biopharma case study supply chain management

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• Iran J Pharm Res
• v.18(2); Spring 2019

Supply Chain Challenges in Pharmaceutical Manufacturing Companies: Using Qualitative System Dynamics Methodology

Asiye moosivand.

a Department of Pharmacoeconomics and Pharmaceutical Management, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Ali Rajabzadeh Ghatari

b Department of Industrial Management, School of Management and Economics, Tarbiat Modares University, Tehran, Iran.

Hamid Reza Rasekh

In today’s competitive market environment, pharmaceutical companies have learned that improving supply chain performance is critical to maintain competitive advantages. Forecasting, planning, procurement, financing, stock levels, and marketing strategies are some of the areas in which managers have to decide about them and balance their enter-related effects simultaneously, to achieve organizational goals. This study is based on the results of literature review, experts’ opinion acquisition, and qualitative system dynamics modeling. So, according to method, triangular researches have been considered. The purpose of this research is to explore pharmaceutical supply chain (PSC) challenges and the dynamics behavior of variables playing a special role in PSC. Also, it provides different policies to overcome the challenges. For the first step to reach this goal, several semi-structured interviews with expert supply chain managers are conducted to explore the main challenges. Inaccuracy in forecasting, long lead times, lack of optimum target inventory, and high SC costs are the most important PSC problems. Then, qualitative system dynamics methodology is used to demonstrate the inter-relationship between variables that have impact on challenges. Finally, three strategic policies are recommended including: Collaborative relationship with suppliers, Investment in new technologies, and Information technology (IT) establishment. Consequently, the results can give PSC managers a comprehensive view for decision making and bringing their attention to the importance of feedback behavior of variables in long term and their effects on organizational decisions and goals.

Introduction

Recently, firms have been increasingly interested in efficient supply chain management (SCM), because they have met extreme competition. This is because of decreasing product life cycle time, varying customer demands, as well as increasing cost of manufacturing and shipment ( 1 ). This condition has led many companies to recognize the critical role of SCM to reach organizational goals via speeding up innovations and product launching to the dynamic market, improving customer value, optimizing utilization of resources, decreasing different types of costs such as production, inventory, transportation, and so on, and increasing profitability ( 2 ). A supply chain as a dynamic process is usually described as a forward flow of materials and a backward flow of information and funds among multiple operating units both within and between chain members ( 3 ). Because of rapid growth rate of technology development, basic supply chain structure has been changed to supply chain network with more complex structure including a higher level of interdependence and collaboration between more entities. Supply chain networks can be used to highlight interactions between organizations; they can also be used to show the flow of information and materials across organizations. Supply chain networks are designed with five key areas: inbound logistics (suppliers), internal logistics (production), outbound logistics (distributors), demand sectors, and shipment assets ( 4 ).

In generic pharmaceutical industry, typical supply chains consist of the following components: manufacturing raw material, manufacturing pharmaceuticals, distributing centers, retail pharmacies/hospitals, and patients ( 5 ). Because of the economic changes, pharmaceutical industry member companies have been trying to restructure their supply chains. The pharmaceutical business is a multipart enterprise accompanied by conflicting purposes and several troublesome limitations. A highly regulated setting combined with the life changing nature of the products describe the pharmaceutical industry as a special challenging system ( 6 ). As Wang said: “the crucial aim of SCM in pharma industry is to make the right product, for the right customer, in the right amount, at the right time” ( 7 ).

Complicated activities in industrial processes are because of existing a multitude of variables and their non-linear dynamics. Also, developing a systematic model to define such these processes behavior is generally difficult or unfeasible ( 8 ). Several different methods have been suggested for modeling supply chains. Most of them are steady-state models based on constant conditions; however, static models are not enough for dynamic specifications of the supply chain due to oscillations, lead time delays, sales forecasting, etc. Owing to this reality, system dynamics (SD) method could be a proper technique for displaying interactions between several factors used in modeling tool.

In this study a wide spectrum of pharmaceutical supply chain (PSC) challenges are discussed and tried to determine the internal PSC problems and the interrelationship between variables which affect PSC performance. The supply chain operations reference (SCOR) model criteria was used for classifying challenges and complicated relationships among various variables are shown using qualitative SD modeling.

Literature Review

Pharmaceutical supply chain challenges

With the increasing changes in business environment, firms have to supply high quality products, deliver fast responses, and make their dynamic competencies better. Particularly, the pharmaceutical industry is facing the same challenges that many other industries have experienced in the past. Only the firms that are eager to accept changes and improve their strategies will achieve long term success ( 9 ).

The challenges that pharma companies are involved in are complicated and have an extensive range including political, economic, social, technical, and legal considerations. The pharmaceutical industry is characterized as a group of organizations, processes and actions, engaged in the invention, and innovation of pharmaceuticals; furthermore PSC is made up of corporations to supply and deliver medications which have an important effect on customer satisfaction ( 10 ).

Today, efficiency of R and D processes, products’ declining life cycle and patent life exclusivity, increasing generic competition, production compliance, and costs, are some of the major complications that pharmaceutical companies encounter with them ( 9 , 11 ). A study by Oliver Eitelwein shows that many pharmaceutical companies have to enhance the main supply chain sections including customer satisfaction, forecasting accuracy, inventory level, and total supply chain costs. Also, he states that the complex nature of products and processes are other important matters which can emerge from various number of causes: the large finished good portfolio, wide variety of materials needed, distribution networks, high investment cost and time of developing new products, capacity constraints, and regulatory restrictions ( 12 ).

Supply Chain challenges related SCOR Perspectives

Like other industries, the supply chain in pharmaceutical industry initiates with the sourcing of material for production. Active pharmaceutical ingredient (API) along with other inactive materials are planned to formulate in to the standard dosage forms and filled into primary and secondary packages with different configurations. Finished products are transferred from manufactures’ warehouses to distributors, retail/hospital pharmacies, and finally to consumers. In contrast, the flow of data and funds starts from end-users to producers through several channels ( 13 ). As mentioned earlier, there are a lot of factors that can affect pharmaceutical industry performance. Discussing all supply chain related variables is not the purpose of this study. Thus, in this research, the Supply Chain Operations Reference (SCOR) is used as a conceptual model to focus on the crucial variables. SCOR model proposed by the Supply Chain Council in makes a helpful structure for performance evaluation and offers standardized definitions for measures and metrics for all members in the supply chain in various industries ( 2 , 14 ) . Many analytical models in business and engineering fields, have been suggested to handle supply chain operational and design matters ( 15 ). While, there are a few holistic models for strategic decisions. Based on Huan survey, “the most promising model for supply chain strategic decision making is the SCOR model developed by the supply chain council” ( 16 ). For the assessment and improvement of supply chain management and performance, the SCOR can creates a cross industry structure ( 17 ). In the SCOR model, the function of SCM from operational perspective is considered. Recently, several studies have looked over SCOR model and have tried to measure the impact of this model on organization performance ( 16 , 18 - 20 ). In the study was conducted by Zhue, the relationship between supply chain process in the SCOR model were proved ( 21 ).

Therefore, this comprehensive model verified by many academics and experts in both academic and business area, was chosen as a frame work in this research to study supply chain problems in pharmaceutical manufacturing companies.

In the SCOR model, supply chain activities are a series of connected inter-organizational processes containing five echelons: plan, source, make, deliver, and return. Each supply chain echelon has individual intra-organizational processes evaluated with five strategic attributes including "supply chain reliability, responsiveness, flexibility, costs, and assets". The first three attributes are related to customer orientation measures (effectiveness) for example delivery performance, while the other two are internal efficiency measures of a company like cash-to-cash cycle time ( 22 ).

Customer orientation perspective

In this perspective, supply chain capabilities including SC reliability, SC responsiveness, and SC flexibility are considered. Reliability is related to delivery performance when the right product with the right quantity, packaging, and documents is delivered to the right place and customer, at the right time. SC responsiveness is defined as how fast the supply chain can respond to customer demand. The flexibility of SC is the ability to effectively increase or decrease aggregate production or switch rapidly from one product to another in response to customer demand changes to achieve or sustain competitive advantage. This ability can reduce the risk of products destocking arising from unexpected increase demands. Additionally, will render companies needless of stocking up on large quantities of inventory ( 23 ).

Nowadays, the common strategy for maintaining competitive advantages is the time-based competition strategy. Supply chain must compress the time required to propose, develop, manufacture, market and deliver its products to provide a respond to customer demands in as short as possible delivery times. Indeed, responsiveness to the market demand is a prerequisite of reliability. Responsiveness can be defined as the ability of the supply chain to respond purposefully and within an appropriate timeframe to customer requests or changes in the marketplace which is also referred to as agility ( 24 ). Agility paradigm can be noteworthy in the pharmaceutical industry because of many reasons such as reducing the product life cycle, increasing merge and acquisitions, changing customer behaviors, and competitive actions which enforce companies to respond faster ( 12 ).

Internal perspective

Supply chain efficiency is important in this perspective in terms of cost and asset management. With efficient SC management, cost of production as well as inventory and transportation are reduced, and customer service levels are enhanced. All costs related to operating the supply chain such as cost of processes to plan, source, make, deliver, and return, cost of goods sold, direct costs (labor, materials), and indirect costs (overhead) are considered to reach productivity. Cost of operation greatly affects profitability thereby affecting the whole firm performance; hence, it is one of the most important indicators to evaluate efficiency. The more the companies optimize the costs, the higher efficiency they gain ( 25 ). Cost reduction is a way in which excellent companies try to create more efficient relationship with partners and other firms to reduced cost of their products , reduce internal lead times and work in process inventories, increase forecast accuracy and repeatability, and adopt just in time delivery strategies for their high cost raw materials. By doing these activities indirect costs have been significantly decreasing ( 26 ).

Supply chain assets management is evaluated by three important variables, cash to cash cycle time, return on SC fixed assets, and return on working capital. Cash to cash cycle time is the time period between the point at which a company pays for purchasing material and gains incomes from the products sale in cash. This factor is used to calculate the financing requirements for current and future operations ( 14 ).

Experimental

System Dynamics methodology

Supply chain systems have a dynamic characteristic because of uncertainties in demand, supply, and various logistics methods. Recently, with increasing complexity of supply chain dynamics using system dynamics modeling has become popular ( 27 ). As SD models are based on feedback models, causal loop diagrams (CLD) were provided to explain intrinsic feedback of activities. “The feedback loop when a change in something ultimately comes back to cause a further change in the same thing” ( 28 ).

Qualitative system dynamics based on causal loops

Many authors suggested that CLDs could be used as a conceptual model and help to structure and solve managerial problems ( 29 - 31 ). With the progression of this concept, two parallel methods were formed. The first concept which is termed " qualitative system dynamics " was intended to apply all phases of system dynamics besides quantification modeling. The idea of setting up model boundaries has specified responsibilities of managers to prospect how processes might be interacted. Furthermore, it could be combined in to most simulation packages ( 32 ). The second concept of CLDs was made as an important part of organizational learning which is named "system thinking". Also, this idea has made managerial perception about the system behavior by concluding, rather than calculating ( 28 ). Visualizing dynamic problems with CLDs is an ideal way to bring the decision points and performance measures to the managers’ attention ( 33 ).

System Dynamics modeling processes

The standard system dynamics method based on Sterman definition is the sequence of activities to study a particular problem ( 30 ). These steps are problem definition, dynamic hypothesis, formulation, testing, policy formulation and evaluation. The SD method is used here to take into consideration all variables in terms of both systemic approaches to the variables interactions and flows, and managerial perspective.

This study tries to explore the pharmaceutical manufacturing supply chain challenges in Iran and find out the relationship between variables affecting these problems by the first two steps of SD method, problem definition, and causal loop diagram. The model provided below is a qualitative model based on extensive literature review and semi-structured interview with experts on pharmaceutical supply chain.

Based on the findings, there are several serious challenges in Iran pharmaceutical industry which have an influence on the competitiveness, profitability, and overall supply chain performance in both external and internal organizations environment. Macro environment troubles include macroeconomics and political situation like sanctions, exchange rate fluctuation, financing issues, lake of proper infrastructure, counterfeit drugs, and lake of transparency and unpredictability of shifts in government economic policies, and highly regulated nature of this business. On the other hand, lack of integration and collaboration between different echelons of supply chain, lack of information visibility, transparency and sharing, high rate of obsolescence machinery, costly and time consuming R and D processes, restricted pricing policy affecting the competitiveness and quality of products, uncertainty in supplying qualified raw materials in their respective required quantity and at the right time lack of effective supplier relationship management are just a number of inter organization problems.

Problem definition (Boundary Issues)

The extent of the model must be defined in any kind of modeling. Conscious decision must be made to clarify where the boundaries of the model are. Otherwise, developing a system model could be ultimately endless.

Therefore, the first part of the research was undertaken by Semi-structured face to face interviews with 25 expert managers from different pharmaceutical manufacturing companies who have at least 5 year responsibilities in any parts of the supply chain, including marketing, planning, commercial, manufacturing, sales, and financing for clarifying pharmaceutical supply chain structure and model boundaries, as well as their challenges related to SCM.

