Principal-led delivery
Senior specialists stay involved from diagnosis through implementation.
Life Sciences & Biotech Consulting
Connect the work behind your next life sciences milestone
GrandView helps life sciences teams connect the plans, data, workflows, and decisions behind clinical and product milestones. We work across Pharmaceuticals & Biopharma, Biotechnology, and Medical Devices & Diagnostics, improving the work around established IBM and specialist systems without making platform replacement the starting point.
Three operating realities
Pharmaceuticals & Biopharma
Biotechnology
Medical Devices & Diagnostics
IBM ecosystem expertise
Business context, architecture, and delivery in one team
GrandView connects the business question to the systems and delivery work required to answer it. Our experience in planning, analytics, data, integration, and AI governance helps us see where a program problem is really a model, data, workflow, or ownership problem.
20 years
average consulting experience across our team
One accountable partner
Planning, data, integration, analytics, and platform expertise stay connected.
A faster path to evidence
Reusable patterns and working models show dependencies before implementation.
Enterprise technology, applied to the way life sciences teams work
Select a partnership to see how it supports planning, data, workflow, and platform improvements around established systems.
IBM Gold Business Partner
Connect planning, data, and AI to a defined business decision
We connect IBM analytics, data, integration, automation, and AI capabilities to a specific life sciences workflow instead of beginning with a technology program.
Planning AnalyticsCognosIntegrationwatsonx
Red Hat technology partnership
Add new services without losing control of the operating environment
We relate platform and hybrid deployment choices to data access, system boundaries, operating policy, and the applications teams already depend on.
OpenShiftAnsibleHybrid cloudApplication services
Motio technology partnership
Bring control into reporting change
Testing, versioning, and change records help teams review releases in Cognos environments used for finance, portfolio, and management reporting.
MotioCIMotioPIRegressionChange history
The operational problems life sciences teams cannot solve in one system
Life sciences work crosses teams, partners, documents, models, and specialist applications. A decision may begin with a clinical or product event and move through planning, evidence, review, and approval before anyone can act on it.
The plan falls out of date when the program changes
Enrollment, site activation, protocol, vendor, or product timing can move during a reporting cycle. The financial view often catches up after teams have already started working from the new reality.
The decision waits while people rebuild its context
Study data, contracts, invoices, quality records, and prior assumptions may each answer part of the question. Review starts after someone finds and reconciles them.
Important work happens outside the organization
CROs, sites, laboratories, manufacturers, and specialist vendors create data and costs the sponsor still has to understand. Their updates arrive on different schedules and in different formats.
The first part of the decision becomes reconciliation
Finance, R&D, Clinical Operations, and leadership may work from different timelines, cost assumptions, or versions of the program before they can agree which view is current.
Standard reports can hide the change that matters most
A delayed site, supplier change, missing document, or unusual quality event may have more business impact than the normal cases around it. These changes often remain in email or manual trackers.
AI can prepare the work, but people still own the decision
Teams need to know which sources an AI service used, what it was asked to do, how its output was checked, and who approved the next action.
One industry.Three operating realities.
The underlying constraint may be shared. Its business impact depends on the product, company stage, and work being performed.
| Operating challenge | Pharmaceuticals & BiopharmaPortfolio and commercial scale | BiotechnologyClinical-stage biotech | Medical Devices & DiagnosticsProduct and quality lifecycle |
|---|---|---|---|
| Program work | Development, manufacturing, launch, and commercial plans affect one another across a portfolio. | A small number of programs depend on sites, CROs, laboratories, specialist vendors, and the timing of the next milestone. | Product, software, quality, manufacturing, and post-market work continue across the same lifecycle. |
| Business measures | Portfolio value, R&D spend, capacity, launch timing, product performance, and revenue outlook. | Milestone timing, study spend, accruals, cash burn, runway, and the next financing need. | Development spend, resource use, unit cost, quality events, service performance, and product revenue. |
| Decision data | Clinical, portfolio, finance, manufacturing, supply, and commercial views across planning cycles. | Enrollment, site, vendor, milestone, contract, invoice, resource, and cash assumptions. | Product, design, quality, manufacturing, complaint, service, and post-market information. |
| Partner ecosystem | Research partners, CROs, manufacturers, distributors, and commercial partners contribute to the operating view. | Sites, CROs, laboratories, consultants, and vendors create much of the evidence, activity, and cost. | Suppliers, contract manufacturers, laboratories, service partners, and clinical sites affect product and quality work. |
| Improvement priority | Connect portfolio and financial planning across established systems and reporting environments. | Connect program assumptions to cost, cash, runway, and management scenarios as the timeline changes. | Connect product and quality information while keeping specialist systems responsible for their records. |
Better life sciences decisions require a shared view
One program change can cross several executive mandates. The improvement has to make sense to the people responsible for delivery, financial performance, architecture, data, AI, quality, and regulatory control.
