ZS: When a life sciences or biopharmaceutical company starts a CRM migration, is it typically a technical project or a transformation? And does the answer change how you plan it?

Srihari Sarangan: Across these industries, a CRM migration program is a transformation, not a technical project. Framing it that way from day one is what separates a successful program from a painful one.

Most companies start by scoping it as a lift: move the data, reconfigure workflows, train users, go live. That framing breaks down fast in life sciences. A CRM program is the operating layer for commercial teams. It shapes territory design, call planning, sample management, compliance and data governance. The real work is redesigning those operating decisions, with the CRM platform reflecting them rather than driving them.

When the system migration is planned as a transformation, the right stakeholders engage early: commercial operations, sales and marketing, medical, IT, analytics and compliance. That alignment cuts rework, balances speed with regulatory rigor and shifts the definition of success from on-time go-live to sustained adoption and measurable impact.

Atul Choudhary: The teams that struggle are the ones that recognize this distinction only after adoption falters or workflows break. Treating migration as a business transformation from day one does not slow delivery. It accelerates value, because the platform ends up supporting how the business needs to run in the future.

This distinction matters even more in platform-to-platform CRM migrations. Teams often assume the shift is straightforward because they are moving within a familiar commercial CRM category. In practice, these migrations require decisions on data model differences, legacy platform dependencies, downstream integrations, reporting continuity, field experience and governance, all of which sit well beyond a pure technical scope.

ZS: How has AI changed what life sciences companies expect from their CRM and what should teams be doing now to stay ahead?

SS: AI is reshaping what CRM does in life sciences. CRM used to function primarily as a system of record. Today, it’s becoming a system of action that synthesizes data across channels, surfaces next best actions and automates engagement in real time. Leading organizations are no longer asking whether a platform can run basic workflows. They are asking whether it can support AI-driven HCP engagement at scale.

The risk is that companies migrate to a modern platform but configure it the way they configured the old one, leaving no room to layer AI on top.

Three things should happen now. First, audit which workflows are still purely manual. Second, assess whether the data model is clean, connected and ready to train on. Agentic AI depends on connected workflows, high-quality data and clear governance structures. Third, make AI readiness a migration evaluation criterion, not a postlaunch consideration. The foundations set during migration will define how much value the CRM can deliver for the next several years.

For organizations moving from a legacy CRM environment to a next-generation CRM platform, the migration is a chance to reset. Use it to simplify legacy configurations, raise data quality, rationalize workflows and put the foundation in place for AI-enabled commercial engagement, rather than carry old constraints forward.

ZS: Can you walk us through a real CRM migration example of what the company set out to do and what happened?

AC: In a recent migration for a large pharma client moving to a next-generation CRM platform, the team initially focused on how field-level and data model changes would affect connected systems. As discovery progressed, it became clear the migration could not be managed as a field-mapping exercise. The bigger risk sat in the broader ecosystem: data warehouse, reporting, alignment, network and other connected platforms.

ZS led a detailed impact assessment across upstream and downstream systems. The work covered identifying affected stakeholders, mapping data warehouse tables and columns, and sequencing changes across the CRM transition. One important design decision was to preserve previous CRM identifiers in the new platform through a custom field. That kept continuity for older records and reduced disruption to downstream reporting and integrations.

The team also worked through translation logic for picklist fields and aligned stakeholders on how historical versus future records would be handled. Older records were retained in a legacy environment while newer data flowed into the new CRM platform.

The outcome was a lower-risk migration with better data consistency, less reconciliation work and more reliable reporting after transition. More importantly, the business kept making decisions from trusted data instead of spending the postmigration period chasing broken data flows

ZS: What breaks during a CRM migration that nobody puts in the risk register?

SS: The most damaging failures in a CRM migration usually sit outside the formal risk register. They surface after go-live and erode confidence in the platform.

