Omnichannel retailing -

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Master’s Thesis 30 credits

Department of Business Studies

Uppsala University

Spring Semester of 2020

Date of Submission: 2020-06-03

Omnichannel retailing -

The art of omnichannel orchestration

Authors:

Edward Toscano &

Nicholas Sanchez

Supervisor:

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Abstract

Digital advances and consumers' buying behaviors disrupt the retail industry demanding more seamless experiences during their buys. In response, retailers are adopting an omnichannel retailing strategy (OCR), which is the integration of retailers' physical and digital channels. However, OCR is a premature concept, and there is still a lack of research in the subject, which limits the guidance for its practical application. Thus, there is still the need to understand the subject.

For OCR managers, it is necessary to understand the main challenges in order to orchestrate it better. Therefore, this research undertakes the task to study the factors that challenge OCR's orchestration, from a managerial perspective. The research departs from primary and secondary data that was later categorized according to its main factor and incorporated into an existing analytical framework of OCR. The findings indicate three main challenge groups that could hinder an orchestrator's impact on the organization. Those are particular capabilities for the OCR, the integration of channels, and technology and data leverage.

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1. INTRODUCTION

Technology is empowering consumers (Faulds et al. 2018) and offering them more channels to choose from during their purchases. Subsequently, they are adopting different channels that better fit them and using them as touchpoints (Adivar et al. 2019; Piotrowicz and Cuthbertson, 2019; Chaffey and Ellis-Chadwick, 2016). Channels could generally be explained as a way or a route of communicating with people, and touchpoints refer to a point where consumers and businesses interact to exchange information, provide services or handle transactions (Piotrowicz and Cuthbertson, 2019). For instance, digital connectivity allows consumers to conduct digital research in several channels through different devices prior to their purchase, in the physical or digital store, collect their order in the physical store, and make another purchase directly in the physical store - all within a seamlessly integrated process (ibid). Ultimately, consumers are demanding more similar buying experiences across multiple and integrated channels, which in practice are challenging retailers. In this regard, omnichannel approaches are assisting them (Melero et al. 2016; Lee et al. 2019; Piotrowicz and Cuthbertson, 2019; Weill and Woerner, 2018)

Mitigating the digital transformation & consumer demands: Omnichannel

In concept, omnichannel means “all channels together” (Mehta et al. 2002). In the business context, Osterwalder and Pigneur (2013) define channels as communication, distribution, and sales interfaces between companies and their consumers, used by companies to deliver value propositions offerings and seeking to solve problems and satisfy consumer needs. Channels are touchpoints that are crucial in the creation of consumer experience ranging from own to partners’ channels, and from physical to digital (Osterwalder and Pigneur; 2013).

Omnichannel retailing (OCR)

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Levy also added the term “Omni-retailing”, referring to the coordination of retailers' multiple channels aimed to deliver a consistent experience to the consumers. Omnichannel retailing is, in essence, the advancement of multichannel or cross-channel retailing (Brynjolfsson et al. 2013; Rigby, 2011; Verhoef et al. 2015) and allows retailers to deliver the experience that consumers are expecting (Melero et al. 2016; Lee et al. 2019; Piotrowicz and Cuthbertson, 2019; Weill and Woerner, 2018). From now on, omnichannel retailing will be referred to as OCR in this research.

Theoretically, OCR allows consumers to interact and move more freely across the channels encountering consistent experience (Juaneda-Ayensa et al. 2016; Gupta, 2018; Milani, 2019). Thus, an advantage is that OCR integrates all channels into one, aligning retailers and consumers (Piotrowicz and Cuthbertson, 2019).

OCR in practice

However, although OCR seems promising for retailers, researchers have also found that companies worldwide are still facing challenges with their transformation toward OCR and during its deployment; this occurs within different disciplines, perspectives, organizational levels, and business sectors. The development and management of OCR are not that easy in practice, but a challenge for retailers (Hossain et al. 2020; Alexander and Blazquez Cano, 2019; Adivar et al. 2019; Orvos, 2019; Von Briel, 2018; Weill and Woerner, 2018; Chen, Cheung and Tan, 2018; Faulds et al. 2018).

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Problem formulation

Previous academic authors have emphasized that researches about OCR are still premature, and there is limited knowledge to guide retailers in practice (Von Briel, 2018; Piotrowicz and

Cuthbertson, 2014; Verhoef et al. 2015). Hence, in reality, retailers are challenged by

implementing an OCR since they face barriers when it comes to an understanding of what is required to orchestrate an OCR (Piotrowicz and Cuthbertson, 2019).

Additionally, studies on the OCR tend to center around its channels and the consumer experience or to define it as a mere phenomenon of marketing, which subsequently limits its understanding of its orchestration (Piotrowicz and Cuthbertson, 2019). However, OCR implies that all parts are interconnected, and they can only be comprehended and explained by referencing the whole, instead of just considering its parts. One is used to break things into parts to make it manageable. However, it should keep in mind that all parts belong to a whole (Gorichanaz & Latham, 2016).

In sum, previous literature suggests that OCR is a way for retailers to adapt to current digital and consumer volatility. However, retailers are struggling to orchestrate it, and there is a lack of studies and understanding of the OCR. Thus, to better understand an OCR and how to orchestrate it, it could be studied considering its integration and orchestration.

Research problem Statement

Considering the previous literature, some considerations that are adding complexity to the implementation of the OCR are:

● The recentness of the OCR concept

● The lack of general study and understanding around the OCR

● The disintegrated perception of the OCR, which misaligns with the integrated view of the concept

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the orchestration’s challenges in real-life (Wallin, 2006). Therefore, the research aims to answer the next question:

Research Question: What factors challenge retailers’ OCR orchestration?

Purpose

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2. LITERATURE REVIEW

In this section, previous researches and studies about OCR will be reviewed.

The benefits of OCR

It has been recognized that the retail industry is advancing towards a more consumer-centric approach and the emergence of new channels, digital and physical, as new touchpoints in consumers' shopping experience (Gupta, 2018; Neslin et al. 2006). In this regard, technology advances have also been allowing retailers to mitigate the disruption, by integrating all their channels, and use them parallelly in order to deliver a more integrated and seamless consumer experience; referring to this as “OCR” (Juaneda-Ayensa et al. 2016).

