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How consumer and retail leaders close the transformation value gap

Photographic portrait of Mehul Desai
Mehul Desai

Strategic Transformation Partner, Ernst & Young LLP

11 minute read 13 Jul 2026

Despite bold AI, innovation and GCC investments, most enterprises fail to capture value. Leaders must align data, decisions and execution to realize compounding returns.

In brief
  • Consumer and retail leaders must establish enterprise ownership and organize around end-to-end processes to coordinate decisions across planning, supply, commercial and finance.
  • As buffers shrink, even small misalignments across pricing, supply and data slow decisions and erode value.
  • When data, processes and decisions move together, brands and retailers can close the value gap and turn transformation momentum into compounding returns.

Chapter 1: When everything looks right, but nothing lines up

When a global consumer and retail enterprise’s CEO, COO and CTO review the quarterly transformation dashboard, progress looks solid. The cloud platform migration is almost complete, and the global capability center (GCC) has expanded. Agentic AI pilots are improving demand forecasting and promotion planning. By every formal milestone, the program appears on track. But the business tells a different story.

The real story

Despite ongoing pricing and promotion changes, margins remain under pressure and inventory volatility persists across channels. AI generates recommendations, but commercial and supply chain teams hesitate to act, relying on experience to navigate demand uncertainty and retailer dynamics. The platform is live, but reconciling forecasts, trade plans and supply constraints requires manual workarounds. The GCC continues to scale, but significant capacity is absorbed by aligning fragmented data rather than accelerating decisions.

Nothing is visibly broken. That is precisely the problem.

Decisions are improving locally, but not at the enterprise level. Value is created in pockets, but it does not accumulate where it matters most — in margins, working capital and overall enterprise performance.

How EY can help

Chapter 2: This is where the different parts of the transformation stop lining up in the business


The conditions for transformation success have shifted, and there is less room for inefficiency. Years of cost pressure have eroded the buffers that once absorbed fragmented execution, so even small misalignments show up quickly as lost sales, excess inventory or service issues that cannot be deferred.

 

At the same time, the consumer and retail value chain has changed as retailers build data-driven media businesses and consumer goods companies invest more directly in customer relationships. As retailers and consumer companies move into the same space, decisions across pricing, promotions, supply and channels need to move together. When they do not, coordination across planning, supply, commercial and finance breaks down, and decisions slow as data needs to be revalidated before action.

 

Previous transformation efforts can also create constraints. GCCs continue to scale, platforms have been put in place but not fully simplified, and data is still reconciled across teams rather than flowing through the business.

 

Concurrently, different parts of the transformation are progressing at the same time. GCCs are expanding, AI is assisting decision-making, platforms are being upgraded and processes are being redesigned. These focus areas for modern transformation succeed in isolation but are not designed to work as a system.

 

This lack of cohesion is common, with organizations continuing to struggle with siloed operating models. The misalignment is easy to overlook during normal operations and only becomes visible when the business needs to mount a quick response.

 

Nothing breaks outright, but pressures on the business expose the gaps. Decisions slow, assumptions drift and execution depends on teams aligning in the moment rather than the system working as one.

Chapter 3: Understanding where the enterprise stands

In 2026, the risk is misdiagnosing the enterprise’s readiness across data, processes and operating models. If leaders get that wrong, they can end up scaling the fragmentation they are trying to fix.

GCCs, end-to-end processes, platforms and agentic AI are already advancing in parallel. This shows up in budget decisions, architecture choices and operating model changes across consumer and retail. The question is no longer whether these are moving forward, but whether the enterprise can coordinate them or continues to manage each one separately, carrying the cost in delayed decisions, duplicated effort and missed value until it shows up in performance.

Navigating complexity

For most consumer and retail enterprises, activity is high and progress looks real at the functional level. GCCs scale analytics and planning support, platforms modernize and AI pilots show promise. But coordination still happens late, often through manual effort and escalation during peak trading periods. Foundations move at different speeds, and the organization reacts under pressure rather than anticipating it.

Accelerating

In some organizations, these gaps start to close. Responsibilities across data, process and execution are clearer, and decisions travel more smoothly across functions. The business starts to behave more like a system, but progress is still fragile and depends more on discipline than momentum.

Compounding

A smaller group reaches a different point. Here, data, process, platforms and AI reinforce one another through real operating cycles. The benefit shows up repeatedly, not because of investment alone, but because the enterprise is set up to make connected decisions.

This applies to most enterprises, but two situations change the starting point.

Knowing where the enterprise stands brings a different kind of responsibility. The work ahead is not about adding more initiatives, but about making deliberate choices that determine how the system moves forward.

Chapter 4: Five steps to turn momentum into compounding value

Knowing where you stand only matters if it changes what leaders do next. These five steps focus on decisions that help transformation create lasting value, not just more activity.

Step 1: Establish enterprise level ownership

In consumer and retail, knowing who is accountable when initiatives overlap is as important as deciding what to transform. Most organizations can name leaders who own GCCs, platforms, AI or supply-chain programs, but do not clearly define who is responsible for bringing merchandising decisions, demand signals and execution constraints together.

Unclear accountability delays coordination. Problems often arise during peak trading periods, promotions or demand swings, and teams solve them through escalation instead of addressing them earlier in the design. Value depends on individual intervention rather than a well functioning system.

This is where a transformation office matters. A transformation office becomes critical across planning, supply, commercial and finance. By making dependencies visible earlier, leaders can better sequence decisions and keep execution focused on business outcomes.

