Empowering Clinical Trial Decisions with Data-Driven Decision Management (DDDM)

Project Structures: How to establish with Planview, Planisware, and Project Online

From a pharmaceutical R&D context, project structures can be seen as a reliable process to organize, track, and deliver the tasks while keeping the stakeholders informed. If you don’t have a well-planned project structure: Portfolio decisions usually suffer from low visibilityTeams start losing alignmentMissing critical deadlines become normal With a strong project structure, key decision-makers can: Have a clear view throughout the entire pipelineEasily prioritize high-value portfolio assets Manage risks more efficiently Project portfolio management tools like Planisware, MS Project Online, and Planview help establish organized structures that accelerate pharma projects, ensure compliance and success. That said, let’s dive into what project structures mean in pharmaceutical context, and how these tools help establish them seamlessly. Types of project structures in pharmaceutical R&DSelecting the right structure is your first step to ensure on-time project delivery with the right resources, without bleeding budgets. Here are three types of project structures to consider: 1. Functional structure As the name suggests, functional structure involves grouping all teams as per specialized functions – be it clinical, manufacturing, regulatory etc. In this model, the departmental head usually manages the team members, while coordinating the projects within functional silos.Functional structures are best for:Small-scale pharma companiesLimited cross-functional project needsWhat to look out for?On the flipside, these models are also known to create communication gaps and slow down decision-making in accelerated R&D settings. 2. Projectized structure In this model, the project manager has 100% authority over the research team and key resources, unlike the former. The PMOs assign their teams to specific projects, often outside their everyday functional roles.Projectized structures are best for:Large-scale pharmaceutical project management needstime-sensitive, high-priority, high flexibility research initiatives What to look out for?Unfortunately, this model can also cause resource duplication and higher costs, particularly when multiple projects are running at the same time. 3. Matrix structure (Best suited for Pharma)Last, but most importantly, the matrix structure brings the best of both functional and projectized structures under one umbrella. Here, teams report to both functional and project managers. This way, resources can be shared across different projects without compromising on functional supervision.Matrix structures are best for:Mid-to-large organizations juggling between numerous programsHigh operational continuity & innovation-led settingsWhat to look out for?Despite being the most common project structure in pharma R&D, it calls for strong communication and higher role clarity, to avoid conflicts or confusion. How to establish Pharma-specific structures using Planisware, Project Online and Planview?Designing and implementing project structures that suit the complex requirements of pharmaceutical R&D become easier with PPM tools. Users can configure project hierarchies, governance models, allocate resources efficiently and support decision-making at every phase. Here are your options and steps to do it:Tool #1: PlanviewFirst on our list, Planview is a major contender in terms of portfolio management and resource optimization. With a little upfront tailoring, its project templates can align well with pharma workflows.How to set up a project structure in Planview?Configure project types: label templates (for example, “Phase I asset”, “Platform”)Define swimlanes as per function (clinical, regulatory, manufacturing)Set up a clear stage-gate workflow in roadmap view with well-defined gatesAttach gate checklists and deliverables to each stageEnable demand/capacity views for cross-functional resource alignment Tool #2: PlaniswareThe Planisware project management tool is purpose-built for life sciences projects, and mirrors pharma R&D workflows like none other in this list. For example, it embeds stage gate logic at every level. The platform natively supports clinical/CMC deliverables, molecule hierarchies, as well as regulatory milestones. Here, teams can easily set up projects that map exactly to asset phases, while having total control over gates and finances.How to set up a project structure in Planisware?Create a project template with WBS (discovery, preclinical, phase 1/2/3)Embed gates after every single phase, linking back to the decision criteria and business case scorecardsAdd key deliverables (for example: IND, CMC dossiers, clinical trial authorizations)Link back the financial/resource modules to WBS for seamless budget/version trackingRoll up to portfolio to maintain proper visibility across molecules and indications Tool #3: Project OnlineLastly, Project Online is a great choice for schedule-level planning; it’s not entirely built around pharmaceutical project management structures in focus. Here, teams need to build everything from ground up. The good part, however? Integrating with Power BI, Teams, and Power Automate.How to set up a project structure in Project Online?Start by designing your custom project template Define tasks for regulatory deliverables and project milestonesTrigger notifications at gate milestones by integrating Power Automate Integrate Power BI to access customized dashboards aligned to R&D phases’ progressManage resources via PWA to assign functional roles How to choose the right tool for your project structure needs?More than