Considering the volatility of digital advances and consumers' buying behaviors, OCR is an approach that offers benefits to retailers to mitigate those challenges. Thus, retailers have been implementing it with the purpose to move from ‘bricks to clicks’ searching to compete better (Milani, 2019; Gupta, 2018; Rigby, 2011). For instance, global retailers such as Nike, Gap, Apple, and Sherwin-Williams have adopted OCR strategies (Adivar et al. 2019). More recently, the OCR concept is gaining more attention, since it has the potential for changing the retailing field. OCR considers all current and emergent channels as touchpoints for consumers (Piotrowicz and Cuthbertson, 2019; Grewal et al. 2017). Physical and digital channels consist of stores, websites, social media, mobile apps, email, telephone, catalog, a direct chat function with the retailer, and in-store kiosks among others. Besides serving as touchpoints for consumers during their buying journey, OCR promotes direct or indirect contact with the retailers or their brand (Verhoef et al. 2015; Neslin et al. 2006). However, OCR is not limited to only retail channels, but includes mobile channels, social media, and touchpoints; it centers on channels and brand interplay across them (Alexander and Blazquez Cano, 2019).

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Cuthbertson, 2019). Thus, OCR has been considered as the future of retailing and it is becoming the rule rather than the exception (Piotrowicz & Cuthbertson, 2014; Von Briel, 2018).

Technology's & consumers dynamics in OCR

Technology is innovating new dimensions of consumers' decision making, interacting and taking actions (Piotrowicz and Cuthbertson, 2019), in this concern, OCR is helping retailers to mitigate this disruption (Milani, 2019; Faulds et al. 2018; Melero et al. 2016).

Nevertheless, although technology helps retailers to cope with the demands, technology is also generating new ways in which consumers interact and make decisions, which is disrupting retailers (Piotrowicz and Cuthbertson, 2019). Technological advances are generating more channels and triggering changes in consumers’ behaviors, which in turn is altering their buying habits and journeys. Subsequently, this is changing the retail industry continuously (Juaneda-Ayensa et al. 2016). In other words, technology is driving consumers’ behavior.

Additionally, digital technologies are blurring the line between physical stores and online stores, and it has the potential to merge the retailer’s brand experience across different interphases (Piotrowicz and Cuthbertson, 2019). However, digital advances in the retail industry are also driving consumers’ demands toward OCR experiences. Consumers are expecting consistency and a better-integrated experience across different touchpoints during their buying journey, which are challenging the traditional retail environment, and complicating the OCR implementation (Piotrowicz and Cuthbertson, 2019; Alexander and Blazquez Cano, 2019). Thus, the consumer’s behaviors are also driving technologies and channels that companies should adopt as well (Juaneda-Ayensa et al. 2016). Therefore, although OCR is an extension for retailing in the technological context (Adivar et al. 2019), it is in essence rooted in the consumers’ behavior (Verhoef et al. 2015).

Data analysis between technology and consumers’ behavior

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deliver more valuable and suitable experiences that could fulfill consumers’ demand (Juaneda-Ayensa et al. 2016).

Also, with data-based decisions, retailers could also define properly which technologies to invest in (Juaneda-Ayensa et al. 2016). For instance, understanding the performance of the touchpoints and their roles across the consumers’ buying behavior contributes to allocating the resources more effectively and adding efficiency to the OCR (Adivar et al. 2019). However, digital capabilities are still new in the area, thus, lacking those capabilities might complicate retailers’ OCR implementation as well (Milani, 2019).

These circumstances are adding complexity to the OCR formulation and implementation, which reinforces previous affirmations that OCR is not an easy task; thus, the fact is that along with the promise to move from ‘bricks to clicks’ with an OCR, in reality, retailers struggle to develop and achieve an OCR (Gupta, 2018; Piotrowicz and Cuthbertson, 2019; Perkin and Abraham, 2017; Orvos, 2019; Melero et al. 2016).

OCR orchestration: Leaders as orchestrators

In practice, OCR is not an easy task (Gupta, 2018; Perkin and Abraham, 2017; Orvos, 2019; Melero et al. 2016) and retailers are challenged by its orchestration (Piotrowicz and Cuthbertson, 2019), which is a crucial practice to sustain the organization and its competitiveness (Wallin, 2006; Urbach and Röglinger, 2019).

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Orchestrators also balance the tension between cooperation and competition, and the resources that help to mitigate the tension created due to competition. Hence, one of the demanding characteristics of an orchestrator is to manage the alignment of the micro and macro network to facilitate the value co-creation, co-learning, and processes (Urbach and Röglinger, 2019; Wallin, 2006). They can be defined as persons who have the task to coordinate, accommodate, and exert control within the organization; thus, the responsibilities of the individual falls in the leader (Wallin, 2006). Thus, if the orchestrator is removed, in many cases, it will result in the ecosystem of the organization to collapse (Urbach and Röglinger, 2019). An orchestrator must also be capable to counteract the challenges and respond successfully to situations based on the collective capabilities within the organization (Wallin, 2006); this collection of skills shapes the organizational capabilities (Grant, 2016). Therefore, an orchestrator's capabilities are fundamental for an organization's competitive advantage (Wallin, 2006).

To conclude, the role of an orchestrator is indispensable for the organization (Day and Moorman, 2010; Piotrowicz and Cuthbertson, 2019). However, there is not enough guidance on how to achieve the integration of channels and synchronizing all operations to present consistency across channels; hence, the challenge of OCR for managers is in fact its orchestration (Piotrowicz and Cuthbertson, 2019; Gupta, 2018; Wallin, 2006).

Summary

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3. THEORETICAL FRAMEWORK

Following the purpose to identify the factors that challenge the orchestration of the OCR from the manager’s perspective. In this consideration, this research will take Piotrowicz and Cuthbertson’s (2019) perspective on the OCR: “Problems concerning OCR”.

Piotrowicz has considerable experience researching subjects related to information systems and logistics, supply chain management, and performance measurement and evaluation. The author is an associate professor at Hanken School of Economics and HUMLOG institute in Helsinki, Finland, and International Research Fellow at the University of Oxford, Said Business School, and is a member of the Wolfson College (ibid). Cuthbertson’s research experience is related to understanding the challenges of the retailers’ digital world, more precisely, technology innovation and customer data. The author is a Senior Research Fellow and Research director at the Oxford Institute of Retail Management at Said Business School, University of Oxford, and Vice-Principal of Green Templeton College at the University of Oxford (ibid).

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Figure 1 - OCR strategy triangle - (ibid)

This model was created from a research that captured the experience of 23 participants from 17 companies in the UK and Finland from academia, public sector (minister and public funding agencies), retail experts (business press, general retail consultancy, digital consultancy, and retail associations), and the retail sector (physical retailers, digital retailers, and shopping center operators). The authors identified activities involved in the OCR strategy across the organizational levels, which were later problematized. However, the three lower levels of the triangle are vital for retailers when determining the competitive advantage for the OCR (ibid).

