Life sciences technology insights: Scaling a product and platform model

The leaders of life sciences companies no longer debate the value of digital technologies and analytics, but rather how best to unleash their full potential within their organizations, and how fast.

Many life sciences companies are adopting a product and platform operating model as a solution. Here, teams of business and technology specialists work together to both develop the products used by customers, patients, and employees and maintain the platforms that support them—all with a relentless business focus that prioritizes work based on its value to those end users.

Companies that have scaled successfully have already realized significant value. A McKinsey survey of more than 50 life sciences product and platform teams found that the model improved customer satisfaction scores by an average of 15 percent and increased speed of delivery by 20 percent. In addition, employee satisfaction rose by 20 percent. Despite this, relatively few companies have successfully implemented the new model at scale across business units, regions, and technologies within their organizations.

McKinsey research suggests that through six actions, companies can achieve scale and realize the full value of the model.

1. Integrate the business as an equal partner

The product and platform operating model hinges on technology and business leaders operating as “one team,” which means a transition to the new model is commonly sponsored by both technology and business executives. However, it is often technology leaders who go on to lead the transition. And while these leaders may well have the clout and connections to pull in business partners when launching pilots, delivering effective technology business collaboration, as the model is extended to dozens of teams across the company, can prove much more challenging. Two mechanisms can help: ensuring that business partners are part of product and platform teams and that every component of the product development cycle is driven by business and end-user needs.

Organize around user experiences not technology applications. Technology leaders often default to organizing teams around technology applications, with separate teams working on websites or mobile applications, for example. But to keep the business focus, it is better to organize the technology portfolio around end-to-end user experiences—that is, into groups of related products that support a user experience, such as patient experience management or clinical operations. Work on products within the group can then be coordinated to deliver on a common mission and user experience. Work on platforms that either serve product groups or the entire enterprise is also coordinated.

The case of one pharmaceutical company illustrates this point. It wanted to accelerate patient access to medicines, but because teams were organized around different digital engagement technologies (for example, mobile, live chat, chatbot, website, social-media integration, and data analytics), they were effectively siloed, which meant the overall user experience became disconnected between the different engagement channels. Moreover, multiple handoffs between teams that were pursuing the same goal added coordination time, slowing the delivery of improvements to patients.

A move to a product and platform operating model that grouped all patient experience technologies into a single product group with its own product, technical, and design leaders made a significant difference. The end-to-end patient experience became cohesive, and the average time to market fell by 30 percent.

Exhibit 1 illustrates how one company reorganized its technology portfolio around the business capabilities needed to support a range of customer experiences.

Organizing the technology portfolio around the end-user experience helps life sciences companies keep a user focus.

Integrate business partners as team members within each product team. Companies that have successfully deployed a product and platform operating model at scale often either appoint a business partner as the product manager or have a business product manager work alongside the technology product manager within each product team, with roles and governance mechanisms clearly defined. The two should be jointly responsible for defining the product strategy and delivering the product, including developing the product vision, objectives and key results, prioritization processes, and product road map. However, the business product manager should also help drive demand intake and prioritization processes to review the value of new work items on the schedule, while also engaging in product demos to provide regular feedback from a business perspective.

Unless business partners are the appointed, dedicated product managers, they will want to clearly understand the level of commitment required. One business product manager spent as much as 20 percent of their time working with a team led by a technology product manager to develop an e-commerce website for a medical technology company. The result was worth the effort: a clear prioritization of work that took account of both business and technology considerations and a far-better work environment, thanks to regular feedback. Previously, technology teams were accustomed to either waiting for input from business teams, which delayed delivery, or proceeding alone only to be told later that certain features failed to meet business needs.

2. Build momentum organically then scale with rigor

Many companies run successful pilots then seek to replicate that success by running still more pilots. This is not the same as adopting the new model at scale. While it makes sense to build early momentum by establishing pilots in parts of the organization where there is enthusiasm for doing so, enthusiasm alone won’t support company-wide adoption. Moreover, pilots tend not to conform to a single way of doing things, which means the organization can find itself stuck in pilot purgatory, with many different and often suboptimal versions of the new model. The following measures can help rapidly scale the new model in a consistent fashion.

