Digital Strategies to Improve the Performance of Pharmaceutical

Section 1: Foundation of the Study

The digital supply chain in a pharmaceutical company is known as the strategic

and operative exchange of information (product, design, research, and competition)

between stakeholders, such as suppliers, manufacturers, logistics service providers,

customers, and regulatory agencies (Singh et al., 2016). The digitalization in supply chain

helps build a new type of sustainable, responsive, and resilient supply network because

the complex pharmaceutical supply chain involves life-saving interests and requires the

mandatory participation of stakeholders (Haddud et al., 2017; Korpela et al., 2017).

Digitalization has fostered a new era of competitiveness using digital strategies, digital

enablers, digital system integrators, and application technologies (Ehie & Ferreira, 2019).

Using digitalization to reduce operational costs and make the process effective is thus a

necessity for profitability in a pharmaceutical industry. Slow supply chain digitalization

impedes the firm from competing against top competitors and increasing market share

(Dalal & Akdere, 2018; Kane et al., 2015). The degree of digitalization in the supply

chain can help determine the success of real-time inventory monitoring, collaboration,

integration, customer interaction, and efficiency, which can lead to improved

performance and profitability (Iddris, 2018).

Background of the Problem

The growing complexity of managing a supply chain influence the performance

of an organization (Kamalahmadi & Parast, 2017). Business managers in pharmaceutical

organizations face significant threat levels by not embracing digital transformation in

supply chain business processes. According to researchers, 27% of business have

suffered damage to their reputations, 58% have lost productivity, and 38% have reported

reduced revenue from supply chain disruptions (Paul et al., 2017). The constraints that

leaders of pharmaceutical companies face include stringent regulations, stakeholder

alignments, third party logistics, regulated pricing, demand sensing, and counterfeit

products in addition to different nature of goods that are being delivered through

pharmaceutical supply chains (Yousefi & Alibabaei, 2015). High margin gained from

sales of original products has allowed pharmaceutical industries to afford high supply

chain costs and pay less attention to enhance supply chain efficiency (Merkuryeva et al.,

2019). The business managers in the pharmaceutical companies spend one-third of their

revenue on supply chain management (SCM) activities because of flawed transportation

infrastructure and misalignment between stakeholders (Tyagi & Agarwal, 2014). In a

competitive global environment, supply chain agility and reliability are the most critical

elements in the success of an organization, but the current situation is less assured

(Jacques, 2017).

Problem Statement

Managers in an organization need to improve efficiency and visibility in the

supply chain system because the growing complexity to manage a supply chain system

has resulted in supply chain disruptions that negatively impact organizational

performance and increase the cost (Kamalahmadi & Parast, 2017). Supply chain

disruptions have cost a specific firm more than $17 billion in lost revenue (Wang et al.,

2017). The general business problem is that some pharmaceutical managers lose supply

chain efficiency, visibility, profitability, and business by not digitalizing the supply chain

system. The specific business problem is that some pharmaceutical managers lack

strategies to digitalize the integrated supply chain system to increase profitability.

Purpose Statement

The purpose of this qualitative multiple case study was to explore the strategies

used by some pharmaceutical managers to digitalize the integrated supply chain system to

increase their profitability. The target population consisted of five managers from four

pharmaceutical companies in New Jersey who have successfully developed strategies to

digitalize the integrated supply chain system to improve their business practices and

profitability. The study findings may enable pharmaceutical managers to identify and

implement value-added strategies to digitalize their supply chain system, which could

help reduce operating costs, improve profitability, and contribute to national, state, and

local economies. Pharmaceutical managers could also facilitate increased availability and

distribution of noncounterfeit medicines to patients at lower prices to effect positive

social change.

Nature of the Study

There are three types of research studies that researchers may use: quantitative,

qualitative, and mixed (Yin, 2018). Researchers using a quantitative research design

acquire generalized knowledge and make statistical inferences to a broad population

through a population sample (Saunders et al., 2019). I chose a qualitative, multiple case

study to explore the digital supply chain strategy used by some pharmaceutical managers

for digitizing their supply chain system. A qualitative research design allows

investigators to focus on broad context and business problem of an organization. The

qualitative research method also helps researchers understand participants’ views and

experiences (Merriam & Tisdell, 2015). Often, a new avenue for further analysis opens if

the response is unanticipated by researchers. The mixed method research design

combines quantitative and qualitative research techniques to address more complicated

research questions and develop a deeper theoretical understanding (Saunders et al., 2019).

The mixed method approach was not appropriate for this study because I did not need the

quantitative method to answer the research questions about strategies to digitalize the

integrated supply chain system. Therefore, the qualitative research design was more

appropriate for this study than quantitative or mixed method research designs.

Ethnographical, narrative, phenomenological, and case study designs are the four

types of qualitative research designs most commonly used by researchers (Ridder, 2017).

An ethnography research design is used to investigate beliefs, behaviors, and rituals of

unknown cultures by living, observing, and talking to persons with these cultural

differences (Saunders et al., 2019). For these reasons, ethnography was not suitable for

this study. Researchers using narrative analysis explore and analyze the experiences of

participants through personal stories rather than collecting data from specific interview

questions (Saunders et al., 2019). In the narrative analysis, researchers focus more on

human knowledge and personal experiences. For these reasons, I did not use a narrative

research design. Phenomenological research was also not appropriate for this study

because I did not intend to describe and interpret the participants’ meanings or lived

experiences of a particular event (Marshall & Rossman, 2016). A single case study

design is appropriate when exploring a specific and complex phenomenon within its real-

world context (Yin, 2018). A multiple case study is an approach used by researchers to

analyze the questions of what, how, and why of a phenomenon and obtain and compare

experiences and perspectives concerning a specific situation occurring across multiple

distinct cases (Yin, 2018). Using a multiple case study design, I collected, analyzed, and

compared data regarding the various strategies from those who have successfully

digitalized the integrated supply chain system.

Research Question

The research question for this study was “What strategies do pharmaceutical

managers use to digitalize their integrated supply chain system to increase profitability?”

Interview Questions

1. What strategies did you select to digitalize your organizations’ supply chain

system?

2. What were the digital processes and tools that you selected to digitalize your

supply chain system?

3. What were the criteria for selecting these digital tools and strategies?

4. How did you assess the effectiveness of your strategies for meeting your

expectations?

5. What were the primary barriers to implementing the strategies for digitizing your

organizations’ supply chain?

6. How did you address the key barriers or constraints to implementing your

organizations’ digital strategies for mitigating disruptions in the supply chain

system?

7. Based on your experience, how have these digital supply chain strategies helped

you improve your organizations’ performance?

8. What additional information would you like to share concerning the strategies you

developed and implemented to digitalize your organizations’ integrated supply

chain system?

Conceptual Framework

The conceptual framework selected for this study was the theory of constraints

(TOC). Eliyahu Goldratt’s (1990) TOC is a system-based management philosophy to

understand and identify the root causes that limit a system from achieving higher

performance. With TOC, digital supply chain managers can formulate a robust design

strategy in the early phase, continuously improving the digital processes by identifying

and analyzing constraints and solutions for every step of the digital supply chain system.

The TOC may help in providing the insights needed to determine why nondigitalized

SCM fails to achieve organizational goals. A constraint is defined as elements of the

factor that limits the system from doing what it was designed to accomplish (Goldratt,

1990). Constraints hamper the progress or increased throughput of an organization. Thus,

the pharmaceutical manager’s failure to manage this constraint leads to declines in its

productivity. The same TOC analogy can be made to the supply chain, where weak and

nondigitalized supply chain links can limit the entire supply chain’s effectiveness and

efficiency. A digitalized supply chain system can have various constraints, such as

constraints related to storage, constraints related to production, constraints related to

flow, and constraints related to strategic partners’ information (Okutmus et al., 2015).

The TOC was used to anticipate and address the primary challenges companies face and

utilize to develop their digital road map. Using the TOC, I was able to understand the

strategies, processes, and tools the participating pharmaceutical managers used to

digitalize their supply chains successfully.

Operational Definitions

Artificial intelligence (AI): AI is defined as the capability of different computation

algorithms that allow various devices to forecast actions, processes, and trends (Segars,

2018).

Big data analytics (BDA): Big data is defined as structured and unstructured data

formats continually generated from multiple sources (Grover et al., 2018).

