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Digital Maturity and Barriers: Next Steps Toward Pharma 4.0™

By Thomas Lee Johnson, Manuela Gottschall, and Jens Solsbacher

Successful Pharma 4.0™ implementation is founded on digital maturity. However, implementing digitalization is not necessarily a straightforward process; there are several obstacles or barriers to achieving the digital maturity model needed for Pharma 4.0™. This article highlights typical barriers that might be faced on the journey to digital maturity and provides recommendations on how to tackle them.

The huge amount of data collected by manufacturing, quality control equipment, and quality systems offers an opportunity for Pharma 4.0™ implementation. Analyzing data from development through commercialization and postmarket life-cycle management takes continuous improvement of manufacturing and release processes to the next level. Analyzing all existing data and predicting potential risks will allow the industry to bring new products to the market faster and improve supply chain stability for products.

One lesson learned from the COVID-19 pandemic has been the importance of increasing digitalization across the pharma industry. In 2020, emerging digitalization concepts and pilot projects got a tremendous push as the “new ways of working” prompted by the pandemic revealed intensified challenges for the pharma industry. These challenges included managing paper documents, analyzing data, submitting filing documentation for new drugs, and using wearable technology for virtual factory acceptance.

Digital Maturity

Digitalization is best guided by a digital maturity model. This type of model is built by first assessing the state of an organization’s current digital operations and then defining a digital roadmap, including an action plan, and monitoring progress toward maturity.

The ISPE Pharma 4.0™ operating model illustrates one way to successfully implement digitalization and Industry 4.0 approaches in pharma organizations. The starting point for this model is the Industry 4.0 model from Acatech, RWTH Aachen, Germany, which defines six levels of maturity (see Figure 1). . The Pharma 4.0™ operating model defines four elements (work areas) of specific importance to the pharmaceutical industry: Resources, Information Systems, Organization and Processes, and Culture. To achieve digital maturity for Pharma 4.0, the maturity levels in these four areas must be increased simultaneously.

Figure 1: Stages in the Industrie 4.0 development path [1].

Barriers to Digital Maturity

Barriers to achieving the levels of digital maturity needed for Pharma 4.0™ can significantly slow or even disrupt the progress of Pharma 4.0™ implementation. They may exist in each element of the Pharma 4.0™ operating model, at each maturity level, and in each level of the organization (Figure 2). Identifying these barriers as early as possible on the journey to digital maturity helps the organization build strategies to prevent or address them.

Barriers may include a lack of visionary thinking by senior management or an organization’s failure to define a digitalization strategy. These obstacles may stem from stakeholders’ lack of trust in employees, processes, and systems. In some cases, 4.0 strategies are created, but they lack well-defined processes and systems, and therefore are not resilient enough to be executed. The lack of well-defined processes and systems can also diminish regulators’ trust in the organization’s efforts.

Figure 2: Main barriers to the different digital maturity levels.

Although figure 2 shows the barriers between maturity steps it’s important to highlight that they can block maturation also within a step. The barriers are also not exclusive to each step. Some of the more common barriers are explained in the following section utilizing anecdotes and listing recommendations on how they have been addressed.


[Computerization is using digital means to bring different information technologies used in isolation from each other. Acatech Study description of Maturity Step 1 – Computerization]

Misalignment may block the Maturity of Computerization in Organization in Pharma 4.0™ transformations by enabling conflicting behaviors within a single manufacturing division. Manufacturing Supply Chain leaders may not be able to computerize the precise chemical systems required for sustained, optimized digitalization without clear prioritization and consistent communication of that prioritization across the entire company.

In 2019, a Fortune 50 Supply Chain executive asked for strategic consultation on a crucial supply chain problem. Her chemical sourcing leaders wanted to digitally optimize the overall delivery time of crucial source chemicals to manufacturing sites around the globe and reduce the overall shipping cost by 20% per unit within 12 months. Her regional sourcing leaders wanted to computerize sourcing sites to reduce scarcity risk. Regional leaders resisted integrating their systems with the end-to-end optimization because they felt the dashboard of the system minimized scarcity risks. Both of her leaders were computerizing their resources however they were misaligned in prioritizing how their resources worked together. The intradepartmental struggles were about to impact delivery of her high revenue pharmaceuticals and perpetuate shipping cost stagnation where direct competitors were reducing inefficiencies by at least 5% per quarter. She wanted to know how to keep her supply chain healthy for current deliveries while simultaneously optimizing for future scenarios where scarcity could create major challenges.

Our recommendations to the executive were to:

  1. Consider creating clarity on what her overarching supply chain Pharma 4.0™ strategy priorities are.

  2. Attempt to consistently communicate priorities on a scheduled cadence and encourage subordinates to do the same.

  3. Consider using the prioritization conversation with her intradepartmental leaders as a moment to reset their priorities, integrate those priorities into the overarching strategy and strengthen their alignment as a team.

