What biotechs can learn about outsourcing work

CROs, CDMOs, and other external parties are crucial pieces of the Life Science commercialization puzzle. But while biotech has embraced outsourcing in principle, we've lagged behind in how we coordinate these partnerships compared to other industries.

Outsourcing critical work is now standard across biotech. From early discovery through manufacturing, relying on external partners like CROs has become necessary to stay competitive. But while biotech has embraced outsourcing in principle, we've lagged behind in how we coordinate these partnerships.

Other industries offer valuable lessons. Semiconductor companies like Apple and NVIDIA create complex chips without manufacturing a single wafer themselves. E-commerce brands deliver millions of packages daily through networks they don't own. They've turned outsourcing from a necessary compromise into a strategic advantage.

The difference isn't in the decision to outsource – it's in the systems built around that decision. While biotech still manages external relationships through fragmented communications and manual processes, these other industries have developed sophisticated coordination mechanisms that deliver speed, visibility, and resilience.

Here are four lessons biotech can apply from their playbooks.

Lesson #1: Treat outsourcing as a structured platform

In semiconductors, companies like Apple, NVIDIA, and Qualcomm are fabless - they design chips, but outsource the most critical step – fabrication – to foundries like TSMC (Taiwan Semiconductor Manufacturing Company). Chip fabrication is staggeringly complex: a single wafer undergoes hundreds of lithography, etch, and deposition steps across a 10–15 week production cycle. A design defect at any stage can sink the entire batch.

To succeed, chip companies and foundries form tightly-knit partnerships rather than simple vendor relationships. A famous case is Apple and TSMC’s partnership – Apple relies on TSMC’s cutting-edge nodes for its A-series and M-series chips. Apple and TSMC coordinate like two divisions of the same company. Apple pre-purchases capacity, co-develops process technologies, and stations engineers near TSMC fabs to ensure tight feedback loops. This is not a series of transactional handoffs – it's a continuous collaboration. Design handoff, test chip runs, yield tuning, ramp-up: each stage is coordinated in real time.

E-commerce takes a similar approach. Brands hand over inventory to 3PL networks like Amazon FBA or ShipBob and let them handle the logistics end-to-end. In all cases, the outsourcing is managed via well-defined processes and tech platforms: merchants must follow specific inbound shipping workflows, and once inventory is in the network, the 3PL’s system drives the order fulfillment process end-to-end. The whole system is built to scale across thousands of vendors, locations, and SKUs.

Across both industries, there’s a high degree of structure that’s lacking in biotech. The typical workflow between biotechs and CROs involves sending samples or specifications, exchanging emails about timelines, holding periodic update calls, and eventually receiving results as standalone files. In reality, effective outsourcing requires a connective layer – whether it's specialized software, shared platforms, or structured protocols – that binds separate organizations into a unified workflow.

Lesson #2: Data exchange should be systematic and standardized

A foundation of successful outsourcing is systematic, often automated, data exchange between a company and its external partners. 

In semiconductors, data sharing is highly structured. Design files, process kits, yield data, and production updates flow between companies via standardized formats (e.g., GDSII, OASIS) and secure pipelines. Platforms like TSMC’s Open Innovation Platform institutionalize this process, aligning foundry roadmaps with design tools and giving customers early access to process data. Internally, companies use PLM systems and supplier portals to exchange bills of materials, design revisions, and engineering change orders, all backed by standards like RosettaNet to enable tight coordination.

E-commerce takes this a step further with real-time, API-driven fulfillment systems. When a customer places an order, it instantly triggers a pick-pack-ship workflow at the 3PL warehouse, with inventory levels and tracking info pushed back to the merchant’s system automatically. Leading 3PLs like Shipbob  have built platforms that integrate merchants, carriers, and warehouse systems into a continuous digital loop. This means merchants can see stock levels and orders in real time as if the outsourced warehouses were an extension of their own system. 

Biotech companies working with external partners usually lack this level of integration. Data from CROs often comes back in inconsistent formats - spreadsheets, PDFs, raw instrument files - with no unified system for analysis. Project managers rely on periodic update meetings, email threads, or standalone tools to track progress, and it’s not uncommon for critical path timelines to live in spreadsheets that aren’t connected to the CRO’s systems. This can all lead to misalignment. For example, a delay in an experiment might not surface until a scheduled check-in. Without standardized data models, APIs, or shared dashboards, results have to be manually reconciled and version control issues are common. 

Lesson #3: Visibility is necessary  

One of the biggest challenges in outsourcing is maintaining visibility into work happening outside your organization. 

