical value. At this stage, organiza-

tions such as Rovio need to focus on assessing the feasibility of

the transformation. BA were actualized to answer questions such

as: What has happened in our industry? How can we understand our

business better? What are the possibilities? .

In our case study, BA afforded access to large, fast-moving data,

ranging from environmental trends to competitor performance,

which provided Rovio with answers to the above questions. BA also

afforded visibility, i.e., the possibility to identify important infor-

mation within a large pool of data across multiple sources. Both

types of action potentials provided Rovio an opportunity to quickly

establish an initial understanding about the changing environment

and to perform an initial self-assessment.

Our analysis also highlighted several organizational arrange-

ments that needed to be put in place for organizations to success-

fully actualize the foundational affordances of BA. At Rovio, one

of the key organizational attributes that drove effective BA use at

this stage was the onboarding of analytics talent. Analytics experts

brought in the capabilities required to enact BA value and helped

drive initial exploration. For example, analysts helped to actualize

he visibility of BA by integrating a large amount of data from mul-

iple sources, and by presenting insights in the form of dashboards

asily accessible to the designers and developers.

.2. Enhance analytical capability

In Stage 2, several functional affordances of BA were actualized

o enrich existing knowledge of analytics to drive further value cre-

tion. This transformation stage involved actualizing the functional

ffordances of BA to support core operational processes. At Rovio,

his is the stage when BA use expanded, as teams started to ask

uestions such as What can we do to improve this task, this activity ?

nd began to look to BA for the solution. BA affords several action

otentials at this stage, including comprehensiveness, i.e. the pos-

ibility to locate and document all necessary information, and vis-

bility, i.e. the possibility to consolidate and present useful insights

n an easy-to-access manner.

Similarly, our analysis shows that actualizing these action po-

entials requires the support of specific organizational arrange-

ents. Firstly, managers play a role in encouraging the incorpora-

ion of analytics into existing models and processes. At Rovio, this

upport was evident as the senior executives championed the use

f analytics in game development and introduced new models and

rocesses to accommodate the change. Secondly, analytics experts

ontinued to play a big role in driving the strategic incorporation

f BA. They were in charge of leading the teams to explore new use

ases for analytics and provided support in actualizing the value of

A. When the value of BA became increasingly apparent, individu-

ls became more proactive in incorporating BA in their work and

ere more open in seeking advice from analytics experts. The as-

iration to becoming more analytics-driven continued to develop

s the list of uses for BA expanded. This optimism helped to foster

urther actualization of BA in the organization.

.3. Engage in analytical decision-making

In Stage 3, several formative affordances of BA were actualized

o drive strategic decisions. Employees at all levels started to en-

age in analytical activities and BA was now deemed as an im-

ortant driver of performance across the entire organization. Ques-

ions such as How can we use analytics to create value and to drive

ecisions? started to emerge. Two action potentials were key to

uilding this confidence in BA. First, BA affords interpretability,

Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655 653

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hich is the possibility for users to understand information ob-

ained, and to present insights in a form that is meaningful for

ifferent users. Second, BA also affords transparency, which is the

ossibility for users to not only freely share insights, but to also

ave visibility over status of ongoing activities and changes unfold-

ng in the organization.

Similarly, our analysis unveiled the specific organizational ar-

angements put in place by Rovio to facilitate increasing engage-

ent in analytics. Firstly, teams were restructured to promote

ross-learning and capability-sharing. Groups of creative, produc-

ion, and analytics experts were assembled into hybrid teams to

ultivate knowledge exchange and generation of new ideas. The

ynergy between game experts with deep domain knowledge and

nalysts with strong analytical capabilities helped to derive value

rom BA. Secondly, management also started to define BA priorities

or the organization, and challenge employees in every functional

rea to incorporate BA into their operations and decision-making.

eams were encouraged, and to some extent required, to use BA

or performance assessment and to regularly share lessons learned

ith others. This deep engagement allowed Rovio to continually

earn from its implementation of BA.

.4. Embrace analytics in organizational culture

In Stage 4, several formalizing affordances of BA were actu-

lized to embed analytics into the organization’s DNA. This was

he stage when Rovio embraced analytics as part of its culture

nd identity, and began regularly asking analytics-centric ques-

ions, such as How do we use analytics to innovate, differentiate and

tay ahead? What’s possible? . Two action potentials of BA found

alient at this stage are, firstly, transparency – which helps to fa-

ilitate collaborative learning, and secondly, persistence – which is

he possibility for conversations, activities and knowledge to re-

ain visible and available over time.

