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From war rooms to launch rooms: how AI is changing the game

Within3’s Jason Smith explores how artificial intelligence is breathing new life into next-generation launch situation rooms; delivering actionable insights for pharmaceutical companies.

A doctor holding a glowing digital interface with medical and AI icons, symbolizing the integration of artificial intelligence and real-time data in modern healthcare and pharmaceutical innovation.

The problem: launch rooms that don’t deliver

Pharmaceutical launches have never been more complex. With development costs now exceeding $2 billion per asset, heightened payer scrutiny and narrower launch windows, the stakes for getting commercialisation right are immense.¹ Yet, despite years of experimentation with launch situation rooms (LSRs), many organisations still struggle to detect risks early, make confident decisions or accelerate uptake.

In principle, launch rooms should help. As cross-functional hubs to monitor performance and facilitate rapid decision-making, launch rooms were intended to provide agility in high-pressure environments. In practice however, too many devolved into static dashboards filled with backward-looking KPIs, monthly reports and bureaucratic processes that provided little real advantage.²

The result is that instead of helping teams see around corners, these first-generation rooms often added reporting burden while failing to prevent missteps that slowed adoption or blunted momentum.²

 

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How we got here: first-generation shortcomings

Why did so many launch rooms underperform? Several common pitfalls stand out:²

  • Late activation. Many were established just three to six months prior to launch, leaving little time to align teams or refine decision-making processes. Best practice suggests starting at least a year in advance while products are still in late-stage trials.
  • Superficial setup. Too often, the emphasis was on organisational charts, office layouts or screen installations, rather than re-engineering workflows. Without changes to how teams worked, the launch room became an ‘empty shell.’
  • Mistrust in data. Siloed systems produced competing dashboards. Teams duplicated analyses, questioned validity and argued over whose numbers to believe, thereby undermining insight confidence.
  • Lack of decision rights. Without clear empowerment, rooms functioned as ‘control towers’ that collected data but could not act on it. Critical issues still required escalation through slow hierarchies.
  • Static KPIs. Reliance on fixed, backward-looking metrics created false security while missing early warning signs, such as slower-than-expected physician adoption, early payer pushback, or unanticipated competitive activity.

Each of these issues shares a root cause: the belief that setting up a launch room, without transforming underlying data, culture and governance, was itself enough to improve outcomes. In reality, the launch room is only as effective as the systems and behaviours it supports. Without unified information flows, empowered decision rights and a culture of accountability, even the most sophisticated setup cannot deliver the intended impact.

 

A launch room is a cross-functional command centre where teams monitor a new product launch in real time, using data and collaboration to make fast, informed decisions and drive successful market entry.

A launch room is a cross-functional command centre where teams monitor a new product launch in real time, using data and collaboration to make fast, informed decisions and drive successful market entry. Image credit: Shutterstock / Bishop Iuliia

Solution: the next-generation model

The shortcomings of early LSRs do not mean the model is flawed. On the contrary, when implemented thoughtfully, next-generation launch rooms can become strategic command centres that not only guide launches but accelerate organisational transformation.³ Three defining features distinguish this new model.

Real-time, AI-driven insights

Next-generation rooms break free from static metrics by integrating real-time data across multiple sources, including claims, electronic medical records (EMRs), customer relationship management (CRM) feeds and social sentiment. AI and machine learning are applied to detect emerging trends, model scenarios and recommend “next best actions.”³

The lesson is clear: when data is unified and analysed in real time, launch teams can anticipate market dynamics rather than react after the fact.

Examples from the industry illustrate how this shift is already being applied in practice. One top-10 global pharmaceutical company launching an oncology therapy used EMR data to support regulatory approval in a new patient population. By combining EMR and prescription data with internal CRM records, the team identified treatment patterns that doubled the number of high-potential physicians reached within the first two years of launch.⁴ Another top-10 global pharmaceutical company, supporting a diabetes therapy in a highly competitive market, applied real-world evidence to demonstrate comparative effectiveness. Using AI-driven segmentation to reallocate 30–40 percent of sales calls towards physicians most likely to drive growth, the company achieved a 60 percent increase in new prescriptions.⁶

The lesson is clear: when data is unified and analysed in real time, launch teams can anticipate market dynamics rather than react after the fact. This shift represents a fundamental pivot from reactive firefighting to proactive opportunity-shaping. Instead of scrambling to explain lagging results, teams can identify signals early, test adjustments and enter the market with confidence that their strategy is one step ahead.