The executive assembled a working session in Los Angeles and encouraged all of her supply chain leaders to attend. At that meeting, they committed to a single source of integrated, supply chain telemetry and to wholeheartedly participate in the optimization campaign. After 1 quarter the executive noted that the dashboard measuring all of the bottlenecks and inefficiencies was capturing reduction of 4% in lead times and 5% reductions in cycle times. She was elated that the campaign was showing small gains so quickly.


Distrust may block the Maturity of Connectivity in Culture in Pharma 4.0™ transformations by employees undermining technologically advanced tools with bias toward only interacting with employees they trust and like. Organizational culture is shaped by employee’s thoughts, feelings and behaviors toward each other, stakeholders and customers. Employee behaviors in connectivity with each other seem to follow social constructs more than mandated processes.

In the Summer of 2020, a mid-sized Medical Technology manufacturer rolled out a new $10M robotics telematics tool that hospital staff could leverage to relay real time diagnostics on surgical robotics to the manufacturer to ensure optimal operations. The telematics tool, surgical robotics, and connectivity to the manufacturer worked flawlessly. However, the Senior Vice President for the Technology Division did not trust the Senior Vice President in the Business Operations Division to interpret the telematics to make decisions that would keep the surgical robots operating at peak effectiveness. He was afraid that pressing the robotics to overperform would increase the $750,000 / month maintenance costs for the robotics systems. He thought the operations leader was too ambitious and wanted to aggressively push more robotics into hospitals before their company had solid data on sustainable use. The technology employees were well aware of their technology leaders bias and so they routed all of the telematics through their own internal systems and gave business operations a trickle of actual data. The distrust in the culture between technology and operations was subverting the connectivity gains that were expected from the telematics tool investment.

Our recommendation to the CEO of that manufacturer was to:

  1. Consider assembling a working session between the key leaders of the technology and operations divisions.

  2. Perhaps have these teams work together to create a Surgical Robotics Maturity Model that takes objective input from the full telematics stream and from surgical staff and hospital administrators.

  3. If this team calibrates the growth opportunities for the robotics based on this Surgical Robotics Maturity Model then the path for growth can be objective and the culture of trust can be restored.

The SVP team did an offsite in Costa Rica and formulated a maturity model with a threshold for maintenance built into the model. All SVPs agreed to pursue new opportunities while minimizing the cost growth of the $750,000 / month maintenance costs to less than 3% per quarter so that profit margins always exceeded cost growth.

Weak Business objectives

Weak Business objectives may block the Maturity of Visibility in Resources in Pharma 4.0™ transformations by not getting investment needed to move the business further towards fully benefiting from digitalization.

Some years ago, a Pharmaceutical Company had the vision to transform the IT landscape and move towards digitalization. At the same time the environment began to change when blockbusters started to be replaced by niche products. This change forced that company to become more cost cognizant and prioritize investments where they bring most value for the company. During blockbuster times business objectives might not necessarily have been defined with cost in mind which led to difficulty in prioritizing projects and explaining why certain projects were funded and others not. In addition, projects that would have contributed to the business objectives but were submitted later in the year had to be deferred to the following year due to budget constraints. Frustration and lack of employee’s commitment was the result.

One example to illustrate what a delay in implementing projects related to Pharma 4.0™ is transforming manual documentation to digital. A successful implementation will enable data-driven decision making utilizing the data collected. Improved data analysis can be very helpful in preventing drug shortages due to quality defects in manufacturing and control processes. Analyzing digitally available deviation records, for example, might reveal themes of potential failures and risks that could be identified and mitigated before they occur and will help to making the supply chain more sustainable. Data integrity and maintaining access to systems becomes a bigger challenge when moving from manual to digital documentation.

Recommendations to the senior leaders were:

  1. Consider defining business objectives with focus on cost and communicate them to the organization regularly and explaining the ‘Why’.

  2. Consider asking project leads to re-submit project proposal if the business case did not indicate how the project contributed to the business objectives in a measurable way. Additionally, being consequent in applying these behaviors to all new project proposals was highly recommended.

  3. Consider stopping projects that do not contribute to the business objectives. If employees see activities that add no value being stopped engagement and commitment increase. Many times, this is easier said than done.

The manager of that organization started requesting better business cases when information on benefit of the project was not clear enough.

Low Respect

Low Respect may block the Maturity of Transparency in Culture in Pharma 4.0™ transformations by not being aware of employee’s angst in trusting a computer.