To address these goals, the interview questions were developed and guided by the wide-ranging literature review and the five main SCOR performance attributes and their associated level 1 metrics ( 34 , 35 ) Table 1 represents the five performance attributes used within the SCOR model and the associated thirteen level one metrics.

The SCOR performance attributes with the associated level 1 metrics

The interviewees were asked to explain the supply chain structure and processes in their companies and specify the challenges which can cause difficulty in achieving supply chain goals, considering SCOR performance attributes. In addition, the interviewees were given the opportunity to add any other challenges that they believed were relevant for their particular operation. The interviews were recorded digitally and the notes were taken during the interviews.

The model boundaries and variables included in each sector of the CLDs were based on the notes taken and the audio recordings of interviews. Figure 1 shows the market oriented pharmaceutical supply chain and model boundaries.

General model boundaries for market oriented pharmaceutical supply chain

In brief explanation, in this industry, the SC Processes initiate by product development and marketing activities as a strategic function. This means that the sales and marketing unit try to find the market needs and change them to demands. They achieve their goals by communicating with physicians authorized to prescribe pharmaceutical products to end users. On the other hand, sales and marketing unit interacts with distribution companies and pharmacies to sell their products. In this way, they can monitor the market as downstream and forecast future demand. Marketing department provides forecast information for planning department to schedule all internal processes including purchasing materials, formulation and making finished products, and distribution in response to market demand. The branded-generic pharmaceutical manufacturing companies also have upstream companies which may have local or international activities, to supply active pharmaceutical ingredients and other inactive materials. Therefore, the supplier selection and supplier relationship are critical tasks for manufacturing companies, they have to evaluated suppliers considering both qualitative and quantitative factors such as quality of materials, delivery performance, their reputation and position in industry, bargaining power, production facilities and capacity, technical capability, geographic location, order fulfillment lead time, net price, total logistics cost etc. ( 36 ).

With these descriptions, the model boundaries of this research has determined all challenges related to pharmaceutical manufacturing company processes which can affect them and have ability to improve the processes by changing the policies and decisions. All other concerns related to entities in up and down stream of manufacturer are placed beyond the study boundaries.

Dynamic hypothesis

Based on the interviews, the supply chain challenges of pharmaceutical manufacturing companies are identified and listed in accordance with SCOR model attributes in Table 2 .

Supply Chain challenges in pharmaceutical manufacturing company

The basic CLDs of market oriented PSC was developed based on literature review and expert opinions. Figure 2 shows the basic relationship between variables playing a role in the pharmaceutical supply chain.

Basic causal loops model

In general, the most important goal of a profit-seeking companies is to maximize stockholder value which can be divided into three sub-objectives including profitability, survival and continuous in existence, and growth. To achieve them, companies must improve financial performance such as - revenue, return on investment, and cash flow - as well as non-financial performance such as - market share, customer satisfaction, number of new products development, and number of employees.

In market oriented pharmaceutical manufacturing companies, all processes start with product development and marketing activities via market research and analysis to find unmet health needs and create demands through promotional actions to introduce products to the health care professionals. On the other hand, the marketing units can calculate the sales forecasts by observing the market and providing it to planning unit to project the production schedule and finished products inventory in accordance to market demands. The appropriate production inventory can increase the distributors’ warehouses inventory and the orders will be fulfilled completely. At this point, the actual sales can be recorded for manufacturing companies; however, the invoices will be paid with a delay of several months. Increasing actual sales leads to more revenue and profit. On the other hand, market share will be also increased. Ultimately, the marketing departments can benefit from profit to increase marketing promotions to boost demands. There is one subtractive loop to balance the two others reinforcing ones. If the production inventory is not enough to meet the market demands, the distributors could not fulfill orders. By declining order fulfillment rate, shortage and sales loss will occur; as a result, actual sales will decrease. Based on the SCM experts opinions supported by literature, Inaccuracy or anomaly in sales forecast calculating and production capacity limitations can be considered as the causes of inadequate production inventories.

On the other hand, two balancing loops can be added to explain the processes of creating product inventory. As noted earlier, material purchasing plan as well as production plan will be conducted based on sales forecasting. The procurement departments prepare raw materials needed from several supplier companies. There are several factors affecting supply performance of such supplier’s ability to cover orders in terms of quality and quantity of raw materials, cost of raw material and shipment, and delivery time. The material inventory and products inventory have a moderating effect on ordering rate ( Figure 3 ).

Internal processes: Planning, Sourcing, and Making

As experts asserted in Iran pharma industry, financial and political issues cause some limitations for supplying APIs especially for imported materials. Also, a lack of collaborative relationship strategies with suppliers can create harder condition for pharmaceutical manufacturing companies such as deviation of forecasts, drastic inventory oscillations, and stock-out episodes. Therefore, they buffer a large amount of materials and products inventory. Although, this strategy enhances responsiveness, increases customer satisfaction, and decreases sales loss, it can cause other problems such as the need for more warehouse space and their management, increasing inventory costs, and the risk of material or product expiration ( Figure 4 ).

Inventories balancing loops and costs

The other major problem in this business is long lead times including time for new product development, capacity acquisition, procurement, production, distribution, regulatory process, and cash to cash cycle time. The long lead times prevent PSC abilities to be reliable and responsive. This property not only can degrade PSC agility and market share; but, may increase overall costs as well. While, to remain competitive, these firms must reduce costs whereas continuously improve responsiveness.

After expressing the PSC problems, the dynamic hypotheses are developed. Major challenges which can affect both effectiveness and efficiency of PSC can be briefly summarized as follows: inaccuracy in forecasting, long lead times, lack of optimum target inventory, and high SC costs.

With such problems, achieving profitability, customer satisfaction, as well as market share would not be possible. There are several improving actions and correcting decisions that have already been experienced in other industries and many researches have showed their effectiveness, and they can be used to overcome these challenges. In the following section, the impact of some of the suggested policies will be discussed on the causal loop model.

Since system dynamics modeling is the interactive process between researchers and participants (manager, owners and associated actors) of problem situation who are experts in their field, after developing the causal loop diagrams the validity of relationship between variables were verified by those pharmaceutical supply chain experts who were participated in the interviews. Then, the suggested policies to mitigate the SC problems were implemented in model and confirmed by them (37, 38). In the next step, the effects of suggested polices were discussed.

Results and Discussion

Suggested policies to overcome obstacles

Collaborative relationship with suppliers

Supply chain collaboration has been well defined by Togar as “two or more chain members working together to create a competitive advantage through sharing information, making joint decisions, and sharing benefits which result from greater profitability of satisfying end customer needs than acting alone” ( 39 ). With collaboration, the firms can manage the negative impact of “bullwhip effect” and become more responsive to the instability of markets ( 40 ). Moreover, the positive impact of collaboration has been proved by several cross sectional studies ( 41 - 43 ).

When improvement of firm performance is targeted through more effective management of the supply chain, the suppliers’ role becomes important to coordinate supply and demand properly ( 44 ). Several researches have been conducted to assess the supplier and manufacturing company relationship and its effects on manufacturing performance. The topics include: supplier selection, supplier alliances and strategic supplier alliances, as well as-supplier management orientation ( 45 - 50 ).

Long term relationship between manufacturer and its supplier is termed strategic supplier relationship. It is used to help firms reach major benefits. Also, it makes companies more capable of working with a limited number of important suppliers efficiently. Strategically aligning firms will save time and effort ( 51 - 54 ). On the other hand, supply chain collaboration with strategic suppliers empower firms to be more responsive to market fluctuations as a result enhanced capability and the high level of knowledge sharing and communication ( 55 , 56 ). Strategic partnership helps pull production companies to be more flexible and utilizes lean manufacturing methods needed for pull production by reducing the cycle times ( 57 ).

As Figure 5 shows, in this study, the effect of collaborative relationship with suppliers on supply lead time, bargaining power and order quantity has been evaluated. Strategic partnership or trust reduces lead times, safety stocks, economic order quantity, and costs; while, increases ability to respond to demand, customer satisfaction, market share, and profitability. These results are supported by several former studies in other fields. Firm performance is positively linked with activities, in which suppliers are involved in organization operations ( 58 ). Also, in different studies the effect of collaboration on resource management, information accuracy, and cost reduction have been proved ( 59 , 60 ). In addition, assessment and prioritizing of suppliers is the main factor for agility of SC in pharmaceutical companies based on result of the study conducted by Rajabzadeh et al. ( 61 ).

Improving policies for overcoming challenges

Investment in new technologies

The other improving policy is applying new technology to enhance R and D processes and quality of products, optimize current production processes, decrease rework and wasted material. In one study the author asserted that production technologies can notably improve competitiveness ( 62 ). Furthermore, other studies have shown flexibility enhancement by using innovative manufacturing technologies ( 63 , 64 ). Then, as flexibility is a necessary attribute of pull production businesses, advanced manufacturing technology can improve efficiency and effectiveness of pull production.

Also, product innovation especially in complex products with unpredictable demand can be increased by new manufacturing technology ( 65 ).

With investment in new and advanced technologies in pharmaceutical companies, flexibility, quality of products, and customer satisfaction are increased. Moreover, by reducing production lead time, responsiveness can be improved. All these behaviors lead to increase actual sale as well as market share. Researches have stated that the environmental uncertainties relate with need for faster adoption new technology to be more flexible and responsive. Logistics executives rank technology as the most important factor in improving SC capabilities ( 66 ).

Information technology (IT) establishment

Information is varying between upstream and downstream of supply chain companies. Every entities in SC have to calculate their possible future market demands based on inadequate information obtained from other SC components. Therefore, all partners keep higher amount of inventory to reduce risk of stock-out and preserve responsiveness to market changes. Thus, the costs would be increased ( 67 ). Establishment of information technology to make visibility or information sharing among supply chain entities, is one of the critical elements for having an effective SC ( 68 , 69 ). By using IT, sales forecasting can be accurate, so need for safety or inactive inventory as well as inventory costs will be decreased. Visibility causes less bullwhip effects and increases reliability ( 70 ).

On the other hand, collaborative behaviors have many advantages for all SC partners such as a clear understanding of future demands and realistic plans to respond to demand ( 71 ). Researchers have recommended the IT system establishment for information sharing and in this way, enabling collaboration in the supply chain ( 72 , 73 ). According to the result of Mehralian study, IT is one of the most important factors that can affect coordination in supply chain ( 58 ). In addition, using IT for improving information sharing, has positive impact on SC performance ( 74 ).

To obtaining value for consumers and supply chain network which is the final purpose of supply chain management, supply chain entities must integrate inter and intra organizational processes. A firm’s competitiveness is extremely related to integrated management. Process integration refers to coordination, and resources and information sharing to manage the process cooperatively ( 70 ). Chopra and Mendhl enumerated the benefits of SC integration including safety stock and costs reduction, flexibility, responsiveness and quality enhancement, optimum resource utilization ( 15 ). However, process integration may have very difficulties in terms of organizational culture, infrastructure and facilities, willing to learn and prepare for changes. Therefore, this model could be a basis for configuration of supply chain system.

Consequently, the policies recommended in this study lead the pharmaceutical supply chain to be more integrated. The collaborative planning, forecasting and replenishment (CPFR) is suggested to implement in pharmaceutical supply chain management to improve replenishment, reduce inventory and backorder value, and decrease procurement and delivery time.

Limitation and management implications

For the first time, the most important internal supply chain challenges in the pharmaceutical market-oriented manufacturing companies were studied in this research. The research findings in this paper focuses on how a qualitative simulation method can effectively assist decision makers involved in the process of creation policies. The proposed causal loop diagrams can visualize the effects of the activities and decisions on organizational goals; hence, it can help managers to make better decisions and overcome problems.

In addition, CLDs can be used in other system dynamics modeling as a conceptual frame work to develop stock and flow diagrams and calculate the effects of organizational policies on supply chain challenges quantitatively. Indeed, having such these frame works help organizations to make and record data based on the CLDs variables for more detailed quantitative analysis. However, in this research, interviewees were SC managers in manufacturing companies. For future studies all the participants along the supply chain, including upstream suppliers and downstream customers can be involved. The study is limited to the pharmaceutical industry, and this could limit generalizability of results to other industry types.

Acknowledgment

This work was a part of Ph.D. thesis of A. Moosivand at the School of Pharmacy, Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran. The authors would like to thank supply chain managers in pharmaceutical companies for their sincere cooperation.

Four ways pharma companies can make their supply chains more resilient

In the past two decades, the worldwide value of pharmaceutical goods traded has grown sixfold, from $113 billion in 2000 to $629 billion in 2019. 1 UN Comtrade Database, United Nations, February 2020, comtrade.un.org; McKinsey Global Institute analysis. Amid this growth, supply chains have become increasingly global, complex, and opaque. More companies are outsourcing production to contract manufacturers, adding new modalities (such as cell therapy), and exploring novel ways to reach patients. For some products, this results in supply chains that are so complex that they start in Asia and circumnavigate the globe twice.