Cross-functional agility

Of equal importance is how teams work once the data is available. Next-gen launch rooms borrow heavily from agile practices, including daily standups, sprint cycles and empowered cross-functional squads.⁵

This setup reduces bureaucratic handoffs, encourages rapid experimentation and ensures issues are addressed immediately. In one case, a pharmaceutical company revitalised a struggling launch by implementing agile practices in its launch room. Meeting time dropped by 35 percent, VP-level leaders participated directly in problem-solving and within three months the team had recovered from a delayed schedule.²

Agility ensures that insights do not languish in reports but translate into action.

Human-centred design

Finally, effective launch rooms are designed for the humans who use them. Applying design-thinking principles, leading organisations map user journeys, identify pain points and build dashboards that are intuitive under pressure.⁴

One approach is to design a dashboard that allows even non-analysts to drill down from global launch performance to individual prescriber behaviour.⁸ Another effective practice is to integrate patient-share metrics with healthcare professional (HCP) behaviour, updated in near real time, alongside AI-driven recommendations for next steps.¹⁰ By focusing on usability, these rooms ensure insights are adopted, not bypassed.

The promise and the pitfalls

When done well, the benefits of next-generation launch rooms are substantial. Teams can make decisions in minutes rather than months, accelerate market uptake through intelligent targeting, and strengthen cross-functional alignment and ownership. These environments also improve job satisfaction by empowering staff to act with greater confidence and clarity.⁵ Additional evidence shows that well-designed launch rooms increase staff engagement and sense of ownership.¹¹

Teams can make decisions in minutes rather than months, accelerate market uptake through intelligent targeting, and strengthen cross-functional alignment and ownership. 

Yet pitfalls remain. Cultural resistance, data limitations and unclear governance can still derail even well-designed rooms.⁷ Timing is critical, as launch rooms that are stood up late in the cycle rarely reach their full potential.⁸

Sustaining new ways of working is equally challenging, with teams often reverting back to ‘business as usual’ when the intensity of launch passes.¹¹ Recognising these realities is essential. A launch room is not a golden ticket but a platform that requires careful preparation, executive sponsorship and ongoing stewardship.

A pragmatic roadmap for leaders

So what should leaders do now if they plan to build or upgrade their launch rooms? Five steps stand out.

The first is to start early. Planning at least 12 months ahead of launch gives organisations time to align teams, define metrics and rehearse decision scenarios.⁷ Just as important is securing C-suite sponsorship, since visible executive backing empowers teams and builds organisational trust. A strong data foundation is also essential. Companies must invest in unified, high-quality, governed data sources before launch to ensure insights are both reliable and actionable.

Clarifying decision rights is equally critical. Launch rooms work best when teams know which calls they can make autonomously versus what requires escalation.⁷ Finally, leaders must sustain the culture by using centres of excellence or standardised frameworks to maintain agility and repeat success across markets.⁹ These steps require investment, but the cost of underperformance – slower uptake, lost share or missed exclusivity windows – is far greater.

Conclusion: a catalyst for broader transformation

Traditional launch rooms promised agility but often delivered frustration. By learning from these shortcomings and embracing AI, pharmaceutical companies can build next-generation launch rooms that truly deliver real-time insights, agile collaboration and user-centric design.

The opportunity is larger than any single product. Well-executed launch rooms become laboratories for new capabilities such as digital integration, agile governance and data trust that can scale across portfolios and geographies. In a market defined by compressed timelines and rising expectations, those who invest in this transformation will define the new standard for launch excellence.

Meet the author

Jason Smith HS.jpeg
Jason Smith CTO, AI & Analytics – Within3 

Jason is CTO of AI & Analytics at Within3. A Harvard-trained computer scientist, he began his career in technology at IBM before becoming a serial entrepreneur in the fields of video encryption, high-performance computing and bioinformatics. He has led the development of multiple start-ups in areas including social networking, data analytics, distributed systems and life sciences AI. Jason holds multiple patents and is an active angel investor, advisor and board member.

References

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  7. ‌McKinsey & Company. Rewired pharma companies will win | McKinsey [Internet]. www.mckinsey.com. 2023. Available from: https://www.mckinsey.com/industries/life-sciences/our-insights/rewired-pharma-companies-will-win-in-the-digital-age
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