When this role is taken seriously, coordination, not individual intervention, drives how work gets done and transformation begins to compound value.

Step 2: Organize around end to end integrated processes

Consumer and retail transformations usually start with a clear business case. Supply chains are modernized, forecasting models improve and analytics capability expands through GCCs. In isolation, these initiatives can look successful. The technology works, accuracy improves and progress is visible.

The problem becomes evident when the business faces pressures, including demand shifting unevenly across categories or promotions hitting multiple channels at once. At that point, decisions slow as they move across supply, commercial and finance. Data does not line up cleanly, assumptions diverge and teams rely on handoffs to keep work moving. By the time everyone is aligned, the window may have closed.

It is not a failure of execution. It reflects how the enterprise has been organized. Transformation still follows functional lines because that is how most organizations evolved. Finance improves reporting, operations modernize supply chains and commercial teams invest in planning and pricing. Each effort works on its own. The gaps appear where those efforts need to come together.

Organizations that make progress recognize this as a structural issue, not simply an execution issue. They stop organizing transformation around functions and start anchoring it around the end-to-end processes that run the business, including Inspire to Buy, Engage to Advocate, Connected Planning, Order to Cash and Innovate to Scale. These flows determine the movement of decisions, data and accountability when conditions change.

This is about designing the enterprise so teams can respond together with less delay during market shifts.

How EY can help

Step 3: Tier the agentic ambition


Across consumer and retail, the ambition is clear. Most leadership teams are aligned on a North Star of an AI led enterprise, where decisions move faster, operations become more autonomous and customer and employee experience improve continuously. The challenge now is how to begin without losing control at scale.

 

Many organizations move quickly to demonstrate progress by launching pilots that show initial promise but are difficult to scale. Data varies across markets; assumptions diverge across commercial and supply teams, and decisions still depend on manual validation. Capability is visible, but impact slows as AI meets day to day operating reality.

 

Many agentic AI initiatives look promising at the start but become harder to sustain as costs rise and value becomes more difficult to prove. The issue comes down to how AI fits into the way decisions are made. When responsibilities across corporate, GBS and GCC structures are unclear, governance weakens and execution falls back on workarounds.

 

The organizations making more progress tend to scale AI more deliberately. AI expands first where data is reliable and decision boundaries are clear, while operating model design, governance and control mature alongside it.

Step 4: Integrating data governance into the operating model

Data governance becomes a leadership issue when teams need to move quickly. If demand signals do not match or trade assumptions differ by team, planning, supply, commercial and finance spend valuable time reconciling inputs instead of making decisions.

Many organizations handle data governance separately from decision making and only review it after work is already in motion. When GCC teams work with data they do not fully trust, they often need to reconcile inputs repeatedly and approach AI outputs with caution because the underlying data lacks consistency.

It is critical to align data governance with decision making. Leaders need clarity on who owns the data used across planning, supply, commercial and finance, and ensure a consistent view of demand, value and performance across the enterprise.

When governance is built into everyday decision making, teams spend less time reconciling the basics and more time acting on the data.

Step 5: Lead with value and use it to re-architect the enterprise

At this stage of the transformation, most of the heavy lifting has been done. Ownership is clearer, processes are better connected, AI is being applied more deliberately, and data is beginning to hold together. Yet many transformations still fall short because of how value is captured as it moves through the business.

Most organizations still run transformation through programs with individual business cases, sponsors and road maps. But value gets diluted when functions, processes and systems do not fully connect, and accountability remains unclear. For example, a pricing initiative may improve margins on paper, but trade data does not align with finance. Or a supply chain upgrade may increase visibility while planning assumptions remain inconsistent across markets. Programs improve, but outcomes remain unchanged.

Instead of asking which programs to fund, successful organizations focus on where value is created, how it moves across the enterprise, and where it drops off. Investments then follow that logic, aligned to outcomes rather than initiatives.

This shift requires more active involvement from the C suite than most are used to. Programs are not simply executed as planned. Some move faster, others are reshaped, and some are stopped altogether. The aim is not to show progress across everything, but to capture value in the places that matter most. The path is not identical for every company. Those under pressure to restore margins will lean into cost transformation, while others will use cost savings to fund growth. The principle holds: transformation delivers when it is continuously reworked around value as conditions change.

Chapter 5: Final reflection

The era of transformation for its own sake is reaching its limit. Across consumer and retail, organizations have invested heavily in analytics, platforms, GCCs and agentic AI, but capability on its own will not deliver the return. The risk now is mistaking activity for progress and expanding the same gaps across functions that continue to limit results.

Closing this gap is a leadership decision, not a technical fix. It requires less focus on adding programs and more discipline around how data, decisions and execution connect across the enterprise.

The choices leaders make next on GCC models, clean-sheet opportunities and how agentic AI scales will be difficult to unwind. Those who act with intent now are positioned to turn transformation into sustained returns.

Summary 

Across consumer products and retail, transformation activity is high, but value is not keeping pace. The gap is not technical, but structural. Organizations that connect ownership, data and decisions across the enterprise are better positioned to turn investment into lasting returns.

About this article

Photographic portrait of Mehul Desai
Mehul Desai
Strategic Transformation Partner, Ernst & Young LLP
Enterprise transformation leader. Client-centric value accelerator. Consumer products and retail industry strategist. Lover of all things Bollywood. Passionate about humanitarian relief. Golf enthusiast.
Related topics
Consumer Products
Transforming retail

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