Specific organizational arrangements play an essential role in

ctualizing these action potentials. At Rovio, teams developed

data-driven orientation as they gradually became adept at

sing analytics to investigate an issue or inform a decision. The

ossibility to freely exchange analytical insights fostered more

ppreciation for BA and helped cultivate an analytical orientation.

t this stage, it was clear to everyone that the organization had

ade significant progress towards becoming data-driven. Overall,

A is enabling data-driven insights that inform strategic decisions

Kunc & O’Brien, 2018 ). The transparency and persistence of BA

ere also actualized to help foster a sense of openness and to

reate a common ground for communication. When knowledge is

asily accessible and communication is clear, analytical capabilities

ecome institutionalized and a data-driven orientation pervades

he organizational culture.

. Implications and conclusion

Based on an in-depth case study of Rovio, this paper has de-

eloped empirically-grounded insights into the actualization of BA

ffordances f or organizational value creation. First, our analysis un-

overed four classes of affordances in supporting the attainment of

our value creation goals. Second, for each affordance, we have pro-

ided a conceptualization on how the affordance was actualized to

chieve the specific goal. Guided by our theoretical lens, our con-

eptualization highlights both the technological and organizational

eatures that are central to affordance-actualization. Underst anding

ow affordances of BA can be effectively actualized to support or-

anizational goals contributes to both the theory and practice of

A in the following ways.

.1. Finding 1: affordances of BA for organizational value creation

We address the call for research on how BA could be adopted

or organizational value creation ( Vidgen et al., 2017 ). Based on a

evelatory case study, this paper proposes a model of affordance-

ctualization and discusses how varying affordances of BA can be

ctualized to achieve value creation goals at different stages. A

enefit of discussing affordances, instead of other relevant con-

epts such as capabilities, is that affordances extend beyond the

roperties of a technology and allow a comprehensive understand-

ng of how the properties or potentials of a technology can be ac-

ualized in a particular context ( Majchrzak & Markus, 2012; Strong

t al., 2014 ). This relational concept offers a rich approach to study

n emerging technology-in-use because it allows us to not only

onceptualize the opportunities, but also the different use patterns

hat arise when a technology is actualized to achieve specific orga-

izational goals ( Strong et al., 2014 ).

Our conceptualization of affordance-actualization shows that

reating value through BA requires a rearrangement of organiza-

ional processes and structure. Leveraging BA to create organiza-

ional value is more than just obtaining access to big data and

nalytics tools ( Watson, 2014 ). To actualize the potentials of BA

equires integrating BA into existing organizational arrangements

Fink et al., 2017; Trieu, 2017 ), or transforming specific organiza-

ional features to align with the new, analytics-driven model. This

onceptualization is important as it emphasizes that “analytics is

ot simply a technical matter” ( Vidgen et al., 2017 , p. 628)—the

ere existence of analytics resources and technologies will not

ead to successful value creation unless appropriate organizational

eatures that support its actualization are in place.

Our findings challenge an existing misconception of viewing

A as an isolated “IT department” issue ( Vidgen et al., 2017 ). As

uggested by our findings, the biggest barriers companies face in

xtracting value from BA are often, in fact, organizational. Many

ompanies struggle to incorporate analytical insights into day-to-

ay organizational processes and are unsure how to best adapt

he technologies to create organizational value ( Ransbotham et al.,

016 ). By highlighting both technological and organizational fea-

ures that are essential for effective BA use, we hope that our

esearch opens new paths of inquiry in investigating the varying

ffordances of BA, and how the affordances can be actualized to

chieve value creation.

.2. Finding 2: effective actualization of BA affordances

In recent years, there has been much investment into devel-

ping organizational analytical capability. However, there has been

imited guidance for practitioners on deriving value from their in-

estment in BA ( Ransbotham et al., 2016; Vidgen et al., 2017 ). In

his research, we make a practical contribution by providing ac-

ionable insights for practitioners to derive value from BA use. We

ummarize these insights in Table 4 . Specifically, Table 4 highlights

our salient affordances of BA, which could be actualized to achieve

ifferent transformation goals in four stages. From a practitioner’s

erspective, it also outlines the technological features of BA and

he organizational arrangements (including actors’ goals and ex-

ertise, as well as key analytical activities) which are required to

ctualize the affordances for value creation.