chasing latest features, choose project portfolio management tools that fit your team’s needs the best. This means judging the tool by how well it aligns with your project structure, people, and strategic goals. Choose Planisware if you would:Manage a mid-to-large pharma/biotech firm with a complex R&D asset portfolioRequire built-in stage-gate models, modifiable for drug development lifecyclesNeed strong portfolio governance & what-if scenario planning at scaleUse Project Online if you would:Require a quick, at-budget tool for basic-level project scheduling/ trackingFocus on daily task management, instead of strong portfolio governanceNeed hassle-free, end-to-end automation integration (Teams, Power BI, Outlook) Go for Planview if you would:Be transitioning from project-level to portfolio-level strategy while scaling upWant to have strong resource demand vs. capacity modelling Need visualized roadmaps, high financial visibility, cross-functional planning etc. Key takeaways at a glanceProject structure informs smart portfolio decisions, points out risks early and surfaces resource conflicts Matrix project structure is the best-suited for pharma/biotech teams, as it comes with a mix of agility, governance, and resource efficiencyMore features don’t ensure success; choose your tool that best fits your team’s maturity level, complexity of portfolio assets, and other key indicators.Planisware project management tool is best for enterprise players with deep pipelines; Project Online suits mid-sized teams focused on scheduling; Planview is the go-to option for strategy-driven PMOsNeed help getting started? Let’s talk about how we can help. i2e Consulting brings 15+ years of PPM expertise. We’ve partnered with leading pharma organizations to establish fit-for-purpose project structures that drive clarity, speed, and smarter portfolio decisions. Connect with us – let’s build a project structure that accelerates your portfolio growth.

6 Warning signs your PPM tool is holding you back and how to fix them?

IntroductionIn a market flooded with Project Portfolio Management (PPM) tools, it is important to find one tool or a combination that fits your business needs, but does it end there? No, it doesn't. As portfolios continue to grow and evolve, so should the tools and processes around them.Right from the evaluation of PPM tool capabilities and integration potential, to ensuring alignment with your project workflows, team structures, and governance models, the journey is anything but straightforward. What looks good on paper may fall short in practice if the tool doesn’t support your organization’s decision-making rhythms, reporting needs, or future scalability. In this blog, we unpack some of the signs that indicate your current PPM may not be working for you.6 Signs to change or upgrade your PPM toolWhether you are managing a local functional level portfolio, or a global multi-therapy portfolio, your PPM tool should scale to match your future vision. Most of the times, the real problem lies in improper customization of the tool, or lack of proper alignment of the tool with the processes around it.As time passes, even the most robust tools can quietly become misaligned as your portfolio grows in complexity and your processes and tool cannot catch up.Here are 6 signs to watch out when your portfolio is growing.1. Lack of visibility and transparencyIn life sciences, where development timelines span years, costs reach billions, and go/no-go decisions hinge on granular data, lack of visibility isn’t just inconvenient—it’s risky. If stakeholders struggle to see the true status of projects, resource bottlenecks, or shifting priorities across the portfolio, it’s often because the PPM tool isn’t surfacing the right information in the right format.This can result inLack of progress visibility to the clinical project leadsResource managers cannot access real-time insights over-allocations across cross-functional teams.Finance and strategy teams operating with inconsistent dataLimited visibility to the senior leadership for proactive decision-makingThe fix: Integrate data across functions and systemsEnable role-based dashboardsConnect strategic governance to operational executionAdopt a layered approach: tools+analytics+services2. Relying on manual processesIf your team is still exporting data from the PPM tool to create trackers, forecasts, or summaries in excel, they are building parallel processes outside the system. In life sciences, clinical milestones are tied to regulatory submissions, resource planning needs to be done across multiple functional roles, and cost forecasting should be incorporated into scenario planning and PTRS-based risk adjustments. When spreadsheets are used for any of the above, it breaks traceability, auditability, and data integrity—which are non-negotiables in pharma.The fix:Audit what is being done outside the tool and whyMap critical decision areas (e.g., resource trade-offs, milestone projections, risk-adjusted value)Extend your current PPM tool with tailored integrations3. Difficulty adapting to strategic changeIn life sciences, strategic agility isn’t optional—it’s mission-critical.Pipeline reprioritizations, licensing deals, market shifts, regulatory delays, and clinical data surprises are part of daily life. When your PPM tool can’t adapt quickly to these realities, it doesn’t just slow down operations—it weakens your strategic posture.If your current tool requiresManual rework to update forecasts or resource allocationsWeeks to reflect new prioritizations from governanceOffline modeling of portfolio impactsThese can cause serious issues during some strategic triggers that require rapid adaptation. For