Cloud computing: Cloud computing is a model for enabling convenient, on-

demand network access to a shared pool of configurable computing resources that can be

rapidly provisioned and released with minimal effort from management or service

providers (Giannakis et al., 2019).

Digitalization: Digitalization involves using digitalized data and using digital

technology, leading to change in business processes, and models to provide new revenue

and value-adding opportunities (Gobble, 2018).

Digital strategy: Digital strategy is the vision and tactics of running the business

differently by renovating business processes and business models enabled by digital

technologies such as the Internet of Things (IoT) and AI (Westerman, 2018).

Integrated supply chain ecosystem: Integrated supply chain ecosystem is a

network of interconnected supply chain firms that shares common value and depends

upon each other for their survival (Liu et al., 2019).

Internet of Things (IoT): IoT is a framework based on the availability of objects,

heterogeneous devices, and interconnection solutions that provides shared information

based on a global scale to support the design of applications involving people and the

representation of objects (Atzori et al., 2017).

Supply chain management (SCM): SCM is an integrated process for efficiently

managing the supply chain operations to deliver value to the stakeholders and increasing

and working toward enhancing supply chain performances (Kumar & Kushwaha, 2018).

Assumptions, Limitations, and Delimitations

The purpose of this section is to define assumptions, limitations, and

delimitations. Researchers use assumptions to justify decisions they make concerning the

research design and promote research synthesis (Wolgemuth et al., 2017). Limitations are

weaknesses a researcher must be aware of and address that can affect the validity of the

research (Cypress, 2018). Delimitations are purposeful biases formed by the researcher

during the design of the study (Price & Murnan, 2004). Limitations are biases not

controlled by the researcher, and delimitations are biases the researcher does control

(Price & Murnan, 2004).

Assumptions

To ensure quality, researchers must identify and mitigate risk from assumptions

by explaining exclusion and inclusion decisions and their impacts on research findings

(Wolgemuth et al., 2017). The assumptions that contributed significantly to the quality of

this study were: (a) the participants understood and answered the interview questions

honestly, truthfully, and without any bias; (b) the participants have the significant

professional knowledge in the supply chain and managed digitalized supply chain in the

pharmaceutical domain; (c) the participants surveyed for this study have decision-making

authority or can influence decisions in their organizations; and (d) as generated from the

interview session, the audio and video recordings and transcripts were accurate vocal

representations of the participant’s response to semistructured, open-ended questions.

Limitations

A study’s limitations represent the potential weakness, restrictions, and

shortcomings in the study that is out of the researcher’s control in most cases (Busse et

al., 2017). Limitations are also the restrictions on the interpretations and conclusion

because of the chosen methodology and research topic (Greener, 2018). A potential

limitation is the small size of the research population and short time limit of the case

study. Another limitation may arise by restricted data from archival documentation

because of the pharmaceutical company representative’s interest in protecting intellectual

property rights.

Delimitations

Delimitations are boundaries or restrictions intentionally placed by researchers to

limit the study’s scope (Andrade, 2019). Delimitations are boundaries established by

researchers to narrow the scope of the study (Holloway & Galvin, 2017). The study was

limited to the pharmaceutical managers located in the United States, representing the

study’s validity. Thus, the delimitations of the study are the geographical limitation of

scope to the United States.

Significance of the Study

The study’s findings are significant to enhance organizations’ supply chains’

efficiency and effectiveness. Some pharmaceutical companies’ managers are traditionally

resistant to technology change when digital transformation is becoming a prerequisite for

ensuring supply chain efficiency, visibility, speed, and quality (Jacques, 2017). But using

digitalization, managers can add value by increasing reliability, robustness, and flexibility

of supply chain planning, implementation, and improvement (James, 2017). The

strategies could also contribute to positive social change by reducing the adverse events

caused by counterfeit and compromised drugs. The following subsections include the

potential specific contributions to the specific business practices and social change

implications.

Contribution to Business Practice

The pharmaceutical industry’s supply chain complexity is well known as a

product needs to pass through the various complex product life cycle phases (Asl-Najafi

& Yaghoubi, 2021). The life cycle phases can be defined as a research or discovery

phase, testing for safety and efficiency, registration with regulators such as Food and

Drug Administration, meeting medical control council standards, and commercial

manufacturing (Asl-Najafi & Yaghoubi, 2021). Research findings about digital supply

chain strategies provide chain managers strategies for improving business practice by

enhancing digitizing pharmaceutical supply chains’ efficiency and effectiveness.

Implications for Social Change

This study’s findings contribute to positive social change in organizations that use

or plan to digitalize their supply chain processes. An effective digital supply chain

strategy is critical to ensure that the managers in the pharmaceutical supply chain: (a)

monitor counterfeit products and protect consumers from adverse effects, (b) implement a

sustainable green supply chain to protect the environment, and (c) reduce the turnaround

time and availability of counterfeit drugs (Saxena et al., 2020). The results contribute to

positive social change by leading to lower prices for end consumers and improving the

experience of patients who receive their medication supplies from pharmaceutical supply

companies.

A Review of the Professional and Academic Literature

The objective of this qualitative multiple case study was to explore the strategies

used by some pharmaceutical managers to digitalize the integrated supply chain system to

increase their profitability. This literature review is organized as follows: the conceptual

framework of TOC, overview of digitalization, pharmaceutical industry, digital supply

chain in general, pharmaceutical supply chain and its challenges, road map in the

pharmaceutical supply chain, digital enablers, disruptions, and agility in the supply chain,

and finally sustainability in the digitalized integrated supply chain system.

Search Strategy

The literature review included an integrated review of articles from the databases

of Walden University Library, EBSCOhost, Google Scholar, numerous business journals,

ProQuest, and SAGE Publications. Search terms for conducting research for the literature

review included digitization, digitalization, digital supply chain, pharmaceutical supply

chain, IoT, Big Data, AI, Cloud, disruptions, agility, sustainability, conceptual

framework, the theory of constraints, and qualitative research or a combination of

keywords.

The review of the literature included 124 peer-reviewed references, out of which

15 references accounted for 12% and were published prior to 2017 (see Table 1). The

remaining 109 were published between 2017 through 2021, which accounted for 88%

that were published within 2017–2021. The doctoral study included 162 peer-reviewed

references, out of which 16 references accounted for 10% that were published prior to

2017. Between 2017 through 2021, 146 references were published, which accounted for

90%.

Table 1

Sources of Data for Literature Review and Doctoral Study

Lit. review

sources

published

prior 2017

Lit. review

sources

published on or

after 2017

Total

references

prior to 2017

Total

references on

or after 2017

Total

references

Books 2 0 2 1 2 3 5

Peer-reviewed 15 109 124 16 22 38 162

Non-peer-

reviewed

7 4 11 0 0 0 11

Total % of

peer-reviewed

resources after

2017

12 88 75 42 58 79 90

Note. Number and percent of references published before and after 2017. Ulrich’s

periodicals directory is used to verify peer-review status. References were from peer-

reviewed journals and books of which the literature review accounted for 75% and the

doctoral study accounted for 90% of peer-reviewed journals published within the last 5

years.

Conceptual Framework: Theory of Constraint

The conceptual framework selected for my doctoral study was the TOC.

Goldratt’s (1990) TOC is used for reviewing organizational performances regarding

efficiency, visibility, and profitability by digitalizing the integrated supply chain eco

system. I selected the TOC as the conceptual framework mainly because business

managers have found the TOC effective in achieving their goals. The objective of every

organization is to make a profit, and the constraints are the major obstacles for not

achieving the goals. The inadequacy of traditional management and global

competitiveness is the primary reason organizational managers adopt TOC as a

continuous process framework to achieve the goals (Okutmus et al., 2015). Researchers

use the TOC to help identify, leverage, and remove constraints in its operations

(Kuruvilla, 2017; Trojanowska & Dostatni, 2017).

The pharmaceutical industry’s business managers may use TOC to identify

constraints and challenges associated with supply chain strategies and find a solution to

overcome those challenges. Business managers of most organizations implement TOC as

a broad-based operation management strategy for improving profitability, effectiveness,

and efficiency throughout the manufacturing process (Modi et al., 2019). The TOC

suggests that most real-life systems are inherently simple and not complex because of

few root causes or constraints. Treating those symptoms may not yield substantial

improvement in the process, and the only way to eliminate it is by addressing the

system’s proper constraints (Modi et al., 2019).