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Considering Piotrowicz and Cuthbertson’s (2019) managerial level, the framework is extended below with support of other theories related to the activities at the managerial level.

Managers’ problems concerning OCR

3.1.1. Competitiveness problem: differentiation, competitive pressures

In the competitiveness problem, Piotrowicz and Cuthbertson (2019) explain that the OCR should take a profitable position in a market that is not exposed to hyper-competition. This level corresponds to the managerial level where the orchestration of the OCR takes place. The correspondent activities related to this problem are presented next: offering unique competitive actions, competitive asymmetries, and idiosyncratic synergies of the integration of channels.

Unique competitive actions:

Activities that are unique within a firm generate competitive advantage (Porter 1996). Thus, viewing OCR as a disruption that forces retailers to adopt it in order to adapt, OCR is considered a best practice. This means that anyone can adopt it, and it is not directly a source of competitive advantage (Piotrowicz and Cuthbertson, 2019). However, Ross et al. (2017) allege that digital strategies tend to focus on increasing the efficiency of retailers’ operations. However, this approach leaves aside the technology-driven solutions or opportunities that are difficult to imitate. Porter (1996) have previously found that although operational efficiency is essential for firms, this is not a source of competitive advantage. Similarly, technological opportunities are best practices; they are available to all retailers in the pursuit to achieve operational efficiency (Porter and

Siggelkow 2008)

Contrary to the digital strategies, OCR has the potential to increase revenues while improving customers’ experience and reducing costs that relate to digital-driven activities through automation, logistic innovation, and economies of scale (Rigby 2011; Cao and Li 2015; Gupta,

2018). In this alignment, Piotrowicz and Cuthbertson (2019) argue that digital solutions are

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Piotrowicz and Cuthbertson (2019) state that retailers should use their asymmetry to their advantage, to be able to differentiate and to compete better. They further highlight that this can be obtained with the help of knowledge, data, and resources. Li et al. (2019) add that retailers can obtain differentiation by integrating the information from the personal transaction, which enhances online loyalty, rather than focusing on general retail information, such as promotions, contact information, and price.

Differentiation is vital in OCR and can be accomplished by exploiting one or several channels in ways that the competitors are not exploiting (Piotrowicz and Cutbertson, 2019). Ross et al. (2017) also suggest that OCR should include the retailer’s position in the market and set up their use of technology, creating a unique activity that the competitors are not engaging at the moment, and it is harder for them to replicate in the future. There is an increase in quality information that consumers can access, which are connected to applications that compare products and sites that review the products. Suppliers are now able to pursue the consumer directly and use emerging platforms as online marketplaces (Piotrowicz and Cutbertson, 2014). Thus, channel integration that offers personalization could benefit the retailers, which could increase the brand image (Li et

al. 2019). However, the problem comes when the retailers aim to offer everything to everyone;

instead, they should focus on choosing a specific market segment or segments and tailor their choices of the channel towards that specific segment (Piotrowicz and Cuthbertson, 2019). Retailers need to develop a clear digital strategy so that they are able to have an integrated portfolio of the customers’ offerings. However, although this approach sounds promising, it ignores other consumers’ segments. Thus, the primary problem for retatiler is to differentiate, and since data is also heterogeneous, it implies that there are no blueprints to differentiate using data that is unique

(Piotrowicz and Cuthbertson, 2019).

Idiosyncratic synergies of the integration of channels:

According to Piotrowicz and Cuthbertson (2019), the emergence of online businesses threatens physical retailers that are already established. All retailers have different ways to configure the integration of both the digital and physical contexts, to leverage synergies from their current channels, and to provide a unique and seamless consumers' experience (ibid).

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groups depend on their physical assets and non-physical resources (knowledge-based), which in turn could be barriers to mobility. Thus, cost efficiency driven by synergies could be a source of competitive advantages for large retailers with multiple channels and physical stores (ibid). In this alignment, the channel integration in OCR could also reduce costs due to idiosyncratic synergies, mainly, firms with several channels searching for cost-efficiency are more likely to benefit, since it eliminates overlapping operations according to Piotrowicz and Cuthbertson (2019).

Nevertheless, another perspective suggested by Piotrowicz and Cuthbertson (2019) is that the cost of the channel expansion should also be considered. Omitting significant investments and operational costs on managing several different store concepts and an extensive online operation in different interfaces, could also become a source of competitive advantage. In this regard, the authors denominate this as a 'minimalistic OCR,' and the problem here is that it involves making decisions resisting the expansion of channels and avoiding investment costs. The savings help retailers to push lower prices. Therefore, this approach differs from retailers with multiple integrated channels. The authors say that "the goal of a minimalistic OCR is to build a great

single-channel experience in a highly standardized store format with online single-channels leveraged only to reduce advertising costs" (ibid - p32). Moreover, the ideal OCR strategy of a physical retailer

might differ from a purely-digital retailer since both are developed within different contexts. Similarly, large actors and small actors have different resources and capabilities which define the approaches they implement for their needs (ibid).

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retailing firms has to orchestrate the internal resources (Sirmon et al. 2011) to gain a unique position in the landscape they compete in (Porter, 2008).

Analytical framework

Using the fourth level of Piotrowicz and Cuthbertson’s (2019) “Problems concerning OCR” model at manager's level, described above, the researchers used the “Competitiveness” problem perspective as a framework to analyze the data in order to identify and explain the challenges that the activities at the managerial level entail for the orchestration of the OCR.

4. METHODOLOGICAL CONSIDERATIONS

This section will introduce the design of the research illustrating the methods that the researchers used in the research for the data collection and analysis in alignment with the research phenomenon and purpose.

Design

The research aims to study the challenges of the orchestration of OCR by capturing the managers' experience in the orchestration of their OCR in the retail industry.

The study aims to gain insights that can provide a better understanding of the phenomenon

(Saunders, Lewis and Thornhill, 2015). The study is qualitative, aimed to gain insights about the

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4.1.1. Research Approach

The research took an abductive approach, meaning that the researchers used data and theory back and forth - combining inductive and deductive approaches. This approach was empirical since it allowed the researchers to make informed decisions regarding the research design, to evaluate the proper research strategies and methodologies for each stage of the study, and to adapt the research design depending on the circumstances (Saunders, Lewis and Thornhill, 2015).

4.1.2. Time horizon

OCR is a premature phenomenon deployed within the digital context, which is a volatile environment (Beck and Rygl, 2015; Rigby, 2011). The researchers adopted a cross-sectional time from 2019-2020 (Saunders, Lewis and Thornhill, 2015) to provide a current overview of it.

