Download the full 2026 Program and Project Management Trends Report here.

This free trends report outlines industry perspectives and expert advice from our team of consultants. You can view an excerpt of the report below, and if you’d like to discuss any of the trends or other challenges in the program and project management space, connect with our team today.

Key Program and Project Management Trends

In 2026, leading PMOs will move beyond reporting to serve as enterprise enablement engines. They will connect strategy to execution, build readiness into delivery from the start, and ensure governance keeps pace with AI and agent deployments. Just as important, they will treat benefits realization as a core discipline, with clear ownership, defined baselines, and early indicators that show whether value is actually being created.  

Clarkston’s program and project management consultants have highlighted the top trends that businesses should consider and keep top-of-mind throughout the year:

1. Governance and Risk Management for Agentic AI
2. Scaling Native AI Delivery Across Functional Operations
3. Value realization as the main KPI for PMOs
4. PMOs Shift to Persistent Product Teams
5. From Project-Based Change Management to Sustained Enterprise Change Capability

Trend 1:

Governance and Risk Management for Agentic AI

Agentic AI is the first wave of automation that behaves less like a tool and more like a junior operator planning steps, calling systems, and completing multi-stage work. This shift – moving from people- and technology-integrated workflows to agentic AI – is happening fast, and it comes with a hard reality check.  

Gartner expects more than 40% of agentic AI projects to be canceled by the end of 2027 when teams fail to demonstrate clear value or build the right risk controls. At the same time, however, adoption will keep accelerating. Reuters reporting on Gartner notes that agentic AI is expected to autonomously handle 15% of daily business decisions by 2028 and be embedded in 33% of enterprise software by 2028. In other words, many organizations will continue moving forward even while a large share struggle to scale responsibly. 

For PTM and change leaders, the implication is clear: agent rollout isn’t just an IT release but rather an operating model change. Before agents touch regulated or revenue-impacting processes, such as pricing claims and returns, trade settlement, or quality events, programs must establish human-in-the-loop decision rights, defined ownership (RACI) for exceptions, audit trails, and production monitoring. If you wait until after deployment to add guardrails, you’ll either throttle the agent into irrelevance or accept unmanaged risk. The risk isn’t just model accuracy. It extends to process accountability: who approved an action, which data was used, what exceptions occurred, and how the organization detected and corrected failure. 

Business reality reinforces why governance has to lead. Benchmarks cited in Business Insider show agent performance can be under 25% success on the first attempt and only around 40% even after eight tries. That gap between a cool demo and a trusted operator is the governance workstream. The winners will treat agents like a new workforce class with training through prompt and workflow design, supervision through controls and monitoring, and performance management through value and quality KPIs. Those that treat agents as simple plug-ins will quickly discover that the real complexity of the business lives in the exceptions. 

Trend 2:

Scaling Native AI Delivery Across Functional Operations

The AI conversation is shifting from which use cases to pursue to a deeper question: what changes when AI becomes embedded in the way work actually gets done? 

That shift is why AI-native delivery (AI being embedded in the entire project life cycle) is a program and change management issue, not a technology one. Gartner’s forecast that at least 30% of GenAI initiatives will be abandoned after proof of concept by the end of 2025 is the clearest warning that scaling fails when organizations don’t address the basics data readiness risk controls and measurable value. 

Gartner also reports that 61% of organizations are evolving or rethinking their data and analytics operating model because of AI. This signals that the constraint has moved from model availability to enterprise readiness. AI programs will succeed or stall based on whether teams can standardize processes, clarify decision rights, and build practical adoption routines that reflect how people actually work. That includes role-based training, adjustments to job design, and policy updates that remove ambiguity. 

Workforce behavior shows how quickly the ground is shifting. Financial Times reporting indicates that 48% of workers in a large survey now use AI every day, up from 31% the prior year. Adoption is moving faster than most formal enablement and governance efforts. When that gap widens, shadow AI becomes inevitable and outcomes grow inconsistent, which is exactly the risk transformation leaders are expected to manage.

Continue reading by downloading the full report below.

Download the Full 2026 Program and Project Management Trends Report Here

The post 2026 Program and Project Management Trends appeared first on Clarkston Consulting.

As the SAP landscape changes, support models must evolve with it. Application Managed Services (AMS) have evolved beyond reactive ticket resolution and system maintenance. AMS now plays a critical role as a strategic enabler, helping organizations maximize the value of SAP investments: maintaining stability, enabling continuous optimization, proactively identifying opportunities for improvement, and aligning the platform with shifting business priorities. 

For many organizations, building and maintaining the right mix of in-house functional and technical SAP resources is increasingly difficult. An effective AMS model introduces flexibility by providing access to specialized expertise across modules while scaling capacity to support upgrades, enhancements, and shifting business priorities. One quarter may require deep Finance support around year-end close, while another may demand supply chain and production planning expertise to navigate peak demand seasons. A scalable AMS structure allows organizations to align the right level of support to their business needs without overextending internal SAP teams. 

Whether transitioning from ECC ahead of the 2027 deadline, expanding S/4HANA capabilities, or reassessing current support models, organizations must determine what role AMS should play in balancing stability, innovation, and cost efficiency within their broader SAP strategy. 

Defining Your SAP AMS Strategy 

Organizations that approach AMS primarily through the lens of minimizing support costs may find that those models struggle to scale with the business over time. 

Defining an SAP AMS strategy is a structural decision about how your SAP environment will be supported, governed, and optimized over time. Regardless of where you are in your SAP journey, AMS should be intentionally designed to operate as an extension of your business – complementing your operating model and aligning with your technology roadmap. 

Before evaluating providers, organizations should assess their internal capabilities, SAP landscape complexity, and business objectives. The right AMS approach depends on several key factors outlined below: 

IT Maturity 

• Do you have sufficient in-house SAP functional and technical depth to support critical SAP processes? 
• Is your organization’s team structured to continue to operate and fix SAP problems without impacting day-to-day operations?  
• Does your organization have the capacity to support enhancements, releases, and continuous improvement in addition to day-to-day operations? 

Organizations with limited depth may require a more holistic AMS partnership, while mature IT teams may benefit from an advisory-led or hybrid model.  

Industry Complexity 

• Are you operating in a highly regulated industry that requires validation documentation or audit support? 
• Does your industry have unique SAP compliance requirements? 
• Does your industry have seasonal spikes or demands that require scalable support capacity? 

Upgrade & Implementation Roadmap 

• Are you planning an S/4HANA migration or major transformation? 
• Do you anticipate frequent customizations or enhancements? 
• Do you have complex deployment models or phased rollouts? 

Integration Complexity 

• How tightly are third-party systems integrated with SAP? 
• How are integrations managed with middleware, APIs, or other custom developments? 
• Does the frequency, volume, or criticality of integrated data increase the operational impact of unplanned downtime? 

Highly integrated environments require AMS providers with strong cross-platform troubleshooting experience, end-to-end process knowledge, and clearly defined escalation paths. 

