For decades, Information Systems (IS) has defined itself through the lens of traditional social science. We have mastered the art of explaining phenomena—why users adopt technologies, how organizations respond to digital change, how data shapes decision-making, and what factors influence system success.

This explanatory tradition has produced strong theories and sophisticated statistical methods. It has given IS a seat at the academic table.

But it has also created a growing problem:

IS has become incredibly good at describing the world, but not nearly good enough at designing solutions to improve it.

This is the quiet crisis inside the IS discipline. And understanding this gap is the first step toward understanding why Design Science Research (DSR) is not just important — it is essential for the future of IS.

Let’s unpack this clearly.

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1. The Dominance of Traditional Social Science in IS

Look at the major IS journals over the past 20+ years. You will find research dominated by:

• Structural equation modeling
• Regression studies
• Theory-driven surveys
• Experiments testing hypotheses
• Interpretive work aimed at explaining human experiences

These approaches are powerful. They reveal how and why things happen.

But here is the catch:

Explanatory research rarely produces artifacts. It rarely builds things. It rarely creates solutions.

Consider a simple example:

A typical IS paper might study why employees resist new technology adoption.
It might generate a new model or identify new variables.

Useful? Yes.
Transformational? Not really.

What organizations needed was a tool, design, interface, process, or system that reduces resistance.
Instead, they got an explanation.

This is the recurring pattern:

✔️ We understand the problem
❌ We do not build solutions for the problem

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2. Why This Gap Threatens the Future of IS

While IS scholars focus on explanation, practitioners face real, messy, urgent problems:

• AI integration
• Digital transformation
• Process redesign
• Data quality
• Automation challenges
• Decision-support failures
• Cybersecurity misalignment

These problems require design — the creation of artifacts.

Meanwhile, fields like:

• Software engineering
• Requirements engineering
• HCI
• Computer science

have embraced design as their research identity.

As a result:

Entire domains that historically belonged to IS are migrating to engineering fields.

Systems analysis and design — once a crown jewel of IS — is now largely driven by engineering research.

Why?

Because engineers value solution-building, while IS overvalues explanatory theory.

Left unaddressed, this trend threatens IS in three ways:

1. Loss of intellectual territory
2. Declining relevance to practice
3. A widening gap between research and real-world problems

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3. What Other Disciplines Understand That IS Often Misses

Engineering disciplines treat design as a legitimate, rigorous, and essential form of research.

In engineering, it is normal — even expected — that a research paper will:

• Invent an algorithm
• Build a tool
• Create a process
• Develop a prototype
• Demonstrate and test it

This is not considered “applied work” or “consulting.”
This is core scientific contribution.

IS, however, has historically held a bias:

If it’s not theory-testing or theory-building, then it’s somehow less academic.

This mindset is slowly changing — thanks to the increasing pressure for relevance.
But the discipline still lacks the robust, shared culture of design that engineering fields enjoy.

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4. The Slow Rise of DSR in IS — and Why It Stalled

Scholars like:

• Hevner
• March & Smith
• Walls et al.
• Peffers et al.
• Gregor & Jones

successfully argued that design is a valid scientific paradigm.
They showed that building artifacts can be just as rigorous — and often more impactful — than traditional theory work.

Their contributions laid the intellectual foundation for Design Science Research.

But here’s the reality:

Despite these successes, DSR has not become mainstream in IS.

Why?

Because IS lacks what every dominant research paradigm needs:

• Shared expectations
• A common structure
• A standard “template”
• A mental model for reviewers and editors
• A clear methodology for researchers

Without these, DSR looks unfamiliar.
Unfamiliar work is harder to evaluate.
Harder-to-evaluate work is harder to publish.

And so the cycle persists.

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5. The Mental Model Problem

Every IS researcher trained in social science knows how to evaluate:

• A regression study
• A survey paper
• A theory-building paper
• A qualitative interpretive paper

We have mental templates for what “good” looks like.

But for Design Science Research?

There is no universally recognized structure.

This creates several barriers:

• Reviewers struggle to assess rigor
• Authors struggle to present their work
• DSR gets mistaken for practitioner consulting
• Journals become hesitant to publish artifact-centric research
• Students avoid DSR because it feels unclear and risky

In short:

DSR is legitimate — but it is not yet “normalized.”

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6. The Missing Piece: A Standardized Methodology

While prior scholars have:

• Described what DSR is
• Listed its components
• Defined its principles
• Defended its legitimacy

They did not provide:

👉 A step-by-step method for doing AND presenting Design Science Research.

Researchers had the “why” and the “what,”
but not the “how.”

This is the gap the Peffers et al. paper you’re reading aims to fill.

It introduces:

• A common framework
• A recognized process
• A reviewer-friendly template
• A mental model for evaluation
• A clear methodology for conducting and communicating DSR

This is why the Design Science Research Methodology (DSRM) became so influential.

It gave IS exactly what it needed:

A shared language for design. A structure. A method. A way forward.

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Final Thoughts: Why DSR Is the Future of IS

The IS discipline sits at the intersection of technology, organizations, and people.
It cannot afford to be a field that only explains what happens — it must also shape what happens next.

Design Science Research is how we build that future.
It allows us to:

• Create new solutions
• Bridge research and practice
• Influence innovation
• Reclaim core IS domains
• Produce artifacts that matter
• Strengthen the discipline’s identity

We need a design-oriented culture because the problems organizations face today demand solutions, not only explanations.

DSR is how IS becomes impactful, influential, and forward-looking again.