Empirical data collection

A multi-method qualitative method was implemented for the data collection since it allowed the combination of primary and secondary data collection methods. These were semi-structured interviews and video-interview recordings. The primary (interview) and secondary data (documentary) captured practical experience from OCR orchestrators (Saunders, Lewis and

Thornhill, 2015).

4.2.1. Primary data

Sampling

A non-probability sampling method was conducted in order to find respondents with the right profile willing to participate voluntarily. It is a way to choose non-random responders, which is one of the most practical in the exploratory research since they have particular expertise in the subject, and they provide valuable data to the purpose of the study (Saunders, Lewis and Thornhill,

2015). Under this frame, the researchers interviewed one manager with experience in OCR.

The informant has over ten years of experience with the implementation of OCR in the retail industry. The respondent's name is Daniel Mogues, who is the CEO of Campusbokhandeln and has ten stores across the country in Sweden (Daniel, 2020; Campusbokhandeln, 2020). He has experience working in OCR in Kicks, helping them to implement and develop their OCR activities

(LinkedIn,2020; Mogues, 2020). Kicks is one of the biggest cosmetic retailers of the Nordic

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Both companies have physical and digital channels and implement OCR from the early days. The informant's experience on OCR from the early stages of the OCR phenomenon on the retail industry helped researchers to capture rich and detailed information. In the findings section, Mr. Mogues was coded as M1.

Semi-structured interview

The primary data collection started with a preliminary semi-structured interview with the CEO that had ten years of practical experience in the orchestration of the OCR for retail companies (M1). An interview guide was used in order to guide the researchers when doing the interview. It had a list of specific themes and key questions departing from observed themes in current literature about the OCR orchestration (appendix 1) (Saunders, Lewis and Thornhill, 2015).

The research interview was done with explanatory purposes because of the intention to understand the relationships between the variables (ibid). By relying on the informant's quality of the contribution, the researchers collected information in specific themes to capture a broader understanding of the challenges for the orchestration of the OCR (ibid), (Interview transcription -

Appendix 2). Additionally, the themes gathered from the informant provided direction to collect

further secondary data for the research question and purpose (ibid).

Interview process

The data was collected through an online video-conference through Google's video-call application, 'Hangouts' (Google Hangouts, 2020). With the consent of the informant, the researchers recorded the video interview and audio with the software application 'Snagit'

(TechSmith, 2020). Next, the interview was transcribed for its analysis (appendix 2). A one-hour

interview, through video conference, allowed the researchers to collect the data, capturing more details, and making annotations (Saunders, Lewis and Thornhill, 2015).

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The researchers collected documentary data, which is defined as data that endure physically unlike the spoken word, hence, text material (academic researches, articles, and books) and non-text material (video-interviews) (ibid).

For the text material, the main sources of data gathering were through academic researches and articles that were accessible through the Uppsala University digital library and complemented with academic books on the subject, finally, other online articles that helped with basic and general information.

For the non-text data, the researchers used YouTube's website (Youtube, 2020) to find documented videos where managers in the retail industry were interviewed and commented on their experience about the orchestration of OCR in different managerial roles. The data was collected starting from 2011 and forward, this since OCR is a recent concept, only nine years (Rigby, 2011). To collect current data, the interviews were sorted starting from 2020. Hence, from this list, the analysis started with the recent video-interviews, backward to 2019. Using a thematic analysis approach, the researchers started to identify patterns and common themes across them. Finally, ten YouTube videos were transcribed and analyzed. In total, 17 managers from different sectors expressed their experience in OCR. They were from USA, Australia and European countries and have experience working with OCR from recognized brands; this ensured their relevance in alignment with the purpose of the research.

In video one, Noz Urbina who is the Co-Founder of OmnichannelX Digital and Founder of Urbina Consulting commented and interviewed Gina Balarin about OCR strategy in the marketing area (Youtube - OCRX, 2020). Mrs. Balarin is a Marketer and Founder of Verbalistics in Sydney Australia (Verballistics, n.d.; LinkedIn: Balarin, 2020). She is also the author of the book "The

Secret Army" (Amazon, 2017). Balarin has participated in the TedTalk presentation and TV

programs where she has been recognized by her broad experience in marketing and OCR (Gina

Balarin - Google Search, 2020). In our analysis, Mrs. Balarin was coded as M2 and Mr. Urbina

as M3.

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CEO at Blue Acorn iCi (Blue Acorn iCi, n.d.; Linkedin - Chris Guerra, n.d.). Blu Acorn iCi is a digital consumer experience company with over 400 persons in its team of engineers, data scientists, Digital commerce experts, Designers, and Strategist (Adweek, n.d.). Mr. Guerra was coded as M4.

In video three, Noz Urbina interviewed Chris Avore and Matthew Grocki about the operations on OCR strategy (Youtube - OCRX b, 2020). Mr. Avore is Head of Customer Experience at Modus Create, Inc (Modus Create, 2019; Linkedin - Chris Avore, n.d.). He has been working for the firm since 2019, but he has been previously recognized for his vast experience in the design of business values in digital contexts for popular international firms such as Boeing, Nextflix, and At&T among others since over ten years back working for recognized companies as InVision and Nasdaq (PRnewswire, 2019; Avore, n.d.). Mr. Grocki is Founder and Content Strategy specialist at Grass-Fed Content (Grassfedcontent, n.d.; Linkedin - Matthew Grocki, n.d.) and has broad experience in the digital business context and has been helping worldwide recognized firms such as Cisco, Nasdaq OMX and Dell among others. He has also written business articles and is recognized by popular digital magazines and digital marketing books (Unger and Chandler, 2009). In our analysis, Mr. Avore was coded as M5 and Mr. Grocki was coded as M6.

In video four, Laryssa Wozniak interviewed Marco Giovanelli regarding the OCR in the luxury sector (Youtube - Joy Joya Jewelry Marketing, 2020). Mr. Giovanelli is Founder and CEO at Giovanelli Consulting and has over six years working with retailing companies worldwide (CONSULTING, n.d.; Linkedin - Marco Giovanelli, n.d.). Mr. Giovanelli was coded as M7.

In video five, Alexander Graf (Dept Agency, n.d.), interviewed Ben Cornelisse about the management of the OCR (Youtube - Kassenzone, 2020). Mr. Cornelisse is CEO at Kamera Express Group and has been working there for over 15 years in the retail sector. Kamera Express Group has focused on becoming the largest photo and video specialist providers in the Netherlands and in Belgium, where they are located in 13 Superstores and three city stores. They have focused on innovation and to offer their consumers something extra when buying with them, even opening up a test room for the photo shoots (Kamera-express.nl, n.d.; Linkedin - Ben Cornelisse, n.d.). Mr. Cornelisse was coded as M8.