Scope of SAP Modules 

• Which SAP modules are your business currently using, and which are most critical? 
• What modules does your business plan to use in the future? 
• Where do gaps, tribal knowledge, or key-person dependency risks exist within your in-house team’s functional and technical expertise? 

Without a clear understanding of your organizational maturity, complexity, and roadmap, it can be tempting to select an AMS provider based primarily on cost and availability. Clarifying these factors enables smarter decisions about the role AMS should play in your SAP strategy and positions organizations to more effectively evaluate what to look for in an AMS partner. 

What to Look for in an SAP AMS Provider 

The right SAP AMS provider should not operate solely as a reactive support team, but as a proactive partner that identifies opportunities to optimize system performance and align SAP capabilities with your organization’s evolving business goals.  

Industry and Process Domain Expertise 

Organizations should evaluate whether the provider brings institutional industry expertise that can be leveraged when complex operational or regulatory challenges arise. Industry context can materially influence support decisions, particularly in environments where SAP underpins core business processes such as manufacturing, supply chain, quality management, or customer-facing operations. Access to firm-wide subject matter experts (SMEs) strengthens governance by improving decision-making and ensuring alignment with real-world business operations. 

SAP Technical and Functional Expertise 

SAP AMS providers should demonstrate deep functional and technical expertise across critical SAP modules, supported by relevant certifications and proven experience in S/4HANA migration, implementation, and post go-live stabilization. Strong knowledge of SAP best practices, standard functionality, and extensibility is essential to minimize unnecessary customization and support a clean core strategy.  

Governance, Security, and Compliance 

SAP AMS providers should have experience supporting audit and compliance requirements to maintain system integrity and mitigate risk. Beyond meeting baseline requirements, a differentiated provider strengthens governance through disciplined documentation and root-cause analysis to prevent recurring issues. Providers that can also identify and recommend improvements in associated areas (process changes, training needs, data issues, etc.) can help drive more sustainable solutions. 

Delivery Model & Support Structure 

Effective AMS providers design delivery models that balance responsiveness, domain expertise, and cost efficiency. While global coverage may be required, organizations should evaluate how support is structured across service tiers, escalation paths, and time zones to ensure business-critical issues are handled appropriately. 

Leading providers often combine scalable global support capabilities with access to more experienced functional SMEs and advisory resources for complex issues, maintaining a balance between operational efficiency and strategic alignment. 

Structured Transition & Knowledge Transfer Approach 

A provider’s transition methodology can significantly impact the success of the AMS engagement and accelerate time-to-value. Organizations should evaluate how the provider structures knowledge transfer during onboarding, particularly when transitioning from an implementation partner or replacing an existing AMS provider. 

Structured documentation reviews, shadowing periods, and clearly defined ramp-up plans help ensure continuity and reduce stabilization risk by enabling the AMS provider to quickly absorb business and system context, including key processes, integrations, configurations, and customizations. 

Without a disciplined transition approach, gaps in system understanding (particularly around customizations and business processes) can lead to slower resolution times and increased operational risk. 

Continuous Improvement & Innovation Capabilities 

Modern SAP environments require more than reactive support. Organizations should evaluate how an AMS provider supports ongoing optimization through enhancement planning, release readiness, and backlog prioritization. 

Providers that allocate structured yet flexible capacity to balance continuous improvement with system stability help organizations sustain long-term value from their SAP investment.  

How to Select an SAP AMS Provider 

Selecting an AMS provider isn’t just about technical capabilities – it’s about how those capabilities are delivered and governed over time. Organizations should evaluate how providers perform in real-world engagements, structure their contracts, and align operationally with the business. 

Consideration #1: References and Past Clients 

Evaluating how an AMS provider performs is most effective when reviewing past or current client engagements with similar SAP environments and levels of complexity. Beyond assessing technical fit, organizations should seek insight into how the provider performed during transition, stabilization, and ongoing support. Reference conversations can also help assess how well the provider adapts to complexity, collaborates with internal teams, and aligns with long-term support needs. 

Consideration #2: Clearly Defined Contract Language 

Clear contract structures help set expectations and maintain accountability over time. Scope, ownership, points of contact, and escalation paths should all be clearly defined, along with the approach to handling out-of-scope requests and evolving support needs. 

Service Level Agreements (SLAs) should establish measurable performance standards, including response times by ticket severity, resolution time expectations, and after-hours support requirements. A well-defined prioritization model should also be agreed upon in advance and aligned with business-critical processes.  

Consideration #3: Communication & Governance Alignment 

Effective communication is critical to a successful AMS relationship, but it extends beyond tools and channels. Organizations should understand how the provider structures communication and how that approach aligns with existing governance, reporting cadence, and escalation processes. 

Equally important is the provider’s ability to translate technical issues into business impact and operate as an extension of the internal team. Providers that integrate effectively into the organization’s working model rather than operating as a separate support function enable stronger collaboration, clearer ownership, and more effective decision-making over time. 

Consideration #4: Ability to Support Change and Evolution 

Organizations should evaluate how an AMS provider will support enhancements, new functionality, and ongoing releases while maintaining system stability and alignment with business priorities. 

This includes the ability to assess and implement enhancements, prepare for releases, and translate proposed system changes into process, data, and training impacts across the organization. A well-structured approach to knowledge transfer further supports long-term sustainability, ensuring both the provider and internal teams are equipped to effectively manage ongoing change. 

Turning SAP AMS Into a Strategic Enabler 

An effective SAP AMS model does more than resolve tickets; it shapes how the platform evolves, how risk is governed, and how innovation is sustained over time. The support structure you design today will directly influence total cost of ownership, upgrade readiness, and your organization’s ability to realize the full value of its SAP investment. 

Organizations that approach AMS as a strategic capability, not just a support function, are better positioned to balance stability with continuous improvement in an increasingly dynamic SAP landscape. 

Clarkston partners with organizations to design and deliver AMS models that combine industry-specific advisory leadership with scalable global delivery. If you are evaluating how AMS fits into your broader SAP strategy, our team would welcome the opportunity to discuss your goals. 

The post How to Choose the Right SAP AMS Provider: Designing a Modern Support Strategy appeared first on Clarkston Consulting.

Download the 4PL Vendor Selection and Implementation Case Study Here

A global, multi-brand leader in the fashion industry, operating over 1,100 retail stores and generating more than $10 billion in annual revenue, faced growing challenges managing inbound shipments across its seven distinct brands. Fragmented systems and limited visibility into shipping milestones created operational inefficiencies for Logistics, Production Operations, and Merchandise Planning teams. Initial attempts to consolidate data through cross-brand reporting helped, but gaps remained in tracking key shipment events. 

To address these challenges and improve supply chain visibility, the client partnered with Clarkston to implement a fourth-party logistics (4PL) provider. The 4PL served as a centralized logistics partner and single point of contact for freight forwarding, from factory to warehouse. Clarkston supported the 4PL vendor selection process and led the integration of the client’s seven brand ERPs into a unified 4PL-enabled reporting framework. 