Leading pharma companies have succeeded in shifting their supply chains to drive growth and manage costs. But unless they assess and plan for the risks that come with these changes, they can suffer huge losses.

Pharma executives say supply-chain risk is a significant reason for their companies’ susceptibility to disruption, according to a recent McKinsey Global Institute survey . Nearly 50 percent of respondents cite sole sourcing of inputs as a critical vulnerability, and 25 percent point to a lack of visibility into supplier risks. Although supply-chain risks are unavoidable, companies can minimize their disruptive effects through greater visibility, rigorous risk management, and newer technologies that help companies better anticipate and respond to shocks. But first, building supply-chain resilience begins with understanding the nature of the risks the chain faces.

Disruptions have become commonplace

Natural disasters, international trade tensions, cyberattacks, and global pandemics are just a few of the shocks that can immobilize pharma companies (Exhibit 1).

Pharma companies are somewhat more insulated from supply-chain shocks than other industries are because they generally hold higher inventory levels, but that can’t protect them from everything (Exhibit 2). In 2017, Merck reported that a cyberattack that occurred in June 2017 unfavorably affected revenue in the fourth quarter of 2017 by $125 million and for 2017 and 2018 by $260 million and $150 million, respectively. 2 “Merck announces fourth-quarter and full-year 2018 financial results,” Merck, February 1, 2019, merck.com. As such events become more commonplace, McKinsey Global Institute estimates that the pharma industry will lose an average of 24 percent of one year’s earnings before interest, taxes, depreciation, and amortization every ten years.

In the pharma industry, cyberattacks and trade disputes create the greatest risk of supply-chain disruption (Exhibit 3). That’s primarily because of the industry’s abundant proprietary knowledge, capital intensity, international data flows, and moderate level of digitization. Trade disputes pose a threat because of the industry’s high levels of international trade and constant pressure to relocate parts of the supply chain for economic and other reasons.

Regional dependencies and potential supply-chain shifts

Although the pharma supply chain is more global than those of other industries, companies often source critical materials from a single region, putting them at risk of shortages during natural disasters and local conflicts. Around 40 percent of pharma trade occurs within a particular region, while the average is 50 percent for other industries (Exhibit 4). For example, 86 percent of the streptomycin sold in North America and 96 percent of the chloramphenicol sold in the European Union come from China. 3 UN Comtrade Database, United Nations, February 2020, comtrade.un.org; McKinsey Global Institute analysis.

Companies can reduce their exposure to single sources and other supply-chain risks by diversifying where they buy materials. To secure an input better, a company might revert to domestic production, nearshore the supply, or offshore to new locations. We estimate that 38 to 60 percent of the international pharma trade, worth $236 billion to $377 billion in 2018, could potentially be considered for sourcing diversification (Exhibit 5).

For pharma companies, relocations are often driven by noneconomic factors, such as governments’ desire to bolster national security and become more self-sufficient. For example, the Indian government is seeking to increase domestic production of bulk drugs and medical devices with a $1.3 billion stimulus plan. 4 “India readies $1.3 billion pharma incentive scheme; aims to be $120 billion industry,” Pharma Letter, June 17, 2020, thepharmaletter.com. And the Austrian government is jointly investing with Sandoz International to support antibiotic production at the company’s Kundl facility to ensure that the country has an adequate supply. 5 “Sandoz announces plans for joint investment to help strengthen future of antibiotics manufacturing in Europe,” Sandoz International, July 27, 2020, sandoz.com.

Four ways to build supply-chain resilience

Supply-chain resilience requires four elements: end-to-end transparency, routine stress-testing and reassessment, reduced exposure to shocks, and supply-chain resilience on the executive agenda.

End-to-end transparency

A lack of visibility into the business practices of suppliers and suppliers’ suppliers can be a significant risk for pharma companies. Major consumer brands have been accused of unfair labor practices when overseas suppliers have been found to have used child labor.

A company must map its suppliers by tier to have an end-to-end view of the supply chain and identify vulnerabilities. It’s also vital to have a clear understanding of exposures beyond supply, including how products are developed, delivered, and stored, because each stage poses its own potential problems. For example, the bankruptcy of a small transportation provider at a critical location could shut down an entire supply chain.

Getting a clear picture of what’s happening at each stage requires gathering from internal and external data sources the leading and lagging resilience metrics in seven areas: data security, finance, operations, organizational maturity, regulation, reputation, and structure (Exhibit 6). For example, a review of one company’s data security may reveal insufficient data-protection protocols. A structural review may uncover a heavy concentration of suppliers in a region subject to significant effects from climate change, such as hurricanes.

To conduct these analyses, companies can use a range of technologies. Some companies partner with third-party organizations, including start-ups funded by venture capital, to make investments (often of less than $1 million) to map their value chains and set up risk-monitoring systems. Others are investing up to $50 million in digital and advanced-analytics use cases to eliminate operational risks. For instance, some pharma companies are using AI-driven root-cause identification to improve quality performance. Others have set up reliability rooms to track performance and risk metrics across their end-to-end networks in close to real time to identify and resolve issues before they cause disruptions.

Routine stress-testing and reassessment

Companies often use scenario planning and simulation models to anticipate their vulnerabilities, quantify the potential impact, and mitigate the effects. For example, during the COVID-19 pandemic, a leading pharma company used a digital-twin simulation to understand the impact of production slowdowns and shutdowns on the supplies of patient medication. This helped the company realize that it had more time than it had anticipated to design and implement safer ways of working at its manufacturing plants, allowing it to take more time to get the best solutions. Once a company has visibility into its supply chain, it can assess the likelihood of different risks continuously.

Reduced exposure to shocks

One of the most common strategies for building resiliency is to expand the network of suppliers. Relying on a single source for critical components or raw materials can be a vulnerability, as can depending on multiple suppliers concentrated in the same place.

But multisourcing isn’t the only answer. A company can also strike a better balance between just-in-time and just-in-case inventory levels, harden its physical assets to withstand hurricanes and storm surges, and provide financial support to distressed but essential suppliers. Many companies are experimenting with technologies that enable quick changes among suppliers and advanced analytics that help predict potential challenges better.

Being able to reroute components and flex production among sites can also keep production going in the wake of a shock. This requires robust digital systems and analytics to explore different scenarios. It also requires a standardized operating model—a company that has different specifications for the same API at each of 20 sites has dramatically reduced ability to flex its production. Also, regulatory filings should include the technical specifications of the supplies on which a product depends. If a company’s filing relies on a particular brand of venous-access device, it’s difficult to substitute alternates.

A case in point is Biogen’s recovery from the impact of Hurricane Maria on its production plan in Puerto Rico. Applying its prior experience with natural disasters, the company identified the threat days before the hurricane made landfall. A global risk team created a war room to pinpoint supply-chain threats and critical subtier suppliers. It transferred production from Puerto Rico to Kentucky and secured alternative suppliers for critical materials in advance, paying $1.3 million for items at risk of shortages. As a result, its stock price recovered and surpassed the prestorm price within 15 days of Hurricane Maria’s landfall.

Supply-chain resilience on the executive agenda

Supply-chain risk and resilience should be embedded in an organization’s strategic planning and day-to-day execution, with structured governance to ensure that decisions are made and acted on at the right level and time. There are two common approaches:

• Embed supply-chain resilience in existing forums. Each function and line of business conducts risk assessments, which are aggregated and discussed in existing forums, such as management-team meetings. Each unit must have risk-identification and -analysis tools, capabilities, and expertise for this approach to work. The organization must combine disparate risk assessments and have the incentives and escalation criteria for unit leaders to take ownership of risk management. The operation-leadership team serves as the forum for reviewing risks and making mitigation decisions about daily and strategic risks.
• Create a chartered risk committee. A risk committee comprises a subset of a company’s operation-leadership team and risk experts. A company can have committees at different levels of its organization. This approach ensures that a group of people is accountable for assessing and managing risk across the company. The committee will need strong analytic capabilities and tools that provide useful data. And there should be tight connections with existing governance forums to secure ownership of risk by functional leaders.

Leaders need to be able to see their organization’s risks and have people continuously evaluate and mitigate them. Supply-chain shocks are inevitable, but as Biogen illustrated during Hurricane Maria, disruptions aren’t. Every pharma company has some of the four elements we describe, but few have all. A company that wants to increase its resilience to shocks can review itself against these elements to determine where to start and how to proceed.

Tacy Foster is a partner in McKinsey’s Charlotte, NC, office; Parag Patel is a partner in the Chicago office; and Kathrin Skiba is a partner in the Hamburg office.

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Pharmaceutical Supply Chains - Medicines Shortages

• © 2019
• Ana Paula Barbosa-Povoa 0 ,
• Helena Jenzer 1 ,
• João Luís de Miranda 2

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• Provides pharmaceutical case studies
• Covers uncertainty and risk aspects of supply chain management
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Table of contents (19 chapters)

Front matter, the european medicines shortages research network and its mission to strategically debug disrupted pharmaceutical supply chains.

• Helena Jenzer, Leila Sadeghi, Patrick Maag, Franziska Scheidegger-Balmer, Katja Uhlmann, Stefan Groesser

Design and Planning of Sustainable Vaccine Supply Chain

• Mafalda Ivo de Carvalho, David Ribeiro, Ana Paula Barbosa-Povoa

Drug Shortages and Their Impact on Patients and Health Care Systems—How Can Systemic and Organizational Frameworks Help to Prevent or Mitigate Them?

• Phung Hoang Truong, Celia Cathérine Rothe, Tomasz Bochenek

Patient Perspective: Reporting on Medicines Shortages—Hemophilia a Case in Latvia

• Baiba Ziemele

Shortages of Medicines Originating from Manufacturing

• Maurizio Battistini

Risk Mitigation and Preventing Medicines Shortages

• João Roque, João Luís de Miranda, Pál Fehér-Polgár

An Exploratory Assessment of Risk and Resilience in Pharmaceutical Supply Chains

• Rachel Ward, Vincent Hargaden

Review of Pharmaceutical Sea Freight and Malaysian Third-Party Logistics Service Providers—A Supply Chain Perspective

• Wai-Peng Wong, Keng-Lin Soh

The Needs and Barriers Within the Supply Chain Actors—Hospital Pharmacy Needs

• Aida Batista, João Luís de Miranda, Ana Paula Teixeira

Patients Perspectives on Medicines Shortages in Hospital Setting

• Darija Kuruc Poje

Rationing of Nursing Care: An International and Multidimensional Problem

• António Casa Nova, Raul Cordeiro, Olga Riklikiene

Linear Programming and Cloud Computing for Pharmaceutical Supply Chains

• Miguel Casquilho, João Luís de Miranda, Miguel Barros

IBM Watson Studio: A Platform to Transform Data to Intelligence

• Roy R. Cecil, Jorge Soares

The Integration of a Flow Model into a Stakeholder-Based Framework for Vaccine Supply Chain Design

• Stef Lemmens, Catherine Decouttere, Nico Vandaele, Mauro Bernuzzi, Kim De Boeck, Sherif Hassane et al.

The Concept of Medicines Shortage: Identifying and Resolving Shortage

• Aurelija Burinskiene

Logistic Operations in a Hospital: A Multi-item Inventory Distribution Problem with Heterogeneous Fleet

• Agostinho Agra, Adelaide Cerveira, Cristina Requejo

A Multiple-Criteria Decision Sorting Model for Pharmaceutical Suppliers Classification Under Multiple Uncertainties

• Renata Pelissari, Sarah Ben-Amor, Maria Celia de Oliveira

Resilience Strategies and the Pharmaceutical Supply Chain: The Role of Agility in Mitigating Drug Shortages

• Emilia Vann Yaroson, Liz Breen, Jiachen Hou, Julie Sowter

Correction to: Resilience Strategies and the Pharmaceutical Supply Chain: The Role of Agility in Mitigating Drug Shortages

• Pharmaceutical Supply Chains
• Medicines Shortages
• Modeling-Simulation-Optimization
• Decision Support Systems
• Engineering Economics

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aF&E Ernährung und Diätetik, Berner Fachhochschule, Bern, Switzerland

Helena Jenzer

João Luís de Miranda

Bibliographic Information

Book Title : Pharmaceutical Supply Chains - Medicines Shortages

Editors : Ana Paula Barbosa-Povoa, Helena Jenzer, João Luís de Miranda

Series Title : Lecture Notes in Logistics

DOI : https://doi.org/10.1007/978-3-030-15398-4

Publisher : Springer Cham

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Copyright Information : Springer Nature Switzerland AG 2019

Hardcover ISBN : 978-3-030-15397-7 Published: 02 June 2019

Softcover ISBN : 978-3-030-15400-4 Published: 14 August 2020

eBook ISBN : 978-3-030-15398-4 Published: 01 June 2019

Series ISSN : 2194-8917

Series E-ISSN : 2194-8925

Edition Number : 1

Number of Pages : XXI, 256

Number of Illustrations : 14 b/w illustrations, 36 illustrations in colour

Topics : Pharmaceutical Sciences/Technology , Engineering Economics, Organization, Logistics, Marketing , Supply Chain Management

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Global or local? Biopharma’s supply chain challenge

Content Type: Article

Drug shortages are common and is a reality that cannot be wished away.

