Editor’s note: The following is a guest post from Sudhakar Shivaraju, VP, global real estate systems at JPMorgan Chase.
Most enterprise software evaluations start with a feature checklist and end with a decision that looks more confident than it actually is.
Having led formal vendor evaluations for enterprise systems twice in my career, in different industries and years apart, I’ve come to believe the real risk in these decisions isn’t picking the wrong vendor.
The real problems arise when leaders evaluate the wrong things, or weigh the right things incorrectly, for the actual constraints. But there’s one structure that, in my experience, holds up across very different organizational contexts.
Leaders should start by looking at functional domains that reflect real usage, not a generic feature list.
Rather than comparing vendors feature by feature, CIOs can break the evaluation into the domains that actually determine whether the system will work for the organization, including:
- Security and compliance
- Integration and API architecture
- User experience and adoption friction
- Vendor support and roadmap transparency
- AI capabilities
- Total cost of ownership, including implementation and migration risk.
Scoring vendors within these domains, rather than against a vendor-supplied feature list, forces a more honest comparison because it reflects how the system will actually function for users, not just what boxes it checks on a spec sheet.
CIOs must weight the domains to their actual constraints, not a generic template. A regulated organization operating globally has fundamentally different priorities than a smaller, single-region company. Security, compliance and data residency should carry more weight in a regulated environment than they would elsewhere.
Vendor support responsiveness matters enormously if the organization depends on fast issue resolution at scale, and matters less if there’s no internal capacity to self-manage most operational issues.
There is no universal weighting. The weighting itself is a strategic decision; getting it wrong produces a technically correct evaluation that still leads to the wrong choice.
A proper assessment
When evaluating providers, executives should treat vendor roadmap intelligence as first-party evidence, not marketing material.
Vendor conferences, product roadmap sessions and direct conversations with vendor leadership produce genuinely useful evaluation data, confirmed release timelines, in-development features that address known gaps and executive-level commitments that carry more weight than a sales deck.
The discipline is separating confirmed commitments from aspirational statements — and being explicit in the evaluation process about which scores reflect current capability versus anticipated capability. Conflating the two produces a decision built on hope rather than evidence.
Businesses can also benefit from scoring vendor support and responsiveness separately from roadmap transparency. These get conflated constantly, but they are not the same. A vendor can be excellent at communicating what’s coming and mediocre at resolving today’s support tickets.
If day-to-day responsiveness is a genuine risk in the evaluation, don’t let a strong roadmap presentation paper over it. That gap needs to be addressed explicitly, often through negotiated service level commitments, not assumed away because the vendor’s future plans look impressive.
AI capability should also be looked at as its own domain rather than a feature bullet point. Nearly every vendor now claims some form of AI capability while nearly every evaluation I’ve seen treats it as a single checkbox instead of a domain worth real scrutiny.
Instead, enterprises should ask specific questions:
- Does the AI feature operate on the organization’s actual data or is it a generic layer?
- What does the vendor’s data privacy and handling model actually look like once AI is involved, particularly if the organization operates under regulatory data residency requirements?
- Is the AI functionality mature and in production today or is it a roadmap promise dressed up as a current capability during the sales process?
Organizations should also account for switching costs honestly, including the ones nobody wants to quantify.
Data migration, user retraining, workflow rebuilding and integration re-establishment carry real operational disruption and cost. Because they are harder to quantify than a license fee comparison, they are often underweighted in vendor evaluations.
An incumbent vendor with real, specific weaknesses can still be the right choice once switching costs are honestly built into the total cost of ownership comparison, not treated as an afterthought.
Estimating true outcomes
The pattern I’ve seen across two very different evaluation processes, in different industries years apart, is that vendors themselves rarely change the outcome as much as the rigor of the evaluation structure does.
A well-structured evaluation, with domains that reflect real usage, weights that reflect real constraints and an honest accounting of both roadmap promises and switching costs, tends to produce a defensible decision regardless of which vendor ultimately wins.
On the contrary, a loosely structured evaluation produces a plausible-sounding decision that often fails to hold up once the system is actually in production.
For technology leaders running their own vendor evaluations, the practical takeaway is simple. Before building a scorecard, decide what the actual constraints are and let those constraints determine weighting.
The vendor comparison is the easy part. Building an evaluation structure honest enough to trust the result, one that treats AI claims with the same scrutiny as security certifications, is the part that actually determines whether you’ll be defending your choice two years from now — or still confident in it.
