For diversified enterprises, few operating model questions are as persistent or polarizing as centralization versus decentralization. Decentralization promises speed, ownership, and local responsiveness. Centralization promises efficiency, standardization, and leverage. Both can be right. Both can be wrong. The challenge is that many organizations end up with both models operating at once, without enough clarity about why.
The result of fragmented systems, duplicated capabilities, inconsistent data, rising IT spend, and a complexity tax that compounds over time is familiar to many CIOs. What starts as autonomy can become architectural sprawl. What starts as enterprise leverage can become bureaucracy. And as companies modernize core platforms, integrate data, and scale capabilities like AI, the tension becomes harder to ignore.
Paul Krebs has lived that tension from multiple vantage points. Most recently as CIO and chief transformation officer at Koch Industries, and previously a technology and transformation leader at The Coca-Cola Company, he’s worked in environments where business units value autonomy, enterprise scale matters, and the wrong operating model can slow progress just as easily as the wrong technology architecture.
His conclusion isn’t that CIOs should pick a side, but they need a more intentional form of centralization, one that starts with business architecture, clarifies decision rights, and continually revisits where capabilities should sit as the organization matures.
Centralization: a design choice, not a doctrine
In diversified organizations, decentralization often starts as the default because it aligns with how the business creates value. Local businesses understand their customers, markets, regulatory environments, and operating realities, and giving them decision rights can increase speed and accountability.
In Krebs’ experience, the default model often leaned toward decentralization, he says, with the belief that optimizing for customers and markets would allow different businesses to be as responsive as possible to the specific customers and markets they served. But that logic isn’t complete. Leaders also need to ask whether there’s a compelling case where a more centralized approach can generate additional value, accelerate progress, or optimize investments.
Digital transformation created one of those moments. Krebs recalls around 2016 when Koch challenged its businesses to build multi-year digital transformation roadmaps. The ambition was there, but the capabilities to execute at the necessary pace weren’t evenly distributed. In response, the organization invested more aggressively from the center, building shared services and centers of expertise in areas such as business transformation, enterprise applications, and data and analytics.
The purpose was acceleration, not control. Centralizing those capabilities helped accelerate learnings, capability building, and their ability to deploy new solutions at scale. But the move wasn’t treated as permanent. “There was always a belief that the centralization push should be re-looked at on a regular basis, not thought of as a forever decision,” he says.
Know what belongs at the center
Over time, Krebs learned that the capabilities most likely to remain centralized were those where scale, consistency, and risk management mattered more than local differentiation. Infrastructure, collaboration platforms, cybersecurity, cloud management, FinOps, and the help desk were natural candidates to remain shared services.
Other areas were more nuanced. Some application capabilities moved back into the businesses as local maturity increased. Many data and insights capabilities also moved closer to the business once teams had built enough muscle to own them. Meanwhile, certain emerging capabilities such as spatial technologies like AR/VR remained centralized because it didn’t yet make sense for each business to build them independently. Many companies have lived this journey as well, for example, with gen AI, which often started with a center of excellence, and then evolved into a more decentralized approach, enabling teams across the business to innovate quickly.
That distinction avoids the trap of treating the enterprise as one uniform operating model. “Both models can be successful, and both have advantages,” he says. “That’s what makes the balance so difficult.”
Centralization provides a clearer path to execution at scale and cleaner decision rights, but it requires change management and careful attention to bureaucracy. Decentralization provides ownership and speed, but it can also over index toward preference versus real differentiation, he adds, while making architecture harder to scale later.
Don’t confuse standardization with centralization
One of the most important distinctions Krebs makes is between centralization and standardization. Many organizations treat them as interchangeable, but they’re not.
“You can have a centralized team that can manage the nuances of different requirements,” Krebs says. “You can also have a centralized standard platform that can be used in a decentralized manner.”
That distinction opens up more operating model choices. A company may centralize a platform but decentralize how business teams configure or use it. It may standardize process patterns while keeping execution close to the region or business unit. It may also centralize architectural governance while allowing local teams to move quickly within defined guardrails.
This is especially important in global organizations, where regional needs are real but not always unique. Krebs advises leaders to examine whether local requirements can be made more generic and reusable. The risk is solving each local requirement as a one-off, so the better path is to understand the underlying requirement, build it in a way that can scale, and still allow local teams to execute within the standard model.
Let business architecture lead technology architecture
Few topics expose the centralization tension more clearly than ERP consolidation. Many diversified companies, particularly those shaped by acquisition, end up with dozens or hundreds of ERP instances. Some leaders push for massive consolidation. Others prefer to build integration layers on top of the existing environment.
Krebs’s starting point is neither technology nor cost. It’s business architecture. “The easiest and most effective path is when the IT or systems architecture follows and aligns to the business architecture,” he says.
If the business is truly going to operate processes separately, separate systems may be appropriate. But if the organization has numerous teams, processes, and tools, leaders need to ask whether there’s enough differentiation and value to justify that complexity.
The same logic applies to M&A. Companies can get into trouble when integration synergies are held hostage by ERP migration timelines. Instead, Krebs advises starting with the business integration strategy. Understand where the synergies are, how the business architecture should come together, and then decide whether the IT architecture needs to be fully integrated, or whether a data layer, reporting platform, or other integration approach can deliver value faster.
Make the cost of complexity visible
CIOs in decentralized companies often face a frustrating dynamic. The business wants autonomy and speed, but the same leadership team still questions why IT spend is high relative to benchmarks. Krebs says the answer starts with cost alignment and visibility.
In environments with a mix of centralized and decentralized services, Krebs saw centralized capabilities like infrastructure, help desk, and security perform well on benchmarks. More decentralized areas, such as BI, reporting, and commercial applications, often had more redundancy and higher cost.
The point isn’t to blame the business but make the economics of complexity visible. CIOs need to show how flexibility in one area may require multiple systems, data stores, or teams elsewhere. “I understand we want flexibility here,” Krebs says. “But leaders must see when that flexibility may cost the company money, and be clear on whether the value justifies it.”
That shifts the conversation from IT cost to business service economics. A single aggregate IT spend number is rarely useful in a decentralized environment. More helpful is a capability-based view that shows which areas are scaled efficiently, which are fragmented, and where the business architecture is driving the technology cost structure.
Revisit the model as maturity changes
For a new CIO entering a decentralized environment, Krebs cautions against immediately declaring that too many things need to be centralized. The better starting point is curiosity. “I would begin with just trying to understand why they’ve made the decisions they have,” he says.
From there, CIOs can engage leaders in a conversation about the target operating model, connecting business architecture to technology, data, and organizational capabilities. Once the direction is clear, he advises CIOs to work with the willing. Find the parts of the organization that already see the need for change, prove the model there, and scale from demonstrated success.
Regardless of execution, though, the right model changes over time. A low-maturity capability may benefit from centralization because the organization needs to build talent, avoid reinventing the wheel, and accelerate learning. As maturity grows, decentralization may make more sense because business teams need flexibility to adapt quickly. Once maturity is high and patterns stabilize, the organization may be ready to centralize again to leverage scale.
“Once I’ve decided I’m going to start with centralized or decentralized, you don’t necessarily need to stay in that model,” Krebs says. “You need to be continually revisiting the operating model as your organization matures and evolves.”
That may be the heart of smart centralization. It rejects the false permanence of operating model decisions, and recognizes that autonomy and scale are both valuable, but in different places, at different times, for different reasons.
Read More from This Article: Finding the right balance between autonomy and scale
Source: News