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Supply Chain with over ten years’ experience. Commonwealth Supply Chain Advisors, LLC is a consulting and advisory service firm, within the supply chain, that is based in Boston. Their consultants offer solutions in areas such as Supply Chain Planning, Distribution Optimization, and Transportation Optimization (Commonwealth-sca, n.d.; Linkedin - Ian Hobkirk, n.d.). Mr. Hobkirk was coded as M9.

In video seven, Andre Hordagoda interviewed Elizabeth Horn about the OCR current relevance and the future about it (Youtube - Go Instore, 2019). Mrs. Horn is Head of Retail Industry at Facebook Elizabeth Horn has over nine years of working with Facebook, in different roles within retail, such as Industry Manager, Head of Industry and Director, Head of Industry and E-commerce. Before Facebook she was Senior Account Manager at Efficient Frontier (Facebook, n.d.; Linkedin - Elizabeth Horn, n.d.). Mrs. Horn was coded as M10.

In video eight, Matt Shares interviewed Eric Quanstrom about the leverage of the OCR (Youtube - SBI TV, 2019). Mr. Quanstrom is CMO at Cience and has a vast experience in retailing working as Business Developer at Logitech in 2007, CMO at Nimble, CMO at Pipeliner where he oversaw the entire Marketing Mix for Pipeliner's CRM and continuing his CMO work at various companies, such as Science where he currently works (CIENCE, n.d.; Linkedin - Quanstrom, n.d.). Mr. Shares is an experienced CEO at Sales Benchmark Index with over 20 years in retailing, consulting, sales and marketing and is currently interviewing other managers on their experience on sales and marketing in its YouTube channel (Linkedin -Matt Sharrers, no date). In this analysis, Mr. Quanstrom was coded as M11 and Mr. Shares was coded as M12.

In video nine, Caroline Sizer, interviewed Meredith Sandland, Andy Hooper, and Adam Saper regarding the operation of the OCR (Youtube - TechTable Summit, 2019). Mrs. Sandland is Chief Operating OfficerKitchen United (Kitchen United, n.d.; Linkedin - Meredith Sandland, n.d.), Mr. Hooper, President & COO at &Pizza (Andpizza, n.d.; Linkedin - Andy Hooper, n.d.). Mr Saper, Managing Partner at Eataly (Eataly, n.d.; Linkedin - Adam Saper, n.d.). They were coded as M13,

M14, and M15 respectively.

In video ten, Stephanie Richelieu interviewed Alexandre Hubert and commented on OCR and the ways to provide experiences that consumers expect (Youtube - Generix Group North America,

2019). Mr. Hubert is Senior Director IT & Logistics at Browns Shoes. Brown shoes is a family

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collection for men, women & children (Brownsshoes, n.d.; Linkedin - Alexandre Hubert, n.d.). Mrs. Stagger is a Chief Revenue Officer at 3Gtms leading and aligning sales and marketing and has over 20 years of experience in the supply chain. She also has been working several years leading international corporate developments for a multibillion IT distributor (3GTMS, no date;

Crunchbase, 2020). Mr. Hubert was coded as M16 and Mrs. Richelieu was coded as M17.

The trustworthiness of the study

Quantitative methods evaluate data based on reliability, validity, and replication criteria; nevertheless, in the qualitative data, those criteria might not be appropriate for its evaluation

(Saunders, Lewis and Thornhill, 2015; Bryman and Bell, 2011). The alternative for assessing the

qualitative data is its "Trustworthiness" criterion to consider how valuable qualitative data is. In this criterion, four aspects are considered: credibility, transferability, dependability, and

confirmability (Bryman and Bell, 2011).

Credibility entails ensuring the good practice of the research and the investigators' correct understanding of the social world (ibid). In this regard, the primary data was collected from a CEO with over ten years of experience in OCR, working with major retail players in the industry in Sweden, and whose experience provided a broader context and guidance in the secondary data collection. The interview with him was necessary due to his vast experience on the subject, but also since the context of it has been developed in a sophisticated digital environment, which is the company Kicks and Sweden, giving the right conditions to get practical experience on OCR. Hence, the insights collected from the informant provided a wide range of essential data for the research. Secondary interviews were collected from YouTube, where the information is also accessible, but most importantly, the interviews were done to managers with similar experience in the retail industry and OCR.

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Dependability relates to reliability and refers to whether the results of the study are repeatable or the degree to which it could be replicated (ibid). The research could be replicated in other contexts and from different perspectives. The research studies the challenges experienced by managers that orchestrate the OCR. Orchestrators of OCR tend to be managers, and other retail companies could adopt the OCR approach in any other contextual frames outside of the USA and European countries. The study analyses several OCR orchestrators in the retail industry, which generates findings that are not specific to companies or conditions. Therefore, the study can be replicated in similar contextual variables under different or similar conditions (ibid).

Confirmability ensures that the researchers have acted in good faith, which means that personal values have not been transferred into the research or in the findings that were obtained (ibid). The researchers undertook a systematic approach to collecting data in all study stages with academic rigor. It provided transparent information on the used academic and public data sources across the whole study, which is accessible for other researchers in the reference section. By analyzing the video-interviews independently by each researcher, they made their annotations on separate files, without discussing the on-going findings. This approach diminished the researchers' potential biases, leaving space for the interpretation of the data to be handled as bias-free as possible.

Methods limitations

Primary data collection sampling, voluntary (snowball), is problematic to obtain the first sample

(Saunders, Lewis and Thornhill, 2015). Conducting interviews with a small number of responders

limits the generalization of the findings under other settings, although this could be generalized in other contexts (ibid). This limitation was addressed by combining primary and secondary data concerning the phenomenon with similar characteristics, interviews with OCR orchestrators from Europe, Australia, and the USA.

Also, since the primary interview was an online video conference, the researchers were limited to annotated factors in the environment that could affect the informant's answers, which could have provided a more abundant data (ibid). The interview was done in a controlled environment to reduce this limitation, the informant's office, and the interviewers' home, respectively.

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research (ibid). To reduce the deviation on the data collection, the researchers considered sources with particular matters to the research. Regarding the online video-interviews, only current and relevant secondary interviews were considered by sorting and filtering them to get a closer match with the phenomenon of the study.