The team created a detailed list of 4PL capability requirements and developed comprehensive data mapping documentation to ensure consistent milestone tracking. They architected an integration strategy tailored to each brand, built and maintained the project timeline, and kept executive stakeholders informed throughout the initiative. Clarkston also led testing efforts for both data ingestion and reporting, conducted user training sessions, and supported hypercare activities post-launch. 

As a result, the client achieved real-time visibility into 17 key shipping milestones across all brands. The Corporate Logistics team now benefits from integrated reporting that consolidates data from seven ERPs into four standardized reports. Over 50 custom integrations were developed with the 4PL provider, significantly reducing the manual effort required for operations teams. The enhanced data consistency and centralized reporting are now leveraged for both current operations and future supply chain initiatives. 

This project delivered a scalable, cross-brand logistics solution that supports continued growth and operational efficiency across the enterprise. 

Download the 4PL Vendor Selection and Implementation case study, and learn more about our Retail Supply Chain Consulting Services by contacting us below. 

Contact Us to Learn More

The post 4PL Vendor Selection and Implementation for a Global Retailer appeared first on Clarkston Consulting.

Are you thinking about implementing a new TPM tool? Or maybe you’ve already started the process to implement a new TPM tool? 

If the answer is yes, have you also considered the quality of your master data, particularly around your product and customer hierarchy and key attributes?  

Master data is often overlooked in a TPM implementation, with most people thinking that because their master data set up and existing data has worked well enough for them so far, they can continue leveraging it in the same way with a new system. However, master data, and specifically product and customer hierarchies, are the foundation of not just a successful TPM implementation but successful usage of the new tool by your end users after implementation.   

If your master data isn’t set up prior to the implementation of your new TPM tool, this could negatively affect forecasting, promotion planning, settlements, and post-promotion. By implementing a new TPM tool, you have the opportunity to not just input a new tool into your sales planning ecosystem, but truly transform the processes in which your organization and employees engage and collaborate within the sales planning process.  

You might be asking, “So if I don’t clean up and harmonize my organization’s master data, that’s bad, but what exactly are the benefits my organization and people could reap from cleansing the master data in our ecosystem? And what would we even clean up or action on?” 

Evaluating and Cleansing Your Master Data for a TPM Implementation  

1. Product and Customer Hierarchy Data 

The first category within the TPM-related master data space to evaluate would be your product and customer hierarchies as well as other ways your accounts may be organized in your ecosystem. When was the last time that you made any changes to the hierarchy or actually sat down with the different functional groups that use the hierarchy to see how they tactically leverage the different hierarchy levels that currently exist today?  

Chances are there may be a level or grouping that made sense when you first created and implemented this current version of your hierarchies, but they don’t quite make sense for how your business works today and aren’t meeting your organizational needs. To evaluate this, some key questions to ask yourself and your key functional groups are: 

• Are all of your customers currently planned at the same level? If they’re not, is this approach something that you want to continue into your new TPM system, and does it really enable efficiency? Do your hierarchies and current set up of customer attributes truly enable your planning process, or do your users have a number of exceptions to the processes for hierarchy usage? 
• Does the setup of your organization’s planning accounts make sense for how your business plans today? Are your customers segmented in a way that maximizes efficiencies for smaller customers while also prioritizing larger or more strategic customers? Do you use an attribute like customer segmentation for this? 
• Does your product hierarchy structure make sense for your sales team and for demand, supply, and marketing? Are your PPGs (Promoted Product Group) organized with clear rules and consistency to best serve the way promotions are forecasted, planned, funded, and then evaluated/analyzed afterwards? 
• Are both your customer and product hierarchies set up in a way that allow for post-promotion evaluation? Anyone who’s been close to data has heard the age old saying – “garbage in equals garbage out.” Without accurate and cleansed data going into your promotions, your teams will not be able to get any data from your promotions to accurately use throughout reporting or KPI. 

2. Active Product Data 

The second category would be to evaluate would be your list of active products and/or the tools you use to assign products to various customers. Implementing a new TPM tool provides the perfect opportunity to clean up this master data because this category is almost guaranteed to not be cleansed simply because of how many different teams or people use and/or change this type of data regularly. Some key questions to ask here are: 

• Are your products being regularly deactivated in order to maximize your current TPM system performance? Is there a process for your end users to follow in order to deactivate products? 
  • Do you have any one-time displays or seasonal/holiday offerings that are still active years after they’ve stopped being sold? This can cause risk to system performance and can also lead to less accurate promotions if these items that aren’t sold are added to promotional events accidentally. This can also negatively impact forecasts. 
• Do you have an authorized distribution list (ADL) in place and being used? 
  • ADLs are critical to maximizing efficiencies throughout your TPM system by ensuring planning accuracy for customers, creating more realistic forecasts and allowing product input into events quicker while leaving less room for human error. ADLs are also much more efficient and effective for users if the product data and PPGs that go into them are already cleansed.  
  • If products aren’t actively being deactivated (or there’s no deactivation process that currently exists), ADLs are likely your best stop gap to prevent products that are no longer sold from being added to events they shouldn’t be. 

3. Master Data Governance   

The third major category is your master data governance process. The longevity of your cleansed master data will only be as good as the robust processes you put in place to govern the master data. Cleaning up master data will be pointless if you don’t also implement governance processes to keep them clean. Otherwise, you’ll face these same master data challenges in just a few short years, possibly shorter depending on the size of your organization.  

Our recommendation is that there should be a singular business owner role for each hierarchy level and attribute for both customers and products, and it likely makes the most sense for the owners to be the people that create the data or feel the impact most when the data is incorrect. A few master data items to consider implementing a governance process for are: 

• Adding a new customer 
• Editing customer hierarchy levels 
• Deactivating a customer 
• Adding a product 
• Editing product hierarchy levels 
• Deactivating a product 
• Editing a customer’s ADL 

Getting the Most Out of Your TPM Master Data  

Master data can be a little overwhelming simply because there can be so much of it with so many people and functions inputting and changing it all the time. But with the right cleansing effort and concurrent governance processes implementation, you can truly set your CPG organization up for success for many years to come throughout so many different business functions.   

Reach out to our team if you’re ready to start your TPM master data cleansing journey or have any questions. 

Contributions by Meg Longwell

The post Considerations for Evaluating and Cleansing Your Master Data for a TPM Implementation appeared first on Clarkston Consulting.

As biopharma and biotech companies grow and evolve, the focus of CSV/CSA efforts may concentrate on the planning or validation of new systems or major upgrades to support the growth of the organization. This can make it more difficult to sustain focus on maintenance activities of the existing business systems in your IT systems landscape – or in the case of lean organizations, resourcing challenges to support both project work and business as usual operations (planned and unplanned). 

While Application Managed Services (AMS) is typically used to help support configuration changes to a specific system as a company evolves, Managed Services for CSV or CSA is able to support the validation activities of the many systems throughout a company’s life.  

