By Dan Jacob
Life Sciences companies are attempting to improve compliance and manufacturing efficiency while they drive to grow revenue and margins. However, current market conditions are creating substantial headwinds to attaining these targets. Some of these headwinds originate with regulators, both because of increasingly complex global regulation and regulatory oversight, as well as recent FDA expectations that industry shift from a compliance view to an “organizational excellence” view.
Other headwinds come from industry itself. Mergers and acquisitions create operational and organizational fragmentation, fear of regulatory action creates an excessive focus on compliance, and underinvestment in process automation places an undue burden on practitioners. This reduces the time and attention to quality’s role in operational performance, financial performance, and corporate success.
Life Science manufacturers looking to achieve their objectives as well as differentiation with customers, and investors must recalibrate. Successful manufacturers will plot a journey from conformance to performance by merging the objectives, cultures, processes, and technologies between quality and manufacturing. Few do this successfully; in fact, today only 16% integrate Enterprise Quality Management Software (EQMS) to Manufacturing Operations Management (MOM) systems. However, those that take the actions prescribed in this paper achieve a median of 10% higher On Time Delivery and 21% higher successful New Product Introductions (NPI).
Read on to understand strategies, frameworks and recommendations from across LNS’s Quality and Manufacturing Operations practices, including:
Life science companies must increase focus on outcomes while complying with increasingly demanding compliance requirements. This requires a new path that improves maturity, merges teams, processes, and technologies, and expands the participation and focus of quality to cross-functional and executive teams.
Over 1,200 executives and other senior leaders coming from a variety of company sizes and geographies across a range of industries have completed the LNS Research Quality Management Survey. The survey questions drill down into the challenges and opportunities that companies face, strategic objectives data, and the most important goals currently being pursued around quality.
There are 54.3% of companies from Discrete Manufacturing industries, with the remainder coming from Batch and Process Manufacturing. A total of 28.5% is in Pharmaceutical, Medical Device, and Biotech manufacturing. Just over half are from North America, followed by just under a quarter from Europe. Almost half, 46.8%, are from small companies, with 38.0% from large companies, and the remainder from mid-sized companies.
Life Science Industry Trends
It is no secret that Life Science manufacturers have substantial compliance challenges, or that the compliance is increasing, regularly changing, and growing in complexity. This is most keenly felt by those that are delivering products in multiple markets. Although efforts such as Identification of Medicinal Products (IDMP) has resulted in some degree of harmonization, and regulators are conscientiously attempting to harmonize Unique Device Identifier (UDI) requirements, there are many variations across regulatory bodies regarding processes, data, and submissions.
Add to this complexity increased oversight. Regulators are inspecting on an increasingly global scale as well, with the FDA tripling its focus on international manufacturers between 2008 and 2015.
As a result, compliance dominates the focus of quality and operations. LNS data shows that the top industry-trend categories in life sciences are regulatory requirements for quality management and serialization and traceability, as reported by 67% and 52% of 747 respondents, respectively. The top strategic objective for quality is far and away to ensure compliance (36%, N=197). This is also true with life science manufacturing operations, which are much more focused on compliance (27%, N=628), versus all others (13%, N=3278).
While understandable, this excessive focus on compliance is a roadblock to performance. This can be seen in quality, manufacturing, and even in Time to Market. Quality management issues are the top issue in speeding products from R&D to the market (51%, N=753).
Balance is needed to improve business and patient outcomes. Compliance is still crucial, but it is necessary to rebalance priorities, increasing the focus on quality improvement and good quality practices. What concrete steps should life science manufacturers take to improve performance?
Quality Maturity and Performance
When deciding to alter course, it is useful to compare performance with others that have already taken the journey. LNS has found the concept of maturity to be valuable in these situations and has generated a fully benchmarked maturity model.
The maturity model is an “Operational Excellence” maturity model, which means that it assesses people, technology, and process capability. This is an important distinction, as many models are based on process maturity only. Culture, competency, and leadership are critical to quality, as is technology’s role in automation, insights, and collaboration. Further information on this topic can be found in numerous LNS research articles.
Maturity increases as manufacturers expand the scope of their quality operations and express the value of quality in metrics that are increasingly relevant to their peers and top management team. These correlations are highly relevant. Quality often struggles to gain the top management priority needed to drive improved maturity, and quality teams need to recast their value in terms of operational and financial performance rather than in siloed benefits for the department.
Maturity is quantifiable, and increases as more people, process, and technology best practices are adopted. LNS aligns adoption of best practices to maturity by identifying the number of best practices adopted per manufacturer and then divides the market into quintiles based on a number of best practices adopted. Therefore, the least mature (L1) quintile currently has adopted between zero and two best practices, then between three and six, and so on. Based on the quantitative model, the market is currently immature, with a long tail at L5.
However, maturity is very important to the market. In fact, it drives substantial operational and financial performance. For instance, the median Overall Equipment Effectiveness increases from 60-75% between L1 and L5, which can often be correlated to revenue. Median New Product Introduction success also increases, and median Cost of Poor Quality (CoPQ) decreases significantly. Every percent reduced from CoPQ adds a percent to operating margin. Given that the average operating margin of the S&P500 is 12.65%, a 4% reduction in CoPQ results in a net increase to operating margin of 32%.
Quality has a substantial impact on operational, financial, and innovation success. This can be difficult to recognize at a low maturity organization, but a quantified maturity-based view makes this correlation obvious. Quality must increase its maturity by adopting more people, process, and technology best practices, and shift from being a cost/compliance center to a value center. This shift occurs as an organization develops its culture of quality, continuity of processes and teams across the lifecycle, and adopts technology that reduces the compliance burden and refocuses quality on improvement, brand, and customer satisfaction.