Form a core team to drive model adoption. The planning and implementation of a transition to a product and platform operating model is no small endeavor and one that needs careful coordination. Countless decisions will need to be made, such as choosing which products to transition when and how to staff those teams; establishing change and communication plans; and determining metrics for tracking and reporting. Setting up a core, dedicated, cross-functional team responsible for all this and more can greatly speed up adoption, particularly if it uses an agile approach to implement transition goals.

Understand which products can transition together. The order in which you choose to transition products to the new model can impact the ease and speed of the effort. Some organizations choose to prioritize those that are ready in terms of staffing and funding, and that have the highest strategic importance. Others mobilize all products within an end-user experience simultaneously. Both approaches can work. But what is important is that interdependent products with a similar vision are transitioned together—for example, all products that support patient engagement across multiple channels. In this way, transitioning teams and other employees will not have to operate in both old and new ways when working on interdependent products. Moreover, governance mechanisms like quarterly business reviews can be installed to consistently carry out prioritization and dependency management across interdependent teams.

One global pharmaceutical transitioned 40 product teams to the new model in just three months by focusing on interdependent products that had the most strategic value and that were well equipped for the transition. This approach proved to be four times faster than the previous method of transitioning individual product teams.

Develop reusable assets. Pilots need extensive, dedicated support—product management coaches, boot camps that teach the fundamentals of the product and platform operating model, and the time and attention of leadership, for example. But no company is likely to have enough resources to rapidly extend the model with such a high level of dedicated support. Implementation could take years. The solution is off-the-shelf self-learning modules that teach the principles of the model, supplemented with repeatable capability-building programs such as product management academies.

One organization developed an interactive online course covering the taxonomy, principles, and practices of the model that each team adopting it had to complete before working with coaches to develop a product management tool kit. Another organization had the new model operating at scale within 12 months by launching a capability-building program for group product managers who then became responsible for implementing the model within their product groups.

Clearly define success by linking it to value and measure relentlessly. Companies may be wary of the value of switching to a new operating model. But this can be addressed by clearly stating the expected outcomes and establishing a value framework that gauges whether those outcomes have been met. One pharmaceutical organization developed a framework with five key measures of success for its program—team defragmentation, work throughput, team health, business satisfaction, and user satisfaction. Each team adopting the new model was required to track and report these measures, helping leaders to spot emerging issues early without having to dedicate the same level of focus and attention as a pilot, but also to demonstrate the power of the new operating model.

3. Support the operating model with organizational changes

Product and platform model transformations must initially focus on the operating model, not the organization. However, at the right time, companies will likely need to make some organizational changes if they are to realize the full value of the product and platform operating model. Two organizational changes are key.

Centralize platforms. As they grow, large organizations often duplicate technology platforms across the business, deploying different vendor solutions to fulfill the same requirements in different parts of the organization. This leads to the unnecessary duplication of work and resources. The transition to a new operating model is an opportunity to tackle this duplication by consolidating platforms with a common purpose into enterprise platforms governed by a single strategy.

One life sciences company had five different business units, each developing its own version of a customer relationship management platform. Consolidating these units into a single enterprise platform with inputs from each eliminated roughly half of all duplication.

Align talent to knowledge disciplines. Distinctive products and platforms need distinctive talent, which can be hard to cultivate in organizations where performance management and reporting lines tend not to accommodate those with specialist skills. A product manager might not appreciate the development needs of a user interface (UI) designer who reports to her, for example. An alternative is to organize employees by discipline. Then when employees report into their discipline, led by a discipline lead, for expertise development and career growth, they get day-to-day direction on priorities from product managers. For example, the UI designer would belong to a design discipline and report to a senior designer who serves as the discipline lead, while a solution architect might belong to and report into an architecture discipline. One pharmaceutical organization grouped skill sets common to all businesses—front-end engineering, scrum masters, and robotic-process-automation engineers—into enterprise-wide disciplines, while keeping specialist skills—R&D engineering, for example—within business unit disciplines.