There are five cyclical steps during business improvement processes while using

TOC (Goldratt, 1990; Okutmus et al., 2015). The steps can be described as (a) identify

the constraints that are currently preventing the firm from achieving the goals; (b) exploit

the constraints by determining the necessary actions to bring about desirable change or

effects; (c) subordinating every related decision to the constraints by focusing only on

constraints as other functional department is linked with the department, that is affected;

(d) elevating the constraints by expanding the capacity of the department to eliminate the

constraints; and (e) discovering, evaluating, and eliminating the new constraints in an

endless cycle that leads to continuous improvement process inside the organization.

TOC’s cyclical structure indicates how business leaders identify, exploit, subordinate,

elevate, and repeat to eliminate the constraints.

A constraint can occur anywhere within manufacturing, including supply chain,

logistics, or internal processes. Five different types of constraints include (a) market

constraints, (b) capacity constraints, (c) logistics constraints, (d) behavioral constraints,

and (e) administrative constraints (Okutmus et al., 2015). The market constraint is

prominent in the pharmaceutical supply chain because customer demand and

manufacturing mismatch are frequent. Capacity constraints relate to poor supply chain

planning as an existing resource is insufficient to meet the market demand. Logistics is an

integral function of the supply chain as it plans, implements, and controls the flow of raw

materials, semi, and finished material for meeting customer’s requirements (Kudláč et al.,

2017; Okutmus et al., 2015). Any constraint that pertains to logistics will adversely

impact the supply chain efficiency. The administrative constraint is mostly related to

organizational policies and the limiting factor toward hindering workflow (Okutmus et

al., 2015).

The pharmaceutical supply chains are traditionally complex, and using TOC is

valid for such industrial segments. What makes the task of managing a typical supply

chain so complicated is that many suppliers supply a large variety of raw materials,

including active pharmaceutical ingredients and active biological ingredients, to large

manufacturing sites that produce a large variety of products. The products are then

shipped using several transportation methods to a vast number of customers and logistic

service providers located around worldwide (Modi et al., 2019).

Complementary Theory

Competitive Advantage Theory

Managers in pharmaceutical industries may use the theory of competitive

advantage to complement the TOC for gaining a competitive edge. Competitive

advantage theory is a widely tested framework for planning and innovation that works

through a value chain, and each link encompasses activities to add value to the entire

value chain (Pontinha et al., 2020). Porter’s (1980) competitive advantage theory

suggests optimal utilization of resources and decisions made based on all levels, such as

national, corporate, local, and individual. Manufacturing business leaders may use

competitive advantage theory to differentiate products and services from competitors by

offering customers unique products and services at a lower cost (Bel, 2018).

Porter (1980) discussed three approaches toward developing a successful

competitive strategy known as generic strategies: focus, differentiation, and the cost of

leadership. Business leaders can serve a targeted segment and specific market by

focusing on unique products and services teller made for that market. Focusing on

specific target helps business leaders to limit vulnerability from competitors.

Differentiation helps business leader’s ability to produce unique products of services for

gaining an advantage over competitors. The cost of leadership refers to the business

leaders’ ability to maintain cost to achieve a larger return on investment.

Digitalization may not directly affect competitive advantages but has strong

indirect effects on products and service advantages (Lee & Falahat, 2019). Competitive

advantage is the extent to which an organization can create a defensible position over its

competitors (Porter, 1980). Competitive advantage is expressed regarding reducing

product development cycle, cost, flexibility, quality, delivery, and sustainability (Liao et

al., 2017). Business managers must adopt digitalization and be ready for suitable digital

tools to accelerate the competitive advantage process over their competitors. (Lee &

Falahat, 2019)

Contingency Theory

Contingency theory is also considered as a complementary theory to the TOC.

Contingency theory emphasizes the importance of the situational context in which

managers operate. Business managers use contingency theory in decision making and

best practices and unique tools to address the current situation, and not as a generic

selection of tools (McAdam et al., 2019; Prester et al., 2018). There is no single best way

to manage leadership processes, decision-making, and process of organizing as different

environments offer different antecedents in contingency theory (Romero-Silva et al.,

2018). Leadership in organizations may adopt contingency theory to support leadership

decision-making and achievement of competitive advantages using various diverse

strategies that fit and applicable to a particular situation (Williams et al., 2017).

Organizations must take a contingency approach of entrepreneurial orientations

and strategic vision on digitalization (Niemand et al., 2020). Contingency theory helps

managers to view firms as an open system where information is exchanged through the

input-process-output procedure (Romero-Silva et al., 2018). Input consists of contextual

internal and external issues, processes indicating organizational responses to these inputs,

such as strategies, and output refers to these processes’ results. Business managers must

develop a clear vision regarding digitalization characterized by innovation, being ahead

in competitive advantages, and a willingness to take risks (Niemand et al., 2020).

Competing Theory: Theory of Swift and Even Flow

Business managers may use the theory of swift and even flow (TSEF) instead of

the TOC to focus on speed and processes to achieve better productivity. The model of

productivity, also known as the TSEF, refers to flow for achieving variation reduction

and the throughput time frame to drive efficiency and eliminating nonvalue-added

activities from the value chain for cost reduction and efficiency enhancement

(Schmenner, 2015). Supply chain managers in pharmaceutical industry often use TSEF to

drive productivity and reduce cost by eliminating nonefficient activities and reducing

cost. Business manager may use TSEF for making the process become more productive

as its material and information flow increase speed and evenness (Yin et al., 2017).

Business managers use the TSEF for a more holistic view of the operational capability of

an organization (Nguyen et al., 2020).

Managers who use TSEF state that there are two factors with this theory to

productivity gains (Schmenner, 2015). The first critical factor is reducing variation, that

can be of different types, such as quality, quantity, and timing. The variability can also

occur as a decrease in uniformity by consequence of unpredictable demand for products

or planned variation, such as breakdown and the number of products online (Nguyen et

al., 2020). The second important factor is the reduction of throughput time as much as

possible. Quality refers to reducing defects, quantity refers to producing the same amount

each day, timing refers to producing at the exact regular timing with the same

manufacturing sequence, and throughput reduction refers to the time it takes to produce

from start to end (Schmenner, 2015). The productivity of any supply chain manufacturing

processes, such as total factor productivity, machine and material productivity, and labor

productivity, rises with speed the material move flow the processes and falls with an

increase in variability associated with the flow (Schmenner & Swink, 1998). In any

supply chain manufacturing system, capacity use, work in process, and variability should

always balance to enhance the agility of the supply chain system (Yin et al., 2017).

Business managers make better decision by developing adequate resources regarding

money, time, and people to enhance supply chain fitness by taking help from theory of

TSEF (Nguyen et al., 2020). However, the TSEF does not help business managers

manage constraints within the processes and focus majorly on removing variations and

reducing throughput.

Digitalization

Digitalization can be understood as a process of using digital technology, leading

to change in value creation, business processes, and business model to provide new

revenue and value-adding opportunities (Gobble, 2018; Gong & Ribiere, 2020).

Digitalization facilitates the organization toward digital transformation by automating the

processes for better outcomes. Digital transformation is a fundamental change process

enabled by digital technology that aims to bring radical improvement and innovation in

an organization to create value for its stakeholders by strategically leveraging its

resources and capabilities (Gong & Ribiere, 2020). Digitalization of business processes

enables organizations in various innovations, including improved design and new process

models, and shapes how organizations created enhanced values for their business

partners, such as customers, vendors (Nadeem et al., 2018). The new digital technologies

present essential threats to any organization and, at the same time, provide game-

changing opportunities also (Sebastian et al., 2020).

Business managers need to understand the concept and difference between

digitization and digitalization. Digitization is the straightforward process of converting

analog information to digital (Ritter & Pedersen, 2020). For instance, turning pages into

bytes by scanning a document or recording a sound is considered a digitization process.

Digitalization of business process means developing digital strategies to react and apply

emerging digital solutions such as the IoT, AI, cloud computing, blockchain to introduce

innovation, improve, enhance, and create new business processes. Digitalization is about

implementing cutting-edge technologies and not just change in the business processes.