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In a letter to doctors on New Year’s Eve, the UK’s chief medical officers made an important point about the Covid-19 vaccination programme: “Vaccine shortage is a reality that cannot be wished away”. 1

For the profession, the message was a reminder that challenges were still to come, despite the emergence of multiple vaccines. For biopharma industry observers, meanwhile, the chief medical officers’ warning was a symptom of a perennial issue.

The biopharma industry has grown increasingly dependent on a global supply chain for the manufacturing and distribution of medicines. This has driven cost efficiencies through economies of scale, but it also makes it vulnerable to bottlenecks.

A complex tangle of processes across multiple countries vastly increases the potential for pain points in the biopharma supply chain, and these have knock-on effects that ultimately delay production. In a pandemic, that is both more likely and more catastrophic.

At this critical point, how is the supply chain performing? Findings from Cytiva’s Global Biopharma Resilience Index suggest a mixed picture.

Drug shortages are common

While 50% of executives and policymakers in the survey say their country never experiences shortages of critical medicines such as insulin, this drops to 26% for more specialised areas such as oncology biologics. Respondents from countries with a lower gross national income (GNI) per capita — Indonesia and Thailand, for instance — are more likely to report shortages. For example, 32% of respondents in Indonesia say that their country experiences shortages of oncology biologics more than once a year, compared with none in Switzerland and just 4% in the US.

Meanwhile 51% of executives say that drug shortages increased in their domestic market during the pandemic, although 33% say that the issue had been increasing over the past five years. This points to underlying issues around supply chain resilience, which have been exacerbated — but not caused — by the pandemic.

Part of the problem of supply chain security is the reliance on others. About half of the executives and policymakers surveyed (47%) say their country is moderately or highly dependent on the import of drugs, which illustrates the sheer expanse of the drug production and delivery process.

China and India in particular have become the epicentres of production for the generics and active pharmaceutical ingredients (APIs) that form so much of the industry’s output. Any breakdown in the supply chain here would create serious problems. 2

“I think even before the current crisis companies were rethinking their supply chains,” says Roberto Gradnik, a physician and the chief executive of Ixaltis, a biotech start-up. “They were moving away from really extreme globalization.”

Is it the end of an era?

Survey respondents agree with Gradnik. Six in 10 executives (59%) say that the era of offshoring drug manufacturing to low-cost countries is over, and 67% say that the manufacturing of biopharma staples such as biologics would dramatically increase in their own countries over the next three years.

The need to build resilience at home is not just an imperative for countries with a lower GNI per capita. Countries such as Switzerland and the US — among the top five countries for supply chain resilience (see chart 1) — acknowledge that they are vulnerable to scarcity. Figures from the US Food & Drug Administration, for example, show that the US currently has more than 100 drugs in short supply; 3 that includes opioid active ingredient morphine sulfate, a key painkiller ingredient, and pindolol tablets used on patients with hypertension.

Chart 1: Lower GNI per capita countries are fragile on their supply chain

These shortfalls are a concern. And although the Global Biopharma Resilience Index indicates that the biopharma supply chain performs better than other aspects of the industry (see chart 2), there are still a number of areas that need improvement.

The way the industry addresses this weakness will vary from country to country. But increasing domestic production while securing stronger networks with suppliers globally could give it the agility it needs to keep operations running smoothly.

Take Chinese firm WuXi Biologics, for example. With about a decade of experience in the manufacturing portion of the supply chain, the company has rapidly become a key partner for the pharma giants. Dr Chris Chen, WuXi Biologics' chief executive, is acutely aware of the risks to global supply chains brought on by Covid-19, but he is of the view that these global bases need reinforcement, while domestic operations are enhanced.

“We are building a very significant facility in Ireland, we have also purchased two facilities in Germany, and we are building a facility in the US,” says Chen. “There will still be a global supply chain. There will be some efforts to build local supply chains but it may not be that easy.”

Martin Meeson, chief executive of Fujifilm Diosynth Biotechnologies, believes that some elements of the supply chain, such as packaging, can benefit from localisation. But he also advocates for stronger global collaboration. “The cost of building a biopharma facility is in the billions,” he says. “And it would certainly not be economically viable for every country to try to put such a facility in place. It would be far more efficient for the world if the level of collaboration that we currently see within the pharma industry is mirrored in the way that the governments interact, in order to use resources efficiently.”

Chart 2 : Much more work is needed to avert a supply chain collapse

The biopharma supply chain on the ground

In a conversation with Adrian van den Hoven, director general of Medicines for Europe, which represents the generic and biosimilars industries, and a closer look at Swiss healthcare giant Roche, we find out how supply chain challenges are playing out in biopharma vs generics, and what industry leaders expect to change in the future.

In conversation with Adrian van den Hoven Director general, Medicines for Europe

How do the supply chain challenges faced by the biopharma industry compare with those seen in traditional pharmaceuticals?

Most of the recent issues in supply chain risks and drug shortages relate to traditional (chemical) pharmaceuticals. This is mainly because production of traditional pharmaceuticals is heavily concentrated in a small number of regions — for example specific provinces in India and China, or in Northern Italy for Europe — and high levels of consolidation can create risks around security of supply.

But this is far less of an issue in biopharma supply chains, because biopharma supply chains tend to be more vertically integrated and have more of the production steps centralised in one location, to make them easier to control. Outsourcing parts of biopharma production to other locations is therefore much less common and Europe has invested quite heavily in local biopharma production in recent years.

How are the supply chain challenges likely to change over the next few years?

Biopharmaceutical supply chains have not yet seen the same levels of consolidation as traditional pharma supply chains, but I believe this is likely to happen soon. This is mainly due to the rise of biosimilars, demand for which has been steadily increasing over the past decade.

As with generics, governments are starting to pursue commodity type pricing for biosimilars, to try and get the absolute lowest possible price. This price dynamic started in Europe, and it is likely to lead to the consolidation of the biopharma production chain within both Europe and Asia. The challenge for governments is that, as well as wanting to lower the cost of biopharmaceuticals, they want security of supply. In particular, during the pandemic it has been a huge advantage to have certain types of drugs produced in Europe. The dual need for lower prices and security of supply is a difficult challenge for the industry to square.

Which countries are likely to become the biggest exporters of biopharmaceuticals?

At the moment, there are a relatively limited number of countries that are exporting biopharmaceuticals. It is limited to the US, Europe, South Korea and Singapore. However, China and India are getting close to reaching the standards required for exporting biopharmaceuticals — and when this happens there is likely to be a lot of consolidation in the biopharma market.

In my view, there is a much more coherent link between the regulatory process and the manufacturing process in the biopharma industry than in traditional pharma, and this may make it slightly more challenging for China and India to break into the market. We will see how effective they are in the next couple of years.

A closer look Building a world-class supply chain at Roche

For Jerry Cacia, the key to navigating supply chain difficulties has been to reinforce industry collaboration.

Roche’s head of global technical development recognises the challenges that have led to increased localisation — “to make sure the supply of critical medicines is secure for each country”.

But Cacia says that this should not cause a total abandonment of the global system. “In some cases, it makes perfect sense to localise manufacturing — parts of your supply chain,” he says. “In other cases I would argue that it does not make sense, because these are very complex processes and frankly the costs will be really high.”

Roche’s success with manufacturing networks, says Cacia, has come from not having the supply chain “purely relegated to a specific country or region” for APIs, but through close relationships with suppliers that act as a pillar of support. It was able to “mobilise very quickly” to join forces with US biotech firm Regeneron, for instance, to support its production of a Covid-19 antibody treatment. 4 In a world without global supply chains, this kind of urgent collaboration would be much more difficult.

1 https://www.gov.uk/government/publications/letter-to-the-profession-from-the-uk-chief-medical-officers-on-the-uk-covid-19-vaccination-programmes/letter-to-the-profession-from-the-uk-chief-medical-officers-regarding-the-uk-covid-19-vaccination-programmes

2 https://www.bain.com/insights/a-strategy-to-make-pharma-supply-chains-more-resilient

3 https://www.accessdata.fda.gov/scripts/drugshortages/default.cfm

4 https://www.roche.com/media/releases/med-cor-2020-08-19.htm

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• Open access
• Published: 15 December 2023

Digitalization enhancement in the pharmaceutical supply network using a supply chain risk management approach

• Wai Peng Wong 1 ,
• Pui San Saw 2 ,
• Suriyan Jomthanachai 3 ,
• Leong Seng Wang 2 ,
• Huey Fang Ong 1 &
• Chee Peng Lim 4  

Scientific Reports volume  13 , Article number:  22287 ( 2023 ) Cite this article

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One major issue in pharmaceutical supply chain management is the supply shortage, and determining the root causes of medicine shortages necessitates an in-depth investigation. The concept of risk management is proposed in this study to identify significant risk factors in the pharmaceutical supply chain. Fuzzy failure mode and effect analysis and data envelopment analysis were used to evaluate the risks of the pharmaceutical supply chain. Based on a case study on the Malaysian pharmaceutical supply chain, it reveals that the pharmacy node is the riskiest link. The unavailability of medicine due to unexpected demand, as well as the scarcity of specialty or substitute drugs, pose the most significant risk factors. These risks could be mitigated by digital technology. We propose an appropriate digital technology platform consisting of big data analytics and blockchain technologies to undertake these challenges of supply shortage. By addressing risk factors through the implementation of a digitalized supply chain, organizations can fortify their supply networks, fostering resilience and efficiency, and thereby playing a pivotal role in advancing the Pharma 4.0 era.

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Introduction.

Supply shortages in the pharmaceutical industry, as highlighted in a recent study conducted by 1 , are a significant concern with far-reaching consequences. Not only does it affect individual health outcomes, but it also affects the broader healthcare system as well 2 . While patients who rely on consistent access to essential medications face uncertainty and potential health risks, healthcare providers and institutions are burdened with the challenge of managing and mitigating the impact of these shortages on patient care 3 . In addition, the economic implications are substantial, as they contribute to increased healthcare costs as healthcare providers seek alternatives, which are often more expensive, or incur additional costs related to managing patient health complications arising from medication unavailability 4 , 5 . These disruptions in the availability of critical medications underscore the need for a closer examination of the root causes 6 . Factors such as manufacturing issues, regulatory challenges, and complex global supply chain dynamics contribute to these shortages, making it essential to investigate comprehensively and implement effective solutions 4 , 5 .

In fact, pharmaceutical supply issues have long been a persistent and significant issue within the global healthcare system 7 . This stems from the complexities of the pharmaceutical supply chain which its characterisitcs are different from other industries. One example of the characteristics is it is fragmented and involve many different stakeholders. Addressing drug supply challenge requires a concerted effort from all stakeholders involved, as emphasized by 8 , without seamless supply coordination, a sudden demand surge could strain supply chain networks and worsen disruptions. Some scenarios that are causing supply issues are such as the misallocation of medication resulting from an increased demand for therapeutic supply could exacerbate drug shortages in community pharmacies 9 . Ref. 10 also reported that healthcare policymakers are constantly grappling with delays and non-fulfillment of medication orders, leading to widespread drug shortages. While the current systems face operational, logistics, and infrastructure challenges, several measures can be implemented to significantly ease the strain and address the issue associated with drug or supply shortages 11 .

Pharma 4.0, also known as the fourth industrial revolution in pharmaceutical manufacturing, is characterized by the integration of advanced technologies such as artificial intelligence (AI) and the Internet of Things (IoT) into the manufacturing process. Pharma 4.0 offers robust and flexible manufacturing processes, less interruption in medicine production and delivery, increased productivity, improved connectivity, and a fast response to drug or supply shortages. As a result, Pharma 4.0 can ensure better clinical and operational performance 11 . Pharmaceutical supply chain processes are critical to improving the overall performance in the Pharma 4.0 era. In this respect, organizations should consider redesigning their traditional business models by adopting a digital supply chain to achieve operational effectiveness and manage disruption 12 .

In this paper, we aim to address two primary research questions: 1) What are the most significant risks factors in the pharmaceutical supply chain in Malaysia that affect supply shortages? How can these risks be mitigated? Therefore, the objective of this study is firstly to evaluate and identify the siginifcant risks factors in the pharmaceutical supply chain. Secondly, to propose an appropriate digital technology platform to address these risks. The contributions of this study are twofold. First, it proposed a risk management approach for risk assessment in the pharmaceutical supply chain. Second, the derivation of managerial insights with a proposed research framework to incorporate and encourage digitalization of the pharmaceutical supply chain. The organisation of this paper consists of 6 sections, namely (i) an introduction; (ii) a literature review on the pharmaceutical supply chain and risk factors and emerging digital-based technologies in the pharmaceutical supply chain; (iii) methodology (iv) results, analysis and discussion; (v) managerial implications; (vi) and conclusion.