The maturity journey is the path to performance. The following sections further detail the state of the market and identify initial priorities for life science manufacturing looking to progress on this journey.
The Life Science Manufacturer’s Path to Performance
Changing course starts with leadership and objectives. The objectives for quality explain what quality means to a manufacturer, and guides the adoption of quality practices. As discussed earlier, life science manufacturers are much more focused on ensuring compliance than the market at large. These objectives result in behavior and best practice adoption that are measurably different than those focused on performance.
A snapshot of the top five most adopted practices tells a compelling story. As can be seen, manufacturers with compliance objectives have slightly higher adoption of compliance and oversight practices as compared to those with performance objectives.
Manufacturers with performance objectives have much higher adoption of cross-functional and evidence-based decision-making practices.
The actions of the performance-centric manufacturers can be isolated into three important differences. Those focused on performance had high adoption of:
Leadership needs to reset their quality objectives to drive value via a cross-functional quality approach that more effectively connects management processes with operations, and leverages cross-functional quality analytics to improve decision-making.
Understanding the Connection between Quality Management and Operations
Connecting R&D, quality management, and operations is critical to achieving value-centered quality objectives. Quality teams have long struggled with the connection between quality management and quality execution. In many organizations, quality is inadequately engaged early in the NPI process, resulting in poor design transfer. Operational Technology (OT) such as Manufacturing Execution Systems (MES), Process Analytical Technology (PAT), and other data from the shop floor are often disconnected from quality management processes such as corrective actions. This is partially due to the relatively low adoption of Enterprise Quality Management Software (EQMS).
To help understand this connection, let us review the ISA-95 model. ISA-95 provides a cross-industry view of OT and Information Technology (IT) processes. This temporal view of processes includes the connection from physical machines to controllers to Manufacturing Operations Management (MOM) systems to business operations. Each of these levels should communicate bidirectionally with adjacent levels, although in practice there are often substantial disconnects between L3 and L4, as L3 and below are OT, and L4 is IT.
This connection between Level 3 and Level 4 is the missing link for quality. In the image below, LNS has illustrated the connection between these levels and added a quality overlay to provide a perspective that illustrates the handoffs between quality management processes, operations management, and quality execution. It also extends the ISA-95 model across the value chain, because quality must communicate across the lifecycle. While some processes are firmly entrenched in the IT or OT world, leaders should focus on those shared processes and analytics that enable collaboration.
Recent advances in connectivity, including connected and edge devices, enable insights from individual devices and machines as well as Machine Learning/Artificial Intelligence (ML/AI). These are captured at Level 2 in the model and have broad applicability to life sciences. The reader is encouraged to reference other LNS research regarding Digital Transformation, Industry 4.0, and the Industrial Internet of Things (IIoT) to gain further insights on these developments.
How does this IT/OT convergence occur in practice? LNS typically recommends that organizations adopt a role-based data mastery approach when connecting IT and OT processes. For instance, the Non-Conformance (NC) process is an overlap area between MOM and EQMS. Given that many NC's are generated by manufacturing quality personnel in the context of other MOM data including Inspections, there is value in Mastering NC's from within MOM.
However, manufacturing NC data is also critical to corporate quality, quality reporting, connections to CAPAs, and regulatory requirements, and manufacturing NC's are not the only types of quality NC's. This means that a MOM system is not likely an effective data master for the entire NC process. Therefore, it may be determined that although manufacturing NC's are initiated from within MOM, at some point in the NC workflow the EQMS system becomes the “system of record;” the data master. Decisions regarding when to transition data mastery is individualized and should weigh EQMS and MOM system capabilities and deployment landscape as well as the user roles and use scenarios.
First Steps on the New Path for Performance
The above guidance regarding maturity, objectives, and IT/OT quality connection identifies the new path for performance, LNS has also identified six best practices that life science manufacturers should adopt along the path. The targeted best practices are aligned with the earlier discussion and are highly correlated with improved performance.
As can be seen from data below, these practices were adopted at much higher levels by more mature organizations, delivering substantial operational efficiencies to these more mature organizations. For instance, the median Level Five maturity organization had adopted 62% of the best practices whereas Level One had adopted a median of 0%.
Those that adopted the six best practices achieved a median of 100% On Time Delivery (OTD), as compared to a 90% median OTD for All Others. OTD is an important operational metric that factors into supplier scorecards and therefore, supplier selection. A supplier with 100% OTD and no large outstanding supplier quality issues is typically a preferred supplier. Typically, a supplier with 90% OTD is not a preferred supplier, although the significance of 90% varies by customer.
Similarly, there is a substantial impact on successful New Product Introductions. Those that adopted the six best practices have a median of 95% successful NPI, whereas the median of all others is 74%. This is a substantial performance impact, as successful NPIs are often aligned with improved revenue. LNS’s criteria for a successful NPI is a new product that meets quality, volume, and time targets.
Life science manufacturers have understandably focused their quality efforts around the complex and evolving world of global regulatory compliance. However, those looking to realize improve corporate operational and financial performance need to chart a new path to performance. The new path to performance begins by redefining objectives and assessing current maturity. It continues by understanding how to effectively connect quality management and operations, and assessing current adoption of identified best practices. Leaders should then build a strategy to adopt the best practices and measure important metrics in the current as-is state. Finally, deploy the best practices and quantify success, using the quantified success to fuel further maturation.
Leaders must define what quality means to them. Is quality a cross-functional pursuit of continuous improvement, strong brands, and customer satisfaction? Or is quality primarily a regulatory compliance organization? We have learned that the former far outstrip the performance of the latter. We have also learned that quality, its objectives, and the best practices it chooses to emphasize, is very important to corporate success. The first step on the path is re-assessing objectives. What should yours be?