Defining your buyer when the decision maker trained in a different discipline
Reading time: 9 minutes
The first three articles in this Pillar 3 series established where your product sits in the workflow, who else competes at the same step, and whether the users running that workflow will pay to change it. This article turns to the person who authorises the change.
In many technology markets, the buyer and the user are the same person, or at least share a professional vocabulary. In ancillary TechBio for developmental and stem cell science, they frequently are not. The scientist running the workflow may be a trained developmental biologist. The person signing the purchase order may be a co-founder who trained as a mechanical engineer, a CTO with a background in data science, a CSO whose doctorate is in polymer chemistry, or a business development lead who came from medical devices. They all have an educated professional awareness of stem cell biology. None of them reads the literature the way a developmental biologist does, evaluates evidence the way a cell biologist does, or responds to the same signals of credibility.
This mismatch defines the buyer problem for ancillary TechBio. Identifying the buyer is not a matter of finding the right job title. It is a matter of understanding which discipline shaped their reasoning, what forms of evidence they trust, and how the internal decision moves from a technical evaluation to a commitment of resources.
The cross-disciplinary decision maker
The decision makers at TechBio companies that build tools for stem cell science have a characteristic profile. The founding and executive teams typically include scientists or engineers trained in domains other than developmental and stem cell biology — physics, mechanical or chemical engineering, computer science, materials science, biomedical engineering — who have developed an awareness of stem cell science through collaboration, prior employment, advisory relationships, or their own reading. They are technically sophisticated, sceptical of unsubstantiated claims, and generally more comfortable with quantitative engineering-style evidence than with the interpretive, context-dependent forms of evidence that characterise much of cell biology.
This profile matters because it shapes what the buyer finds convincing and what they find opaque. An engineer evaluating a new imaging tool for stem cell characterisation will look for specifications: resolution, throughput, signal-to-noise ratio, repeatability across defined conditions. These are familiar metrics. What they may not be equipped to evaluate is whether the biological readout the tool provides — a marker expression profile, a differentiation propensity score, a viability measurement — is a meaningful predictor of what the cells will do downstream. That question requires the kind of contextual biological knowledge that sits outside their training.
The inverse also applies. A developmental biologist evaluating the same tool may recognise immediately that the biological readout is informative for one cell type but misleading for another, that the marker panel omits a critical indicator, or that the culture conditions used in the validation study do not reflect manufacturing conditions. But they may not be the person who decides whether the tool gets purchased, because they do not hold the budget, the operational authority, or the strategic responsibility.
The practical consequence is that the TechBio company selling the tool has to satisfy two different evidentiary standards simultaneously: the engineering standard of the decision maker and the biological standard of the user. Failing to satisfy either is sufficient to block the sale.
How different disciplines read evidence
Understanding the evidentiary preferences of cross-disciplinary decision makers is not a question of stereotyping. It is a question of recognising which forms of reasoning each discipline prioritises and where the gaps in translation sit.
Engineers and physicists tend to evaluate claims against defined specifications, controlled comparisons, and statistical confidence intervals. They are comfortable with quantitative benchmarks and expect reproducible performance under stated conditions. They may be less comfortable with the inherent variability of biological systems, where the same protocol produces different outcomes depending on the cell line, the passage number, the donor, or the season. A claim that a tool "improves cell yield" without specifying the conditions, the baseline, and the variance will not satisfy an engineering-trained buyer — nor should it. But a biologically rigorous study that reports results narratively without engineering-style metrics may also fail to register.
Data scientists and computational biologists evaluate claims against dataset quality, model assumptions, and statistical methodology. They will scrutinise sample sizes, ask about batch effects, and expect transparent data-processing pipelines. A tool that generates a biological readout without explaining how the data was processed, what the sources of noise are, and how the algorithm was validated will face resistance from this buyer even if the biology is sound.
Business development and commercial leads evaluate claims against the strategic fit with the company's portfolio, the size of the addressable market, the credibility of the team presenting the tool, and the risk profile of the adoption decision. They may not evaluate the biology at all; they may rely on an internal scientific advisor's assessment and focus instead on commercial terms, supply-chain reliability, competitive positioning, and the speed of return on investment.
The pattern across all three groups is the same. They are not hostile to biological evidence. They are trained to read evidence in forms that biology does not always provide. A tool that presents its case in the forms the decision maker is trained to evaluate — quantified specifications, controlled comparisons, transparent methodology, clear commercial framing — has a structural advantage over one that presents the same evidence in a form that requires biological fluency to interpret.
The internal decision path
Identifying the buyer is necessary but not sufficient. The tool also has to traverse the internal decision path, which in a TechBio company typically involves multiple roles with different concerns.
The technical lead or scientific officer evaluates the tool against the biological requirements of the workflow. Their question is: does this tool do what it claims, under our conditions, with our cell types, at our scale? Their evidence standard is biological performance data relevant to their specific use case.
The operations or manufacturing lead evaluates the tool against the practical constraints of the workflow. Their question is: does this tool fit our facility, our throughput requirements, our data systems, our SOPs? Their evidence standard is operational compatibility.
The regulatory or quality lead evaluates the tool against the compliance requirements of the products the workflow serves. Their question is: does this tool come with documentation, traceability, and validation data sufficient for our quality system? Their evidence standard is regulatory fitness.
The CEO, CTO, or founding team member makes the final resource-allocation decision. Their question draws on all three evaluations but is ultimately strategic: does this tool advance the company's position, at a cost we can justify, on a timeline that aligns with our milestones?
