#digital operations

Operations Management forms the groundwork of the day-to-day running of an enterprise. Operations management is the administration of the business in a way that provides maximum efficiency. Maximum efficiency means maximum profits. The operations management aims at perfection within the organization. It aims at using the resources of the company to the maximum capacity. The task of converting the material and labor to finished goods as efficiently as possible for profit maximization falls into the purview of the operations management. It balances the cost and the revenue to generate the highest net profit. Benjamin Choukroun’s UK, Electronic Check can help with digitalizing the operations administration support to save money and time. The following are the duties of an Operations Administrative support.

Daily Business Operations: The work of the operations administrative support is to sync the day-to-day working of the company. The support has to work closely with the operations manager to ensure the smooth running of the company. The aim is to utilize the resources of the company as a way to maximize efficiency.

 Enforcing Company policy and procedures: The operations administrative support is responsible for enforcement of the company’s policy and procedures. The company makes a set of rules and regulations that need to be followed by the employees to ensure that there is no wastage of time and money. The operations support has to make sure that there is no deviation from the set rules of the company.

 Make Recommendations: The Operations administrative support has to be actively involved in the whole process of running the company. The operations administrative support should give recommendations to improve the sales of the company. Higher sales mean higher profits for the company. 

 Work together with different departments: The Operations administrative support is not concerned with any single department. It has to work together with all departments to reach the company’s goal of maximizing its profits. The communication among different departments has to be carried out for maximum efficiency.

 Monitor Sales Reports and supplier relations: The suppliers have to be well maintained so that there is no delay in the supply of raw materials. The relationship with the suppliers should be amicable to avoid any discrepancies and arguments. The Operations Administrative support has to ensure that the suppliers are happy with the company in terms of payments, etc. Operations Administrative support has to also monitor sales reports to make sure that the sales are always on the rise. 

 Emails from customers, clients, and contractors: The correspondence with the various channels of the organization is vital for the smooth functioning of the organization. The emails are to be handled skillfully to avoid any confusion.

Keep track of Industry trends and consumer market: The operations administrative support is required to be updated about the ever-changing trends of the industry and the consumer market so that the company can benefit from the knowledge and make maximum profits.

Singapore’s ATM Managed Services and Digital Cash Ops Market is valued at USD 1.2 Bn, driven by rising digital payments, cashless transactions, efficient cash management systems and technology-led banking infrastructure.

As banks, retailers and public-sector users modernise financial access, ATM networks are evolving beyond cash withdrawal into integrated digital cash operations, multi-function services and secure transaction management.

Article Highlights

A five-component business case architecture that has secured approval for digital operations investments exceeding $50 million at three Fortune 200 enterprises.

Real U.S. market data—from McKinsey, Gartner, and the U.S. Bureau of Labor Statistics—that your CFO cannot dismiss as vendor propaganda.

A contrarian perspective on why your board may be right to hesitate, and how to address their unspoken objections before they are raised.

Your board is not skeptical about digital—they are skeptical about unfunded promises. Every quarter, senior leaders at mid-to-large global brands in retail, CPG, DTC, financial services, and industrial manufacturing present digital operations proposals that get deferred, downsized, or dismissed because the business case fails to connect technical investment to enterprise value. You need a framework that translates operational complexity into the language of return on invested capital, risk mitigation, and competitive positioning—and this article delivers exactly that, based on four decades of advising Fortune 500 leadership teams.

Key Statistics and Facts

McKinsey & Company (2026): Companies that align digital operations investments directly with measurable business growth outcomes achieve a 23% higher total shareholder return over three years compared to peers who invest in technology without a corresponding operating model redesign.

Gartner (2026): 68% of enterprise digital initiatives fail to meet stated business objectives—not because of technology failure, but because the business case omitted cross-functional process redesign and change management costs.

Deloitte (2026): Organizations that implement a structured technology stack rationalization program before migrating to new platforms reduce total cost of ownership by an average of 31% over 24 months.

U.S. Bureau of Labor Statistics (2026): In manufacturing and logistics, fulfillment cycle time reduction of 15% correlates directly with a 9% improvement in customer retention rates—a metric your board will recognize as a driver of recurring revenue.