A CSV Managed Services partner can provide relief to your internal team by helping to prepare key validation activities and tasks, allowing you to focus on when and where you are needed most. 

Benefits of Validation Managed Services 

#1

Periodic reviews help confirm that systems (including ERP GxP modules, LIMS, MES, eQMS) remain in a validated state by assessing a number of factors, including Quality Events (QE) directly related to the functionality of the system. Access controls and user access reviews ensure users have the correct permissions, and you can audit trail integrity through the life of the system. One of the best uses of periodic reviews is identifying opportunities for remediation before they become compliance risks. 

Having dedicated validation services individuals on your team can mean having a fresh pair of eyes when examining periodic review content. It is often the case that organizations utilize System Owners for QE examinations during periodic reviews. CSV Managed Services individuals may be able to help identify related QEs or audit trail events in the system that were not initially examined. CSV Managed Services involvement also removes the burden of work from the system owners.  

#2

Validation support for system upgrades, patches, and configuration changes to existing business systems ensures that enhancements or vendor-driven updates do not compromise functionality and compliance. In a GxP environment, even minor system changes, such as configuration adjustments, can introduce unintended impacts to validated functionality or data integrity. Validation Managed Services support can help proactively evaluate the appropriate actions for any change to a system, including determining the appropriate level of testing and making updates to lifecycle documentation that confirm that critical requirements continue to be met. 

With the number of systems that in-house quality and validation stakeholders are dealing with, it can be beneficial to have a CSV partner producing the initial, and thorough, drafts of lifecycle documentation and test scripts. This can help reduce bottlenecks, such as with individuals who may be involved in many upgrades.  

#3

CSV Managed Services support can be especially useful when evaluating and implementing vendor-driven updates, particularly in IT environments with cloud-hosted or SaaS platforms where scheduled releases can happen multiple times a year. These often occur on defined release cycles, requiring proactive planning and coordination between different teams.  

A validation managed services provider can be used to coordinate logistics between the involved parties, such as IT, Quality, and Business System Owners. Validation support in these cases may include reviewing release notes, assessing new or modified functionality that would benefit the business or process, challenging vendor documentation where appropriate, and ensuring that testing evidence adequately demonstrates continued control of GxP-related processes. 

CSV Managed Services: Worth the Investment 

Engaging outside support may seem challenging, in areas such as ensuring the validation managed services team is familiar with your systems and procedures and is up to speed on upgrade roadmaps. However, the initial time investment, combined with proactively aligning on your responsibilities and your validation managed services partner responsibilities, leads to an effective validation function that supports your business and ensures system compliance throughout its lifecycle.  

Whether your CSV/CSA function is a team of one or a team of many, a validation managed services partner can be a valuable investment to help focus your team’s energy on the most strategic initiatives and projects for the year.  

Together, these ongoing CSV activities reduce regulatory risk, support inspection readiness, and reinforce patient safety by maintaining confidence in the systems that manage and report quality and manufacturing data. 

The post Exploring the Benefits of a CSV Managed Services Partner appeared first on Clarkston Consulting.

Download the full 2026 Supply Chain Trends Report here.

This free trends report outlines industry perspectives and expert advice from our team of supply chain consultants. You can view an excerpt of the report below, and if you’d like to discuss any of the trends or other challenges in the supply chain space, connect with our team today.

Key Supply Chain Trends

In 2026, supply chain transformation will accelerate through rising AI adoption and deeper integrations across core technologies. Organizations will experiment with and hone in on specific AI uses cases within supply chain planning and execution to drive cost savings and efficiency within the supply chain. Ongoing supply chain uncertainty and increased cybersecurity risk will continue to challenge organizations, highlighting the importance of assessing supply chain network and optimizing supply chains to be agile and adaptable, while emphasizing the importance of risk management within daily operations. 

Clarkston’s supply chain consultants have highlighted the top trends that businesses should consider and keep top-of-mind throughout the year:

1. Expansion of AI use cases within supply chain
2. Managing supply chain uncertainty with network design & optimization
3. Leveraging integrated technology to drive supply chain outcomes

Trend 1:

Expansion of AI use cases within supply chain 

In 2026, we anticipate the focus of AI utilization to rapidly expand beyond planning to include greater emphasis on execution. As agentic AI matures, organizations are starting to venture into autonomous supply chain execution, often with minimal or no human intervention required. 

Within the planning function today, AI is primarily leveraged to enhance decision-making: improving the quality of forecasts, identifying trends, and recommending actions or exceptions for teams to evaluate. Going forward, we can expect to see organizations experiment with agentic AI to directly make business decisions and act vs. recommending actions for teams to implement. Rather than relying on planners to interpret insights, revise orders, and develop production schedules, agentic AI can assess all available information, determine the best course of action, and autonomously carry out these tasks. However, achieving this vision requires organizations to shift their approach across several key areas. 

Data quality and analytics maturity play a foundational role in adopting an AI-driven approach. Organizations with high levels of maturity in this area can implement faster and extend AI across a wider set of use cases, but that doesn’t mean others can’t start realizing the value of AI within strategic areas and focused use cases. Investing in data engineering, data governance, and advanced analytics to ensure foundational data is consistent and reliable drives the potential for unlocking further AI capabilities. As part of that foundation, organizations also need to evaluate how they’re factoring in today’s rapidly changing environment and the relevance of historical data given the constant change in recent years (e.g. COVID impacts, tariffs, purchasing pattern changes) as advanced models and data tools are heavily reliant upon the accuracy of this data.   

Governance frameworks and guardrails are equally critical to setting agentic AI up for success and aligning the utilization approach across the organization. Clear boundaries need to be defined for when agentic AI can act independently, when decisions need to be escalated, and where human approvals remain essential. Doing so helps ensure autonomous execution stays aligned to business strategy, customer commitments, and the organization’s overall risk appetite. 

Cross-functional alignment and business process redesign are also needed to support an AI-driven approach. Enabling agentic AI across business functions (e.g. planning, sourcing, production, logistics, and customer operations) requires new ways of working, along with mechanisms to integrate decisions across various functions so organizations can optimize solutions and create a more adaptive, resilient supply chain. 

Finally, successful adoption depends on closing the gap between AI literacy and business expertise, supported by key layers of talented individuals with skillsets that span both areas. In parallel, performance measurement should evolve to evaluate the effectiveness of AI-driven models.  

Organizations should monitor the learning rate at which models incorporate new data, adjust to changing conditions, and refine the logic used to make decisions. They should also assess the time taken to detect issues, which helps clarify how quickly the system can identify anomalies or supply chain disruptions, enable quicker intervention, and reduce downstream impacts. Advanced planning tools are incorporating AI capabilities to enhance planning efficiency and drive the organization to focus on the true exceptions that need to be managed.  

Continue reading by downloading the full report below.

Download the Full 2026 Supply Chain Trends Report Here

Contributions from Kate Poknis

The post 2026 Supply Chain Trends appeared first on Clarkston Consulting.

