The DeLone & McLean Model Is Dead. Here's What ERP Research Should Use Instead.

What DeLone & McLean got right

William DeLone and Ephraim McLean published the original model in 1992 and updated it in 2003. It earned its dominance honestly. It gave a fragmented field a common language: a system can succeed technically and fail in use; benefits must be net of costs; satisfaction and use are related but not identical. Any serious ERP study still owes it rent.

But notice what the model assumes. It starts measuring at the point where a system already exists and people are already using it. System quality, information quality, service quality — these are properties of the technology and its support. Use and satisfaction are properties of the individual's encounter with it. Nowhere in the model will you find the organization that has to change: its readiness, its leadership, its capability, its willingness. The model measures the success of a system inside an organization it treats as a constant.

In 1992, that was a defensible simplification. Software was installed, training was an event, and the organization bent around the system slowly. In 2026 it is not defensible. ERP is cloud-delivered and continuously updated. AI copilots are being layered onto workflows quarterly. The organization is not a constant — it is the variable.

The blind spot: readiness and adoption are mediators, not outcomes

Here is the empirical problem every practitioner recognizes and the classic design keeps missing. Two companies implement the same ERP, with the same integrator, on the same timeline. One captures the business case; the other drowns in workarounds. Score both on DeLone & McLean at go-live and they can look identical: system quality fine, information quality fine, users logging in, satisfaction mediocre in both. The difference that explains the divergence sits upstream of every D&M dimension — in whether the organization was ready: leaders aligned, managers equipped, roles redesigned, adoption campaigned for rather than announced.

In research terms, readiness and adoption are mediators. They carry the effect of technology, organization, and environment into the success outcomes. A model that omits them does not just leave variance unexplained; it misattributes the variance it does explain, crediting system quality for what leadership readiness actually did.

The contemporary design: TOE + readiness + D&M

The stronger design now used in current ERP empirical research keeps DeLone & McLean — but demotes it to what it actually is: the measurement of the dependent variable. Around it, the study is rebuilt:

Independent variables — the TOE framework. Tornatzky and Fleischer's Technology–Organization–Environment framework (1990) supplies the explanatory structure: technological factors (complexity, compatibility, relative advantage), organizational factors (top management support, digital capability, business process fit), and environmental factors (competitive pressure, vendor and regulatory environment).

Mediators — change readiness and user adoption. Between the TOE conditions and the success outcomes sit the two constructs that convert potential into results: organizational change readiness — the shared resolve and capability to implement the change — and actual user adoption, meaning demonstrated use of the new workflows, not attendance at training.

Dependent variable — ERP success, measured on the D&M dimensions. System quality, information quality, service quality, use, user satisfaction, and net benefits remain the right outcome battery. They are simply no longer asked to explain themselves.

Modern extensions plug into the same architecture where the research question demands it: AI adoption and human–AI collaboration maturity, organizational agility, and business process fit are the additions showing up most often in contemporary designs — and in health-sector IS research, the HOT-fit tradition (Human, Organization, Technology fit; Yusof and colleagues, 2008) makes the same point from a different direction: the human and organizational terms were never optional.

The contemporary design, at a glance:

• Independent variables (TOE): technology (complexity, compatibility, relative advantage) · organization (top management support, digital capability, business process fit) · environment (competitive pressure, vendor and regulatory forces)
• Mediators: organizational change readiness and user adoption — the constructs that convert conditions into outcomes
• Dependent variable: ERP success measured on the DeLone & McLean dimensions — system, information and service quality, use, user satisfaction, net benefits
• Modern extensions: AI adoption, organizational agility, digital capability
• The discipline: readiness is measured before and during implementation, in evidence — never inferred from satisfaction scores after go-live

What this means in practice — for researchers and for sponsors

For researchers, the implication is methodological discipline. If your ERP study has no readiness construct, you are studying system quality and calling it implementation success. If readiness appears only as a satisfaction proxy in a post-go-live survey, you have measured the mediator after it finished mediating. Readiness must be measured before and during implementation, with evidence statements about what the organization demonstrably does — leaders articulating the case, managers able to explain role impacts, lessons from failed initiatives changing the next attempt — not intentions self-reported on a Likert scale after the fact.

For practitioners, this is the design logic behind CHANGEReadyX™, the readiness diagnostic I built at TAPAS Advisory. Its 24 evidence statements across the Transformation Intelligence Index (TII™) pillars — cognitive and learning agility, human–AI collaboration maturity, ethical and cultural resilience, execution velocity — exist to operationalize exactly the mediator this article argues for: readiness measured early, in evidence, so that intervention happens while it can still change the outcome. An ERP business case does not die at go-live; it dies in the gap between a system that works and an organization that was never readied to work differently.

Go-live at sunrise — the dashboards all glow bright green; readiness decides.

The question to ask of every ERP study — and every ERP program

DeLone & McLean will keep being cited, and they should be: the outcome dimensions are theirs. But the next time you read — or fund — an ERP success study, ask one question: where is readiness in this model? If the answer is nowhere, the study will tell you, with great statistical confidence, that the system was good. It will tell you nothing about whether the organization was ever going to let it succeed.