The analytical activities highlighted in our findings are broadly

onsistent with Hindle and Vidgen (2018) recently proposed

usiness Analytics Methodology (BAM), which highlights four

ctivities involved in gaining value from BA: (1) problem situation

tructuring, (2) business model mapping, (3) business analytics

everage and (4) analytics implementation. While the BAM has

n emphasis on the business model, which is different from

ur focus on BA affordances and actualization, our findings have

654 Y. Tim, P. Hallikainen and S.L. Pan et al. / European Journal of Operational Research 281 (2020) 642–655

Table 4

Actualizing BA affordances for organizational value creation.

Affordance- Actualization (AA)

Goals BA features Key actors Key analytical activities

Stage 1: Establish an initial understanding (actualizing accessibility and visibility affordances)

What has happened in our industry? • Exploratory data (e.g. market research, user data)

• Employees to have intrinsic and extrinsic motivation to adopt analytics

• Organize : Consolidate data from multiple sources

• Descriptive analysis to understand trends and behaviors

• Analytics experts to provide guidance in data collection and analysis

• Describe : Analyze data to identify opportunities and challenges in the

environment

Stage 2: Enhance Analytical Capability (Actualizing Visibility and Comprehensiveness Affordances)

What can we do to improve this

task/activity?

• Diagnostic data (e.g. performance data)

• Decision makers to promote the incorporation of analytics into existing

processes

• Implement : Incorporate analytics to improve existing processes

• Visualization and dashboards to develop performance metrics

• Analytics experts to lead the exploration of new analytics use cases

• Diagnose : Use analytics to make informed adjustments

Stage 3: Engage in Analytical Decision-making (Actualizing Interpretability and Transparency Affordances)

How can we use analytics to create new

value?

• Predictive data (e.g. consolidated dataset)

• Decision makers to modify organizational structure (e.g. hybrid team) to promote

collaboration and cross-learning

• Decide : Use analytics to inform strategic decisions

• Query and guided analysis to discern patterns and relationships

• Decision makers to define strategic priorities for analytics

• Share : Sharing of analytics tools and results to promote collective learning

Stage 4: Embrace analytics into organizational culture (actualizing transparency and persistence affordances)

What is possible? • Prescriptive data (e.g. a big dataset of internal, external and historical data)

• Decision makers to encourage a data-driven orientation

• Integrate : Formalize analytics as an essential part of the organization

• Integrated analytics and customized reporting to perform forecasting

• Employees to embrace an analytics-driven culture

• Prescribe : Proactively create new use cases for analytics to maximize value

A

t

S

f

R

A

A

B

B

B

C

D

D

D

E

captured a similar set of analytics activities in the same logical

precedence. For example, in stage 1, the key activities identified

from our findings involved a consolidation of market and user

data to develop an initial understanding of the environment. This

activity is aligned with “problem situation structuring” in the

BAM.

The organizational arrangements highlighted in our findings

also align with Vidgen et al. (2017) . In this study, the authors

advocated the importance of considering organizational features

when embarking on an analytics-driven transformation. Our find-

ings extend Vidgen et al. (2017) ’s discussion on the organizational

reconfiguration by presenting a staged model that outlines spe-

cific organizational arrangements that are critical in each stage. As

informed by our analysis from a technology affordance perspec-

tive, our findings are able to distil specific organizational features

that fundamentally drive effective implementation of BA. These

findings could serve as a useful guide for managers to overcome

many of the BA value creation challenges identified in Vidgen et al.

(2017) and generally to make more informed decisions in every

transformation stage. It is also worth noting that while our find-

ings were developed from our research in the gaming industry,

the proposed insights on the actualization of BA affordances, which

are organized into four maturity stages, will be relevant to organi-

zations in other industries looking to embrace an analytics-driven

transformation.

In closing, we hope that this research inspires further investi-

gation of how analytics can be actualized to create value for or-

ganizations. While many companies today are beginning to utilize

data and analytics to address tactical and strategic issues, there is

still a lack of guidance for businesses to effectively leverage BA for

value creation ( Brydon & Gemino, 2008; George et al., 2014; Rans-

botham et al., 2016; Vidgen et al., 2017 ). We hope that through our

thought-provoking findings, we are able to inspire more research

to explore the opportunities and challenges associated with orga-

nizational BA use. Future research could also expand on our find-

ings to uncover new affordances of BA in different organizational

contexts, and examine how the affordances of BA can be actualized

to facilitate the attainment of organizational goals.

cknowledgement

This work was funded by the National Natural Science Founda-

ion of China , Grant/Award Numbers: 71529001 and 71632003 .

upplementary material

Supplementary material associated with this article can be

ound, in the online version, at doi: 10.1016/j.ejor.2018.11.074 .

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