Reporting continuity is the first to break. Historical data rarely maps cleanly to a new data model, and leaders lose year-over-year visibility right when they need reassurance the most. The gap undermines trust before adoption has a chance to stabilize.

Informal workarounds disappear next. Field teams and operations have spent years building Excel trackers, repurposing fields for unintended uses and creating undocumented processes. These shadow systems are invisible during design and acutely felt the moment they vanish.

Downstream dependencies show up late. A field that looks benign in the CRM may be feeding a contract management tool, a sample accountability system or a compliance report. Those issues land weeks after launch.

People risk is the one nobody puts in the register. The internal CRM expert who knows where every workaround lives often disengages or leaves midmigration, taking critical context with them.

AC: In a platform-to-platform CRM migration, even a small field-level change can ripple through data warehouse tables, reporting logic, alignment processes and connected systems. Legacy CRM identifiers are a clear example. They look like background plumbing but often anchor historical reporting, reconciliation and integration logic, which is why how they are carried forward matters.

Successful migrations treat these as design inputs, not surprises—and plan accordingly.

ZS: What risks or gaps only become visible once a CRM migration is underway?

AC: In the middle of a migration, the biggest surprise is how quickly complexity reenters the program. What looks like new requirements is often scope reopening: stakeholders who were not aligned early surface critical needs late, forcing rework and eroding confidence in decisions already made.

Data is the second shock. Organizations routinely underestimate the data quality debt they are carrying. HCP/HCO hierarchy issues, deduplication and territory alignment problems that were tolerated in the previous system become hard blockers when moving to a modern CRM with tighter governance and analytics expectations.

Change fatigue is just as risky. As timelines extend, field teams disengage from training and UAT, which almost guarantees a rough go-live.

Compliance review cycles are the final blind spot. In life sciences, regulated workflows need legal and regulatory sign-off, and that review is almost always underestimated in the plan. Delays there can stall otherwise ready releases.

The programs that hold up best put a clear migration governance model in place early. Decision rights are defined across commercial, IT, data, compliance, analytics and field leadership, so late-breaking requirements can be assessed and accepted or deferred without constantly reopening prior design decisions.

ZS: What migration challenges are unique to life sciences that generic CRM advice misses?

SS: Life sciences migrations carry structural complexity that generic CRM playbooks do not account for. Commercial teams are not managing a single-buyer relationship. They operate across intertwined ecosystems of HCPs, HCOs, IDNs, payers and GPOs, each with its own engagement rules and data dependencies. Generic guidance rarely accounts for that multientity reality.

Regulation raises the stakes further. Promotional compliance, fair market value controls and spend transparency reporting are not items to bolt on. They shape how data models, workflows and integrations must be designed from day one. Miss this and migrations stall late or fail quietly after go-live.

Field execution adds another layer. Sample management, formulary and access data, and medical legal regulatory approval flows introduce operational complexity that traditional B2B CRMs never face.

Data governance is different at its core. Patient-adjacent data, sensitive prescriber information and restricted commercial contracts require controls that generic playbooks underestimate, putting both adoption and risk posture in jeopardy.

ZS: When life sciences companies migrate from a deeply embedded CRM platform, what happens to the ecosystem built around it?

AC: When companies move off a deeply embedded CRM, the core platform is rarely the source of friction. The ecosystem around it is. Over the years, life sciences companies built extensive layers of custom applications and integrations to support medical affairs, speaker programs, sample management, marketing activation and analytics. These assets do not lift and shift. Each one must be deliberately rebuilt, replaced or retired.

Partner and ISV ecosystems compound the challenge. They are platform-specific. Tools the field relies on daily may not exist in the new environment, or may require new vendors with different contracts and support models. API dependencies are often undocumented, with finance, supply chain and patient support platforms pulling data from CRM in ways nobody mapped at the time the integration was first built.

In a platform-to-platform CRM migration, the same discipline applies to the legacy CRM environment: custom objects, integrations, reporting layers, data warehouse dependencies, middleware, mobile workflows and companion applications all need a clear disposition of migrate, rebuild, replace, retire or defer.