Yet many of those assets have not been reevaluated through today’s capital and risk lens. 

These pressures have led many organizations to ask questions about owned vs. asset light manufacturing models and to rethink the best approach for their organization. Rather than leaning into a strictly owned manufacturing or asset-light strategy, an asset-intentional manufacturing strategy incorporates a disciplined evaluation of every production asset against competitive advantage, capital efficiency, and risk-adjusted return on capital. Owned assets must earn their place in the portfolio. 

Where Ownership Creates Advantage 

Asset ownership is justified and fits into a capital strategy in two scenarios: differentiating assets and strategic control assets. 

Differentiating assets are those where the organization leverages proprietary formulation or manufacturing methods; economies of scale are difficult to replicate externally; quality precision is an anchor to brand equity; regulatory oversight requires direct control; or speed to innovation is critical to achieving competitive advantage. 

Strategic control assets represent manufacturing that provides supply resilience across high-risk categories, guarantees supply across high-volume SKUs, or where internal manufacturing is the optimal choice for cost optimization. 

For many organizations, a review of their product and manufacturing portfolio often highlights that only a portion of their business falls into this category. 

Where Ownership Becomes a Capital Drag 

Manufacturing assets are capital intensive, reinvestment heavy, and balance sheet constraining. The current macroeconomic environment and high interest rates are pressuring organizations further, highlighting the opportunity cost of capital tied up in manufacturing. 

Non-strategic areas are where leveraging outsourcing can drive the best results for an organization. Scenarios where outsourced production tends to be the optimal capital strategy include product categories where co-packer or co-manufacturer capabilities and capacity are high, production of products is standardized, differentiation is driven by the brand (not the process), and where economies of scale are hard to achieve with internal manufacturing. Appropriately identifying and developing strategies to mitigate risk and build supply resilience can make outsourcing production of these goods a positive capital strategy for the organization. 

In one recent project, Clarkston partnered with a CPG brand to assess its long-term manufacturing strategy. A portfolio-level review revealed that several owned production assets weren’t tied to proprietary differentiation and were generating below-portfolio Return on Investment Capital (ROIC). Through a structured asset-intentional assessment, leadership aligned on transitioning select production to external partners while retaining ownership in strategically differentiating areas. Post-execution, the organization is now redeploying capital toward brand expansion and innovation investments while building governance capabilities to support a hybrid network. 

Measuring Capital Efficiency with Return on Invested Capital (ROIC) 

Financial analysis and framing of capital utilization is critical to aligning an optimized strategy. ROIC is the metric that should be evaluated in setting capital strategy, as it layers in the effectiveness of capital at generating return for an organization, rather than focusing on EBITDA and a common approach of leveraging fixed cost reduction narratives. ROIC enables organizations to align financial and operational goals while assessing capital turnover and the true cost to capital utilization.  

Owning facilities and production assets ties up significant capital, and the opportunity cost should be evaluated as part of the equation. Instead of owning assets, could the capital be better deployed to drive innovation, brand investment, automation, or acquisition? 

Adding in outsourced production creates complexities as well that need to be balanced in this equation. Layering in the co-packer or co-manufacturers margin adds cost, contract complexity, drives implications across logistics, and shifts the organization towards a variable cost model.  

Balancing Risk in Manufacturing Strategy 

Increasing supply chain complexities and challenges have highlighted the importance of supply resilience over the past several years. It’s essential to appropriately balance risk in designing a capital strategy around manufacturing. In shifting toward an asset-intentional strategy, organizations need to evaluate the right balance of supplier concentration, geopolitical exposure, raw material volatility, and regulatory oversight to balance risk exposure with cost optimization. 

In another project for a CPG client, Clarkston conducted a comprehensive co-manufacturing benchmarking and strategy assessment that extended beyond production footprint to include commodity pricing, logistics cost analysis, and warehousing contract strategy. As a core component of this analysis, each co-manufacturer and commodity were evaluated to fit within the desired risk portfolio of the client. The recommendations included opportunities to leverage their strategic partnerships in new ways to optimize costs and improve supply chain resiliency. 

Depending on the risk appetite of the organization, this may lead them to retain ownership of certain production to materially reduce risk exposure. Where external production is selected, a diversified external supplier network can provide flexibility and improve business continuity in the event of a supply challenge, cost impact, or other significant event occurring. 

Aligning manufacturing strategy with this method can reduce risk and ultimately enhance supply resilience while finding a healthy balance between capital strategy and supply chain optimization. 

Governance is Imperative to Successful Implementation 

Shifting manufacturing strategy toward a hybrid network or a fully asset-light approach introduces additional complexities into managing the business, both operationally and financially. Governance maturity is a prerequisite to successfully enabling a strategic shift in manufacturing strategy. This requires end-to-end digital visibility, disciplined S&OP integration, scenario modeling capabilities, structured contractual risk allocation, and formal supplier performance management. 

With these core capabilities, hybrid or asset-light manufacturing networks can outperform a traditional owned manufacturing model. Lacking these capabilities can create undue risk and result in negative supply and cost scenarios when challenges occur.  

The Strategic Outcome 

Asset-intentional manufacturing delivers capital flexibility, scalable capacity, and risk calibrated supply resilience. It aligns capital strategy with operational execution, enabling organizations to: 

• Redeploy capital to accelerate growth 
• Create network agility and scalability 
• Build risk calibrated supply resilience 

Asset-intentional organizations routinely ask: 

• Would we build this facility today? 
• Does this asset protect proprietary differentiation? 
• Is each asset’s ROIC above the portfolio average? 
• Does ownership materially reduce risk exposure? 
• Do we possess governance maturity to outsource responsibly? 

At Clarkston, we help our clients answer these questions and many more as we partner with leadership teams to evaluate, design, and operationalize asset-intentional manufacturing strategies that balance capital efficiency, competitive advantage, and risk exposure. 

The post Asset-Intentional Manufacturing: A Capital Strategy for Modern CPG Leaders appeared first on Clarkston Consulting.

Many legacy ERP systems struggle to provide the agility retailers need. As a result, organizations are increasingly transitioning to cloud-based platforms. In 2024, 70% of new ERP deployments were cloud based. SAP Cloud ERP is helping retailers modernize their technology foundation while preparing for long-term growth. Below, we outline what SAP Cloud ERP offers and how retailers can approach adoption strategically. 

Understanding SAP Cloud ERP 

SAP Cloud ERP (Public Cloud) is a software-as-a-service ERP platform designed to be deployed quickly and updated continuously. Because it is cloud-based, it delivers real-time insights without requiring on-premise infrastructure. 

Retailers can also extend the platform through SAP solutions built specifically for the industry. For example, SAP Customer Activity Repository (CAR) provides centralized retail data, enabling better visibility into customer behavior and sales performance. 