Literature review

Pharmaceutical supply chain and factors contributing to the risks.

A pharmaceutical supply chain (PSC) with optimum operational performance is essential for efficient delivery of medications to the patients. This can be measured by 5 different aspects, which are cost, quality, delivery, flexibility and dependability 13 . However, PSC is much more complex compared to other industries, considering the products are potentially life-saving for the patients and it has to be accurately and adequately provided to suit the needs of patients, not to mention that the industry has been advancing to personalised and patient-specific medications 14 , 15 , 16 , 17 . PSC covers a widespread network, often extending to other countries, that involves a plethora of stakeholders.

Referring to Fig.  1 , PSC can be segmented into three distinct levels, which are upstream (sourcing), central (distribution) and downstream (consumption) respectively. The sourcing process can loosely be defined as the manufacturers and the importers; the distribution process includes the wholesalers or distributor; while the consumption process is composed of the pharmacies (i.e., hospital pharmacies, clinics, community pharmacies) as well as the end users which are the patients.

Pharmaceutical supply chain and the main processes, modified from Saha et al. 11 and Musamih et al. (2021).

The manufacturing and distribution processes have to be reliable, responsive and flexible in adapting to the demands of pharmaceutics, which are often time unpredictable by nature 18 . This is because it is not only affected by external factors such as political, social and economic status, but also highly dependent on consumer factors and drug factors 19 . As for consumer factors, other stakeholders such as prescribers, pharmacists and payers are most of the time the main decision-makers of consumption rather than the patients themselves, hence the difference in practices and policies could complicate the forecasting of demand. The competition within the pharmaceutical market also varies from drug to drug as the replaceability of a therapeutical product depends on patents, availability of generic products and clinical evidence 20 . Given that PSC is inherently associated with these complex properties, inefficiency of operational performance is bound to occur within PSC, which poses varying degree of disruption risks to the PSC.

Factors contributing to the risks

The factors that contribute to this are interrelated to properties of PSC described above. Firstly, the large number of stakeholders involved in the fragmented PSC has led to disconnections and in turn lack of accountability between the supply chain partners, where information is not transparent across the intermediaries and the multiple consumption points 17 , 21 , 22 . Secondly, the lead time in PSC is usually long due to the time needed for the processes at each level of the PSC, especially when there is a need to fulfil the regulatory requirement 18 . As such, any changes in the demand at downstream, which is unpredictable in the first place, could cause a phenomenon known as “bullwhip effect”, where there would be a large fluctuation in quantities required to be supplied at the upstream level, hence the demands may not be met 21 , 22 . Financially, inaccuracy in demand forecast could lead to losses due to declining of sales if the amount of stock is inadequate. Therefore, high operating costs is required to maintain an optimum inventory level and warehouse spaces. However, this comes with a few downsides as it also affects the cash flow by prolonging the cash-to-cash cycle time and may potentially cause wastage due to damages and expiration of the products.

Besides the risks associated with operation and inventory management, different modes of transportation are also associated with their respective risk which could occur during the shipment preparation, storage and transportation process and lead to delay in delivery, damage to the goods and temperature excursion 23 . Crises of various foreseeability like natural disasters, political instability and pandemics can impact every stage of the supply chain, leading to different magnitudes of disruptions, damages and losses 24 , 25 . Lastly, regulatory issues such as documentations including licensing and permits, bureaucracy, changes in regulatory standards and drug recalls are major risks with high severity 26 , 27 .

In a nutshell, the pharmaceutical supply chain's distinct vulnerability to disruptions and risks, encompassing factors such as demand uncertainty, operational inefficiencies, inventory management, transportation challenges, and regulatory compliance, can significantly impede production and disrupt the seamless flow of drug/medication products, ultimately resulting in supply shortages within the pharmaceutical supply chain 28 . Shortages of essential medicines not only harm patients but also have a significant impact on the economy 29 . Drug shortages present a multi-dimensional challenge 30 . In-depth investigation in the local context is therefore crucial for determining the root causes of supply/medicine shortages and the complex interplay between various factors such as supply chain logistics, regulatory policies and manufacturing processes 11 .

In Pharma 4.0, manufacturing processes can become more robust and flexible, which could result in fewer interruptions in medicine production and delivery, better connectivity, faster responses to drug shortages, and increased productivity. Ref. 11 also highlighted that Pharma 4.0 could improve clinical and operational performance. To highlight the challenges in the pharmaceutical supply chain, the following sub-sections examine emerging digital-based technologies in the Pharma 4.0 supply chain.

Emerging digital-based technologies in the pharmaceutical supply chain

Studies on the emerging digital-based technologies in the pharmaceutical supply chain in Google Scholar (period of 2011–2022) are reviewed and summarized in Table 1 . Specific contributions of each technology were stated in the third column of Table 1 .

Methodology

Methodological approach.

Risk management is a systematic process employed by organizations to identify, evaluate, and mitigate potential risks that may impact their operations. It involves the comprehensive analysis of uncertainties and threats, enabling businesses to make informed decisions and enhance their overall resilience. One powerful tool for risk assessment within this framework is Failure Mode and Effects Analysis (FMEA), which systematically examines potential failure modes, their causes, and their consequences 47 . This enables organizations to prioritize and address critical risks, ensuring a proactive approach to risk management and ultimately strengthening their operations.

Figure  2 depicts the conceptual methodology of this study. The concept begins with the Failure Mode and Effect Analysis approach (FMEA). FMEA was chosen because it is a well known technique used in risk assessment 48 , 49 . The failure modes associated with the pharmaceutical supply chain are investigated after identifying the main supply chain processes. The main supply chain processes were discussed in detail in section " Risk assessment metric " and summarized in Appendix (Table A). Following the identification of failure modes or risk events, the risks are assessed by calculating the values of three factors: the O (Occurrence) factor, the S (Severity) factor, and the D (Detection) factor. In a real-world setting, we conducted interviews with respondents to ascertain these values. The O-factors are generated by asking, “How often does this event occur?”. The S-factor can be investigated, with the question: “If this failure occurs, how long will it affect the operations?”. The S-factors are developed based on the idea that the severity of a supply shortage can have a varying level of impact on patients concerning different categories of medicine products, increasing the difficulty of analysis. The duration of disruption 50 is used to investigate this factor in this study. In addition, the D-factors are calculated using the question “How effective is current digital-based technology in detecting or preventing this failure?” For risk analysis, these three O-S-D factors are scaled based on 48 perspective, as shown in Table 2 .

The conceptual methodology of a digitalized supply chain using a supply risk management approach.

Subsequently, the O-S-D risk is assessed. Note: The O-S-D risk factor analysis is presented in section " Risk assessment metric ".

To assess the failure mode, given the inherent subjectivity and potential fuzziness in human inputs, we utilized the Fuzzy Inference System (FIS) and Data Envelopment Analysis (DEA). These methods were employed to handle the linguistic variables associated with both inputs and outputs, facilitating the evaluation of results.

The risk assessment metric and failure mode evaluation using the FIS and DEA are explained in sections " Risk factor fuzzification "–" DEA and the cross efficiency method ". In this study, as mentioned in prior Sect. (3.1), the risk measure is based on FMEA. Since the traditional FMEA suffers from the uncertainty and ambiguity of expert assessment in real-world environments 51 , we apply the fuzzy approach of FIS to FMEA to overcome this drawback. Then, DEA is employed to calculate the risk based efficiency. DEA is also useful for overcoming the simplified mathematical formula in calculating the risk priority number (RPN) in FMEA, which can provide counterintuitive statistical properties. In contrast, the use of DEA with FMEA can tackle issues such as non-consideration of the direct/indirect relationships between failure modes. Instead of directly applying fuzzy DEA, which uses the fuzzy sets of O-S-D factors as the input of the DEA method, we exploit the FIS to provide fuzzy inputs with a fuzzy rule set based on the significance of O-S-D factors. For this purpose, the rule set comprising different weights of O-S-D factors can be utilised to incorporate expert experience and viewpoint on the identified weights of O-S-D input variables, in order to make the corresponding fuzzy inference 52 . The advantage of employing FIS on the inputs, as opposed to directly applying fuzzy DEA, lies in FIS’s superior ability in handling qualitative or linguistic data. FIS allows for the incorporation of domain knowledge and expert opinions into the model, enhancing the interpretability of the results.

Risk assessment metric

In this study, the risk assessment metric is developed based on the risk management concept. Firstly, the risk identification process is carried out. Table 3 depicts the findings on risk identification pertaining to supply shortage in the pharmaceutical supply chain, which is based on the respective critical processes. A scheme to analyze the level of risk factors is developed, as shown in the Appendix. Based on the pharmaceutical supply chain in Malaysia, the manufacturer node evaluates the metric related to the sourcing, manufacturing, and order fulfillment processes. The distributor node validates the metric for the distribution, order fulfillment and inventory replenishment processes. The pharmacy shop node also assesses the metric for replenishment and consumption.

Risk factor fuzzification

Instead of binary values, fuzzy logic takes into consideration multiple levels of value to address the concept of uncertainty or ambiguity 61 . Since risk assessment in FMEA entails uncertainties from expert judgment, a fuzzification process is used to convert a crisp input into a fuzzy input characterized by a series of fuzzy membership functions 62 . The fuzzification step involves using the fuzzy membership function with implication to evaluate the rules in the rule bases and then aggregating the results of the implication on the rules 52 .

In this study, the input parameters of FMEA risk factors (O-S-D) are fuzzified. During data collection, the risk factors are defined to express the importance of the O-S-D inputs. Based on the experts' recommendations, the corresponding membership functions of each risk factor are defined for all inputs. Following that, a rule set is created by defining various if–then rules based on experts’ opinions to determine the best output formed by various input combinations. Each rule has two main parts: an antecedent (if) and a consequence (then) 63 . In each rule, the antecedent serves as a condition on the inputs to compute the result or output. This step creates a robust structure for applying experts’ viewpoints on the input variables for performing fuzzy inference 52 . An inference is implemented on the input of risk variables based on the fuzzy operators. An FIS is designed independently for each risk factor. Initially, fuzzy propositions are presented using the implication operator during the inference phase 64 .

The FIS inputs (i.e., O-S-D risk factors) consist of experts’ viewpoints while the output consists of judgment on the O-S-D factors. In the FIS, the triangular membership functions are defined for the inputs, while the trapezoidal membership functions are defined for the output. As shown in Tables 4 , 5 , 6 and Figs.  3 , 4 , 5 , the membership function outputs are used for the inference engine with fuzzy if–then rules. Using the FIS toolbox in MATLAB (R2020b), a total of 10 rules for the FIS are defined based on the number of input levels of the O and S factors, along with 6 rules of the D factor.

The membership functions of O-factor, ( a ) = input and ( b ) = output.

The membership functions of S-factor, ( a ) = input and ( b ) = output.

The membership functions of D-factor, ( a ) = input and ( b ) = output.

Risk factor defuzzification

Defuzzification is used to convert the fuzzy outputs to crisp outputs after the inference process. In defuzzification, various methods for approximating fuzzy outputs to non-fuzzy values are available 65 . The Mamdani type is used in this study. The FIS outputs are calculated using three defuzzification methods to determine the best defuzzification result 66 . They are the Smallest of Maximum (SOM), Middle of Maximum (MOM) and Largest of Maximum (LOM) (see Fig.  6 ).

An example of defuzzification methods of SOM, MOM, and LOM.

According to 67 and 52 , SOM, MOM, and LOM can be selected from a fuzzy set of outputs, as follows:

where \(\underset{u}{{\text{sup}}}\) and \(\underset{u}{{\text{inf}}}\) are the lower bound (LB) and upper bound (UB), \({\mu }^{cnceqe}\) is the membership function of fuzzy set \(u\) , and \(U\) is the range of possible output values. Corresponding to the number of risk factors, three values of SOM, MOM and LOM are calculated. According to the proposed method, each potential risk is tagged with three values computed for each O-S-D factor.

The fuzzy numbers of risk factor

The FIS toolbox in MATLAB (R2020b) is used to process the fuzzy inputs based on fuzzification of O-S-D factors. Then, the SOM, MOM, and LOM output scores are computed based on the possible number of crisp values of each factor. The results are shown in Table 7 .

DEA and the cross efficiency method

We use the input-oriented DEA model in this study to illustrate the CRS (Constant Returns to Scale) method of 68 ,

Where \(n\) denotes the number of DMUs with index \(j\) . Parameters \(m\) and \(s\) represent the input \({(x}_{i})\) and output \({(y}_{r})\) numbers. Moreover, \({s}_{i}^{-}\) and \({s}_{r}^{+}\) are the slacks in the input and output. A DMU converts the inputs to outputs in DEA. Its efficiency can be measured using a productivity-related output-to-input ratio 69 . For evaluation, a set of DMUs is used. Each DMU has some managerial discretion in decision-making.