Ethical implications

The research design follows the ethical standards to research without harming, embarrassing or causing pain or disadvantage to the responder and the audience in general (Saunders, Lewis and

Thornhill, 2015). With this intention, the researchers used a sampling method that did not pressure

the participant; it was voluntarily granted access. Hence only individuals willing to participate were considered. Refusal answers were accepted and addressed professionally. Considering the respondent's confidentiality, the interviewee got the option to ensure his privacy and was asked about their permission to record the interview before the video-interview. Information and transparency were also provided (ibid). Considering the on-going situation with COVID-19

(WHO, 2020), besides the convenience of the online video-conference, the researchers used this

method in order to ensure it did not harm both the researchers and the informants' health (Saunders,

Lewis and Thornhill, 2015). In the secondary data collection, it used academical, public and

accessible data where the consent for its use without commercial purpose was considered to avoid privacy issues.

Data analysis method

A qualitative thematic analysis method followed the study. This method helped the researchers analyze the gathered qualitative data to search for themes or patterns (Saunders, Lewis and

Thornhill, 2015). This method is systematic, a useful characteristic to analyze large or small

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Process of thematic data analysis:

For the primary data, the researchers transcribed the one-hour interview with M1, read it, and familiarized it with the content (Appendix 2). For the secondary data, to become familiar with the data, the researchers viewed the video-recorded interviews from YouTube in order to determine if they had valuable information and could fulfill the purpose of research. Once the videos were selected, the researchers transcribed the video-interviews into textual format.

In total, the researchers transcribed one primary interview (M1) and ten recorded interviews and seminars from secondary sources with 16 managers in the retail sector with experience in OCR (M2-M17). Next, the researchers analyzed the data to find common themes and patterns that could provide broader knowledge regarding the orchestration of OCR in practical settings. To avoid biases in the analysis, the researchers analyzed it individually (Saunders, Lewis and Thornhill,

2015).

The approach to finding the themes was based on emergent themes in the data that were mentioned continuously by the managers (M) (‘in vivo’). Additionally, the researchers created themes by interpreting the data (ibid). Next, those themes were compared to later find common themes and patterns indicating the challenges that managers perceive when orchestrating an OCR - this is presented in the finding chapter. Next, the challenges were allocated within the theoretical framework to make sense of the challenges identified in the data, with previous literature regarding the orchestration of the OCR at the managerial level. This is presented in the analysis chapter.

5. FINDINGS

The findings outlined four different common factors that challenge the orchestration of the OCR. The challenges were expressed explicitly or implicitly by the managers (M). The factors and their challenges are:

1. Organizational management 2. Consumer centric

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Organizational Management

The challenges were related to the management of the organization in the OCR. Challenges such as silo organizational mindset, organizational integration, the integration of diverse channels, managerial decision making, asymmetries between technologies and capabilities, were identified. Those are described below.

Silo mentality was recognized by managers as a problem of retailers when implementing an OCR.

M1 stated that challenges could arise internally during the transformation toward OCR,

specifically: “when you go from being an actor that has online sales and brick-and-mortar sales,

and try to merge them is the attitude of the brick-and-mortar, physical stores. Because it is not uncommon that they (staff) feel that they are threatened by the sales, ‘the online sales will take sales from us, we will lose our jobs... therefore we don’t want to place orders on the iPad’ and stuff like that”. M17 expressed that the silo mentality in the organization is not productive for OCR

since it limits the integration of all parts that conforms to the OCR and creates a holistic organization. She said: “silos are killers if your organization today is still operating in silos, your

effectiveness of being able to create that customer experience to do everything that’s required with the OCR environment is going to be severely limited if not completely a fail scenario”. In the same

reasoning, M10 suggests that retailers tend to have a silo mentality in their cultural organization and mentioned that: “there are reasons why teams are set up in silos and getting them

(organization members) to talk to each other can be a challenge”.

Managers also indicated concern about the organization of all elements that integrate the OCR.

M1 acknowledged that integrating elements in the OCR is complicated and added: “we will have

this set up for the physical and we will have this set up for the online sales, but the online sales are very tightly linked to the physical toward our online solutions. So, this might occur, so just teach the supplier that ‘this is the way we work’ and your total sales will increase”. M7 added

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suppliers' locations are not coherent with retailers’ physical stores, warehouses or consumers; which can cause troubles not only for the organization but also in collaborations. He exemplified:

“there was actually challenges with the suppliers' chain, because we are buying everything to our warehouse in the south Stockholm in Örebro and send this to customers from our main warehouse in Finland and to Norway, and they were where like “no, this is a different business area, you are cannibalizing on us…”. So that was also a challenge, but this is like an online sales challenge”.

Another underlined challenge by the managers was the diverse channels where consumers tend to be, which complicates its integration to generate an OCR. M4 argues that some retailers are pushing the boundaries when integrating online and physical channels, which implies creating an integration for different contexts and channels, such as in-store fitting rooms, systems, and eCommerce websites. M1 also mentioned its experience with a similar situation. Due to the business model, there was no solution to create a seamless integration of internal and external processes to create an OCR experience. He further continued by stating: “there were not

non-systems created for this business/way, so clients could come and let something read it in non-systems, manage it, so we don’t take in so many (of the literature), make the warehouse able in all boutiques.... So, at the beginning, we started with the boutiques, as there was no central warehouse”.

The organization of OCR also sets managers’ capabilities to make decisions to test. For instance,

M11 thinks that all leaders in companies face the challenge of knowing where the next revenue is

coming from with OCR. M12 suggested that there are many ways to surround or target ideal customers. However, it is not easy, and the respondent added “it seems common sense to say that

we should all use an OCR approach to reach our prospects, but it’s expensive, and it’s difficult if all the channels are open and don’t know which ones are the right ones. When do I use them? How do I use them? How do I leverage them in the most effective manner?”. Additionally, M2

mentioned that the manager’s role in the organization could be affected due to biases. This was endorsed by M10, who highlighted that heuristics, such as assumption, could challenge managers' decisions in the creation of the OCR. M7 also mentioned that managers often based their decisions on feelings. In this regard, several managers underlined progressive and ‘A/B’ testing approaches to OCR, which has its operational and economic implications; as M4 mentioned, technologies imply a challenge to adopt and adapt. He added: “you’re constantly testing because customers

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critical element that managers could use as complementary. However, this implies to account with the capabilities to understand the data.

Managers also underlined their struggle to challenge the alignment of resources needed for an OCR and the capabilities to use them, where asymmetries could be presented. As M5 stated,”

Getting to the core of why someone thinks one of these latest and greatest technologies is important, is oftentimes just as important as how you would implement technology in the first place. Because in a lot of cases what they’re asking for is different than why they need it”.