Since SAP manages infrastructure, updates, and system maintenance, retailers avoid the hardware and IT overhead required with traditional on-premise systems. This model provides scalability, ongoing innovation, and a foundation that evolves alongside the business. 

For organizations currently running on-premise ERP environments, migration planning should be an early consideration when evaluating SAP Cloud ERP. 

Key Considerations for Retail ERP Transformation 

As you explore SAP Cloud ERP for your retail business, there are a few key best practices to keep in mind:  

Identify Business Areas Most in Need of an Upgrade  

Retailers should begin by assessing which areas of their organization are under the most stress. Legacy ERP systems can struggle to support real-time inventory visibility or have siloed data, and identifying high impact areas can help to prioritize where SAP Cloud ERP can deliver the most immediate value.   

Pinpoint Where SAP Cloud ERP Can Unlock Value and Support Growth  

Once high-need areas have been identified, retailers should evaluate how SAP Cloud ERP can enable further growth and innovation. Through add-on solutions, like SAP Predictive Analytics, for instance, retailers can automate operations and better support evolving business processes. SAP Cloud ERP can also integrate data across departments, creating a more complete and accurate view and enhancing retail efficiency.    

Align Budget with Current and Future Growth Goals  

In addition to use cases, cost and scalability are critical considerations for an SAP Cloud ERP adoption. SAP Cloud ERP has a subscription-based cost structure, and retailers should keep this in mind during budgeting season.  While upfront costs for a cloud ERP are less expensive – and Total Cost of Ownership comparisons are consistently 30-50% less than on-premise alternatives – retailers should still evaluate the long-term ROI that SAP Cloud ERP offers to ensure the solution is sustainable for them.   

Plan for Integration Early  

Once a business has committed to an SAP Cloud ERP adoption, they should start taking steps to plan for integration. According to Forbes, poor planning is one of the top causes behind why an ERP implementation fails. That said, planning for integration early is crucial to ensuring SAP Cloud ERP migration goes smoothly and delivers value across the business.  

Strengthen Data Governance  

Establishing strong data governance and strategy before integration begins is a key first step to preparing for adoption. Data quality problems can increase project failure rates by 60%, but high-quality, well-organized data helps make the transition easier. Without strong data governance prior to migration, errors that may have disrupted the success of the prior system will be carried over to the new ERP system.   

Prioritize the Services That Make the Most Sense for Your Business  

Determining the most relevant SAP Cloud ERP services needed can also help map out the integration process. During integration, starting with the core capabilities before incorporating more advanced add-ons can make the process easier.  

SAP Cloud ERP comes with the core ERP, which includes services for finance, sales, procurement, and supply chain, and add-on services can also be considered. SAP S/4HANA Retail for Merchandise Management, for example, is an add-on service for helping users manage their entire retail value chain and improving customer experience.   

Incorporate Change Management  

SAP Cloud ERP often comes with pre-built rapid deployment and integration, but there are still considerations retailers should keep in mind to help the transition go smoothly. Most importantly, effective change management is crucial for helping train employees on how to use the new technology.  

Consider an SAP Partner   

During adoption, retailers should also explore the possibility of working with an SAP partner with SAP Cloud ERP experience, as these companies report a higher success rate at 85%. This partner can advise the business on the process and help the transition go smoothly, which is especially beneficial for companies without strong SAP-literate teams.   

Final Thoughts

An SAP Cloud ERP adoption in retail can be a complex and strategic process that requires careful planning. Businesses looking to adopt SAP Cloud ERP should start by assessing their needs, making the business case, and budgeting for adoption before designing a clear roadmap for implementation.  

Above all, having the right SAP partners by your side throughout the process can make all the difference. Reach out to us today to chat more. 

Contributions from Natalie Pollock 

This piece was originally featured by Crescence, a Clarkston Consulting company and authorized SAP Partner and value-added reseller. 

The post Navigating SAP Cloud ERP Adoption for Retailers appeared first on Clarkston Consulting.

Download the full 2026 Diagnostics Trends Report here.

This free trends report outlines industry perspectives and expert advice from our team of life sciences consultants. You can view an excerpt of the report below, and if you’d like to discuss any of the trends or other challenges in the diagnostics space, connect with our team today.

Key Diagnostics Trends

The diagnostics industry is being shaped by the push towards telemedicine and remote solutions, proactive over reactive healthcare, the fight against antimicrobial resistance, and affordability in diagnostic testing. It’s imperative that businesses identify ways to incorporate advanced technologies and develop innovative diagnostic testing that allows for faster, more accurate results while addressing data security and cost concerns associated with the new world of diagnostics. 

Given our deep industry knowledge, Clarkston is well-suited to help businesses in successfully navigating these changes – whether it’s exploring new data storage and analysis options, conducting supply chain landscape assessments, or incorporating AI in your diagnostic research. Reach out to our team to learn more about how these advancements are influencing healthcare in the future and how we can work with you to stay ahead of the curve in this ever-evolving market. 

Clarkston’s life sciences consultants have highlighted the top diagnostics industry trends that businesses should consider and keep top-of-mind throughout the year:

1. Continued Growth of Remote Diagnostics
2. Shifting from Reactive to Proactive Care with Personalized Diagnostics
3. Fighting Antimicrobial Resistance with Diagnostics
4. Affordability is a Key Barrier in Molecular Diagnostics Adoption

Trend 1: 

Continued Growth of Remote Diagnostics 

The remote diagnostics sector continues to advance in line with the growth of digitization as a whole. Patients and healthcare providers alike appreciate the accessibility and flexibility that telemedicine and virtual care offer, but sustained progress will depend on more than convenience alone. Continued advancements in remote diagnostics are increasingly intertwined with digital infrastructure and data-enabled care models.  

We are starting to witness a strong correlation between the upward trend of personalized medicine and remote diagnostics with wearable devices, such as continuous glucose monitors, blood pressure monitors, and even smart clothing integrated with sensors. These tools can provide real-time notifications regarding the status of a patient’s health, offering diagnostic solutions more quickly and cutting out the inconveniences of on-site visits. 

Many individuals are familiar anecdotally, if not from personal experience, with telemedicine. For years, and especially after the Covid-19 outbreak, virtual doctor appointments have been a convenient option to seek clinical advice and diagnoses based on descriptions of symptoms. The world of remote diagnostics continues to evolve as now clinicians aren’t only able to rely on phone and video calls to interact with their patients but can also analyze digital images of molecular samples remotely.  

One of the most critical challenges and concerns impacting patients in remote diagnostics is data privacy, particularly with the global remote diagnostics market size expected to reach $653.29 billion by 2033. Advanced technology in data storage and analysis, such as cloud-based data infrastructure, will play an important role in resolving the data security and privacy concerns associated with remote diagnostics. 

Trend 2:

Shifting from Reactive to Proactive Care with Personalized Diagnostics 

The U.S. healthcare system has long functioned in a reactive manner, identifying illnesses in patients and developing treatment plans based on their symptoms or more detailed diagnoses – in fact, reactive treatment currently consumes over 75% of healthcare spending in the U.S. As cost pressures intensify, one of the most valuable cost-saving strategies in healthcare is to invest in prevention rather than treatments. 