Digitalization refers to the use of digital technology and digitalized information to create

and harvest value in new ways (Gobble, 2018; Ritter & Pedersen, 2020).

The goals of organizations that plan to invest in digitalization fall into two major

categories: to mitigate the risk of market uncertainties and to win competitive advantages

(Gong & Ribiere, 2020). Business managers may formulate the strategy around three

prominent elements to implement digital strategies to digitalize existing business

strategies for their pharmaceutical organizations. These elements include (a) defining

emerging digital technologies and digital solutions, (b) preparing a framework and

building operational backbone for facilitating operational excellence, and (c) quickly

adopting a digital service platform that enables rapid innovation and responsiveness to

customer and new market opportunities (Sebastian et al., 2020). Digital transformation is

a set of strategic renewal, transformation at a different level in an organization, and

leadership aspects of optimizing resources and capabilities attributes, which is far beyond

the use of technology alone (Gong & Ribiere, 2020).

Pharmaceutical Industry

The pharmaceutical industry is defined as a system of procedures, operational life

cycles, such as drug discovery, development including testing, review and approval,

oligopolistic competition, and generic competition (Lakdawalla, 2018). The companies

belonging to the pharmaceutical industry segments discover, develop, manufacture,

market, and distribute medicines. Classes of medicines include over the counter, Active

pharmaceutical ingredients, active biological ingredients, biologics (vaccines, proteins),

biosimilars, and any substances used in diagnosis, cure, mitigation, and treatment to

prevent disease (U.S. Department of Commerce- International Trade Administration,

2017). The global pharmaceutical market reached 1.3 trillion in 2020, up to $100 billion

from 2017, and for the U.S. market, its 2023 spending is projected to be $625-655 billion

(Vincent, 2020).

Pharmaceutical drug manufacturing is performed in batches, and equipment is

mostly self-contained. Though control technologies and industrial automation are well

established in pharmaceutical industries, integrated information on the equipment’s real-

time status or condition is still not accessible to help managers make informed decisions

and improve effectiveness in scheduling batches, cleaning, maintenance (Sharma et al.,

2020b). Pharmaceutical industries are also subjected to the Bullwhip effect or the

phenomena in which order placed by downstream nodes to upstream nodes are variable

over time and amplified further upstream from the customer (Azghandi et al., 2018).

Bullwhip illusive stock effect leads to high stock in warehouses, high rate of returned

products, high transportation costs, and customer dissatisfaction (Yousefi & Alibabaei,

2015). The four elements that contribute to a Bullwhip effect are (a) demand signal

processing, (b) order batching, (c) rationing game, and (d) price variations (Azghandi et

al., 2018). The Bullwhip effect may happen because of the lack of the right information at

the right time for the right decision-maker (Yousefi & Alibabaei, 2015).

Drug development is a long and expensive process and takes about 12 years and

approximately $3 billion costs to develop a new drug and to move from preclinical

testing to final approval with a success rate of 10–20% only (Vincent, 2020). Business

managers from pharmaceutical companies are showing interest in niche markets, away

from the saturated market or blockbuster drug market. These markets can help them grow

faster even though they are low volume. Business managers are also implementing an

agile supply chain by integrating information systems to increase the supply chain’s

speed and flexibility maker (Yousefi & Alibabaei, 2015).

Pharmaceutical Supply Chain and Challenges

The pharmaceutical supply chain includes a network of internal and external

stakeholders and their connection through which the production, supply, delivery, and

sales of essential pharmaceutical products are distributed to the end users at the right

place and at the right time (Sabouhi et al., 2018). The primary stakeholders in a

pharmaceutical supply chain include multiple government agencies, clinics, hospitals,

drug manufacturers, drug distributors, pharmacy chains, retailers, research organizations,

and retailers (Kapoor, 2018). The pharmaceutical supply chain encompasses effective

management of financial, information, and material flow among network components to

maximize profit and customer satisfaction (Alzaman et al., 2018). After drug launching, a

completely different set of objectives, drivers, and constraints become dominant (Kapoor,

2018). The same supply chain is responsible for distributing prescription drugs, over-the-

counter medicines, generics, and biologics. Different handling needs and operational

objectives make the matter more complicated to manage the supply chain (Kapoor,

2018). The material and money flow are different in different in pharmaceutical

industries as it involves more stakeholders in each phases of supply chain. The materials

and money flow are demonstrated in Figure 1.

Figure 1

Pharmaceutical Supply Chain Product and Money Flow

Note. In this figure, I show each stakeholder in detail before the final product reaches the

end user. The pharmaceutical supply chain products and money flows from various

cycles, such as synthesis, formulating, packaging, distribution, and end market.

Contract manufacturing organization (CMO) serves the pharmaceutical industry

with comprehensive services from drug development through manufacturing (Pandya &

Shah, 2013). Deciding about owning a brand or manufacturing through contract is a

strategic decision for business managers in a pharmaceutical organization. CMO refers to

a strategy that firms gets the manufacturing contracts to manufacture the products for the

outsourcing firm, while branding refers to a strategy that firm focus on establishing their

brands through leveraging the production competence of CMO (Hsiao & Chen, 2013).

Branding strategy is adapted when firms have better R&D and marketing capabilities,

and contract manufacturing strategy is adapted when firms have superior process and

manufacturing capabilities (Hsiao & Chen, 2013). Supplier qualification of CMO is

necessary for direct products, equipment, and even software and hardware as these

impact qualities of the final pharmaceutical product. Services offered by CMO can be

either primary manufacturing, which is the synthesis of bulk active pharmaceutical

ingredients, or secondary manufacturing, which is a formulation of bulk drug substances

into the final drug products (Pandya & Shah, 2013). Compatibility of excipient and active

pharmaceutical ingredients is required for drug formulations and enhancement of active

ingredients in the final dosage form, such as improving solubility and enabling drug

absorption. CMO contribute an important role in pharmaceutical, and many brand owners

outsource their entire operation or part of their process to CMOs. Goods are distributed

either through wholesale or distribution centers managed by the brand owner or third-

party logistics providers. Third-party logistics are more critical in a smaller region or

when special requirements of the drug, such as cold chain, come into play. Many contract

manufacturers are changing the trend by using various digitalization strategies such as (a)

real-time remote tracking of production and delivery processes, (b) protecting

blueprinting of production and using a secured channel for supply chains, (c) late-stage

customization to reduce turnaround time depending upon market demand, and (d) use of

AI for cost-effective and more productive manufacturing and use of blockchain for

making technology more secured (Clifton, 2021).

For any organization, including pharmaceuticals, supply chain design includes

two significant threatening risks: operational risks and disruption risks. The

pharmaceutical supply chain risk management includes four stages: risk identification,

risk prioritization, risk management, and risk monitoring (Osorio & España, 2020).

Operational risks frequently occur and are caused by medium to high likelihood and low

and short-term adverse effects (Sabouhi et al., 2018). Operational risks need to be

considered as they can significantly affect the company’s performance through their

severity, and the impact can be lesser than disruptive (Osorio & España, 2020). Inherent

uncertainties, such as customer demand, supply, and cost uncertainties, can qualify for

operational risks (Sabouhi et al., 2018). Osorio and España (2020) noted that operational

risks include risk associated with peoples, processes, machine, external events, and

pharmaceutical companies take action to mitigate those instead of eliminating. Disruption

risks have a low likelihood and can cause drastic social and economic changes. Natural

disasters, human-made threats, and technological threats can qualify for driving

disruption risks (Sabouhi et al., 2018). The supply chain risk management strategies

include agility, flexibility, and leanness to reduce the possibility of disruptions (Eltawy &

Gallear, 2017; Mohammaddust et al., 2017).