Forrester Research (2026): Enterprises that deploy AI-driven business transformation in their supply chain operations report a median 18% reduction in inventory carrying costs within the first fiscal year, with no increase in stockout rates.

Analysis and Alternate Viewpoints

1. The Five-Component Business Case Architecture

After advising over 120 senior leadership teams at enterprises including Walmart, Procter & Gamble, JPMorgan Chase, and Caterpillar, I have distilled the board-ready business case into five components. Each component must be quantified, sourced, and stress-tested against U.S. market realities.

Component One: Baseline Operational Cost Structure. Your board needs to see current-state costs in three dimensions: direct operating expense, indirect friction costs (expediting, rework, manual handoffs), and opportunity costs (lost revenue due to fulfillment delays or stockouts). A typical Fortune 500 manufacturer in the U.S. loses between 4% and 7% of gross revenue to operational friction—a figure that often exceeds $200 million annually.

Component Two: Technology Stack Rationalization. Before proposing new investment, you must demonstrate that you have eliminated redundancy. One CPG client of ours maintained 14 separate warehouse management systems across 23 U.S. distribution centers. After a structured rationalization—guided by our technology consulting practice—they consolidated to three platforms and freed $12 million in annual licensing and support costs.

Component Three: Cross-Functional Process Redesign. Technology without process change is a tax, not an investment. Your business case must include a timeline and budget for reengineering workflows across supply chain, finance, and customer service. The digital transformation consulting engagements that succeed allocate 30% to 40% of total project budget to process redesign and organizational change management.

Component Four: Fulfillment Cycle Time Reduction. For U.S.-based retailers and manufacturers, every 24-hour reduction in order-to-delivery cycle time correlates with a 3% to 5% increase in repeat purchase rate. Model this explicitly using your own customer data, benchmarked against sector averages from the U.S. Census Bureau’s Annual Retail Trade Survey.

Component Five: AI-Driven Business Transformation. The 2026 landscape demands that you specify which AI capabilities—predictive inventory optimization, dynamic routing, or automated quality assurance—will drive specific, measurable outcomes. Our AI consulting services practice has helped clients build models that predict fulfillment exceptions 48 hours in advance, enabling proactive intervention rather than reactive expediting.

2. The Contrarian View: Why Your Board Might Be Right to Hesitate

Let me steelman the board’s position. According to a 2026 study by the Korn Ferry Institute, 57% of U.S. corporate directors report that they have approved at least one digital transformation initiative in the past three years that failed to deliver the projected ROI. Their skepticism is earned. The three most common failure patterns are:

Overpromised speed of value. Vendors and internal champions routinely project positive cash flow within 12 months; the reality for complex operations transformations is 18 to 24 months before net benefits appear. Address this by presenting a three-year NPV model with a clear inflection point in month 20.

Underestimated organizational friction. The hidden costs of retraining, productivity dips during transition, and cultural resistance are almost always understated. A 2026 study by Boston Consulting Group found that U.S. enterprises allocate only 8% of digital transformation budgets to change management, when the effective minimum is 20%.

Misaligned incentive structures. If your supply chain team is still measured on unit cost rather than total landed cost, your new digital operations platform will be used as an expensive spreadsheet. Your business case must include a recommendation to revise KPIs and compensation models.

Address these objections head-on in your presentation. A board that sees you have anticipated their skepticism will trust your projections more.

3. The Metrics That Matter to Your CFO

Your CFO does not care about “digital maturity” or “cloud migration.” They care about free cash flow, return on invested capital (ROIC), and earnings before interest, taxes, depreciation, and amortization (EBITDA) impact. Every line item in your business case should map to one of these three metrics.

Consider the example of a U.S.-based industrial manufacturer with $4 billion in annual revenue. By investing $28 million in a unified order-to-cash platform—supported by data science and analytics consulting—they reduced order-to-cash cycle time from 14 days to 6 days, freeing $160 million in working capital. That freed capital was reinvested into a new product line that added $90 million in annual revenue. The board approved the investment in a single meeting because the business case was expressed entirely in working capital and revenue growth terms.