The ancillary technology company that understands this internal path can prepare materials, data packages, and conversations that speak to each role. The one that does not will find that a successful technical evaluation stalls at the operations review, or that a positive operations assessment is overruled by a regulatory concern, or that all three evaluations are positive but the strategic decision is to defer the purchase because the budget is committed elsewhere.
The workforce context
The cross-disciplinary decision problem is magnified by a workforce reality in the cell and gene therapy sector. A 2024 roundtable review published in Cytotherapy, involving the International Society for Cell & Gene Therapy and the Alliance for Regenerative Medicine, documented the skilled worker shortage across CGT manufacturing and quality control, and noted that the roles being filled increasingly require competencies that cut across traditional disciplinary boundaries [1]. The report observed that automation could lower barriers to entry for a wider pool of talent but would not replace the need for on-site staff, and that training strategies would need to differ substantially depending on the type of manufacturing operation [1].
For the ancillary TechBio company, this has a direct positioning implication. The people evaluating your tool may be newer to stem cell biology than you assume. A manufacturing technician assessing a cell culture tool may have come from a pharmaceutical small-molecule background and have limited hands-on experience with pluripotent stem cells. A quality manager reviewing your documentation may be applying frameworks developed for conventional biologics that do not map cleanly onto cell therapy products. The evidence you provide needs to be self-contained enough to be evaluated by someone whose training in your specific domain may be recent and practical rather than deep and academic.
A survey of FACT-accredited cell processing facilities in the United States found substantial variability in infrastructure, quality practices, and use of automation across facilities, even within a common accreditation framework [2]. The implication for the tool vendor is that the buyer profile is not uniform even within a single market segment. The people making procurement decisions at one facility may have a very different background, experience base, and evidence threshold from those at another.
Practical guidance for reaching cross-disciplinary buyers
Four principles follow from the analysis above.
Lead with the workflow problem, not with the mechanism. The cross-disciplinary buyer cares about what the tool does for their workflow. The biological mechanism by which it works is important to the scientific evaluator but secondary to the decision maker. Open the conversation with the workflow step, the before-and-after performance, and the operational fit. Let the mechanism come later, in technical documentation, for the audience that needs it.
Provide evidence in the buyer's native format. If the buyer is engineering-trained, provide quantified specifications: throughput per hour, yield percentage with variance, comparability data against a defined baseline. If the buyer is commercially oriented, provide a cost-per-unit analysis, a competitive comparison against the status quo, and a projected return-on-investment timeline. If the buyer is regulatory-focused, provide documentation of material traceability, process validation, and qualification data. The same underlying evidence can be presented in multiple formats. The effort of formatting it for each audience is repaid in shorter sales cycles and fewer stalled evaluations.
Anticipate the internal handoff. The person you speak to first is rarely the person who makes the final decision. Ask, early in the conversation, how the evaluation process works internally: who will be involved, what their concerns are likely to be, and what evidence they will need. Offer to provide a data package tailored to each role. This is not a sales technique; it is a recognition that the internal decision path involves multiple disciplines and that a single set of materials cannot serve them all.
Respect what the buyer knows and what they do not. The cross-disciplinary buyer is not ignorant. They are trained in a different discipline. They bring analytical rigour, operational experience, and strategic judgement that the cell biologist may lack. The positioning conversation is not a tutorial; it is a collaboration between two forms of expertise. The ancillary TechBio company that treats the buyer as a peer to be informed, rather than a student to be educated, earns trust faster and loses it less often.
What this leads to next
Defining the buyer and understanding their decision process prepares the ground for the next question: how to describe the product in language that those buyers recognise as credible. The article on framing technical value addresses this directly — how to write about a tool in terms that biologists and engineers both respect, without either condescending to one or losing the other. For applications where the biology itself is the enabling technology and the buyers are even further from the core science, the article on prior art in laboratory and domesticated species adjusts the buyer logic for the conservation and emerging-application context.
For readers who want the biological grounding that informs what the cross-disciplinary buyer is evaluating, the Pillar 1 series on developmental and stem cell science provides the foundation. The Pillar 2 series on why TechBio fails provides the failure-mode context that many of these buyers are working to avoid.
References
[1] Hopewell E, Pike NR, Lembong J, Hewitt M, Fekete N. Filling the gap: the workforce of tomorrow for CGT manufacturing as the sector advances. Cytotherapy. 2024;26(6):540-545. DOI: 10.1016/j.jcyt.2024.03.007
[2] Elsallab M, Bourgeois F, Maus MV. National Survey of FACT-Accredited Cell Processing Facilities: Assessing Preparedness for Local Manufacturing of Immune Effector Cells. Transplant Cell Ther. 2024;30(6):626.e1-626.e11. DOI: 10.1016/j.jtct.2024.03.016
About StemCells.Help
StemCells.Help is an advisory consultancy that aids innovation and real-world impact of life science applications built on developmental and stem cell biology. Founded by Dr Paul De Sousa, it draws on over four decades of experience spanning early embryo development, animal cloning, pluripotent stem cell manufacturing, and technology commercialisation. If you build tools for these domains or work in an emerging application where the biology is the enabling technology, StemCells.Help can provide experienced scientific counsel to ground your decisions. To discuss your needs, talk to Paul.
ORCID: 0000-0003-0745-2504
Web: stemcells.help