When a standard FMEA model is performed on the DEA, the failure modes correspond to the DMUs , while the inputs ( O-S-D) correspond to multiple inputs of the DEA. Furthermore, multiplying O, S and D results in the RPN (i.e., the FMEA output). The limitations of crisp RPN scores in a standard FMEA model have been highlighted, such as the simple mathematical formula used to compute the RPN can lead to non-intuitive statistical properties 70 . Furthermore, the RPN does not take into account both direct and indirect relationships between each failure mode, and is insufficient to deal with systems or processes with a large number of subsystems and/or components 71 . DEA can be exploited to tackle the mathematical formula issues of RPN computation, as it can handle risk factor weights and consider direct and indirect relationships between the failure modes 72 .

Because the RPN does not match the DEA output, previous research studies have proposed using any DEA model without outputs, or constant outputs equal to one, when applying DEA to FMEA to achieve an efficiency score for risk prioritization, instead of the traditional RPN score 52 , 70 , 73 , 74 . Traditional DEA methods, however, have some limitations, such as a low discriminating power in efficiency evaluation. The cross-efficiency method strengthens the discriminatory power of DEA 75 . Thus, this study employs the DEA cross-efficiency method to improve FMEA for risk analysis.

The traditional DEA model is expanded in two stages in the cross-efficiency method, including self- and peer-evaluation. This addition assesses the overall performance within each DMU by taking into account not only its individual weights but also the weights of all DMUs 76 . To self-evaluate, Eq. ( 4 ) is used, where DMU \(j\) is evaluated using its extremely favorable weights. In addition, \({\mu }_{rj}\) and \({\nu }_{ij}\) are the optimal output and input weights of the self-evaluation stage for a given DMU \(j\) \((j\in N)\) , respectively. It is easily demonstrated during the peer-evaluation stage that by using the cross-efficiency method, all DMUs are evaluated using a similar set of weights. Indeed, the \(j\) th DMU value of cross-efficiency \(({CE}_{j})\) can be computed using Eq. ( 5 ) 77 :

For DMU \(j\) ( \({E}_{jk}\) ) to obtain the cross-efficiency scores of all DMUs, Eq. ( 5 ) must be solved \(k\) times, each time for a target efficiency score. As shown in Table 8 , all the scores can be displayed as a \(j\times k\) cross-efficiency matric, with the diagonal part displaying the CRS-efficiency scores \({E}_{jk}^{*}\) 76 .

Results, analysis and discussion

The developed model is applied to a case study of firms supporting a pharmaceutical supply network in Malaysia. Figure  7 depicts the supply chain structure of the study. This diagram depicts three drug manufacturers (A, B, and C), one distributor (D), and two community pharmacies (E and F). Semi-structured questionnaires designed based on the risk metric of each node (Tables A to C in Appendix) are used during the interview with an expert from the top management of each firm (plant manager, logistics manager, or shop manager). The data collected are analyzed, and the outcomes of the risk assessment, including individual nodes and overall supply chain results, are discussed in the following subsections.

The supply chain structure of the case study.

The risk of the manufacturer node

For the manufacturer node, the DEA cross-efficiency method (Eq. ( 5 )) is used, as shown in Table 9 and Fig.  8 . Because this indicator is expected to be as low as possible when a constant output is considered, all three fuzzy risk factors (O-S-D) of SOM, MOM, and LOM as in Table 7 are considered as the inputs. The output is set to one, and this value is shared by all DMUs. All risk events are dependent on the three manufacturers producing the DMUs in the DEA cross-efficiency method, totaling 48 DMUs.

The cross-efficiency of manufacturer node.

The RPN is employed to determine the relative risk for each failure mode. It is a standard metric for assessing the relative risk of failure modes 78 . To maintain this perspective, we add dummy DMUs of the lower and upper ranks when analyzing the efficiency score. This technique is suitable for a study with multiple nodes or organizations, such as a supply chain, because we analyze different node groups at different times. It provides appropriate results when comparing different node groups because the dummy DMUs run the standard metric.

The results of a comparison between the DEA cross-efficiency and the traditional RPN are presented. When the DEA is used, a low RPN is usually associated with a high-efficiency score. However, as shown in Fig.  8 , the efficiency scores of DMUs using this method do not entirely rely on the RPN value (as indicated by the fluctuation of the line chart). This phenomenon suggests that the DEA result is more reasonable in risk prioritzing because it does not adhere to the RPN result, which is still based on a simple mathematical formula, i.e., multiplication of the S, O, and D scores 75 . When the value of cross-efficiency scores concerning each manufacture is prioritized (Table 9 ), B yields an average efficiency score of 0.3329, which is at the highest risk level. This is followed by A and C, with 0.485 and 0.5153 average efficiency scores, respectively. For B, the failure mode of B-S1 (unavailability of raw materials due to a limit or single supplier yield as a material source from a specific source) has the highest risk score of 0.1303. Following that, B-S2 (raw material scarcity as a result of political turmoil) produces a score of 0.1671.

The risk of distributor node

For the distributor, all risk events from a single case study are assigned to DMUs using the DEA cross-efficiency method, yielding a total of 9 DMUs. When the value of cross-efficiency scores is prioritized (Table 10 and Fig.  9 ), the average efficiency score of distributor D is 0.7902. The failure modes of D-D2 (supply is unable or delayed as a result of transportation and distribution facility failure), D-D3 (supply is unable or delayed due to transportation disruptions), and D-F1 (inability or delay in downstream supply due to inefficiency of just-in-time or lean inventory systems or lack of buffer stock control) have the highest risk, with a score of 0.4719.

The cross-efficiency of distributor node.

The risk of pharmacy node

The risk event is determined by both pharmacies that comprise the DMUs in the DEA cross-efficiency method, yielding a total of 16 DMUs. When the value of cross-efficiency scores for this node (Table 11 and Fig.  10 ) concerning each shop is prioritized, E yields an average efficiency score of 0.3274, which is at a higher risk level than that of F. F has an average efficiency score of 0.3897. For E, the failure modes with the highest risk of score of 0.1811 are E-C2 (unavailability of a product for patients due to an unexpected increase in demand in a short period of time), E-C3 (unavailability of a product for patients from many drugs that do not have substitutes or substitutes that are less effective), and E-R3 (upstream supply is unable or delayed because only a few manufacturers produce drugs).

The cross-efficiency of pharmacy node.

The efficiency of supply chain

To describe the overall risk level of the pharmaceutical supply chain, the quantitative values are converted into linguistic variables to describe the risk in words 79 . As a result, the risk scores of cross-efficiency are transferred to the linguistic level for further clarification. Table 12 shows the rank of risk level in this study based on the cross-efficiency score. As an example, if the original value of O-S-D is 5–5-5, the cross-efficiency score of this value is 0.2599, indicating a moderate risk level based on the step explained in the methodology. Overall, there are four levels of risk: low (cross-efficiency score from 0.5 to 1), moderate (cross-efficiency score from 0.25 to less than 0.5), high (cross-efficiency score from 0.125 to less than 0.25), and critical (cross-efficiency score less than 0.125). Table 13 shows the overall risk levels of the pharmaceutical supply chain case study.

According to Table 13 , the average risk of A, B, and C in the manufacturer node is moderate (cross-efficiency score is 0.4444). It is discovered that the failure mode of MS6 (delay in raw material supply due to overseas suppliers) is a high risk. Similarly, developing countries like Malaysia rely heavily on foreign countries such as China, India, and Russia to import various chemicals and other raw materials for the pharmaceutical industry 80 . As a result, natural, man-made and other disasters can have a significant impact on raw material imports.

The average risk level for the distributor node is low (cross-efficiency score is 0.7902). Three items pertaining to the moderate level (cross-efficiency score is 0.4719) are: DD2 (supply is unable or delayed as a result of transportation and distribution facility failure), DD3 (supply is unable or delayed due to transportation disruptions), and DF1 (inability or delay in supplying downstream due to inefficiency or lack of buffer stock control in a just-in-time or lean inventory system). Moreover, drug availability and quality losses during storage and transportation are the most significant challenges of the pharmaceutical supply chain. The transportation and sorting processes affect the delivery time, while breakdowns and uncertainty are the primary issues 81 . Furthermore, transportation disruptions can cause severe effects to the pharmaceutical supply chain operations, necessitating a timely response to such a challenge 82 . This factor is particularly significant in developing countries where drug administration is hampered by a lack of transportation infrastructure and facilities. It can also affect drug delivery accuracy 83 . Pharmaceutical product shortages can be exacerbated by lean inventory management practices. A just-in-time inventory management system is widely used by manufacturers, distribution centers, and healthcare organizations. However, in many cases, it leads to lower inventory levels across the supply chain, which increases the likelihood of shortage occurrence 84 .

The pharmacy node has a moderate risk level (cross-efficiency score is 0.3586). In comparison with other nodes, this node poses the greatest risk. The reason is that it covers three failure modes that fall in the high-risk level, including PC2 (unavailability of a product for patients due to an unexpected increase in demand in a short period), PC3 (unavailability of a product for patients from many drugs that do not have substitutes or substitutes that are less effective), and PR3 (upstream supply is unable or delayed because only a few manufacturers produce drugs). In general, drug shortages can occur for a variety of reasons. As an example, unexpectedly high demand or demand fluctuations can cause drug shortages, which typically affect front-line delivery by pharmacies 85 . Moreover, substitution medicines can help avoid some of the issues that pharmacies face daily, such as the risk of delivery delays, damaged medication, and seller stockouts. Nonetheless, there are only few or no substitute medications available 86 . Additionally, if only few independent manufacturers produce some specialty drugs, these manufacturers can pose a risk to the front-line pharmacy 87 . Correspondingly, the average cross-efficiency score of all nodes in the pharmaceutical supply chain is 0.4734, indicating a moderate level of risk. This average value is appropriate for defining the overall efficiency when using the DEA method in network structures such as supply chains 88 .

The following section will discuss the interaction of digital technologies with the risks factors, along with managerial implication and proposed framework to guide digitalization supply chain for risk mitigation.

Interaction of digital technologies with risks level

This study further explores the interaction of digital technologies with the risks in the pharmaceutical supply chain. The hierarchical cluster analysis (HCA) method in the DATAtab laboratory ( https://datatab.net/ ) was used to cluster the potential digital technologies related to the risk level of cross-efficiency score. Based on the column mapping to digital technology in Table 3 , HCA was exploited to assign the risk events to four primary technologies. Figure  11 shows the cluster dendogram illustrating the interaction between digital technologies and risks level in the pharmaceutical supply chain.

Cluster of Pharma 4.0 main technologies related to the failure mode and its cross-efficiency score using the hierarchical cluster analysis method.

According to Fig.  11 , the three high risk events (PR3, PC2 and PC3) are located in the cluster of information sharing technology such as blockchain. Another high risk event (MS6) is situated in the cluster of data analytics and machine learning. Hence, to deal with these various risks events, advanced methodologies and principles must be followed to meet the needs of this complex pharmaceutical supply chain network both internally and externally. Variations in the market economy force the related pharmaceutical firms to change their strategies from time to time. Owing to a constant and fluctuating demand, predicting the correct volume is challenging. Moreover, the time spent at each level of the supply chain is critical in determining supply delivery on time. Practical strategies and methods used by all players to achieve on-time delivery and address product complexity are required 89 . Many useful insights are derived from the digitalization supply chain and the Pharma 4.0 era to develop a conceptual framework for the effective operation of any given pharmaceutical supply chain.

Managerial implications

Considering that this study's risk assessment of the pharmaceutical supply chain is based on a risk management approach, it is logical to adopt the method of controlling and prioritizing risks within a network of interconnected risks. This approach is instrumental in reducing or mitigating risk exposure effectively. Managing these risks necessitates the utilization of a risk portfolio rather than addressing individual risks in isolation.

In this section, we explore risk mitigation strategies for interdependent risk portfolios by identifying potential technologies with similar marginal contributions. Based on the findings of risk assessment in the case study, the implications on the significant risk level and cluster of potential digital technologies recommendations are presented, as follows.

The collaborative technology for information sharing is significant for the overall players in the pharmaceutical supply network. The main collaboration initiative is to administer a strict inventory control and to let stakeholders know how many products are available, leading to resolving a shortage or reducing the bullwhip effect in the network. To successfully collaborate in a supply chain, various members must agree on mutual goals and synchronize their decisions. By exchanging information in real-time, digitalization has the potential to convert and reshape the pharmaceutical supply chain and improve coordination among supply chain partners. The blockchain technology can bridge the supply chain information such as the inventory visibility gap by improving end-to-end data visibility among the supply chain partners through sharing of backlog information.