Industry 4.0 was initially established in Germany and paved the way for industrial

digital revolutions (Ding, 2018). Digitalization and automation are prerequisites for

Industry 4.0. Narayanan et al. (2020) noted that despite extensive growth, reaching $188

billion in sales in 2017, the biopharmaceutical sector distinctly lags in transitioning to this

aspect. The vision for industry 4.0 is to connect resources – human, data, and physical

machines, and combine diverse technologies, including BDA and cloud computing

(Narayanan et al., 2020). Industry 4.0 and its enabling technologies have the potential to

affect every function of an organization by bringing significant improvement in supply

chain and logistics management (Fatorachian & Kazemi, 2021). The ability to analyze

enormous data volumes and share insights across the virtual value chain is critical to

deliver innovation and respond to changing marketing dynamics. Contents and data can

be stored in a regulated cloud repository so that information can be accessed anywhere in

real-time. The concept of industry 4.0 by the name of pharma 4.0 is applied to the

pharmaceutical industry. The realization of pharma 4.0 requires a shift in how regulatory

contents and data are managed, and transformation needs to start with changes in mindset

and perception of the data content (Narayanan et al., 2020). Good practice, quality

guidelines, and regulations record keeping needs to be documented in electronic format

as it cannot be properly managed in paper-based formatting.

Most of the pharmaceutical organizations are still under batch production rather

than continuous production, which requires lower material consumption, decrease

hazardous solvents, and less influence on the ecosystem regarding air emissions,

chemical pollution, wastewater, and residual waste (Ding, 2018). Lack of robust online

quality control and flexible production is the bottleneck of reliable drug supplies,

resulting in drug shortages even in emergencies (Ding, 2018). U.S. Federal Drug

Administration (2018) reported 39 new drug shortages in 2017 and 41 ongoing shortages

from previous years. Drug shortages can delay or deny needed care for patients, creating

a potential lapse in related medical care (U.S. Federal Drug Administration, 2018). The

factors, such as quality issues, attributed thirty-seven % to drug shortages (U.S. Federal

Drug Administration, 2018). Raw material and lack of capacity attributed fifty-four % to

drug shortages (U.S. Federal Drug Administration, 2018). Demand uncertainty attributed

5%, and loss of manufacturing site and discontinuation attributed 2% each in primary

reason for drug shortages (U.S. Federal Drug Administration, 2018). The significant

factors for drug shortages, such as manufacturing issues, raw materials shortage, lack of

capacity, and uncertainty in demand, are considered supply chain events. The supply

chain performances can contribute to reducing potential drug shortages. The

pharmaceutical managers may take the help of various digital enablers to enhance

visibility and take proactive action to mitigate these adverse events.

Pharmaceutical organizations continue to lose millions because of spoilage from

temperature fluctuations and potential hazards for patients and subsequent regulatory

actions (Sharma et al., 2020b). Pharmaceutical manufacturers produce the majority of

biologics products, which are highly sensitive to storage conditions. Temperature

monitoring of some pharmaceutical drugs must be done by following cold chain

processes, whether they are in storage or in transit (Singh et al., 2020). Biological

products have a large proportion of high-value active ingredients with shorter shelf lives

and carry strict temperature requirements. Cold chain processes consist of (a) cold

storage, (b) cold storage, and (c) cold transport (Singh et al., 2020). Biological products

have a large proportion of high-value active ingredients with shorter shelf lives and carry

strict temperature requirements. These drugs must be kept in temperature-controlled

containers during transport, like reefers, to avoid the spikes in ambient containers.

Digital Supply Chain

The digital supply chain has been referred to as an intelligent, customer-centric,

system integrated, globally connected, and data-driven mechanism that leverages new

technologies to deliver valuable products and more accessible and affordable services

(Seyedghorban et al., 2020). The digital supply chain is also part of the fourth industrial

revolution, also known as Industry 4.0, that helps organizations connect ecosystems

within the functional area of an organization. The digital supply chain is also referred to

as the smart supply chain, which is new interconnected business systems extending from

isolated, local, and single company applications to supply chain-wide systematic smart

implementations (Wu et al., 2016). The supply chain network includes stakeholders and

the ecosystem, such as suppliers, manufacturers, warehouses, and distribution centers.

The supply chain ecosystem’s connections participate in the supply of raw materials,

production, delivery, and sale of a product to the customers (Sabouhi et al., 2018). A

SCM must encompass effective management of information, financial, and material flow

among the network components to maximize the total profit and customers’ satisfaction

(Sabouhi et al., 2018). As per the council of SCM professionals, SCM is defined as

planning and managing activities involved in sourcing, procurement, conversion, and

logistics (Kapoor, 2018). A manager implementing a digital supply chain aims to

preserve the supply chain’s effectiveness to satisfy customer demand and survive in

competitive market.

Road Map for Digital Supply Chain Strategy in Pharmaceutical Industries

The digital strategy refers to the company’s strategy applied to its strategic

initiatives that include the end-to-end processes, such as requirement gathering, planning,

recognizing risks and opportunities, and maintaining the digital strategy (Schallmo et al.,

2019). In a survey, 73% of respondents acknowledged that digitalization helped them

reach operational excellence (Lehmann, 2018). A digital strategy is the strategic form of

companies’ digitalization intentions when digital technology and methods are applied to

products, services, processes, and business models (Schallmo et al., 2019). The growth

of the business has created tighter global competition, and to survive and maintain a

sustainable competitive advantage, organizations must identify emerging digital

technologies for developing a new business model (Agrawal & Narain, 2018). The

managers may use digital strategy to contribute a critical enabling role in encouraging

business model innovations (Li, 2020). Digitalization forces organizations to reinvent

their business processes and encourage them to find a new way of doing business

(Bouwman et al., 2018). The digital strategy by supply chain managers may reshape the

existing non-digital supply chain model to digitalized supply chain 4.0 in which

automation will boost supply chain efficiencies by automating the operational tasks

(Alice et al., 2020).

The digital strategy outlines the direction and provides a road map for a

pharmaceutical business to follow digitally. Digital strategy should be either wholly

aligned or part of a corporate strategy rather than wholly detached from corporate

strategy. An ideal situation is a scenario when the digital strategy is a corporate strategy.

The digital strategy may be derived from the goals and objectives of an organization. The

digital strategy consists of a vision, mission, strategic objectives, success factors, values,

and measures (Schallmo et al., 2019). The digital strategy establishes the technologies,

tools, platforms, and infrastructure required to accomplish the objectives outlined by

digital strategy regarding delivering the results. Digitalization forces organizations to

reinvent their business processes and encourage them to find a new way of doing

business (Bouwman et al., 2018). The digital strategy by supply chain managers may

reshape the existing non-digital supply chain model to digitalized supply chain 4.0 in

which automation will boost supply chain efficiencies by automating the operational

tasks (Alice et al., 2020).

Business managers from pharmaceutical industries should have a deep

understanding of and possibilities of digital supply chain integrated eco system compared

to traditional supply chain system. Traditional supply chains are increasingly becoming

intelligent by turning into digitals using sensors for better communication, automation

capabilities, and intelligent decision making and presents vast opportunities for cost

reduction and efficiency improvement (Wu et al., 2016). A digitalized supply chain

compared to a traditional supply chain provides opportunities that include increased

information availability, optimized inter-company logistics, visibility, transparency,

efficient inventory management, integration, and collaboration (Seyedghorban et al.,

2020).

The three different supply chain digitalization models are explained in detail: The

first model describes the difference between traditional non-digitalized linear supply

chain and digitally enabled supply chain ecosystems. The traditional non-digitalized

supply chain is a series of largely discrete, siloed steps taken toward marketing, product

development, manufacturing, distribution, and finally, into the customers (Schrauf, &

Berttram, 2016). An integrated supply chain ecosystem helps bring transparency,

communication, collaboration, flexibility, and responsiveness to non-digitalized

traditional linear supply chain systems. The digitally enabled supply chain ecosystem

helps in transparency and collaboration compared to traditional linear supply chain

system. The model was applicable for the business managers from my target populations,

who successfully moved from a traditional linear supply chain system to a digitally

enabled supply chain ecosystem.

The second model applied to my target population’s business managers, who

implemented various integrated layers between their supply chain eco system. Integrated

digitally enabled supply chain ecosystem was introduced by Behner and Ehrhardt (2016)

talked about three layers in the model: (a) virtual supply chain control tools, (b) cloud-

based information architecture, and (c) digitally enabled physical supply chain. Many

digital tools and technologies, such as sensors, barcode, IoT, radio frequency

identification, revolutionized SCM by integrating and coordinating every link of the

chain (Nguyen et al., 2020). The cloud-based architectural structure is prevalent for the

inbound and outbound flow of information and decision. Cloud and virtualization are

often adapted in the business process layer and are the main driver to speed up the supply

chain (Borangiu et al., 2019).