The rise in proactive healthcare is reshaping expectations for the diagnostics industry. To support earlier intervention, diagnostic tools must deliver insights and results sooner and faster than ever, often before symptoms are even evident. Personalized or precision medicine plays a pivotal role in this evolution; even as the focus moves upstream toward prevention, the need for diagnostic testing remains strong, particularly as testing becomes more individualized and embedded in long-term disease management and therapeutic research.  

With personalized medicine, tools like wearable monitors enable live, real-time tracking of patient data, supporting earlier recognition of potential health concerns. Diagnostic tools such as Sepsis Watch demonstrate how advanced analytics can be applied to diagnostic data to identify deterioration sooner and guide timely intervention. Similarly, methodologies such as AI-enabled continuous glucose monitoring – which allows proactive forecasting of glucose levels – are proving helpful in enhancing predictive diagnostics and for risk modeling to identify high-risk individuals based on biological markers before symptoms arise.  

Incorporating AI-powered analysis and data modeling tools can aid in analyzing trends, developing care plans, detecting abnormal patterns, and providing alerts to enable early intervention. These capabilities are helping shifting the industry from one centered on treating disease to one focused on anticipating and preventing it. 

Continue reading by downloading the full report below.

Download the Full 2026 Diagnostics Trends Report Here

Read last year’s Diagnostics Trends Report here.

The post 2026 Diagnostics Trends appeared first on Clarkston Consulting.

This free trends report outlines industry perspectives and expert advice from our team of life sciences consultants. You can view an excerpt of the report below, and if you’d like to discuss any of the trends or other challenges in the medical device space, connect with our team today.

Key Medical Device Industry Trends

Medical devices companies continue to embrace digital technologies, allowing patients and healthcare providers to make informed decisions regarding patient care. Continuous monitoring and AI-driven insights are giving patients and providers greater visibility into health trends and potential risks, helping shift care beyond isolated clinical encounters. 

As these technologies become more embedded in everyday care, the responsibility to balance innovation with trust grows. Staying aligned with evolving regulatory expectations, and treating data security and patient safety as foundational requirements rather than afterthoughts, will be critical as companies continue to bring new, connected devices to market.  

Clarkston’s life sciences consultants have highlighted the top medical device industry trends that businesses should consider and keep top-of-mind throughout the year:

1. Evolving FDA Oversight of Consumer Health and Diagnostic Device
2. Expansion of Remote Patient Monitoring Elevates Cybersecurity Requirements
3. Continued Growth of AI-enabled Medical Devices 
4. Tariffs Impacting Pricing and Medical Device Supply Chains

Trend 1:

Evolving FDA Oversight of Consumer Health and Diagnostic Devices

In the last few years, wearable fitness trackers have added novel functionality to providing health and wellness metrics at patients’ fingertips. Users can track more than just steps on a watch or hours slept. Wearable devices like the Apple Watch enable continuous heart rate monitoring, track sleep apnea, and capture other critical health metrics. The newest Apple Watch even includes features that allows users to track blood pressure and identify cases of hypertension, which is significant given that almost 1 billion people worldwide live with high blood pressure, often without a diagnosis.  

These new monitoring and diagnostic features have the potential to be lifesaving, especially for undiagnosed conditions. However, as patients receive this health information almost instantaneously, it’s imperative that the data and collection methods are accurate.  

Apple has worked closely with the FDA on its health-enabled features on the Apple Watch, including sleep apnea monitoring irregular heart rhythm notifications, and the hypertension notification, which has received FDA approval. Moving forward, companies must invest in regulatory expertise and continue to collaborate with the FDA in such a rapidly evolving regulatory environment. 

Over the last several years, consumer electronics have also increasingly implemented health tools that blur the line between wellness products and medical devices. Now, the convergence has extended in the opposite direction, as medical device companies like Dexcom introduce innovations such as the first over-the-counter continuous glucose monitor, Stelo.  

Marketed to adults who aren’t taking insulin, Stelo allows individuals to proactively track their blood sugar levels and identify potential risks earlier. For individuals with limited access to care or inadequate health insurance, tools like Stelo can also offer valuable diagnostic insight and increased visibility into their health. According to the Stelo website, the product is marketed toward adults who aren’t taking insulin and can be purchased by anyone seeking additional information on their glucose levels. 

However, while these technologies can enhance awareness and detection, they’re intended to complement, not replace, guidance from a healthcare provider. 

Trend 2:

Expansion of Remote Patient Monitoring Elevates Cybersecurity Requirements

Wearable devices such as wellness trackers and continuous glucose monitors can now collect and analyze health data 24 hours a day, expanding what’s possible with remote patient monitoring: a practice in which patient data is collected at home with healthcare providers accessing the data, providing a fuller view of patient health as opposed to traditional, episodic care. 

When health and wellness features are embedded into devices people already use, patients are more likely to stay engaged and actively participate in their own care. Software-enabled devices, including the Apple Watch and Dexcom’s Stelo, enable data sharing with healthcare providers, making it easier for patients and clinicians to view trends over time, supporting earlier detection and leading to more informed medical decisions. 

However, this also raises important questions about how that data is shared and protected. As remote patient monitoring becomes more common, it’s increasingly important that these systems are capable of safely handling and protecting sensitive health information. While greater access to real-time patient data has its benefits, it cannot be implemented without considering risks, including security breaches.  

In response to this growing risk, the FDA has issued new guidance on ensuring cybersecurity in medical devices prior to marketing the device. Adhering to this guidance is essential for companies developing connected health technologies, helping ensure that sensitive patient identifying information and patient health information is kept secure.

Continue reading by downloading the full report below.

Download the Full 2026 Medical Device Industry Trends Report Here

Read last year’s Medical Device Industry Trends Report here.

The post 2026 Medical Device Industry Trends appeared first on Clarkston Consulting.

Download the full 2026 Apparel Industry Trends Report here.

This free trends report outlines industry perspectives and expert advice from our team of retail consultants. You can view an excerpt of the report below, and if you’d like to discuss any of the trends or other challenges in the apparel space, connect with our team today.

Key Apparel Industry Trends

In part due to tariff and general geopolitical uncertainty, customers are being more discerning with purchases. Consumers, especially Gen-Z, are searching for differentiated value with each purchase and will continue to do so moving into the second half of the 2020s. Differentiated value can come as lowered price points, sustainability commitments, personalization, high premium, and conscious marketing. However it’s delivered, brands that clearly communicate value performed better in 2025 and are positioned to continue doing so in the year ahead. 

Despite a difficult market, there are pockets of growth. Jewelry is gaining share as consumers lean into self-expression and purchases that feel more enduring. Wearable technology is also gaining traction. With strides in AI and digital offerings, companies are becoming leaner and faster than ever before, which they will need as they move into another uncertain year. Apparel companies positioned to win in 2026 and beyond will pair a clear value promise with streamlined operations and a practical approach to AI and digital execution.  