Additionally, M17 added that companies often lack the right competencies to maximize the leverage of the technology that is being implemented. In this concern, M16 suggested that it is vital to the retailers; nevertheless, it is essential to account for the right talent that implements the solution. In this regard, M9 argued that retailers tended to outsource some core capabilities to complement its OCR initially; nevertheless, this started to have a shift since retailers are trying to have ‘in-house’ capabilities for better integration purposes and because they started to feel more confident in the digital context. In this regard, M16 added that capabilities are sometimes the problem, and M17 mentioned that talent acquisition is a challenge.

Consumer Centric

In this factor, the challenges were related to the sources of consumers’ demand, the value proposition in the offerings, and the OCR experience's delivery.

Managers emphasized that the consumer is the center in OCR, and referred that understanding consumers' perspective in each decision is a key for OCR and a challenge since it entails predicting consumer expectations. M1 described it as: “It is always the customer! Always the customer

perspective! The customer has to feel like there are no thresholds to buy. It should be seamless for the customers, more or less the same experience as in the physical stores as in online, and also the same quality, the same service and experience in what they read in their tablets and the phones or the laptops. So, the experience must be the same”. Additionally, managers underlined consumer

behavior and natural human behavior as ground elements in the OCR experience, as M9 added that “I would say companies should just revisit their thought process in terms of what the consumer

really needs”. It was further emphasized by M17, where it was mentioned that there is much to

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that: “you need to bring your innovation towards the consumer, this is the most difficult part of a

producer of a product”. M13 added that although firms can influence consumers to go to one

channel or another, they cannot make consumers choose the company. The manager added: “if

they decide that they want to go to GrubHub one day, and your website another day, and who knows where else, that's what they're gonna do. So, we view our job is trying to make it as easy as possible for that consumer”. M13, M12, and M14 referred to trends that could impact consumers’

behavior on their OCR. This was also recognized by M4 and M10, who underlined that trends disrupt retailers' and change consumers' behavior.

Another common challenge expressed by managers was creating value for consumers. In this reasoning, M1 highlighted the importance of this, exemplifying that: “The speed of offer and

keeping the fight to be in top of the mind of the customer, you have to be relevant, something new all the time”. Similarly, M8 implied that the product does not represent the total value for

consumers; therefore, one has to add other values to the consumer experience. The manager said:

“Offer something that adds value. For example, you buy a camera from us which cost 399 euros, we offer you a free photography course in our academy software,... which teaches you how to use your product and it has a personal value of 89 euros but because the possibilities digitally it's very affordable for us to create that content and distribute it to all customers who buy such camera”.

For example, M4 also outlined the stream toward personalization as a value. It stated: “Ultimately

personalization is giving you what you want, when you want it, where you want it, regardless of channel”. Similarly, value co-creation was also a common theme identified, where M8 suggested:

“We need to facilitate their platform, their usage, that connect them with each other to be able to

have them exchange knowledge together - there's also not just being able to offer web-shop but also a community platform, new types of ownership”. However, all managers recognized that

bringing value to consumers is not as simple, as M10 also recognized that a challenge is to create the value, emphasizing: “how do we make that easier? How do we get some of the friction out of

that process?”.

Managers’ concerns about the OCR experience to other stakeholders were also expressed. M1 acknowledged that one of the challenges is that suppliers could also disrupt the retailing organization, which also could impact the consumers. He stated that: “I will tell you that setting

up an ecommerce and the setting up the OCR; setups for the retailers, the challenges are basically not in the logistics, it is more with the suppliers and with the team and stuff like that!”. Also, M2

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adding: “do your homework like everywhere. Absorb information, figure it out from every single

part of your organization...what your internal stakeholders want, what your external stakeholders (want).... figure out the business once and then strategy was simply connecting the dots between the two”.

Additionally, M10 and M14 highlighted that retailers should be able to remove friction in processes from consumers and operations since the OCR experience also touches other stakeholders. Similarly, M17 endorsed that to serve the consumers better, easing the internal processes will have an impact on the consumer’s experience as well. She further explained that: “don't over engineer the processes that you're putting in place. Ensure how your internal parties

are internal constituents and supply chain partners, as an example, are able to collaborate, connect etc, internally as well as externally, with the client and that the client or the consumer is also able to interact”. Many others implied that in OCR, channels expand to consumers,

employees, collaborators, or even influencers, as M10 stated that influencers are used as part of the marketing campaign.

Leverage of Data and Business technologies

In this factor, the challenges were related to the role of technology and data in OCR, more precisely, the business systems, the impact of external technological factors, and the leverage and administration of data.

All managers recognized the critical role of the technology in their OCR orchestration; nonetheless, they also pointed out that the leverage of technology imposes a challenge. M10 added that technology is a tool for retailers to reduce friction across internal and external processes and to gain knowledge on the consumer. Nonetheless, M1 explained that systems could decrease its logistic challenges by integrating processes to centralize its warehouse. Nevertheless, he also stated that this requires a grade of knowledge in systems and data and understanding the outputs.

M6 also recognized that the implementation of the technology also implies some challenges. M1

added that the challenge for retailers lies in acquiring the right system and implementing it so that all the different divisions become integrated. M1 stated: “The challenges are System wise; you

need the right system in order to other systems parts or the way to link everything so you can have this kind of experience, the seamless experience for the customer”. He further implied that retailers

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important than technology is its implementation. Similarly, M17 added: “Very often you see

software being implemented and then the company is lacking the talent to really maximize on that solution. I think that's an important point …”. In this regard, the managers also emphasized the

flexibility of the systems; M16 added that technology integration and flexibility are needed, but more importantly, its leverage, to this, the capabilities across the organization are essential.

Managers also highlighted the importance of the data and its challenges in the orchestration of OCR. M1 mentioned about the challenges about data and explained that retailers are still using the data in a basic way, implying that data is not fully leveraged and there still more advanced ways to leverage it: “I have not seen anything that resembles the idea of what I have with the customize

offer, with for example - ‘Daniel, I want to make you happy, this is what you need’. In that sense, what exists now is like: ‘You usually buy this, we have this for offer or people that have bought the things that you have, also bought this’. It is quite primitive, to be honest. Instead of studying the data of buys and my persona, that is being developed now and offering something to me that I might be interested in or something that I have not thought about, but YES this is for me. That is the next step”. In this regard, M10 also thinks that companies tend to capture data. However, they

fail to leverage it and suggested that knowing the consumers through their data “can be your

superpower as a retailer”. She exemplifies that: “If it is a fashion brand, they know my style, they know my size, they know my buy frequency. So, you can probably predict gaps, and can probably predict if I have been buying the exact same pair of black trousers every autumn”.