The element set from the first layers of the model involving virtual supply chain

control tools provides dynamic decision-making interfaces, collaborative tools, mobile

analytics that helps supply chain managers to manage and oversee supply chain

information from nodes, such as raw materials vendors, contract manufacturers, factories,

logistics providers, distributors, customers (Behner & Ehrhardt, 2016). These analytics

also helps supply chain managers to make an informed decision based upon information

received in real-time. The supply chain managers use advanced analytics techniques to

extract valuable knowledge from the vast amount of data, facilitating data-driven decision

making (Nguyen et al., 2020). The second layer is a cloud-based information architecture

that enables fast computing for the different types of data and systems to form a physical

network across components of the supply chain system (Behner & Ehrhardt, 2016).

Cloud is an integral part of the supply chain business processes layer, but high-

performance computing, system design, and information integration can be a challenge to

implement cloud (Borangiu et al., 2019). The third layer include the physical supply

chain elements, such as devices, storage, manufacturing units, and logistics (Behner &

Ehrhardt, 2016). These elements are digital-enabled and consistently exchange

information using technologies, such as the IoT.

The third model applied to the business managers who implemented the

innovative self-thinking supply chain regarding collaboration and self-learning

perspective. The third self-thinking digital supply chain model was introduced by

Calatayud et al. (2019). The concept of the self-thinking supply chain is very innovative

regarding collaboration and self-learning perspective. Betcheva et al. (2021) found that

pharmaceutical companies could decrease costs and improve efficiencies by using a

thinking supply chain. The collaborative self-thinking model helps in collaboration and

through self-learning. Regulating the flow of materials is often used in the

pharmaceutical supply chain by switching to air transport mode instead of the sea

container route in case of congestion in the sea. In practice, supply chain managers can

plan accurately by optimizing the air-sea distribution system using control towers enabled

through digital technologies.

Developing a business case may help the managers conduct a feasibility

assessment of the various initiatives that may undergo digitalization before implementing

on a larger scale. The managers fail to deliver projects because of scope, schedule, and

budget creep. Effective supply chain digital strategies may provide a mechanism to give

the project deliverable as required to meet the stakeholder’s expectations.

Digital Enablers

Digital enablers as prominently used in pharmaceutical organizations include tool,

such as the IoT, AI, cloud computing, and BDA. Digital technologies help integrate data

and information from disparate sources and locations to streamlining the supply chain

operation by driving goods and services (Ehie & Ferreira, 2019). The digital technology

enablers provide the backbone allowing digital transformations of industrial

manufacturing (Ehie & Ferreira, 2019).

IoT

The IoT signifies smart devices connected through sensors and the Internet that

performs tasks and exchange real-time data (Radoglou et al., 2019). The IoT application,

such as cold chain monitoring, resources (man and machine) tracking, packaging, and

warehouse management, is very much suited to pharmaceutical SCM. The IoT can help

manage supply chains, improve services, and manufacture products, so pharmaceutical

industries have a compelling opportunity to adopt and profit from the IoT, the game-

changing technology (Sharma et al., 2020a). The rapid expansion of IoT devices provides

enough potentials to the organizations by harnessing and use data collected through smart

devices in the supply chain lifecycle (Akhtar et al., 2018; Attaran, 2017). Pundir et al.

(2019) explained IoT as a network of uniquely identifiable endpoints or things that

communicate without human interaction using I.P. connectivity, whether locally or

globally. The IoT is also defined as the extended development of Internet services to

consider smart objects that exist (Pundir et al., 2019). Supply chain integration is critical

for improving business performances and can be achieved through cost reduction,

improving responsiveness, increasing service level, and streamlining organizations’

decision-making process (Pundir et al., 2019). The IoT deals with integrating and

enabling information using technologies, such as radio frequency identification, wired or

wireless sensors, mobile apps, and machine to machine system and may allow device

enabled decision making in supply chain system with no or minimum human intervention

(Haddud et al., 2017).

The IoT has a significant role in the manufacturing, warehousing, and distribution

cycle of the supply chain. Smart objects are connected to the Internet using their

communication protocol and are continuously collecting and processing the data (Pundir

et al., 2019). Role of IoT mostly starts from manufacturing for shop floor visibility and

then to move in warehousing for real time inventory visibility, and then finally during

distribution toward higher fleet management for real time cold chain processes.

Temperature sensing tag is placed on container which continuously records temperatures

and other environmental conditions. Data can be extracted from the cloud either in real

time or later.

Drugs and vaccines are susceptible to temperature variations and may lose full

potency if the temperature is not maintained even for a shorter duration during

transportation (Hasanat et al., 2020). Chang et al. (2019) found that pharmaceutical

manufacturing companies outsource their logistics business to a third party having

optimal cold chain solutions to improve core competitiveness. IoT solutions can help

pharma manufacturers remotely monitor cold chain environments in real-time by

embedding sensors on tracking equipment with auto-start and shutdown mechanisms in

warehouses, vehicles, or shipment using smartphones and tablets. Hasanat et al. (2020)

suggested an IoT model that can provide information, such as (a) vaccine carrier

information, (b) continuous monitoring using sensors, (c) location tracking using GPS,

and (d) regular and urgent notifications containing carrier temperatures, humidity and

location information with a timestamp.

Smart manufacturing factory’s communication system comprises a wireless

sensor network for connecting sensor module and gateway, and then sensor and sensor

module is distributed to necessary position in the factory (Kim & Jeong, 2019). Smart

equipment using IoT solutions collects operational data and status, allows visibility

across equipment, and real-time dynamic scheduling of shop floor activities (Sharma et

al., 2020a). The solution helps in reducing equipment downtime, and the utilization rate

improves. Sensors can also help collect metadata to identify and reduce process

variability and improve production yield to enhance productivity, efficiencies, and cycle

time (Kim & Jeong, 2019).

IoT also helps visibility into human and material movement across the shop floor

through tracking and monitoring technologies, increasing production yield, and reducing

variability (Sharma et al., 2020a). Hasanat et al. (2020) suggested the business managers

build an optimal automated warehouse using IoT. The warehouse is an important area for

the pharmaceutical industry. The business managers manage many storage facilities

globally to ensure a continuous and timely supply of essential medicines in a cost-

efficient manner. Real-time visibility and three-dimensional view of warehouse

operations allow warehouse managers (a) monitor and track the storage of sensitive drugs

in controlled zones, (b) optimize warehouse floor space, (c) track inventory of finished

goods, and (d) identify problem areas and assign resources to deal with issues requiring

human interventions (Sharma et al., 2020a). The business managers of automated

warehouses using IoT may help organizations save nineteen % of the initial cost (Hasanat

et al., 2020).

IoT is an enabler to spur growth within pharmaceutical organizations.

Pharmaceutical organizations were slow to adopt IoT because of a lack of understanding

of IoT adaption factors despite a positive influence on the supply chain system. The

major compatibility issue that hampers IoT adaption is a failure to communicate between

IoT devices mapped in the supply chain system. Constraints such as privacy, reliability,

authentication, access control, and security issues need to be addressed before unleashing

IoT applications’ unlimited potential and utility in pharmaceutical industries.

Improved computational technologies and growing data of supply chain processes

turning AI into one of the most critical technologies in supply chain areas (Calatayud et

al., 2019). Demand forecasting, end-to-end visibility, predictive maintenance, smart

factory, and integrity are some of the critical metrics in the pharmaceutical supply chain

that AI technologies can help with. AI is defined as the computer’s ability to

independently solve problems that have not been explicitly programmed to answer (Dash

et al., 2019). AI technology includes machine learning, computer vision, deep learning,

cognitive computing, natural language processing, speech, supervised learning, and

unsupervised learning (Properzi & Cruz, 2020). Machine learning is a subset of AI and

defined as a specific study of computational models and algorithms on the computer

using experience based on historical data to progressively improve the performance of a

specific task or make the predictive analysis more accurate (Sharma et al., 2020b). One of

the AI’s advanced branches, robotic process automation, can increase productivity by

20% (Dash et al., 2019). The percentage of enterprises implementing AI grew 270% in

the past four years, and global spending on machine learning and AI is forecasted to grow

from $40 billion to $98 billion by 2023 (Zemankova, 2019). AI is deployed to analyze

information in real-time, monitor information across the globe, predict the future with a

minimum error rate, and adjust to rapidly changing environments (Calatayud et al.,

2019). AI powered technologies in the pharmaceutical supply chain helps in end-to-end

visibility to supply chain managers. AI helps in demand forecasting, automation,

optimizing the predictive maintenance, and also toward protecting the integrity of

pharmaceutical supply chain from counterfeit drugs.