In 2020, a project team working on upgrading a quality management system discussed the utilization of a translation software to allow employees in different manufacturing sites around the globe to enter e.g., discrepancies, change control, CAPA, records in their local language only instead of documenting them in English additionally. In a few cases the documentation in English was not done properly which made a cross-site collaboration and best practice sharing more difficult. In such cases, employees translated the examples they wanted to share with the network themselves utilizing publicly available translation software to provide a rough idea about the topic which could take up to 15min per record When the idea came up to incorporate a translation software in the quality management system that translates all records into English automatically, in addition to the local language, a huge debate started about who should review and approve the translation. Knowing that the translation might not be 100% accurate led to a huge resistance of the employees based on lack of trust in the computer. Ultimately, the translation software was not implemented. The aspect the project team did not anticipate was the amount of angst the employees had that the computer takes over certain activities. Lack of understanding employee’s feelings and ultimately low respect for the employees prevented implementing a solution that could have simplified certain day-to-day tasks significantly.

Recommendations to the project team were:

  1. Consider involving the employees early in the project by performing Gemba walks and collecting Voice of the Customer feedback.

  2. If the employees had been given the opportunity to understand that when they translate records utilizing a translation software on their own the result is not more accurate compared to the software that would have been built into the system, the implementation could have been a success.

  3. Consider establishing a robust organizational change management program as early as possible for projects.

Change management programs have been integrated for bigger projects at least. Implementing them in smaller projects is work in progress.


Inflexibility may block the Maturity of Adaptability to provider, patient or market expectations for organizations. Adaptability requires responsive organizations and processes that are willing to shift from unyielding structures to more dynamic practices. Investments in streamlined automation do not always return on expectations if there are uncompromising processes in place.

A manager for a Fortune 500 medical device manufacturer demanded a rigid, extensive department meeting cadence and exhaustive progress reporting framework remain in place despite company-wide Product Life Cycle automation, that gave near real-time reporting, being in place for a year. Her team complained that the weekly, four-hour meetings and the extensive reporting was monopolizing upwards of 45% of their work hours and they were less capable of innovating on the market adaptive, patient-centric medical devices that their director had requested. When the director confronted the manager about her inflexibility she pointed to her high-performance metrics on compliance and revenue predictability for all of her medical device products. Her group produced the most predictable revenue year over year for the company. The director noted that was true, however she had not contained $100,000s cost growth, nor brought any new device features, patient-centric revisions, or provider-centric efficiencies to market in years.

Our recommendation to the director was to:

  1. Consider giving the manager and her entire department a few tours of other areas that are fully leveraging the Product Life Cycle automation, meet less often and work more efficiently.

  2. Perhaps analyze the alignment of the entire organizations' annual performance appraisal and financial incentives. Possible considerations for updated to incentive measures include: expectations to deliver improvements across compliance, reduce cost growth, profit growth, provider-centric measures, patient-centric measures and new feature market performance.

The manager and her team toured other sites that were using fully automated Product Life Cycle management tools and made a major discovery: less meetings = more productivity! The manager recalibrated their meeting cadence and duration down to biweekly, 2 hour meetings. She felt she could confidently utilize the automated near real-time reporting more proficiently with the additional training her director gave her.


Digital maturity is an enabler for Pharma 4.0™ and includes an assessment that is performed regularly during the journey of implementing Pharma 4.0™. Identifying barriers early and defining mitigation actions is as important as assessing the maturity level of an organization’s digital operations. The focus area for the ‘Impact & Maturity’ sub group of ISPE’s Special Interest Group Pharma 4.0™, is collaborating with the other sub groups in determining how digital maturity, and identifying barriers can be utilized.

Analysis of Barriers

Figure 3 provides key findings from the survey, followed by result details that can offer recommendations for future action. Looking into some of the results in more detail allows driving recommendations from conclusions and insights.

Predictive Analysis finds a high correlation between low sense of purpose among employees and weak business objectives for Industry 4.0 initiatives. There is a similar correlation between high sense of purpose among employees and strong business objectives.

Predictive Analysis finds a high correlation between low sense of psychological safety among employees and feeling marginalized away from Industry 4.0 initiatives. There is a similar correlation between psychological safety among employees and engagement.

Predictive Analysis finds a high correlation between low respect among employees and weak collaboration for Industry 4.0 initiatives. There is a similar correlation between high sense of respect among employees and strong collaboration.

Figure 3: Survey results indicating barriers to digital maturity.

Predictive Analysis finds a high correlation between limited alignment among employees and leaders and common data standards. There is a similar correlation between full alignment among employees and leaders and common data standards.



1. Günther Schuh, et al. (eds.). Industrie 4.0 Maturity Index, Managing the Digital Transformation of Companies, Update 2020, RWTH Aachen University. page 18.

About the authors

Thomas Lee Johnson

Manuela Gottschall

Jens Solsbacher


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