M17 also recognized that the data that arrives from different systems could help managers make

informed decisions. However, she recognized that the quality of the data should be considered, but more importantly, its integrity. She said: “We have a bigger challenge to overcome, which is

around the data integrity”. Similarly, M16 added that data is a key in retailing for managers but

that the real value comes when the data leverages other levels. He said: “we really start seeing a

lot of value for us when we start focusing on training our staff in the stores”. Additionally, M14

alluded that there is a paradoxical view of the leverage of data in OCR. He pointed out: “there's a

bit of a catch-22 of like you can't really know your guests until they’re yours”. This reasoning

suggests that to understand and get consumers, one needs to understand the consumer’s data; nevertheless, one needs to have consumers first to get the data.

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and artificial intelligence could benefit retailers. However, they also recognized that the challenge lies in its implementation. M5 also stated that although advanced technologies benefit retailers, they still need to consider its usability and applicability, so capabilities are still necessary. Similarly, M9 implied that technology is useful to some extent, but its applicability to both contexts, digital and physical, is limited. M4 mentioned that consumers are always changing their behavior. Therefore, technologies help retailers to cope with it. Nevertheless, he implied that there is no accuracy in which technology retailers need setting managers in an A/B testing phase, which compromises OCR efficiency.

OCR Principles

In this factor, the challenges were related to the need to ground the OCR in some principles that allow agile responsiveness, having a focus, and using channels more efficiently.

Managers highlighted concerns about the firms' flexibility to move, respond, and adapt to sustain the OCR. For instance, M1 exemplified that: “it has been a question of speed, comparing online

players with the OCR player and you want to play in an even playing field then the OCR player has to move faster in brick and mortar and online”. M16 mentioned that it is crucial to find the

right solutions to respond to the changes; otherwise, the rigidity will constrain their flexibility to compete better, the manager underlined: “if you're not flexible like maybe you won't be there in

five years from now”. M9 pointed out that some factors that make OCR orchestration difficult

regarding adaptation are factors such as events, seasons, customer segments, international market, demographics, technologies, and bigger competitors. Thus, he recognized that retailers must be capable of adapting to those emergent events. M1 further commented this as: “No, not, is not just

to attract, but it is because the competition is moving so fast. Driving by the online players, because they can say, "Ok, it is going to be sunny 'next days' and all people are winter pale, we need to put sun blocks on offer".... So only online players can do this like this (‘snap fingers’ meaning instantly)”.

Managers are also concerned about the challenges that the use of channels in the OCR entails. As

M7 stated: “if you wanna attract or try to reach customers or the market with different channels

there is nothing wrong with that but invest wisely, your time and effort, and understand what the specific channel is made for”. In a more current situation, M1 described how the COVID-19

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the channels in helping them to adapt to current difficulties: “The stores, physical stores, we have

actually been forced to close two stores for customers. We are still in the store, picking orders and shipping but not opened for customers. That of course, affects the sales in these stores but on the other hand we have seen a good increase in our total sales, thanks to people ordering online... I think that has been a good thing for us”. It implies that it is not about the number of channels they

use, but more about which are relevant to reach the consumers. In this sense, M15 thinks that data is part of the process to understand what channels are adding value to the firms, and implied that channels do not add the same value to all companies. In this regard, M6 recognized that companies are mistaken, taking OCR as a way to be in all channels. M14 also mentioned that managers tend to assume that all channels are created equally, meaning that there is no difference in which to adopt, which is not. Nevertheless, most of the managers mentioned that physical channels are still having a dominant role in consumers' experience in OCR, as M8 illustrated: “we saw that the

physical touch points are a very dominant role in that journey of trying out and consulting but as well the convenience”. Additionally, M9 referred to the challenge of maintaining consistent

logistics when there are different channels.

Summary of the empirical findings

The empirical findings were presented in the previous section representing the managers’ perception and experience on the orchestration of the OCR.

Organizational Management

A factor that was commonly recognized by managers was the challenges in managing the OCR organization, which entails setting the organizational foundation for the implementation of the OCR. Secondary and primary data pointed out that those challenges were related to:

● Managers' capabilities to create a holistic organization and integration across internal and external stakeholders,

● To manage the integration of diverse channels ● To be prepared to make decisions

● To set the particular resources and capabilities for the OCR across the organization and have symmetry between them. Being coherent between the technology and the

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The findings pointed out that another challenge for managers is to maintain their operation around consumers, meaning that they need to be capable of aligning according to consumers' demands by being consumer-centric in their approach. For orchestrators, this implies:

● To be aware of the sources of consumers demands and follow them, rethink the value they offer to consumers

● To create value to consumers through all the channels

● To deliver an OCR experience to all its stakeholders, both internal and external, such as employees, suppliers, consumers, collaborators, or other actors related to the OCR

Leverage of Data and Business technologies

The findings also highlighted that managers struggle as well with the leverage of technology and data. The challenge here relates to:

● The proper use and exploitation of technology, to the needs of the firm, in regards to the consistent and unexpected needs in OCR implementation. This implies managers' awareness of the role and value of technology in the creation of the OCR.

● The use of the data in the most effective way to enhance the overall OCR organization and deliver more value to consumers and benefit the firm.

● This is a consequence of the challenge to get and align the particular knowledge and capabilities required for the OCR. Both themes were mostly consistent, one with the other, technology, and data.

OCR Principles

It was also highlighted that managers try to achieve and establish some principles on the OCR that are commonly persuaded. The OCR principle implies that retailers have:

● To be agile in responding to external changes that could impose challenges or opportunities

● To be capable of planning its transformation toward OCR, set the main focus in their mission from the initial start, and to create competitive qualities in the OCR.

Omnichannel retailing -

Master’s Thesis 30 credits

Department of Business Studies

Uppsala University

Spring Semester of 2020

Date of Submission: 2020-06-03

Omnichannel retailing -

The art of omnichannel orchestration

Authors:

Edward Toscano &

Nicholas Sanchez

Supervisor:

Abstract

Table of Contents

1. INTRODUCTION

Mitigating the digital transformation & consumer demands: Omnichannel

Omnichannel retailing (OCR)

OCR in practice

Problem formulation

Research problem Statement

Purpose

2. LITERATURE REVIEW

The benefits of OCR

Technology's & consumers dynamics in OCR

Data analysis between technology and consumers’ behavior

OCR orchestration: Leaders as orchestrators

Summary

3. THEORETICAL FRAMEWORK

Managers’ problems concerning OCR

Analytical framework

4. METHODOLOGICAL CONSIDERATIONS

Design

Empirical data collection

The trustworthiness of the study

Methods limitations

Ethical implications

Data analysis method

Process of thematic data analysis:

5. FINDINGS

Organizational Management

Consumer Centric

Leverage of Data and Business technologies

OCR Principles

Summary of the empirical findings