Life Sciences Managed Services
A Platform That Keeps Finding Patients After Launch
The first two quarters after launch generate more change than the build did. Someone has to run the feeds, keep the territories straight, and ship the next release. That is this engagement
What Changes After Go-Live
The build had a scope and a finish line. Operations do not. The data keeps arriving on its own schedule, the field keeps asking for the next thing, partners change file layouts without warning, and the targeting model has new patients to learn from every month. That starts the week after go-live and does not let up. The usual answer is to hire an internal admin and data team before anyone knows what the platform needs day to day. Ours is to run it as part of the program for as long as the program runs: the same team that built the warehouse, the feeds, and the CRM keeps operating them, and the engagement grows as the program adds indications, markets, data licenses, and users. The same team that delivered the rare disease launch platform keeps it running from the first week of real use
Seven Things That Need an Owner
This is the standing scope of a pharma managed services engagement. Some months run heavy on releases, some run heavy on data. All of it comes off the same team
CRM Administration
Change requests, user setup, permission changes, and end-user support run through a queue your team can see. A rep who cannot find a record. A new hire who needs access on day one. A field manager who wants two columns moved on a list view. Each item is small, and they stack up fast when nobody owns them
Data Warehouse Operations
Every recurring data feed and refresh cycle gets monitored and validated against the prior load. Row counts, key overlap, date ranges, column layout. When a delivery arrives at half its usual size or a vendor drops a field, it gets flagged before it reaches a dashboard. Data warehouse operations is the least visible part of this work and the first thing anyone notices when it stops. The build itself is covered in our commercial data warehouse work
Territory and Targeting Maintenance
Alignment updates as the field organization changes. A territory splits, a region gets a new manager, two reps swap accounts, and the assignment rules have to follow within the week. Target lists refresh as new data arrives, and governed target change requests get worked against the rules your commercial team set. An alignment change that never reaches the CRM shows up two weeks later as reps calling on accounts that belong to someone else. The model underneath comes from HCP targeting, and this keeps it current
Analytics and Reporting
Reports, dashboards, and ad hoc analysis for sales, medical, and leadership, with every figure traceable back to a source table. When a number in a board deck gets questioned, someone can point at the query that produced it and the load it came from. Medical and commercial reporting stay separated the same way the platform separates them, so a medical dashboard does not pick up commercial figures because a folder got shared with the wrong group. Requests here run from a one-line filter change to a new dashboard for a therapeutic area review
Partner Integrations
Hub, specialty pharmacy, copay, and marketing platform feeds stay current as partners change formats, cadences, and contracts. A hub switches vendors. A specialty pharmacy moves from weekly dispense files to daily. A copay vendor adds three fields and drops one. Each of those is a small change to a working pipeline, and each one breaks reporting if nobody makes it
Enhancement Releases
The MVP keeps getting built out on a release cadence. Scope comes from what the field asks for in the first months of real use, which is rarely what the requirements doc predicted. Enhancements get bundled, tested in your sandbox, and shipped on a schedule your team can plan around. Anything that touches a validated process gets flagged before it enters a release, since that changes who has to sign off. Care coordinators, field reimbursement managers, and MSLs all send requests, and they rarely want the same thing
Patient-Level Targeting Refinement
As more patients start therapy, the knowledge workbench gets re-weighted, and each refresh delivers updated patient leads, linked to their treating providers, into Salesforce. Each pass has more confirmed cases to learn from than the last one did. We run the refinement with your commercial team, so what the field is seeing feeds back into the ranking. The method is the same one described in patient-level targeting
How the Engagement Works
Post-launch support falls apart when nobody can tell where a request went or when it ships. Four things keep that from happening
A Queue You Can See
Requests, status, and turnaround are visible to your team. Nobody has to email an account manager to find out whether last Tuesday's report change got picked up
Business-Hours Coverage
Business-hours coverage with a defined response window, set in the agreement, plus an escalation path for feed failures. A pipeline that dies Friday night should not wait until Monday for someone to notice
Release Cadence
Enhancements get bundled and shipped on a schedule, tested in your sandbox before they touch production. Your team knows what is in the next release and roughly when it ships
Grows With the Program
A second indication, a new market, another data license, a bigger field team: each one adds feeds, users, and reports, and each one gets folded into the same cadence. The engagement scales with the program instead of restarting as a new project
Why Teams Keep Us On
The Same Team That Built It
The people who built the warehouse, the feeds, and the CRM are the people running them. Nothing has to be reverse engineered out of a handoff document, and there is no discovery phase before the first request gets worked. A question about a feed goes to someone who wrote the pipeline
Tuned for Life Sciences
Commercial and medical firewall, consent-gated partner feeds, de-identified analytics keyed to a tokenized patient identifier, and the refresh cycles pharma data vendors run on. These are the standing conditions of the work here, handled as routine
Frequently Asked Questions
What does managed services cover?
CRM administration, data warehouse operations, territory and targeting maintenance, analytics and reporting, partner integrations, and enhancement releases. In practice that is the daily and weekly work of keeping the platform running, plus a release cadence for the things your team wants added.
Scope is written into the agreement so both sides know what is standing work and what gets quoted separately. A new partner integration or a major new module is usually its own project, and the ongoing engagement covers everything around it.
Do you run the data warehouse too, or only Salesforce?
Both. The warehouse, the feeds, and the CRM get managed as one platform, because that is how they behave. A specialty pharmacy file that arrives short changes what a rep sees in Salesforce two days later, and splitting those across two vendors means the diagnosis takes a week.
If you already have a data team running the warehouse, the engagement can be scoped to Salesforce managed services for pharma plus the integrations between the two.
How do enhancement requests get prioritized?
Your team sets priority. We size each request, flag anything that conflicts with existing configuration or a validated process, and schedule the work into the next release on the cadence.
What usually happens is that the first two release cycles fill up with things nobody predicted during the build. Field feedback after real use looks different from requirements gathered before it.
What happens as the program grows?
The engagement grows with it. A new indication or market brings new targets, new partners, and usually a new data license, and all of that arrives in the same queue and the same release cadence you already use. We resize the coverage on a schedule rather than renegotiating every time something is added.
Everything stays documented as it is built, including runbooks for the recurring feeds, the validation rules, and the deployment process, so nothing depends on one person's memory. That documentation exists so the platform survives staff changes on both sides. We run the platform for as long as the program runs.
How is this different from generic Salesforce managed services?
The life sciences specifics. Partner feeds from hubs, specialty pharmacies, and copay vendors change format on their own timelines. Patient-level analytics has to stay de-identified. The commercial and medical firewall has to hold in the configuration, beyond what a policy document says. Targeting refresh cycles run on data vendor delivery schedules nobody controls.
For Salesforce support outside life sciences, our general Salesforce managed services engagement runs the same way without the pharma data feeds.