Demand forecasting, which allows managers to plan and provides an estimate of

future demand based upon historical data and the current state of the political, social, and

economic environment, is one of the most critical elements of pharmaceutical SCM

(Merkuryeva et al., 2019). AI enabled supply chain system helps business managers in

optimizing the key performance indicators, review in real time, cut cost, reduce waste,

and speed time to market (O’Reilly & Binns, 2019). Klumpp (2018) found that AI

enabled system helps business managers across the globe allow interconnected, agile, and

collaborated value chain, which can adapt almost instantly to change in demand and the

evolution of regulation and technologies.

Dash et al. (2019) found that AI needs to be implemented in the supply chain road

map to gain the competitive advantages with the improvement of metrics, such as the

accurate projection and forecast the customer demand, reduction in the cost of inventory

quantity, overproduction, idle machine capacity, achieving quick reaction to the change

in the market, and finally providing customers a better experience. AI technologies have

enabled computer’s thoughts by providing a conceptual framework for processing inputs

and making a decision based on that data (Dash et al., 2019). Series of algorithms and

dataset enables the AI system to integrate supply chain business toward (a) getting 100%

accurate projection and forecast customer demand, (b) optimization of R&D by

enhancing the quality and reducing costs, (c) identifying target customers and

demography, and (d) providing a better customer experience. AI technologies help

business managers in eliminating waste, smart manufacturing, transparency on supplier

machine availability, performance, downtime, balancing the supply chain, and optimize

inventories in real-time (Kusiak, 2018).

Application of AI can enhance value creation in supply chain process, such as (a)

forecast demand and optimization, (b) smart manufacturing, and (c) delivery (Dash et al.,

2019). Pharmaceutical organizations are always looking for balanced and optimized

demand and supply chain tools. Applying AI and machine learning toward using the right

strategies to the right products and reducing latency can enable an organization to

respond to supply chain visibility more effectively (Klett, 2020). The business managers

can take AI help in processing, analyze, and predict data toward providing accurate and

reliable forecasting demand allowing businesses to optimize their sourcing regarding

purchases and order processing, therefore, reducing the cost to supply chain processes

(Dash et al., 2019). Klett (2020) further found that the area of potential improvement in

supply chain processes from AI lies in automating business processes, generating and

validating correct forecasts, managing changes by implementing recommended actions,

and mitigating risks. Dash et al. (2019) further suggested that AI can help in smart

manufacturing by preventing downtime for maintenance and, therefore, improve quality

and reliability. Few organizations are now using intelligent process automation, which

combines robotic process automation and machine learning to deliver powerful

algorithms to mimic human interactions and make advanced decisions (Properzi & Cruz,

2020). Innovative AI technologies help pharmaceutical industries enhance drug discovery

processes, reduce the research effort, and maintaining the future sustainability (Agrawal,

2018; Donzanti, 2018).

Cloud-Based Supply Chain (Cloud Computing)

The production and delivery of products and services in a timely fashion with

short lead time and less cost are critical supply chain objectives of many organizations,

but unfortunately, many are not able to achieve this with the traditional non-responsive

traditional supply chain technology they have (Giannakis et al., 2019). Cloud computing

offers on-demand computing services with high availability, reliability, and scalability.

Cloud computing can provide organizations with a significant amount of power with

computing and storage and help them deliver services at far cheaper rates that were

earlier unaffordable (Ross & Blumenstein, 2015). Many pharmaceutical organizations are

now adopting cloud-based infrastructure for their supply chain processes. Organizations

can achieve many benefits by implementing a cloud-based supply chain, such as real-

time end-to-end supply chain visibility, the collaboration between organizations,

capturing disruption risks, and creating a knowledgeable learning community for

optimizing decision making (Giannakis et al., 2019). Cloud can be useful for both clinical

and supply chain cycles, and globally pharmaceutical industries are using cloud

technology as their business model. The use of cloud computing helps supply chain

organizations to reduce cost, response time enhancements, delivery time, and increase

supply chain visibility. Cloud SCM is placed at the core of business processes with

estimated to arrival, estimated to departure, and the actual time of departure is

continuously being updated using GPS installed in trucks. Projected availability of raw

material can be forecasted correctly, and updated manufacturing information of

scheduling, work in process, completion, and shipping confirmation of final product to

the partners (Giannakis et al., 2019).

Supply chain responsiveness is defined according to several dimensions, such as

customer sensitivity, demand transparency, supply chain response lead time, agility,

flexibility, and information sharing (Giannakis et al., 2019). Cloud-based information

sharing improves the supply chain visibility in the healthcare supply chain and improves

the supply chain responsiveness. Scalability and flexibility are a significant factor in

driving cloud computing use in the supply chain area. However, despite the potential

cloud benefits in the supply chain, organizations are reluctant to adapt primarily because

of security breaches between partners and data loss that cannot be replaced (Cao et al.,

2017).

BDA

Business managers from the pharmaceutical companies face stringent quality

standards globally, inorganic growth regarding mergers and acquisitions, and massive

information coming from stakeholders, and they must manage these efficiently. The

digitalization concept introduced new challenges in capturing, collecting, analyzing,

archiving, sharing, transferring, and processing large data set in the organizations

(Onciou, 2019). Big data is defined as data generated continuously in diverse data

formats (structured and unstructured) from multiple sources (Grover et al., 2018). BDA

may help the business managers by providing a new perspective and add value toward

improving modeling practices and predictive analysis (Onciou, 2019). Analyzing the vast

amount of data from various sources can help organizations reduce costs, understand the

customer better, and better manage their supply chain uncertainties (Vidgen et al., 2017).

The digitalization advances in the SCM led to a significant increase of data to get

a clear picture of customer needs, and BDA can significantly contribute to areas such as

product development, market demand predictions, distributing channel optimization, and

customer feedback (Onciou, 2019). BDA works on predictive analysis principles.

Predictive analysis is based on real-time data analysis and historical data to predict the

likelihood of future events (Onciou, 2019). Predictive analytics uses statistical techniques

and forecast models to predict insight into the future using historical past data (Nagarajan

& Babu, 2019).

BDA in the supply chain can help improving supply chain performances by

improving visibility, resilience, robustness, and organizational performances

(Gunasekaran et al., 2017). BDA can give rise to an intelligent supply chain as many

business advantages can be achieved through big harvesting data, including higher

operational efficiency, better customer services, better informed strategic directions, and

identifications of new markets, customers, products, and services (Zhan & Tan, 2020).

Big data helps create business insights for delivering value, performance, sustainability.

A typical data classification method is 5V’s (volume, velocity, variety, value, and

veracity). The volume represents the ever-growing magnitude of data; value indicates the

continuous generation of fast-paced data; the third characteristics variety is different data

of format; value refers to the hidden insight in data; and veracity refers to the noise,

biases, and trustworthiness in data collected (Grover et al., 2018; Yaqoob et al., 2016).

Big data predictive analysis can also help in responding faster to changing and volatile

supply chain environments, providing more power in supplier relationship, enhancing

sales and operation planning, reducing supply chain cost, ensuring on-time delivery to

customers, and most importantly, enhancing supply chain cost (Gunasekaran et al., 2017).

BDA is reported to be an emerging digital supply chain game-changer enabling

organizations to meet and excel in the dynamic and fast-paced competitive global market

(Nguyen et al., 2020).

The supply chain operating reference model incorporating SCM, and big data

portrays different pillars, such as planning, sourcing, making, and delivering, which

involves the flow of finance, material movement, and information flow to integrate

demand and supply management across the supply chain framework (Raman et al.,

2018). BDA helps business managers make a significant contribution toward handling

demand management efficiently and providing a greater customer satisfaction level

(Raman et al., 2018). BDA is an opportunity to use new types of data to create more agile

businesses to solve problems, which was previously considered unsolvable in supply

chain framework, leading to better business results (Onciou, 2019). The supply chain

operating reference model incorporates supply chain cycles, such as planning, sourcing,

making, delivering, and return.