In the event of a drug shortage or a lack of substitute drugs (PC2 and PC3), drug sharing or exchange in the pharmacy network can be investigated. Again, the blockchain technology offers an ideal solution. To establish a drug-sharing network based on the blockchain technology, decentralization (i.e., a transparent medium) enables data exchange and recording; thus, entities searching for records in such a credible distributed system could find solid and transparent data on transactions. As a result, securing explicitly open and trustworthy repositories that are required for the drug supply chain in the pharmaceutical business network, where the required data can be easily accessed and tracked by all involved entities, is essential.

Additionally, blockchain technology is advantageous for mitigating the moderate risk of drug shortages due to unpredictable demand (PC1), particularly relevant to PC2 and PC3 (as indicated in Fig.  11 ). Furthermore, if the blockchain system is tailored to connect with distributors and manufacturers, it can facilitate the reliable transmission of shortage item information to enhance their performance. This improvement includes reducing delivery times, expanding production capacity, and implementing stringent waste control measures, which are associated with the high risk of PR3 and the low risks of DR3 and DD4. Expanding the blockchain network is also valuable for enhancing network coordination, mitigating the low risk of PR2 and DR2, and enabling members to steer clear of unethical or unregulated marketing practices for scarce items.

In the context of data analytics and machine learning, supply chain managers in manufacturing can employ a de-globalization strategy, supported by big data analytics. A recent study by 90 have noted that the trend toward de-globalization, while resulting in higher costs, can also introduce higher supply volatility due to fewer input sourcing channels. Big data analytics is recognized as a technological pillar that enhances cost competitiveness for onshore production, influences production retention decisions, and aids in the selection of local or regional multi-supliers based on their performance. This strategy mitigated the risk of supply delays from overseas suppliers, particularly the high risk of MS6. It also addresses related global spply chain issues such as the moderate risk of MS4 (trade disputes) and the low risks of MS2 (political turmoil) and MS3 (armed conflicts)..

During application, digital de-globalization is outlined as the state of a digital form that connects regional and national industries, companies, and individuals through digitally enabled or supported flows of data, information, ideas, and knowledge, as well as flows of goods, services, investment, and capital. Big data analytics are common technologies that support such flows, while digitization-enabled platforms like e-commerce and online marketplaces abundantly prompt digital trade and transaction flows that provide a big data source of business. In this context, the moderate risk of MS1, involving limited or single supplier dependence, can be addressed using supply source big data.

Moreover, in pharmacies, AI algorithms can deal with unexpected and unpredictable increases in demand (PC1, PC2 and PC3) in a short time by providing advanced forecasting methods. To forecast trends and obtain optimal models with good accuracy, cutting-edge AI and deep learning algorithms offer viable solutions.

A Proposed framework to incorporate and encourage digitalization of the pharmaceutical supply chain

Based on the results of the risk assessment in Section " Results, analysis and discussion ", it is evident that there are high-risk events within the pharmaceutical supply chain. These high-risk events include: S6 (Delays in raw material supply, primarily associated with the sourcing process); R3 (Delays in supply due to poor order fulfillment and inventory replenishment, which are interconnected processes); C2 and C3 (Unavailability of products in the consumption process).

These risks can be effectively mitigated through the strategic implementation of digital technologies, as discussed in the previous section. For instance, the utilization of big data and data analytics technologies can play a crucial role in mitigating risks associated with sourcing issues. Similarly, the adoption of information sharing technologies can enhance the management of risks related to order fulfillment and inventory replenishment. Furthermore, better demand forecasting in the consumption phase can be achieved through these technologies.

It's important to note that addressing these high-risk events with these technologies can simultaneously help mitigate other corresponding moderate and low-level risks due to the positive side effects of these actions, as illustrated in the previous section on risk portfolio addressing a network of interconnected risks.

Figure  12 shows the framework on how digital technologies can be harnessed to address risks in the pharmaceutical supply chain. Big Data and data analytics technologies (DA) can effectively mitigate risks in the sourcing and manufacturing processes and should be primarily employed by manufacturers. Information sharing (IS) technologies can significantly reduce risks in the distribution, fulfillment, and replenishment processes. Therefore, a collaborative approach involving manufacturers, distributors, and pharmacies is recommended. Within the consumption process, establishing a drug-sharing (IS) network at both government, community, private and chain pharmacies can be a valuable strategy to mitigate supply shortage risks (Fig.  13 ).

Framework to incorporate digital technologies in the pharmaceutical supply chain.

Integration of digital technologies in the pharmaceutical supply chain.

This framework serves as a guideline for the incorporation of digital technologies into the pharmaceutical supply chain. The implementation of these digital technologies should be a collaborative effort among the various chain members. For instance, instead of creating discrete information-sharing platforms exclusively among pharmacies, it may be beneficial for distributors or manufacturers to take the lead in setting up the infrastructure. This approach can expedite the flow of information upstream, enabling faster responses to address supply shortages.

Furthermore, the proposed framework has the potential to inspire future research and encourage deeper discussions with stakeholders. The framework can be further refined and improved through triangulation and further inputs from all key stakeholder and policy makers.

Pharmaceutical supply issues or drug shortages are not a new concern; they have long been a serious and growing challenge in the global healthcare system. This is especially true in under-developed or developing countries where drug supplies are limited. In the Pharma 4.0 era, a digital supply chain of pharmaceutical supply processes is critical to improving the overall supply chain performance. In addition, several emerging technologies are beneficial for use in the pharmaceutical supply chain to address supply shortages. This study introduces the concept of risk management for identifying key risk factors in the pharmaceutical supply chain and propose an appropriate digital technology platform for pharmaceutical supply chain management to overcomehis serious issue. This study has contributed to the interaction of technologies in pharmaceutical supply chain performance and provides managerial insights with a proposed framework on how to incorporate and encourage digitalization of the pharmaceutical supply chain for achieving robustness in supply chains using a risk management approach. Through a case study of the pharmaceutical supply chain in Malaysia, this research has discovered that the pharmacy node is the most critical. Shortages arise due to unexpected demand, the same applies to scarcity of specialty or substitute drugs. To address these shortages, this study proposed the implementation of appropriate digital technology platforms for supply chain collaboration, including big data analytics and blockchain technologies.

The study's limitation lies in its focus on a small supply chain, restricting the generalizability to pharmaceutical supply chains in other countries or regions. To address this limitation, future research should encompass larger supply chain networks and diverse geographical contexts to provide a more comprehensive evaluation. Furthermore, enhancing the proposed digital technology integration framework for the pharmaceutical supply chain can be achieved by gathering additional inputs and feedback from key stakeholders.

Data availability

The data that support the findings of this study are available from the corresponding author on reasonable request.

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This study was supported by the Monash University Malaysia through the IT-Pharmacy Cross-Disciplinary Research Grant Scheme.

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Wai Peng Wong & Huey Fang Ong

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W.P.W. and S.J. contributed to the study conception and design. Material preparation, data collection and analysis were performed by W.P.W., P.S.S., S.J.i., L.S.W. and H.F.O.. The first draft of the manuscript was collaboratively written by W.P.W., P.S.S. and S.J.. All authors reviewed the manuscript. C.P.L. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Wong, W.P., Saw, P.S., Jomthanachai, S. et al. Digitalization enhancement in the pharmaceutical supply network using a supply chain risk management approach. Sci Rep 13 , 22287 (2023). https://doi.org/10.1038/s41598-023-49606-z

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Case Study: Tracking and Tracing Drugs in the Pharmaceutical Supply Chain

Failures or lack of visibility in the many-tiered pharmaceutical supply chain have multiple repercussions. Drug shortages have adverse economic and clinical effects on patients — they are more likely to have increased out-of-pocket costs, rates of drug errors, and, yes, mortality. Hospitals and health systems allocate over 8.6 million hours of additional labor hours to […]

Failures or lack of visibility in the many-tiered pharmaceutical supply chain have multiple repercussions. Drug shortages have adverse economic and clinical effects on patients — they are more likely to have increased out-of-pocket costs, rates of drug errors, and, yes, mortality.

The US had about 150 to 300 drug shortages every quarter from 2014 to 2019.

For drug managers, maintaining excess inventory to try to avoid shortages brings significant costs in storing pharmaceuticals — and waste when they are not used. They also struggle with being able to predict where a particular drug is likely to be needed at a particular time.

The average pharma holds 180 days of finished goods inventory, and could free up $25 billion if it reduced that to a target of 80 to 100 days. With increased competition from generics and rival brands, cutting costs in the supply chain lets them redirect money to competitive ends such as funding product development.

Compliance is another issue. Serialization compliance required by the FDA’s Drug Supply Chain Security Act requires manufacturers, re-packagers, wholesale distributors, and pharmacies to be capable of lot-level product tracing and to provide applicable transaction information, history, and statement.

To protect patients and prevent falsified medicines from entering the supply chain, the EU’s Falsified Medicines Directive was passed to increase the security of the manufacturing and delivery of medicines across Europe. The main focus is on counterfeit and falsified drugs that can be ineffective or even dangerous.

By 2023 in the US, lot-level tracing will move to unit-level serialization. Russia’s serialization gives pharma companies until this year for complete unit- and batch-level traceability. Brazil’s track and trace regulations go into effect in May 2022. In South Korea and India, companies must uniquely serialize drug products. Saudi Arabia’s Vision 2030 plan includes adopting technology for tracking all human registered drugs manufactured in Saudi Arabia and those imported from abroad. China has published regulations providing for the development of a new national drug traceability system by 2022.

Regulations that require that manufacturers add serial numbers to medications give them more data than previously, a benefit for having information about the status of drugs wherever they are in the supply chain. But getting this right requires that partners in the supply chain participate in the tracking.  

Track and Trace in Action

Global pharmaceutical company Merck KGaA Healthcare is working on this issue. It maintains about 150 days of drug inventory, which is expensive to keep in-house and particularly wasteful when it comes to personalized drug therapies with short shelf lives. Its supply-and-demand forecasts are 85 percent accurate today.

One of the drugs it manufactures is related to amino oncology drugs. It was looking for a way to improve forecasting for these potentially life-changing and life-saving drugs. These are personalized medications, expensive and valuable. It’s imperative to ensure the drugs make it to the right place at the right time. It all starts with drawing blood from the patient and sending it to the lab, where a therapy is formulated based on the patient’s DNA. The drug created from this must travel along the supply chain in temperature-controlled environments, and it must reach the patient within a specified time frame for treatment.

Merck KGaA Healthcare has piloted a project with TraceLink , using the vendor’s Digital Network Platform to improve supply-and-demand forecasting and reduce shortages of critical immune-oncology drugs. Serialization on its own is still fairly new and even as it matures, TraceLink’s platform focuses on further enhancing the supply chain process. Not only does it generate serial numbers, but it also provides a centralized hub where third-party participants in drug companies’ supply chains can share relevant information such as manifests and product master data with each other. Bringing everyone together on the same platform is a more efficient way of trading this information than drug companies’ having to create point-to-point connections from their internal systems with the systems used by the companies they need to share data with.

Contract drug manufacturers, which in many cases manufacture generics for multiple drug companies, use the platform as well as brand-name big drug companies, and smaller ones that sometimes are the creators of blockbuster drugs. It’s hard for them to track all those relationships.

“With the network, you integrate once and interoperate all down the supply chain to increase visibility and lower the bar to sharing data,” said John Hogan, TraceLink Senior Vice President of Engineering. “The network changes the process of integrating between individual supply chain and inventory systems, which is difficult and for pharmaceutical companies and is not necessarily their strong point.”

The company has defined canonical data formats for internal management; it maps pharma supply chain partners’ data (logistics companies, dispensers, and wholesalers) into that and then back out into the format that another member of the network might need.

Compliance was the first problem TraceLink tackled but it realized the huge value in the data for many other purposes. “If you know how particular products traveled along the supply chain, you have unique insight that can be used for dealing with recalls or obstacles in the supply chain,” he said. “You can make things more efficient and avoid having those problems repeat themselves.”

It’s also providing APIs that other businesses can use when they see other use cases for the Digital Network Platform to leverage its core construction — for instance, to create new user experiences and provide a different preferred view into the same information using built-in machine learning algorithm. “In the future, you can imagine use cases where people involved in clinical trials might want to let their information be shared to prove the efficacy of those trials,” Hogan said.

Over the next five years the pharma track and trace solutions market is expected to surpass $2.38 billion. Other vendors that are in the pharma track and trace space include rfxcel, Adents, Acsis, Frequentz, Optel Group, Arvato Systems, E2open, Retail Solutions, UpNet, iControl and Nulogy.

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Welcome to Supply Chain Challenges – Team Approach to managing Supply Chain Risks

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Revolutionizing digital collaboration at work

Global biopharma company embraces innovation to improve work-life balance.

Call for change

Striking balance between personal and professional

What if success at work revolved around results? What if collaborating and connecting with colleagues didn’t depend on location? What if your priorities dictated your calendar instead of the other way around? What if you could be truly empowered at work?

Leaders at a global biopharma company wanted to answer these questions … once and for all.