This kind of structure helps to foster a sense of community within each discipline, maintain consistent standards across teams, ensure appropriate learning and growth opportunities are available to all, and direct resources to the highest-priority work. All are critical if a product and platform model is to operate well at scale.

4. Build talent and capabilities internally

Talent is the engine that drives the product and platform operating model, which means companies should consider a comprehensive talent strategy to equip themselves with the necessary capabilities. Exhibit 2 shows where gaps may exist. Demand for some capabilities, such as engineering and data and analytics, will probably remain stable in the new model, so they can be met by existing employees. But some roles, such as product managers, represent new capabilities.

Outsourcing or partnering with vendors could be part of the solution to acquire these capabilities. But if the model is to be scaled and sustained, hiring new talent and investing in upskilling the current workforce, rather than relying heavily on external contractors, as is the case today, will also be important. This is particularly true for product management capabilities, as they are the linchpin of the model at every level. Group product managers oversee all related technology products that build distinct capabilities for a customer experience, while product managers do the same at the individual-product level. People currently holding roles not central to the new model—project managers, client leaders, and business analysts—can potentially be upskilled to fill product management roles.

Roles and capabilities can evolve within a product and platform operating model.

One biopharmaceutical company was keen to build its own product management capabilities not only because it realized just how extensively they would be needed, but also because it was concerned the company might end up with the same digital capabilities as others in the industry if it used the same vendors to build them.

5. Integrate enabling functions to realize end-to-end benefits

To broaden its potential, an at-scale product and platform operating model should not only integrate business and technology teams but also functions such as risk management, compliance, and cybersecurity.

Take compliance, for example. The compliance function within a life sciences organization typically works independently, testing software handed off from the technology team. Embedding compliance analysts in teams to ensure good-practice requirements are met at every stage of the product development life cycle can speed up the process. But the team is still left relying on a single person to conduct the work. It is far better, therefore, to automate low-risk compliance processes and train product team members to conduct others. Risk and cybersecurity work can be integrated similarly.

It will be important for each product and platform team to also deploy DevSecOps (development, security, and operations) practices, such as test automation, real-time monitoring, and automated code deployment to improve speed to production and the quality of outcomes.

One large North American medical technology organization accelerated delivery by 15 percent and improved team health by 10 percent by adopting the product and platform model. But it then went on to reduce testing time by 50 percent and improve team health by a further 20 percent by reducing silos between the compliance function and the delivery teams, as colleagues were able to dedicate more time to value-added tasks instead of manual validations.

6. Adopt a holistic, long-term funding model

Companies should consider adapting the way they fund products if the new operating model is to deliver its full-potential value.

Commit to long-term, but still performance-driven, funding. Current budgeting processes in life sciences organizations are typically geared toward funding digital projects for a fixed but relatively short period of time—a 12-month project to install the next-generation manufacturing execution system, for example. Yet product and platform teams will likely require funding for several years, as the goal is not simply to build or deploy a solution but also to continuously improve it to meet evolving user needs. A commitment to long-term funding does not mean open-ended commitment, however. By adopting a product-focused funding model, the periodic release of funds can be tied to performance outcomes that are gauged through quarterly business reviews.

Fund the whole product—not just new features. Product and platform teams often find themselves under pressure from business units to develop new features, faster—particularly for enterprise products that are used by multiple business units. Funding, therefore, tends to prioritize new features at the expense of other important activities, such as responding to user feedback on existing features, resolving technology debt, and experimenting with innovative features. When scaling the product and platform model, it is imperative that teams are funded to deliver on the product holistically and that goal-setting frameworks reflect this.

The six actions described here are key to scaling and realizing the full benefits of a product and platform operating model. Some of them entail significant change, but the return is worth the investment. With a test-and-learn mindset that seeks to make continuous improvements, companies can incorporate the changes at the speed that best suits them on their journeys to achieving digital excellence.

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