example, businesses acquiring a biotech pipeline- Entire new projects and data sets need to be integrated rapidly.The fix:Enable scenario modeling within the PPM environmentTie prioritization to strategic driversAllow real-time, role-based replanningConnect strategic decisions to execute workflows4. Data silos and integration issuesWhen systems cannot talk, people build manual work arounds, and that’s when errors, delays, and mismatches happen.In life sciences, portfolio success depends on how accurate and real-time the data is flowing between clinical, regulatory, finance, and commercial teams. But if your PPM tool is not integrated well, it creates data silos, and decision-making blind spots.For example,Clinical trial milestones are updated in the CTMS but not reflected in portfolio timelines, Finance forecasts in SAP does not align with resource assumptions in the PPM tool,Resource planning tools operate separately from program plans, creating over- or under-utilizationThe result? Reporting becomes reactive, portfolio insights become outdated, and governance decisions are made on partial or inconsistent data.The fix:Identify and map critical data touchpointsUse APIs , data warehouses, or middleware for seamless flowCentralize reporting with a unified data layerImprove adoption by reducing complexity5. Frequent project delays and missed timelinesIn life sciences, R&D timelines stretch over years, and project delays and missed timelines can impact patient access, revenue realization, and consistent project overruns. If projects across your portfolio areSlipping their milestonesMissing regulatory submissions targetsRequiring last-minute firefighting on resource or budget allocationAnd the project teams have no visibility before this can happen, so it’s often not the science or the team—it’s a sign that the PPM tool is no longer providing the right foresight to plan and execute effectively.The fix:Configure timeline logic to reflect real-world dependenciesAdd risk triggers and milestone health checks inside the toolEmbed resource forecasting modules into the toolActivate portfolio-level impact tracking6. Lack of reporting and analyticsIf your PPM tool cannot generate the right reports, or it is bound to export raw data to just build custom views, then your PPM tool is slowing down decision making or is causing the team to rely on outdated decisions.Common indicators areComplicated to compare budget vs actuals by function or programReports lacking granularity and clarityStatic portfolio views with no trend lines, variance tracking and drilldownsWithout timely, trusted insights, your team is stuck in reactive mode—reporting the past instead of steering the future. It is time to explore the reporting capabilities of your existing tool or evaluate the need to build an external reporting system.The fixDesign role-based dashboards for decision-makersIntegrate real-time performance tracingInclude trend analysis and historical viewsLayer predictive analytics for decisionsBuild Reporting Database and integrate data from PPM tool, financial toolsConclusionAdopting a PPM tool means countless hours of research, training and change management. Even if you notice one or many of these warning signs, you need not always replace the entire tool. Many times, with a few customizations and process fixes, portfolio management systems can be configured to support your growing portfolio needs.i2e can helped global life sciences organizations fix and extend their PPM tool capabilities byDesigning a maturity-based roadmap customized to your portfolio complexityExtending the current PPM tool with integrated analytics and dashboardsConfiguring milestone logic, risk signals, and resource forecasting inside your toolAutomating reporting and scenario planning across portfolio layers

From chaos to confidence: How i2e and Databricks transformed risk-based quality management at scale

Risk-Based Quality Management (RBQM), a method of evaluating risks on clinical trials and then applying statistical methods to find outliers at clinical trial sites, has long promised to reshape clinical trial oversight—bringing smarter, faster, and safer decisions to the forefront. But making RBQM operational at scale is hard. Legacy tools, fractured workflows, and inaccessible data often slow progress to a crawl. At i2e Consulting, we specialize in transforming these complex environments into platforms for innovation. For one of the largest global pharmaceutical companies, we helped do just that—modernizing RBQM through a powerful combination of Databricks, Posit, and cross-functional collaboration. The result? Validated, efficient, and collaborative solutions—all delivered under budget. Before: A Fragmented, Manual, and Siloed Ecosystem The client’s RBQM operation was built on legacy infrastructure: Bulk data files were generated by a legacy system and stored on a file server. However, not all needed files were included in the data lake, and others required intensive programming time to prepare. A team of 50 people across the globe, Central Monitors, had to manually open, adjust, and repackage datasets, often in SAS Studio, to get the full view. Supporting analytics relied on desktop Python scripts that only a few could run, due to complex dependencies and inconsistent setup. Data access for additional complex analysis was clunky—long, fragile credential strings and individual workarounds slowed everyone down or made the work impossible to complete. There was no shared development space or common validation pathway, so every new insight felt like a one-off project. The system took years to develop and the client was not able to change it at need. This was working