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Editor’s Note: The following is a guest post by Sudhakar Shivaraju, vice president of global real estate systems at JPMorgan Chase.
Most enterprise software evaluations start with a features checklist and end with a decision that looks safer than it actually is.
Having led formal enterprise systems vendor evaluations twice in my career, in different industries and several years apart, I have come to believe that the real risk in these decisions is not choosing the wrong vendor.
The real problems arise when leaders evaluate the wrong things or misjudge the right things in the face of real constraints. But there is a structure that, in my experience, holds up in very different organizational contexts.
Leaders should first look at feature areas that reflect actual usage, rather than a generic feature list.
Instead of comparing vendors by feature, CIOs can break down the evaluation into the areas that actually determine whether the system works for the business, including:
- Security and compliance
- Integration and API architecture
- Friction in user experience and acceptance
- Vendor support and roadmap transparency
- AI capabilities
- Total cost of ownership, including implementation and migration risk.
Evaluating vendors within these domains, rather than a vendor-provided feature list, forces a more honest comparison because it reflects how the system actually works for users, not just what boxes it checks on a spec sheet.
CIOs need to weight domains based on their actual limitations, not a generic template. A globally operating, regulated organization has fundamentally different priorities than a smaller, regionally operating company. Security, compliance and data residency should be given more weight in a regulated environment than elsewhere.
Vendor support responsiveness is extremely important when the business relies on rapid problem resolution at scale, and less important when there is no internal capacity to manage most operational issues on its own.
There is no universal weighting. The weighting itself is a strategic decision; Getting it wrong will result in a technically correct evaluation, which will still result in the wrong choice.
Table of Contents
A correct assessment
When evaluating vendors, executives should view vendors’ roadmap information as first-party evidence rather than marketing material.
Vendor conferences, product roadmap meetings, and direct conversations with vendor leadership result in truly useful evaluation data, confirmed release schedules, features in development that address known gaps, and executive-level commitments that carry more weight than a sales presentation.
The discipline is to separate confirmed commitments from ambitious statements – and to explicitly state in the evaluation process which evaluations reflect current performance compared to expected performance. Conflating the two leads to a decision based on hope rather than evidence.
Companies can also benefit from assessing vendor support and responsiveness independent of roadmap transparency. These are constantly mixed, but are not the same. A vendor can be good at communicating what to expect and mediocre at resolving today’s support tickets.
If day-to-day responsiveness is a real risk in the assessment, don’t hide it with a strong roadmap presentation paper. This gap needs to be addressed explicitly, often through negotiated service level commitments, and cannot be underestimated because the provider’s future plans look impressive.
AI capability should also be viewed as its own domain and not a feature bullet point. Almost every vendor now claims to have some form of AI capability, while almost every review I’ve seen treats it as a single checkbox rather than an area worthy of real consideration.
Instead, companies should ask specific questions:
- Does the AI function work with the organization’s actual data or is it at a generic level?
- What does the provider’s data protection and handling model actually look like when AI is involved, especially if the organization operates under regulatory data location requirements?
- Is the AI functionality already mature and in production or is it a roadmap promise disguised as a current capability during the sales process?
Companies should also honestly account for transition costs, even those that no one wants to quantify.
Data migration, user retraining, workflow rebuilding, and integration restoration all come with real business disruption and costs. Because they are harder to quantify than a royalty comparison, they are often underweighted in vendor evaluations.
An established vendor with real, specific weaknesses can still be the right choice if switching costs are honestly included in the TCO comparison and not treated as an afterthought.
Estimate true results
The pattern I’ve observed across two very different evaluation processes in different industries is that the vendors themselves rarely change the outcome as much as the rigor of the evaluation structure.
A well-structured assessment with domains that reflect actual usage, weights that reflect actual constraints, and an honest accounting of both roadmap promises and switching costs tends to result in a defensible decision, regardless of which vendor ultimately wins.
On the contrary, a loosely structured evaluation leads to a plausible-sounding decision that often no longer holds true once the system is actually in production.
For technology leaders conducting their own vendor evaluations, the practical takeaway is simple. Before you create a scorecard, determine what the actual constraints are and let those constraints determine the weighting.
Comparing providers is the easy part. Building an evaluation structure that is honest enough to trust the outcome, and treats AI claims with the same care as security certifications, is the part that will actually determine whether you defend your choice in two years – or are still convinced by it.
https://www.ciodive.com/news/cio-evaluate-enterprise-software-vendors/826151/
