Why Innovation Requires a Wider View: When Solving One Problem Creates Another
A powerful medicine improves health but increases pressure on access and affordability. AI helps people work faster but enables organizations to generate more demands than they can absorb. A clean technology reduces emissions in one place while creating environmental costs elsewhere.
Each solution works. Yet each can make another part of the problem worse. Healthcare costs, organizational overload, AI disruption and climate change are not isolated failures. They are outcomes produced repeatedly by interconnected systems.
Dominant innovation approaches – breakthrough and design thinking – often miss the ripple effects they produce across employees, customers, supply chains, costs and natural resources. Systems thinking widens the view. It asks not only whether a solution works, but what else it changes.
How can we apply this wider view without mapping every connection? Four questions proposed by Tima Bansal and Julian Birkinshaw in Harvard Business Review offer a practical way forward.
Because progress is not only solving today’s problem faster. It is making sure today’s answer does not become tomorrow’s problem.
Why successful solutions can fall short
Problems usually draw attention where their effects are most visible: patients unable to obtain treatment, employees overwhelmed by work or environmental damage that continues despite cleaner technologies. The natural response is to intervene where the pressure appears.
But the visible pressure may be only one part of the problem. Access to an effective medicine also depends on its cost, insurance coverage, healthcare budgets, duration of treatment and the number of people who need it.
When one part changes, the surrounding system responds. Demand may grow, resources may shift, incentives may change and new pressures may emerge. The problem is not static while we try to solve it.
A solution can therefore succeed on its own terms while falling short across the wider system. Systems thinking asks two questions: Does the intervention work? What happens around it when it does?
Three ways to approach innovation
Not every problem requires systems thinking. Different problems benefit from different approaches.
Breakthrough thinking starts with an idea: what powerful new solution can we create? It drives transformative medicines, digital platforms and technologies. But in a complex system, moving fast may create consequences that appear only later.
Design thinking starts with the user: what does this person need? It makes products and services more useful, accessible and humane. But a solution centered on one group may transfer costs or difficulties to others.
Systems thinking starts by zooming out: what relationships, incentives and behaviors keep producing this problem? It examines how the parts interact – and how they may respond when one part changes.
The three approaches are complementary. Breakthrough thinking drives technological progress. Design thinking connects innovation with human needs. Systems thinking becomes essential when a problem crosses boundaries, affects many stakeholders and changes in response to our attempts to solve it.
It asks not only whether an intervention works, but what else it changes. That wider view may slow the beginning of the process, but it can prevent a solution from creating the next problem.
What a wider view reveals
Systems thinking does not diminish innovation. It reveals what innovation must connect with if its benefits are to endure.
The medicine works. Does the healthcare system?
GLP-1 medicines represent an extraordinary advance in treating obesity and related diseases. But what happens when millions of people may need expensive treatment for many years? How will healthcare systems manage access, insurance coverage, long-term adherence and unequal availability? How should treatment connect with prevention and the conditions that continue to contribute to obesity?
Clinical effectiveness remains essential. But a medicine’s capacity to improve population health also depends on the system through which it reaches people.
AI makes work faster. What happens to the work?
AI can help people analyze information and complete tasks more quickly. But when priorities remain unclear and responsibilities fragmented, greater efficiency may create room for more requests, output and decisions competing for attention.
Just as wider roads can attract more cars, greater productive capacity can attract more work.
AI may help people process their unresolved tasks – or “open tabs” – faster [ When your mind has too many tabs open]. Systems thinking asks why the organization keeps opening so many and why so few are completed, delegated, scheduled or released.
For organizations and investors, the value of AI depends not only on what the technology can do, but on how the surrounding system responds when it does.
A green solution can move the damage elsewhere
Electric vehicles eliminate tailpipe emissions, but their total environmental impact also depends on electricity generation, mineral extraction, battery production and what happens to batteries afterward.
This is not an argument against electric vehicles. It shows why technology cannot be judged through its most visible benefit alone. An innovation may reduce harm in one part of the system while increasing pressure elsewhere.
Across healthcare, work and climate, the question is not only Does the solution work? but What happens throughout the system when it does?
Four questions for thinking systemically
Seeing every connection in a complex system is impossible. Systems thinking does not require a perfect map before action begins. Building on a streamlined framework proposed by Tima Bansal and Julian Birkinshaw in Harvard Business Review, four questions can widen our view while allowing us to move forward.
1. What future are we trying to create?
Begin with the outcome we want the entire system to produce – not only the immediate problem we want to remove. In healthcare, the objective is not simply to develop effective medicines. It is to help treatments reach the people who need them and produce sustainable improvements in health. A company may seek greater productivity, but its desired outcome may be an organization in which people can concentrate on value-creating work.
Defining that destination prevents separate solutions from pulling the system in conflicting directions.
2. How does the problem look from elsewhere in the system?
The same medicine may look different to a patient, physician, insurer and employer. Greater AI productivity may look different to an employee receiving more assignments and an executive seeing faster output.
Examining different perspectives reveals consequences that remain invisible when only one experience defines the problem.
3. What incentives, relationships or flows keep producing it?
Problems persist partly because resources, information and decisions follow established pathways. Incentives may reward treatment more than prevention, activity more than outcomes, or short-term savings more than long-term resilience.
Changing these flows – or what the system rewards – may accomplish more than adding another product, policy or feature.
4. What small intervention could show us how the system responds?
Complexity should not become an excuse for inaction. A limited pilot, changed decision point or carefully placed constraint can reveal how the system responds before a solution is expanded.
The objective is not to predict everything. It is to act carefully enough to learn – then use what the system teaches us to choose the next step.
Final thoughts
The hardest part of systems thinking may not be understanding complexity. It may be resisting the comfort of an immediate answer.
Systems thinking does not promise perfect foresight or eliminate complex relationships, competing interests and difficult trade-offs. It helps us ask better questions, involve the people who experience the problem differently and test our assumptions before expanding a solution.
The strongest solutions do more than relieve the pressure we can see. They improve the wider system without simply shifting the burden elsewhere.