Build your case using your own company’s financial statements. Use the U.S. Securities and Exchange Commission (SEC) EDGAR database to benchmark against peer companies. If your inventory turns are 4.2 and your closest competitor turns at 6.1, that gap represents a quantifiable opportunity.

4. The Strategic Sequencing Problem

One of the most common errors I observe in digital operations business cases is the assumption that all components should be implemented simultaneously. This is almost always wrong. The correct sequence, based on our work with over 80 enterprises through our corporate strategy consulting practice, is:

First: Technology stack rationalization and data normalization. Without clean data and a lean application portfolio, every subsequent investment is built on sand.

Second: Cross-functional process redesign for the highest-friction workflows—typically order management and fulfillment.

Third: AI-driven business transformation applied to the redesigned processes.

Fourth: Scaling to adjacent functions like procurement and customer service.

This sequencing reduces risk, generates early wins within 6 to 9 months, and builds organizational credibility for larger investments. A phased approach also allows your board to approve stage one with a relatively modest commitment—$3 million to $8 million—while seeing the full three-year roadmap.

5. The Role of External Validation and Market Intelligence

Your board will trust external benchmarks more than internal projections. Incorporate data from business research and market intelligence to show how your proposed investment aligns with industry best practices. For example, the 2026 Manufacturing Operations Benchmark Report from the National Association of Manufacturers shows that top-quartile performers in digital operations achieve 22% higher asset utilization and 18% lower warranty costs than median performers. If your company is in the third quartile, the gap represents a measurable addressable opportunity.

Similarly, for financial services firms, the Federal Reserve Bank of New York’s 2026 Operations and Technology Survey indicates that institutions investing in automated reconciliation and settlement processes reduce operational risk events by 34% and cut settlement cycle times by 41%. These are the kinds of externally validated statistics that turn a proposal into a mandate.

6. AI-Driven Business Transformation: The 2026 Imperative

In 2026, AI is no longer a differentiator—it is a table-stakes requirement for operational competitiveness. However, the board will reject any AI proposal that lacks specificity. Do not say “We will implement AI in our supply chain.” Instead, say: “We will deploy a transformer-based demand forecasting model that ingests 14 data streams—including point-of-sale, weather, and macroeconomic indicators—to reduce forecast error from 32% to 18% within 12 months, generating a $6.3 million reduction in expedited freight costs.”

Our AI consulting services practice has observed that the most successful business cases for AI-driven operations include three elements: a clear problem definition (not a solution looking for a problem), a measurable success metric, and a fallback plan if the model underperforms. Boards appreciate intellectual honesty about AI’s limitations.

7. The Human Capital Dimension

Your business case must address who will run the new digital operations. The U.S. Bureau of Labor Statistics (2026) projects a 12% shortage of qualified data engineers and operations analysts through 2028. Your board will want to know: Can we hire the talent? Can we retain them? Or should we partner with a firm like Guldstreet Consulting to provide interim leadership and capability building?

Include a talent acquisition and retention plan with specific salary benchmarks from the 2026 Robert Half Technology Salary Guide. For example, a senior supply chain data scientist in the Chicago metro area commands a base salary of $165,000 to $195,000. Budget accordingly. If your proposal omits this, your board will assume you have not thought it through.

8. The Governance and Accountability Framework

Finally, your business case must specify how the investment will be governed. The Project Management Institute (PMI) 2026 Pulse of the Profession Report indicates that U.S. projects with a dedicated executive sponsor and a cross-functional steering committee are 2.3 times more likely to meet original goals. Propose a governance structure that includes:

A senior executive sponsor (COO or CFO-level) with budget authority.

A monthly steering committee with representatives from operations, IT, finance, and the business unit.

A quarterly board-level update with a standardized dashboard showing actuals versus plan for cost, schedule, and benefit realization.

This level of rigor signals to the board that you are managing the investment as a fiduciary, not as a science project.

Projections and Recommendations

Forward-Looking Projections (2026–2029)

By 2028: U.S. enterprises that have not completed a technology stack rationalization will face a 15% to 20% cost disadvantage in fulfillment operations compared to peers who have, according to projections from Gartner’s 2026 Supply Chain Technology Roadmap.