In semiconductors, companies like Qualcomm or Apple get continuous updates from foundries like TSMC on production status, yield, and quality. Secure portals track wafer lots through each manufacturing step – lithography, etch, packaging – so teams can intervene early if issues pop up.

Similarly, e-commerce brands have complete visibility into inventory levels, order statuses, and fulfillment metrics across their partner networks. In logistics, Flexport clients get a real-time dashboard of their shipments: which ocean containers have cleared customs, which trucks are delayed, which warehouses are receiving stock. ShipBob offers merchants SKU-level visibility across all fulfillment centers. You can see if Order #14839 is in picking, packing, or transit. This level of visibility means exceptions get caught early. You don’t need to wait for a quarterly review to discover a delay - you see it the day it starts.

Biotech rarely has this level of transparency. CROs and CMOs often deliver data only after a batch or study is complete, with no visibility into real-time progress. Sponsors may not learn about delays or failed assays until formal reports arrive. Fragmented systems and data we mentioned earlier contribute to this. While some CROs now offer project portals or shared tools, these are the exception, not the norm. As expectations shift, biotechs are beginning to demand the same real-time visibility that other industries already consider table stakes.

The principle is simple but powerful: you can't manage what you can't see. As expectations shift, biotechs are beginning to demand the same real-time visibility that other industries already consider table stakes.

Lesson #4: Exceptions happen and systems should catch them

Risk is inevitable when you outsource complex work. The real question is whether your systems are designed to absorb and respond to it.

In the wake of the pandemic-era chip shortages, semiconductor companies invested heavily in resilience. This included second sourcing (i.e. having a backup partner), long-term agreements to secure capacity, and inventory buffers for critical components. 

E-commerce fulfillment operates similarly. When Flexport sees a port delay, its system can automatically rebook trucking, shift warehouse slots, or notify the merchant and customer. If Amazon FBA hits a fulfillment bottleneck in one location, orders are rerouted to another. This illustrates exception management in action: detect delay -> update plans across multiple partners (port, trucker, warehouse, customer) -> execute contingency (later pickup, etc.).

Biotech’s exception handling looks a lot like crisis management. When something breaks - an assay fails, a CRO misses a milestone, a CMO hits a production snag - the default response is to scramble. Everyone tries to patch the problem without derailing the whole timeline. But there’s rarely a system in place to catch the issue earlier, reroute work, or capture what went wrong for next time. The same failure modes - reagent variability, contamination, equipment downtime - show up again and again, and each time it’s treated like a one-off. There’s no structured way to say: “Here’s what happens when our primary assay fails,” or “Here’s our backup plan if CRO X slips on timelines.”

Some teams try to preempt risk by working with multiple vendors, stockpiling materials, or keeping tasks in-house, but those are insurance policies, not response systems. What’s missing is a layer of operational infrastructure, like dashboards that flag when a CRO misses key milestones, backup vendors or protocols pre-validated and ready, and exception-handling playbooks that turn emergencies into manageable workflows. 

Ultimately, biotech is behind on systems  

The good news is that biotech doesn't need to invent solutions from scratch. The playbook for effective outsourcing already exists in other industries. APIs, shared platforms, standardized data formats, and exception management systems are proven approaches waiting to be adapted to our context.

Semiconductors and e-commerce didn't transform their outsourcing models overnight – they evolved over years as complexity and scale demanded better coordination. Biotech is following a similar trajectory, just at an earlier stage.

At Kaleidoscope, we're helping accelerate this evolution. Our platform provides biotech companies with the same coordination capabilities that power outsourcing in other industries: real-time visibility into external work, structured data exchange between organizations, and collaborative workflows that connect internal and external teams. By bringing these approaches to biotech, we're working to turn partner coordination from a friction point into a strategic advantage.

The companies that adopt these coordination principles first will gain significant advantages: faster development timelines, better resource utilization, and more resilient operations. We’re excited about this shift –  when biotech companies can coordinate with external partners as seamlessly as Apple works with TSMC or brands work with fulfillment networks, we'll all benefit from faster, more reliable paths to bring new therapies to patients.

Kaleidoscope is a software platform for biotechs to robustly manage their R&D operations. With Kaleidoscope, teams can plan, monitor, and de-risk their programs with confidence, ensuring that they hit key milestones on time and on budget. By connecting projects, critical decisions, and underlying data in one spot, Kaleidoscope enables biotech start-ups to save months each year in their path to market.