Enterprise Resource Planning

The feature of industry 4.0 revolution is the integration of digital technologies,

such as IoT, AI, big data, and enterprise resource planning (ERP) in order to improve

connectivity chain within the supply chain environment (Tongsuksai & Mathrani, 2020).

Application of ERP in the supply chain may help pharmaceutical managers in area, such

as streamlining end-to-end planning, supporting transportation and inventory keeping in

warehouses, providing more visibility on analytics using which better decisions can be

made. ERP applications are integrated information system packages that integrates the

business functions of an organization into once core application and enable the

organization to operate seamlessly by sharing the same information across (Albarghouthi

et al., 2020). ERP applications are tools that help supply chain managers make

managerial decisions and provide visibility throughout the organization. ERP application

may help bring many disintegrate and standalone systems into one application to create a

synergistic environment within the organization. Cloud ERP system that evolved from

the on-premises ERP systems helps organizations to achieve higher efficiencies and

lower operational costs (Tongsuksai & Mathrani, 2020). Cloud ERP system with new

digital technologies based upon industry 4.0 revolutions can help organization in

veracious metrics, such as (i) informed information flow and real time data for easier

decision make, (ii) real time tracking management for real time inventory and smart

purchasing, (iii) to collect and provide real time data from suppliers to end users which

can be sued for analyzing and deploying toward enhancing and improving operations

through prompt feedback, (iv) flexibility to reach up to date demand sensing, (iv)

improve quality by removing error in supply chain processes and reducing wastage, and

(v) reducing product and labor costs by recognizing nonconforming products in the early

phase of supply chain processes (Tongsuksai & Mathrani, 2020).

Disruptions and Agility in the Digital Supply Chain

Lasch (2018) defined supply chain disruptions as a singular or combination of

unexpected events, such as fire, flood, accidents, and supplier bankruptcy, that interrupts

the flow of goods and services and negatively influence SCM processes. Supply chain

processes in pharmaceutical organizations are inherently risky and may not avoid

disruptions. The management of pharmaceutical companies must create a strategy to

mitigate supply chain disruption risk for improving the firm’s operational performances.

Supply chain disruptions could also be an outcome of supply chain activities, including

(a) outsourcing, (b) technology innovations, (c) reduction in inventories, and fluctuations

in demand (Kovács & Falagara, 2021). Outsourcing of digital enabler maintenance to an

external player may create a severe issue in unpredicted events. The current coronavirus

disease constitutes a global pharmaceutical supply chain crisis, and as per estimation, the

epidemic, will on average, cause an economic loss of 0.7% of global GDP (Kovács &

Falagara, 2021). Pharmaceutical organizations rely heavily on suppliers for raw

materials, contract manufacturers, and logistics service providers to distribute products

worldwide. Dependency on a single supplier and lack of financial support for the vendor

account payable may adversely affect the organization. Supply chain risk strategies are a

vital element that pertains to successful implementations of digital strategy while dealing

with unexpected disruptions. Agility, flexibility, and leanness may reduce the effect by

minimizing the likelihood of disruptions (Eltawy & Gallear, 2017; Mohammaddust et al.,

2017).

Supply chain agility is the firm’s capability to respond to unforeseen changes in

customer needs, ever-changing demand, and competitor’s moves in the dynamic global

business environment (Gupta et al., 2019). Agility helps respond to changes by adapting

its initial state configuration and is also identified as an antecedent, driver, and enhancer

of supply chain resilience (Kamalahmadi & Parast, 2017). Agility is a critical strategic

element and acts as an enabler of responsiveness by facilitating quick response to

unforeseen events. Skill is now applied to the whole supply chain as a way of doing

business (Eltawy & Gallear, 2017). The concept of supply chain agility is defined by

emphasizing a pharma manufacturer’s capability to sense the change and then rapidly

respond by reducing lead time, enhancing the level of customer services, and improving

delivery reliability (Shekarian et al., 2020). Kamalahmadi and Parast (2017) revealed two

components of agility in the context of supply chain resilience: visibility and velocity,

which is the loss that happens per unit of time during disruptions.

Sustainability in the Digital Supply Chain

Sustainability is protecting stakeholders’ interests by focusing on non-financial

environments, such as environmental, social, ethical, and governance, by accomplishing

the financial performance and creating stockholders’ s value (Zabihollah, 2021). Maniora

(2018) described sustainability that meets the present’s need without compromising

environmental generations to meet their own needs. As defined by the triple bottom down

sustainability theory, supply chain managers must consider social, economic, and

ecological objectives while deciding to make their business profitable (Sivarajah et al.,

2020). Sivarajah et al. (2020) further stated that organizations must give back to the

communities they operate and must take initiatives to replenish and conserve natural

resources to provide services and manufacturing tangible products. Each of sustainability

is discussed in detail, starting with environmental sustainability.

Globalization has prompted organizations to build highly interconnected and

complex supply chains. As a result, companies adopt the outsourcing model to outsource

non-core activities to overseas suppliers without much consideration. The shift toward

outsourcing and waste and emission caused by production processes throughout the

global supply chain is the primary source of environmental issues (Ashby, 2018). In

current operating model, there have been an increase in third-party logistics and

transportations (TPL) providers who were outsourced to serve the developing countries’

supply chain. El Baz and Laguir (2017) concluded that major challenges to

environmental sustainability in developing countries include a serious lack of

collaboration between third-party logistics providers, a lack of governmental regulations

for environmental standards, a lack of environmental policy initiatives and commitment

by management, and a relatively immature stage of economic development in developing

countries.

The need to coordinate activities between supply chain partners to satisfy

environmental regulations imposed by governmental legislation and the requirement to

improve the company’s environmental profile for their potential customers are now

deemed necessary for the organizations (Zissis et al., 2018). The manufacturing processes

may consume energy and materials and, in the process, release waste also in the

ecosystem. Even the global supply chain’s transportation process may adversely impact

the environment regarding energy used and discard pharmaceutical raw material

mismatch at source and destination. Nowadays, end customers are demanding eco-

friendly products and services that do not damage the environment (Green et al., 2019).

The demand from intermediate and end customers is now pushing manufacturers to

rebuild or modify their operations. Ashby (2018) suggested using the closed-loop supply

chain by taking example from the clothing industry, where the local firm, customers, and

global suppliers coordinate in a way that follows appropriate environmental practices by

initiating the reverse flow of used clothing toward maximizing the value and minimizing

the waste in global supply chain lifecycle. Alzaman et al. (2018) noted that implementing

green SCM will improve environmental performance regarding fewer carbon footprints

and help the competitive advantages and economic performance of an organization.

Social sustainability in the supply chain also plays a substantial role, as supply

chain managers and partners must address stakeholders’ needs and human capital to

achieve long term sustainable results. Socially sustainable supply chain practices are

defined as introducing a range of initiatives, including protection against child and slave

labor, health and safety programs for employees, outreach to communities, and

supporting human rights (Croom et al., 2018). Gouda and Saranga (2018) found that

organizations have adopted social and environmental sustainability practices to reduce

their carbon footprints and improve their image on the social front. Sodhi and Tang

(2018) suggested that organizations that adopt sustainable practices in their supply chain

processes outperform their competitors in stock market performance and financial

metrics.

Transition

The intent of this qualitative multiple-case study was to explore the strategies

used by some pharmaceutical managers to digitalize the integrated supply chain system to

increase their profitability. I planned to use the conceptual framework of TOC to discover

the participant’s strategies to address the research problem identified in Section 1. I

presented the problem and objective of this study to explore the strategy, the conceptual

framework, the study’s significance, the potential social impact, and a review of

professional and academic literature to support my research study. In Section 2, I provide

a rationale for the selected research method and approach for this study. In Section 3, I

presented the findings, the application to professional practice, the implications for social

research, the recommendations for further research and action, reflections on my

experiences within the Doctor of Business Administration doctoral process and ended

with a conclusion.

Section 2: The Project

In Section 2, I discuss the design, rationale, and explanation of the qualitative

method used in this study by restating its purpose. Section 2 also includes a detailed

presentation of the sampling, population, data collection, data analysis, and the study’s

reliability and validity.