The company faced steep challenges when it came to helping employees strike a balance between professional and personal lives. After listening to employees, the company recognized the need to:

• Improve engagement outside of meetings through digital methods
• Allow for flexibility in daily schedules at all levels of the organization
• Improve innovation, productivity and creativity by prioritizing focus time

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The project included in-depth research, creation of over 150 content assets, and embedding a “ Net Better Off practice .” The success of the program depends on trust and the universal adoption of simple yet significant changes.

For team effectiveness, we designed a change management approach to drive a more outcome-focused organization. For better engagement, we created a digital worker toolkit centered around Microsoft Teams. For flexibility, we designed strategies to help employees better manage their time.

The team developed more than 50 supporting products—including collaboration technology to reduce email traffic and opt-in experiential learning using NextGen learning methods and tools.

So how does this look in practice?

One of the teams was tapped to nurture and measure the empowerment of a people mindset before rolling out to the rest of the company. The pilot launch included half-day experiences, coaching and operating models to transform the team’s ways of working.

For example, some employees in this group were in 40-50 hours of meetings, with approximately ten hours of meetings a week outside of “working hours” and back-to-back meetings, without a break. The team launched two experiments to address this issue. First, they instituted virtual commutes with a five-minute gap between meetings. Second, the team moved meetings from outside to inside working hours as set in Microsoft Outlook. Teams were also given the tools to collaborate digitally to enhance the effectiveness of work happening globally.

A new digital platform

Microsoft’s centralized platform helped the client transition to a unified digital space for communication and collaboration. Additionally, Microsoft Viva Insights, which helps users auto-schedule their work time, helps company employees analyze recent work patterns so they can adjust their schedules and actions accordingly. Microsoft Planner is also used to assist employees in aligning with individual and team priorities daily.

Throughout the transformation process, employees and managers were encouraged to stay aligned on priorities and progress while all involved tested flexible approaches to when and where they work. The focus was on the result and providing the employee with the flexibility to achieve it.

There has been a 30% increase in one-on-one meetings with managers at least once a month, an indication that employees are more connected and almost half of employees reported that they are more empowered to get work done more flexibly.

A valuable difference

Putting people first and reaping remarkable results

Sometimes the simplest solutions are the best.

The company has successfully shifted away from a “presenteeism” culture, where meetings are the primary way for employees to demonstrate their value. Teams now use digital collaboration to fuel progress. The pressure to “always be on” has lessened, thanks to the increased trust and flexibility on how, when and where they work. And employees now have clear, regularly updated shortlists of priorities that reflect the latest needs of the business and expectations of managers and teams.

Employees have expressed that the new approach gives them hope that they can now do what they love without sacrificing their personal lives. Before the implementation of this solution, some had said they were considering leaving their jobs. However, they now believe they can stay and continue to serve patients. Others shared anecdotes of how their daily lives have improved.

Going forward, the desire is to continue the shift away from heavy email traffic and more toward collaboration platforms like Microsoft Teams, to have days with shorter, less frequent and more effective meetings to enable employees to have a greater sense of ownership and trust.

The company’s bold experiment has demonstrated that an organization can achieve outstanding results by putting its people first, and the company is committed to deliberately driving this change going forward.

Can you be truly empowered at work? At this global biopharma company, the answer is yes.

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Accelerating Biotech Commercialization: Insights Ahead of the 2024 ISPE Biotechnology Conference

In the bustling city of Boston, amidst the vibrant biotech community, the 2024 ISPE Biotechnology Conference will gather industry leaders and innovators for a pivotal set of discussions on Track 4: Lifecycle Strategies for the Acceleration of Commercialization. This conference track will serve as a beacon of insight into methodologies and case studies aimed at expediting commercialization, reducing time-to-market, and navigating the intricate landscape of product lifecycle management for both Gen 1 and Gen 2 products.

Why is the commercialization of biopharmaceutical products still so slow?

The industry still needs a lot of experiments, technical expertise, time, and costs to define the right design space, hence how to properly the process control strategy to predictively ensure product quality.

Project teams are still encountering surprises when scaling up the commercialization process: the control strategy, which was defined in process characterization, did not hold its promise to cover scale-up effects.

Many organizations struggle with evidencing sound science-based chemistry, manufacturing, and controls (CMC) process understanding to file flexible operating ranges and holistic control strategies, because the relationship between inputs (process parameters and raw material attributes) and outputs (Key Performance Indicators and Critical Quality Attributes) is complex.

Companies still need fire brigades of subject matter experts to fight against out-of-specification results to find the root cause and save the batch, because data at not governed properly and knowledge is not extracted holistically from the data.

These components cover the main difficulties of commercialization, experienced during the product life cycle. So why this hassle? Basically, the industry must realize that it still faces missing data governance and low process understanding, while aiming for commercializing complex products and processes.

Which methods can help?

Organizations need more platform methodologies to solve the above-mentioned difficulties of commercialization. ISPE can play a central role in creating awareness through sessions provided in this track and finally help the industry to get faster to the market, streamline validation approaches, and achieve lower production costs.

This track will include very impactful contributions from reputed industry leaders.

In " API-Lean Tactic to Accelerate Process Commercialization ," Lenora Dieyi, representing GlaxoSmithKline (GSK), will provide a case study highlighting a methodology that will help with the evaluation and selection of new technology platforms. The goal of this methodology is to help organizations move toward the acceleration of technology transfer and the commercialization of a portfolio of similarly behaving products.

Miheala Simianu of SmartSkin Technologies will take the stage with a presentation titled, " Core Digital DP Knowledge and Speed to Commercialization ." Simianu’s discourse will emphasize the transformative potential of digital technologies in expediting the journey from development to commercialization.

Peter Blennerhassett, representing Blynksolve, will introduce attendees to a new concept during his presentation, " Unified Knowledge Space - A Novel Lifecycle Enabler ." Blennerhassett’s presentation will underscore the importance of integrating knowledge management systems throughout the product lifecycle.

Sebastian Scheler, of Innerspace GmbH, will delve into the realm of risk management with his presentation, " Autogenerated Risk Profiles to Accelerate Process Design ." Scheler's discourse will shed light on how data science and automated workflows can expedite the identification and mitigation of risks in process design.

Finally, Thomas Zahel, representing Körber Pharma Austria, will demonstrate how companies can accelerate commercialization while minimizing risks and costs, using end-to-end digital twins in a real-time context, allowing for real-time release.

The common denominator to accelerate commercialization

What do all those contributions have in common? They show novel approaches and use cases focusing on:

• How process simulation, modeling, and self-learning systems can reduce experimental efforts in process development and accelerate facility and operational readiness
• How to predict the success of technology transfer using holistic data management and data science tools
• How to provide a robust control strategy using end-to-end approaches and for integrated continuous biomanufacturing (ICB)
• How proactive lifecycle management planning can reduce development cycles and accelerate the introduction of the process into the commercial facility

The common denominator across these areas is data science. Executives must understand that the commercialization of biopharmaceuticals is a digital business. Furthermore, the digital aspects go beyond proper data housekeeping ensuring data integrity: teams need to leverage the value of data along the ISPE data maturity model .

Please join the ISPE community in attending the 2024 ISPE Biotechnology Conference to learn and contribute to good practices on how to accelerate commercialization, time-to-market, and progress through the product lifecycle. Get familiar with state-of-the-art digital enablers and digital twins to predict process outcomes and achieve a robust control strategy.

Exchange solutions for the final steps of the data maturity model, hence self-adapting capabilities, real-time architectures along AI, and automated workflows.

Why did the authors not write this blog post (other can the first paragraph) with ChatGPT? Because AI can only summarize and combine what has already been invented by human beings. As this track covers novel concepts and innovative ideas regarding product lifecycle strategies, only the conference’s interactive discussion between humans will advance them.

Please join ISPE and pave the future for successful and accelerated commercialization of novel drugs for patients.

Register Now!

Disclaimer:

In case it wasn’t evident, the authors used ChatGPT to author the above paragraph. The remainder of the blog was authored by their own grey matter.

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'Convergence' Key to Efficient Supply Chain Systems, Gartner Exec Says

"Bob" told his story of working for a fairly well-known retailer but one that was active in only one part of the country. He said his company recently had begun using Manhattan Associates' Point of Sale retail software, a relatively minor part of Manhattan's business compared to its transportation management and warehouse management systems, which are industry juggernauts.

So here he was at Momentum, a new Point of Sale customer for Manhattan Associates, but more importantly, part of the supply chain migration away from spreadsheets and other old applications and on to platforms that provide "convergence" — migrating key applications to a single platform to drive efficiency.

While Bob in his lunchtime chat at the conference here this week didn't use the word "convergence" the need for a system that could work smoothly with processes at his now larger company clearly met the definition of the term as laid out by Brock Johns.

In a presentation at Momentum about the state of transportation management, Johns talked about the levels of convergence.

Level 1 applications are basic solutions, such as key performance indicators (KPIs). But as a company moves up to Level 5 and the applications become more complex, convergence among the company's operations becomes possible through greater adoption of technology that in turn is increasingly complex itself.

The result, Johns said, illustrating the process with an arrow, is that while convergence between warehouse management systems and transportation management systems was possible in the past, it is now spreading to activities such as yard management systems that are converging with TMS and WMS. The last addition to the arrow was supply chain planning.

"Some of these things have come to fruition, and that's where we really start to see a lot of the benefits" Johns said, describing convergence as "bringing all these different parts of functional silos together." And it's happening, Johns said, because "we're seeing the technology architectures change."

The pace of change is "tremendous" he added. As convergence occurs, it raises the prospect of a more integrated planning approach to a company's supply chain.

But not everybody can do that. Companies that can use the convergence of various tools such as WMS and TMS are more "mature" according to Johns.

On a slide Johns presented, the goal of the convergence was spelled out: "Align the function of supply chain planning to supply chain execution." His presentation made it clear that he believes convergence is making that possible.

Getting people and systems to speak to each other

But the solution is not just technology, Johns said. Part of it comes in culture.

"How do we get the folks in other functional areas to come sit at the table?" he said. "How do we talk about shared data, shared information?"

A day earlier at Momentum, Bart De Muynck, a longtime independent supply chain consultant, spoke on a panel about supply chain execution and bringing in the disparate parts of a company's supply chain. One of the clients he described sounded like an example of the need to share data and processes that Johns discussed.

Without identifying the company, De Muynck said he and the company's executives realized that "to get more productivity out of our digital operations, we needed to get more visibility." The lack of visibility was most stark in the fact that orders for particular products, some of them with strong demand, would come down to the sales team with a lead time of "like a few days."

But the company's planners had information about likely demand for the product, and it wasn't shared. "The problem was the supply chain planning systems didn't talk to the TMS system" De Muynck said.

The fix wasn't easy. "We ended up building something, but it took us about two years" he said. "I'm not going to mention how many millions of dollars it cost us to build something in between the company's [enterprise resource planning] that connected the supply chain planning systems to the TMS. We finally got something, but imagine if you have these systems that talk to each other. You wouldn't have to go through all these challenges."

And that was one of the points of Johns' presentation about convergence: It is happening but not everywhere.

How big will AI be?

A day after Warren Barkley of Google spoke about the AI capabilities that can be brought to bear on supply chains, Johns brought AI into his presentation on what's brewing in transportation management.

He spelled out a few specific applications: using generative AI to create written content, such as drafting KPIs; writing standard operating procedure manuals; using chatbots (which Barkley also discussed); and summarizing meetings and communications.

But Johns was notably less boastful than Barkley about the prospects for AI in supply chain management.

He noted that AI is not just generative AI. Examples such as KPIs were "primary use cases." But he added, "You've got people in your organization and on your team that think GenAI is going to solve world hunger, and it will not."

"These are things that can help us do processes better. They can help us have a better user experience" Johns said. "There will be more use cases in logistics." But for now, Johns said, there may be value in "pumping the brakes."

The post ‘Convergence' key to efficient supply chain systems, Gartner exec says appeared first on FreightWaves .

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Port of Seattle Starts Work on 'Self-Sustaining' Maritime Innovation Center

A mock-up of the Port of Seattle's new Maritime Innovation Center. Photo: Port of Seattle

The Port of Seattle has broken ground on renovations for its Ship Supply Building , in a bid to transition it into an environmentally sustainable Maritime Innovation Center. 

According to a release from the port on May 21, the new facility be able to generate its own energy, capture its own water, and process its own waste. The original Ship Supply Building was built in 1914, and in its new iteration, it will house 15,000 square feet of work space for anchor tenants, incubators, and accelerators, as well as areas that can be reserved for meetings, seminars, and classes. 

“The future of the maritime industry and the ocean economy is innovative, sustainable, and equitable,” Port of Seattle commissioner Ryan Calkins said. “The Maritime Innovation Center will foster an atmosphere of collaboration and innovation which will ensure that all the sectors of the maritime industry, from commercial fishing to the growing green maritime economy, have not only a home but an anchor in Seattle.”

The project was first announced in August of 2023, and is expected to finish by the end of 2025 for $32.6 million. That's in addition to $100 million in investments from the port to maintain docks for commercial fishers and enhance other facilities in the area. 

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