Our recommendation is to run a rigorous ecosystem audit before finalizing migration scope, sequencing and release plans. In many migrations, the cost and risk of reconstituting the ecosystem outweigh the CRM migration itself.

ZS: How do data quality and data model differences between platforms derail timelines—and how do you catch it early?

AC: For companies moving from one CRM platform to another, this is more than a field-to-field exercise. Teams need to account for differences in object relationships, field names, picklist values, incumbent CRM identifiers, reporting assumptions and integration dependencies. Small data model differences create outsized downstream impact when they surface late in the migration.

The way to stay ahead is to treat data as a first-order design decision. Run a data quality audit and a data model gap analysis during discovery, not during build. Bring a data architect into the room alongside your CRM configurators from day one. That early alignment is what protects your timeline later.

ZS: What does ZS actually do in a CRM migration—and where does your work end and the client’s begin?

SS: ZS typically enters CRM migrations in one of three ways: upstream, helping leaders decide whether to migrate and which platform best fits their commercial strategy; midstream, providing program leadership to run a complex, multiworkstream migration; or tactically, supporting specific needs, such as data migration, analytics or change management.

What clients get from ZS is experience they can’t easily build internally, including pattern recognition from dozens of life sciences migrations, proven accelerators for common CRM and analytics workflows, and the confidence to challenge scope or design choices that look reasonable on paper but break down with real users.

AC: In complex CRM migrations, ZS helps clients see not only what changes inside the new CRM platform, but what those changes mean for the broader commercial ecosystem: data warehouse, reporting, alignment, network, analytics and other connected platforms. We assess upstream and downstream impact, preserve continuity for legacy identifiers, coordinate stakeholders and reduce disruption through cutover.

Clients remain firmly in the driver’s seat on executive sponsorship, final business decisions, field engagement and long-term governance. The most successful migrations are true partnerships—where ZS builds internal capability and steadily works itself out of the job, rather than creating dependency.

ZS: How do you get life sciences field reps and sales ops to actually adopt a new CRM?

SS: Adoption isn’t a post–go‑live problem, it’s a pre‑go‑live leadership mandate. In our experience, CRM success is largely determined in the six months before launch. If field reps first encounter the system during training, skepticism is already locked in.

Reps need to clearly see what’s in it for them: fewer clicks to log calls, sharper territory and account insights, and less administrative drag. When a new CRM feels like “the same work, different screen,” adoption stalls.

Sales operations are the critical, and often overlooked, lever. These teams shape how the CRM actually gets used, creating workarounds and serving as informal trainers. Involving them early in UAT and design turns them into advocates rather than passive observers.

AC: In platform-to-platform CRM migrations, adoption also depends on helping users understand what is familiar, what is changing and why. Even small shifts in navigation, terminology, workflows or reporting creating friction if field teams are not prepared for them well before go-live.

Finally, treat the first 30 days after go‑live as decisive. Define success metrics upfront, monitor adoption daily, and intervene quickly. Waiting for a 90‑day review is too late.

ZS: What’s your single most important piece of advice for a team six months into a CRM migration and starting to feel the pain?

AC: At the six‑month mark, most CRM programs stall not because the technology is wrong, but because the work has drifted away from the original business intent.

When teams are buried in data defects, edge‑case workflows and configuration debates, we advise pausing to reanchor on the business case that justified the investment in the first place. Reengage the executive sponsor, restate what success looks like, and let that definition instead of sunk effort drive decisions.

SS: At the same time, be ruthless about scope. What felt essential at kickoff is rarely what’s essential for a successful go‑live. Focus on a minimum viable CRM that gets the field productive on day one, and deliberately phase the rest. A clean launch with momentum always beats a delayed launch with everything.

Finally, don’t protect the timeline at the expense of the outcome. If a reset is needed, do it early; it is far less costly than recovering from a bad launch.