Can we see how a change in enrollment, site timing, or resources affects the program plan?
Milestones · sites · vendors · delivery
Can we explain runway and the next financing need using assumptions the program teams recognize?
Spend · accruals · cash · scenarios
Can teams reuse data and AI without losing source context, access control, or ownership?
Architecture · access · lineage · model lifecycle
Can we reconstruct the evidence, review, and approval behind the result?
Evidence · review · change history
Start with the business problem. Improve only what solves it.
We diagnose before we prescribe. The engagement begins with the business outcome and the way work happens today, not with a predetermined platform.
01
Define the outcome
Choose one process or decision and agree how improvement will be measured: forecast cycle, manual adjustments, wait time, rework, missing information, or time to an approved answer.
Output · agreed baseline and decision
02
See the complete workflow
Reconstruct how representative work moves across teams, partners, systems, spreadsheets, and documents. Map assumptions, owners, exceptions, review points, and controls.
Output · current-state evidence map
03
Improve a practical scope
Select a bounded flow such as a trial forecast, portfolio review, cash runway model, quality event, supply decision, or defined use of AI.
Output · controlled intervention design
04
Prove the operating result
Test the flow with real roles, representative data, and the exceptions that usually cause trouble. Keep required review and approval with the people responsible for the decision.
Output · measured pilot evidence
05
Scale from evidence
Use the result to decide what should expand, what should stay unchanged, and where the next investment will improve the outcome.
Output · next-step roadmap
Technology that improves how life sciences work gets done
GrandView combines the capabilities required by the workflow instead of forcing the entire problem into one product category. The architecture depends on the organization's existing systems, process, data, and controls.
GrandView helps Finance and program teams build or improve models for trial budgets, cash forecasts, portfolio choices, workforce, and management reporting. For clinical-stage biotech, this connects enrollment, site timing, vendor estimates, and program milestones to cash burn, runway, and funding scenarios.
Technology layer
Explore Planning Analytics
- IBM Planning Analytics
- TM1
- IBM Cognos Analytics
Relevant when a clinical update must reach Finance, a quality event needs several reviewers, or data from a CRO, laboratory, or manufacturer needs a reliable route into an existing process.
Technology layer
Explore Integration & Automation
- IBM App Connect
- IBM MQ
- API Management
- Business Automation Workflow
- Decision Rules
The objective is not to move every scientific, clinical, quality, and enterprise source into one database. It is to make the information required by a defined job available with clear ownership, quality rules, lineage, and access.
Technology layer
Explore Data Solutions
- IBM Cloud Pak for Data
- watsonx.data
- IBM Knowledge Catalog
GrandView helps teams give an AI use case named owners, approved sources, evaluation criteria, monitoring, and a record of change. Private AI Search can help people find and summarize approved internal knowledge while keeping the source visible. The qualified expert or business owner still makes the decision.
Technology layer
Explore AI Governance
- IBM watsonx.governance
- IBM watsonx.ai
- Private AI Search
- Red Hat OpenShift
Life sciences organizations often need to retain specialist applications while improving access, integration, and the services around them. GrandView helps define system boundaries, expose selected capabilities, and choose where private, cloud, or hybrid deployment fits the workload.
Technology layer
Explore Application Modernization
- Red Hat OpenShift
- Ansible
- IBM Integration
- API Management
Let's identify where GrandView can make the clearest difference
Bring us one plan that keeps falling behind the program, one decision that begins with conflicting assumptions, or one data or AI constraint holding back useful work. We will help you determine whether the issue sits in the model, workflow, data, integration, platform, or operating ownership.
Schedule a Life Sciences Diagnostic
Rusty Pennington
CFO & Partner, GrandView
Business planning and technology advisory
IBM ecosystem expertise for life sciences planning, data, analytics, automation, AI governance, and platform modernization