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Volatility does not automatically create value. Businesses can turn disruption into an advantage only when they can change priorities and carry those decisions through without destabilizing their operations. In a 22 September 2025 opinion article for CIO, Spryker co-founder and co-CEO Alex Graf argues that leaders should build that ability into their teams, systems, and investment choices.
What it means to turn volatility into value
Graf uses volatility to describe frequent, unpredictable changes that can disrupt operations, including price fluctuations, higher capital costs, labor shortages, and supply-chain interruptions. He uses value to mean a measurable business advantage, such as greater efficiency, market share, or customer loyalty. These are the article’s working definitions and argument, not a universal formula for predicting business results.
The practical point is that disruption becomes an opportunity only if an organization can respond effectively. A company may need to revise a plan, change a channel, or adjust how it serves customers. If each change requires a major rebuild or lengthy internal handoffs, the business may be unable to act while circumstances are still changing.
Assess how quickly decisions become action
Graf’s central test is structural agility: can a company change priorities without breaking the systems and processes that support its work? Leaders can make that question concrete by tracing a real decision from approval through execution.
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- Time to act: How long does it take to launch a new channel, adjust a product offer, or respond to a regulatory change after leaders decide to do so?
- Cost and complexity: What teams, systems, approvals, and operating costs are involved in making that change?
- Scope of change: Can one market or business unit adapt locally, or does the change require rebuilding shared systems across the organization?
- Resilience and affordability: Does the proposed approach make the business more adaptable at a cost it can sustain?
- Customer trust: Which tasks can be automated, and where do customers still need human judgment or support?
These questions form a diagnostic, not a platform ranking. Graf’s article does not provide a neutral vendor comparison, a total-cost analysis, or quantified evidence that one operating model works best for every company.
Build flexibility into teams and technology
Adaptability is not only a matter of choosing a new technology. Teams need clear authority to adjust priorities, and operating processes need to accommodate change. Leaders can shorten the gap between deciding what to do and being able to do it by identifying avoidable handoffs, rigid dependencies, or systems that turn a local adjustment into a company-wide project.
Consider architecture as a trade-off
Graf contrasts monolithic systems with composable approaches, in which capabilities can be assembled or changed in components. He argues that this flexibility can make it easier to adapt channels or business processes. That is a case for evaluating architecture by how well it supports change—not proof that composable systems are always cheaper, simpler, or right for every firm.
Before an architecture investment, ask what needs to change, how often it changes, and what the current system makes difficult. Compare the time and operational complexity of making that change with the cost and complexity of the proposed alternative. A flexible design has business value only if it solves a real constraint without creating burdens the organization cannot manage.
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Strengthen foundations before pursuing AI use cases
Graf advises leaders to address data and infrastructure foundations before chasing AI personalization. The sequence matters: a new application cannot compensate for underlying data or systems that do not support the work. Tie investments to a defined business need, and determine how the organization will judge whether the change improved execution or customer outcomes.
Automate selectively and preserve human judgment
Automation can reduce routine work, but a faster process is not automatically a better customer experience. Decide which interactions are straightforward enough to automate and which involve large orders, exceptions, or trust-sensitive decisions that benefit from human handling. Graf uses Swiss Krono’s B2B portal as an illustration of combining automation with a human role in larger orders; the article does not independently document the example or establish its results.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Read company examples as illustrations, not proof
Graf’s article describes Jungheinrich as operating more than 40 country-specific storefronts on a composable backbone, and says Rose Bikes launched a customized commerce experience in weeks. It also points to Metro AG’s localized B2B shops, PepsiCo’s changes to distribution and fulfillment during the pandemic, and examples involving Amazon, Tesla, and Gap.
These cases illustrate the author’s argument that adaptable operations may help companies respond to change. They are claims reported in an opinion article, not independently verified case studies in the article; they do not establish that a particular technology caused a business outcome. Treat timelines and company counts as examples attributed to Graf, not as industry benchmarks.
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A practical starting point for leaders
- Choose a plausible disruption. Consider a supply interruption, a new regulatory requirement, a change in customer demand, or a cost increase relevant to your business.
- Trace the response. Map who must decide, which teams and systems must act, and where work is delayed or duplicated.
- Identify the constraint. Separate problems caused by decision rights, process, data, infrastructure, or architecture rather than assuming a new platform is the answer.
- Test a focused change. Choose an investment or process adjustment tied to the constraint, and assess its cost, complexity, and effect on the ability to respond.
- Review the outcome. Measure the time from decision to execution and whether the change met the business need without weakening resilience or customer trust.
The aim is not speed for its own sake. It is to make important changes reliably, at a cost the business can support, while retaining human judgment where it matters.
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