Clarkston’s apparel consultants have highlighted the top apparel industry trends that businesses should consider and keep top-of-mind throughout the year:

1. Navigating Tariff Impacts
2. Exploring Multi-Country Sourcing
3. Meeting the Needs of Value-Seeking Shoppers
4. Watching the Growing Jewelry Sector
5. Wearable Technology Gaining Popularity
6. Looking into AI and Cost Cutting

Trend 1:

Navigating Tariff Impacts

The apparel sector has especially felt the impacts of Trump’s tariff negotiations in 2025. The U.S. imports 89% of apparel and leather products sold in the country, leaving the apparel sector as one of the most impacted.   

Most companies regard tariffs as the most pressing challenge to the industry moving into 2026. Victoria’s Secret, for example, reported approximately $100 million net tariff impact in 2025. Tapestry, consisting of Coach, Kate Spade, and Stuart Wiseman, reported the total expected impact on profitability from tariffs at around $160 million, representing nearly 230 basis points of margin headwinds.  

However, despite the tariff burdens, most U.S. apparel companies are attempting to avoid price hikes due to concerns about consumer spending. Instead, many are pursuing gradual increases over time while attempting to absorb the near-term hit. 

URBN describes its approach as “gentle price increases” to preserve value for customers. Colombia Sports is similar attempting to absorb the impact of tariffs by not altering prices of their seasonal product line, but rather offsetting over time with gradual price increases, vendor negotiations, expense efficiencies, and other mitigation tactics.  

To support longer-term cost control, many companies are also optimizing inventory through SKU reduction. Tapestry, for example, reduced handbag styles by over 30% in the fall, allowing them to further streamline their offerings. Value apparel brands like Bershka and H&M reduced SKUs by 15-25% between 2023 and 2025.  

In addition to lowering overhead and supply costs, SKU discipline can free up capital and help brands react faster to shifts in consumer sentiment. As companies plan for sustained uncertainty and ongoing cost pressure, leaner inventories are likely to continue. 

Trend 2:

Exploring Multi-Country Sourcing

Multi-country sourcing is also becoming a core lever for long-term cost control. Companies have already been diversifying beyond China, with the share of apparel and textiles sourced from China down by 6% between 2019 and 2023. This is in part due to the fragility of single country sourcing, as exposed by COVID-19, but additionally due to the rising labor and shipping costs.  

Many companies have shifted more production to other Asian markets, specifically Vietnam, Bangladesh, India, and Cambodia, due to lower labor costs. Vietnam has been a particularly prominent sourcing destination for U.S. apparel retailers, with Vietnamese exports up 35% between 2015 and 2020. Diversification across Vietnam and other Asian hubs is expected to continue into 2026. India is also attempting to capitalize on this shift, with the government investing about $2.5 billion in incentives and reforms aimed at encouraging foreign sourcing and manufacturing.  

While Asia is unlikely to lose its central role given established manufacturing infrastructure, nearshoring is gaining renewed attention as shipping costs rise and tariff outcomes remain uncertain. Shipping costs between the U.S. and Asia increased sharply, skyrocketing 165% between December 2023 and February 2024.  

Nearshoring isn’t a new topic – it became a buzzword in the corporate boardroom especially in the late 2010s and early 2020s. However, despite the buzz, the shares of imports to Europe and the U.S. from nearshoring countries has remained flat since 2019. Limited manufacturing capacity has been a major constraint, despite advantages in labor rates, shipping costs, and tariffs.  

Renewed interest in nearshoring will likely lead to improved capabilities moving into the second half of the 2020s. Foreign direct investment in nearshoring manufacturing has increased by 20% in the last five years, and the Americas Act, if approved by Congress, would dedicate $14 billion to apparel subsidies and investments in nearshoring capabilities. Mexico is emerging as a key nearshoring hub for the U.S., and heading into 2026, nearshoring investment is expected to continue, supporting expanded Mexican manufacturing capacity. 

Continue reading by downloading the full report below.

Download the Full 2026 Apparel Industry Trends Report Here

Read last year’s Apparel Industry Trends Report here.

The post 2026 Apparel Industry Trends appeared first on Clarkston Consulting.

At the same time, Artificial Intelligence (AI) and machine learning are raising the bar for trusted, well-described data. However, analytics and generative AI are only as good as the context and quality of the data they use. Without shared semantics and reliable governance, teams spend more time debating metrics than acting on insights. 

Below, we dive into making the business case for SAP Datasphere and how it can help, outlining a practical view of what it is, why it matters, and how it supports both IT leaders and business users.  

SAP Datasphere: Unifying and Simplifying the Data Landscape 

SAP Datasphere is SAP’s cloud data service on SAP Business Technology Platform (BTP) positioned as the next generation of SAP Data Warehouse Cloud (announced March 8, 2023). It’s designed to connect and harmonize SAP data with non-SAP data while preserving business context. 

Datasphere is a unified data service that brings together data integration, cataloging, semantic modeling, data warehousing, and virtualization patterns across SAP and non-SAP data. Datasphere is positioned as the foundation for a business data fabric approach, helping organizations deliver meaningful data to consumers with business context and logic intact.  

A data fabric approach unifies access to data across systems while improving governance and reuse. SAP’s “business data fabric” framing emphasizes preserving business semantics so people can work from consistent definitions rather than rebuilding logic in each tool.   

Instead of treating data as “just tables,” Datasphere emphasizes business semantics. For SAP S/4HANA data, much of that semantic meaning already exists in the Virtual Data Model (VDM), which is represented by Core Data Services (CDS) views. Datasphere can leverage that structure so teams spend less effort translating raw tables into business-ready entities and definitions. 

Benefits for IT Leaders & Business Users 

For IT, Datasphere can reduce integration overhead by standardizing connectivity patterns and supporting centralized governance practices across the data landscape. In some scenarios, it can simplify legacy warehousing architectures by reducing duplication and improving reuse, though most organizations adopt it alongside existing platforms as part of a phased modernization. 

For business users, the value is faster access to trusted, contextual data for analytics and decision-making, without waiting for every request to be modeled from scratch. When paired with SAP’s analytics layer and ecosystem, this can shorten time to insight and reduce the back-and-forth of metric reconciliation.  

On the AI side, SAP has announced generative AI and data governance enhancements connected to Datasphere and SAP Analytics Cloud, emphasizing governed access and enterprise-wide availability of insights. 

Turning Data into Decisions 

SAP Datasphere aims to bridge a familiar gap: IT needs control and governance, while the business needs speed and usable context. By supporting a business data fabric approach, Datasphere can help organizations scale analytics and AI initiatives with consistent definitions, improved trust, and a clearer path from raw data to decisions.  

Contact our SAP team to discuss further. 

Contributions by Heather Hilgendorf 

The post Making the Business Case for SAP Datasphere appeared first on Clarkston Consulting.