Most organizations do not set out to create complexity. It accumulates—new systems, products, regulations, acquisitions, spreadsheets, and workarounds that become permanent. Over time these decisions connect into layers of processes, approvals, interfaces, exceptions, and tribal knowledge. People stop asking why. They simply learn how to get it done.
The Work Behind the Work
Behind every visible customer activity is another layer of work that is rarely measured:
- Claims: A claim is reported in the front-end system, but payment still requires a spreadsheet reconciliation between the claims platform and finance before the check can be issued.
- Policy: A mid-term endorsement is quoted, then manually re-keyed into a legacy rating engine because the core policy system cannot handle the exception.
- Underwriting: An underwriter pulls data from three systems to answer a simple question about exposure—because no single source of truth exists.
That work consumes time, people, and money. It is the work behind the work.
Scale vs. Unnecessary Complexity
Large insurers are complex by nature—hundreds of products, multiple channels, decades of business rules. That is scale. Unnecessary complexity looks different:
- Two departments define “active policy” differently, so production and finance reports never match.
- Three systems hold three versions of the same customer record after an acquisition; staff learn which one to trust for which purpose.
- A state filing creates a one-off product variation that permanently lives in a shadow process outside the core system.
Scale is managed. Unnecessary complexity can be removed.
The Technology Trap
When problems surface, the first instinct is often a new system. Sometimes that is right. Often technology is only where the problem becomes visible.
Why are two systems maintaining the same information in the first place?
Example: Hours spent reconciling premium between the policy admin system and the general ledger may point to an integration project. The harder question is why the same premium data is being maintained—and corrected—in both places at all. Technology can automate a bad process or make a complicated process faster. Neither necessarily makes the process better.
How Complexity Grows—and What It Costs
Exceptions harden into standard process. A special product, a state variation, a legacy limit, a regulatory control—each seems justified. Over time the operating model is built around exceptions, and the cost is hard to see because no single exception looks expensive.
Concrete patterns in insurance:
- Claims: Catastrophe coding or large-loss reviews that began as temporary controls become permanent handoffs, adding days to cycle time.
- Billing: Agency-bill vs. direct-bill exceptions that require manual intervention on every statement cycle.
- Reporting: “Just one more” management report that no one has retired, while three other reports still answer the same question with different numbers.
Employees spend more time finding information, checking work, and navigating systems. Experienced people become the unofficial operating manual—when they leave, undocumented knowledge becomes operational risk. Complexity also creates data inconsistency: multiple versions of the truth that better reporting alone cannot fix.
Finding It
Understand how work actually gets done—not how the org chart or procedure manual describes it. Follow a real claim, endorsement, or renewal from start to finish on a Tuesday afternoon. Look for the fingerprints:
- Multiple handoffs
- Duplicate data entry
- Manual reconciliations
- Shadow spreadsheets
- Repeated approvals
- Conflicting business rules
- Unclear ownership
- Duplicate systems
- Unnecessary reports
- Exceptions and workarounds
- Tribal knowledge
- Rework and defect correction
Simplification Is a Business Strategy
Simplification is not an IT initiative. Technology can consolidate systems; only the business can decide whether the underlying work is necessary. The goal is fewer unnecessary steps, handoffs, versions of the truth, exceptions, and processes that depend on one person.
Why is the work so difficult in the first place?
That question shifts the focus from applications to outcomes—and sometimes reveals that the organization does not have a technology problem. It has a complexity problem.
Complexity Has a Price
What the Research Shows
- Finance costs nearly 60% lower (as % of revenue) in low-complexity organizations, with 66% fewer staff and 30% less technology spend. The Hackett Group, finance complexity benchmarking
- Complexity estimated to cost U.S. food-and-beverage manufacturers up to $50 billion in gross profit annually; large insurers with high complexity often show cost ratios far above top-quartile peers. McKinsey & Company analyses
- Organizational complexity can drain roughly 7% of annual revenue; complexity-management programs have delivered 10–35% cost reductions. Freshworks Global Cost of Complexity survey; Bain & Company results
The AIA Perspective
Technology should enable the business—not define it. We look at the full operating environment:
Change one without understanding the others and complexity often moves rather than disappears. Understand the business problem first. Then decide what needs to change. Sometimes the most valuable technology investment is the one you no longer need because you removed the complexity that created the problem.
The Opportunity
Every organization has complexity. The question is whether it creates value or simply creates work. When unnecessary complexity is removed, people have more time, data becomes more useful, technology is easier to manage, decisions are clearer, and change is faster.
The first step is not always to change the technology. Sometimes it is to understand the work.
The most expensive process in an organization may be the one everyone has learned to accept.