Decision automation software is essential business infrastructure. As organizations scale and data becomes central to every process, the need for swift, policy-aligned decisions has never been greater. Whether you’re validating transactions, detecting fraud, or optimizing pricing, automation ensures consistency, compliance, and clarity.
But this raises a pivotal question: Should your team build a custom decision automation system, or buy a proven solution?
One way to approach the choice is through the lens of Nobel Prize-winning economist Ronald Coase. In his foundational work, The Nature of the Firm, Coase introduced the idea of comparing administrative costs, the costs of coordinating work internally, against transactional costs, costs associated with acquiring external solutions. Applied to software, his logic offers a clear way to evaluate where your time, talent, and investment deliver the most value.
In this blog, we’ll use that framework to explore the build vs. buy decision in the context of decision automation: what’s involved, what each path demands, and how platforms like InRule help strike the right balance between control, speed, and scalability.
Understanding Decision Automation Software
Decision automation software enables organizations to make structured, scalable decisions that comply with policies and regulations, minimizing manual intervention.
These systems typically combine three core capabilities:
- AI models analyze data to uncover patterns and surface predictions that inform downstream actions.
- Business rules engines enforce decision logic by applying internal policies and regulatory frameworks in a transparent and auditable way.
- Automation tools then apply those decisions directly within enterprise systems, triggering next steps in customer service, finance, or operations.
This structure allows organizations to act quickly without compromising accuracy or accountability. Industries that manage high-stakes, high-volume decisioning benefit significantly from this approach. Examples include:
- Financial services: Banks use decision automation to assess credit risk, monitor transactions for signs of fraud, and ensure compliance with regulatory standards. Each decision follows a consistent logic path, reducing both manual effort and the risk of error.
- Healthcare: Payers and providers use automation to verify eligibility and adjudicate claims. These systems also help enforce clinical policies and payer contracts, improving both efficiency and compliance with care standards.
- Retail and e-commerce: Brands apply automation to adjust pricing based on real-time inventory, personalize promotions for different customer segments, and streamline fulfillment across channels.
With data insight and governed execution, decision automation allows enterprises to move fast without compromising on accountability. Now let’s dive into the economics behind the build vs. buy dilemma for decision automation software.
The Economics Behind Build vs. Buy
According to Coase, firms exist because they can sometimes coordinate production more efficiently internally, rather than relying on the market. This efficiency hinges on minimizing transaction costs: the hidden costs of negotiating, managing, and enforcing exchanges.
When it comes to decision automation, the same logic applies:
- Build when internal coordination is less costly and more efficient than dealing with the market.
- Buy when the market provides a solution that reduces the total cost of achieving the same outcome.
Let’s take a look at the pros and cons of building vs. buying decision automation software, particularly for key considerations like cost, time to deployment, customization, IT resource requirements, and scalability.
The Case for Building Decision Automation Software
Organizations often lean toward building when they have highly unique needs, proprietary systems, or strict regulatory frameworks. Still, that path comes with tradeoffs that should be carefully considered.
The Pros of Building
- Custom development aligns precisely with internal workflows, so teams receive a platform built around how the organization actually operates.
- The organization enjoys direct control over system architecture and logic, allowing for full ownership of how decisions are executed and maintained.
- Legacy systems can be tightly integrated, reducing the need for replatforming or workaround solutions.
The Cons of Building
- Organizations must pay high up-front costs and work on extended development timelines, especially during initial design and implementation.
- Ongoing internal maintenance responsibilities, including performance tuning and compliance updates, consume internal time and resources.
- Rule changes depend on developer availability, which can delay updates and slow response to business needs.
According to Coase, building increases internal coordination costs, particularly when a system must be developed and maintained across teams. While a custom solution may appear better suited to specialized needs, it can reduce agility as business demands evolve.
The Case for Buying Decision Automation Software
Buying shifts the responsibility of development and upkeep to the vendor, giving internal teams more room to focus on managing logic and outcomes. Proven platforms come equipped with built-in architecture, support, and compliance frameworks that accelerate deployment and make scale easier to achieve.
The Pros of Buying
- Time to deployment is faster, with prebuilt architecture and guided implementation.
- Costs remain predictable, with licensing models that simplify budgeting and reduce financial risk.
- No-code and low-code tools support collaboration, enabling business users to update logic while IT maintains oversight.
- The platform scales with complexity, allowing decision logic to expand without rework or system strain.
The Cons of Buying
- Vendor software may require configuration work, especially to align logic with internal processes and existing systems.
- Organizations may perceive some limits on control, though governance features and customization options can address this concern.
Coase’s framework suggests that when a vendor offers a proven solution with lower coordination costs, buying becomes the more strategic and efficient path.
Summary of Key Factors to Consider When Choosing Build vs. Buy
These five factors often shape the decision between building a custom solution and adopting a proven platform. Each one reflects how coordination, cost, and control are distributed across teams, and how those decisions impact the ability to scale decision automation effectively.
Cost
- Build: Requires significant up-front investment along with ongoing costs for maintenance, updates, and support.
- Buy: Offers a predictable pricing structure, with licensing models that include platform access, technical support, and compliance features.
Time to Deployment
- Build: Demands extended development timelines, often stretching over several months.
- Buy: Deploys quickly with prebuilt architecture and guided onboarding, often launching in weeks.
Customization
- Build: Provides full control over system behavior and interface design, but increases complexity and resource requirements.
- Buy: Delivers high configurability through APIs, low-code rule editors, and integration tools that adapt to most business environments.
IT Resource Requirements
- Build: Relies on dedicated engineering support to manage performance, updates, and logic changes.
- Buy: Allows business users to author and update rules directly, while IT focuses on integrations, system stability, and security.
Scalability
- Build: Scaling requires additional engineering effort as decision volume, logic complexity, or business scope expands.
- Buy: Scales efficiently across teams and geographies, supported by built-in rule management and high-performance processing.
These factors reflect Coase’s view that when external solutions offer flexibility and governance, the overall cost of change remains low. In these cases, buying becomes the more efficient and strategic choice.
How InRule Offers a Smarter Alternative
InRule delivers the benefits of buying without the friction. Its decision automation platform lets business users control rules via no-code tools, while IT manages integrations and infrastructure.
- Low-code and no-code interfaces accelerate deployment and enable quick updates to decision logic.
- Built-in governance tools support version control, rule visibility, and auditability across teams.
- A scalable architecture handles growth in decision volume and complexity without added system strain.
InRule reduces the coordination effort required to manage decisions across teams, while preserving the flexibility to adapt logic as the business evolves.
This reflects Coase’s principle: Rely on the market where it adds value, and keep control where it counts. For decision automation, the smartest approach is the one that minimizes the long-term effort of making and adjusting decisions as needs change.
Explore how the InRule Rules Engine can help you strike balance, combining the speed of the market with the control of a custom build.