against the goals of a modern RBQM program and the need to be proportional per ICH E6(R3) After: A Validated, Unified Platform Powered by Databricks and POSIT With i2e leading the transformation, the RBQM capability evolved from siloed tools to an enterprise-grade, validated platform: 1. Centralized, Scalable Data Access with Unity CatalogUsing Databricks’ Unity Catalog, our admin granted secure, governed access to the client’s data lake and existing database estate in a single setup. Everyone on the team—from engineers to Central Monitors—could access the same data without redundant effort or manual patchwork. For files missing from the data lake, we uploaded them directly into Databricks, creating a safe and validated environment. We developed a risk based approach to validation with our testing partners. As this is a secondary system, we followed the principles of say what you are going to do, then do what you said you were going to do and document that you did what you said you would do. This is aligned with best practices for risked based validation for clinical trials. 2. Shared, Collaborative Development with Databricks NotebooksWith Databricks notebooks connected to GitHub, development became collaborative, version-controlled, and transparent. The friction of setting up environments disappeared, and code became portable, maintainable, and scalable. From exploratory analyses to formal pipelines, all work could live in a governed, shared ecosystem—one that supported CI/CD (Continuous Integration/Continuous Delivery) for validation-ready software releases. 3. Streamlining Operations with Databricks Workflows Efficient orchestration was critical to transforming the client's RBQM operations from fragmented manual processes into a seamless automated pipeline. Leveraging Databricks Workflows, we built robust job orchestration that systematically generated and refreshed essential data files, eliminating the dependency on manual file preparation. Jobs that previously required manual intervention and extensive coding in SAS Studio or Python scripts were now centrally managed, scheduled, and monitored from a unified interface. Built-in monitoring and alerting capabilities provided immediate visibility into job execution statuses. Any potential issues were proactively flagged, enabling swift troubleshooting and minimal downtime. 4. App Deployment with Posit By connecting to Posit Connect and Workbench, we delivered a suite of workflow apps as part of the“CM Toolkit”. These allowed Central Monitors to interact with complex tools through clean, intuitive interfaces—all without writing code. Additionally, API integration with Databricks Workflows enabled the Posit apps to trigger workflows directly, creating a modular, interconnected architecture that improved responsiveness and flexibility. These apps weren’t in the original scope, but thanks to Databricks’ efficiency and flexibility, and the skills of the i2e team, we delivered them as an add-on feature—while still coming in under 50% of the original budget. 5. End-to-End Integration We leveraged two existing production APIs by creating scheduled Databricks jobs that periodically consumed and integrated the RBQM environment with both the: ticketing system for workflow tracking, and central monitoring platform to contextualize findings. These integrations enabled real-time communication between business and technical systems, improving both insight and responsiveness. 6. Organizational Milestones This became the first validated deployment of Python apps at this sponsor organization. It happened through intentional partnerships—with platform, architecture, and validation teams—and through i2e’s leadership in: Training and enablement Role modeling engineering best practices Building and maintaining complex, production-ready code We gave Central Monitors “training wheels”—letting them safely participate in the tooling ecosystem without needing deep technical knowledge, while still making meaningful progress. Outcomes: Validated Results, Delivered Fast The transformation brought measurable results: 4 validated releases in less than 12 months (Historically, 1 such release a year would have been successful)EDC (electronic data capture systems for clinical trials) onboarding time reduced by two-thirds—from multiple quarters to under 3 months Over 8 workflow applications delivered via Posit Delivered under 50% of budget, with expanded scope More importantly, the organization now has a repeatable, collaborative, and validated RBQM capability—one built for speed and scale. What’s Next: Databricks Apps, GenAI, and Exploratory Acceleration The journey doesn’t stop here. We’re now focused on: Transitioning to Databricks Apps for simplified architecture and streamlined access control—bringing compute, access, and app deployment into a single pane and removing licensing costs. Increasing use of the Databricks Assistant to support Central Monitors and developers alike. Exploratory analysis apps and GenAI use cases that help surface quality signals, generate narratives, and improve efficiency across trials. Most importantly, we hope to showcase a model for others: That business-led and professionally supported software development can coexist—with the right tooling, process, and team culture. And for us, the platform that made this possible is Databricks. At i2e, we bring more than just tools—we bring a blueprint for transforming clinical trial data into a strategic asset. From zip files and scripts to validated apps and APIs, we helped this client move from chaos to confidence. And we’re just getting started. Article by: .profile-image img{ width: 200px !important; height: 200px !important }