By 2029: AI-driven demand forecasting will become a regulatory expectation for publicly traded U.S. retailers under proposed SEC disclosure rules related to supply chain resilience. Early adopters will have a 24- to 36-month compliance advantage.

By 2027: The cost of delaying digital operations investment will exceed the cost of investing, as labor shortages in logistics and manufacturing drive up the premium for manual operations. The U.S. Bureau of Labor Statistics projects a 9% increase in warehouse labor costs through 2028.

Five Immediate Actionable Recommendations

Audit your current-state operational costs within 30 days. Use your ERP system to extract the true cost of manual exceptions, expedited shipping, and rework. Benchmark against your industry using Dun & Bradstreet’s 2026 Operations Benchmarking Database.

Build a three-year NPV model with a clear inflection point. Use a 12% weighted average cost of capital (WACC) for U.S.-based enterprises, and stress-test the model at 8% and 16% WACC. Present all three scenarios to your board.

Propose a phased investment with a pilot in one high-friction process. For a retailer, start with ecommerce fulfillment. For a manufacturer, start with order management. Prove value before scaling.

Engage external validation early. Commission a digital transformation consulting assessment from a firm with verifiable U.S. enterprise experience. The cost of $50,000 to $150,000 is trivial compared to the cost of a failed $20 million implementation.

Prepare a one-page executive summary that contains only three numbers: current operational cost as a percentage of revenue, projected cost after transformation, and the net present value of the investment over five years. If you cannot reduce your case to three numbers, your board will not approve it.

Conclusion

The gap between digital ambition and operational reality is not a technology problem—it is a business case problem. Your board is not opposed to digital operations investment; they are opposed to risk without rigor, promises without proof, and technology without transformation. By building a business case that quantifies baseline costs, sequences investments strategically, addresses organizational friction, and ties every dollar to a measurable business growth outcome, you transform from a supplicant requesting budget to a partner presenting a fiduciary opportunity.

The U.S. market in 2026 rewards operational precision. Companies that can fulfill faster, adapt to demand shifts in real time, and eliminate waste through AI-driven processes will widen the gap against competitors who remain stuck in pilot purgatory. The question is not whether your board will approve a well-constructed business case—it is whether you will build one.

If your team needs support constructing a board-ready business case—including technology stack rationalization, cross-functional process redesign, and AI-driven transformation—Guldstreet Consulting’s digital transformation consulting practice has helped over 80 U.S. enterprises achieve measurable business growth. Schedule a confidential briefing with our senior advisors to discuss your specific operational challenges.

References

McKinsey & Company. Digital Operations and Shareholder Returns: The 2026 Global Study. 2026.

Gartner. Enterprise Digital Initiative Success Rates: The 2026 Benchmark Report. 2026.

Deloitte. Technology Stack Rationalization: Total Cost of Ownership Impact Analysis. 2026.

U.S. Bureau of Labor Statistics. Manufacturing and Logistics: Fulfillment Metrics and Customer Retention. 2026.

Forrester Research. The Economic Impact of AI in Supply Chain Operations. 2026.

Korn Ferry Institute. Board-Level Digital Transformation Oversight: A 2026 Survey of U.S. Corporate Directors. 2026.

Boston Consulting Group. Change Management Budget Allocation in Digital Transformations. 2026.

National Association of Manufacturers. 2026 Manufacturing Operations Benchmark Report. 2026.

Federal Reserve Bank of New York. Operations and Technology Survey: 2026 Results. 2026.

Project Management Institute. Pulse of the Profession 2026: The Governance Advantage. 2026.

Robert Half. 2026 Technology Salary Guide. 2026.

U.S. Securities and Exchange Commission. EDGAR Database: Peer Company Financial Benchmarking. 2026.

Dun & Bradstreet. 2026 Operations Benchmarking Database. 2026.

Gartner. Supply Chain Technology Roadmap 2026. 2026.

Guldstreet Consulting — New York, NY.

Guldstreet Consulting New York, NY guldstreet.com

The transition from retrospective audits to proactive governance is now defined by the adoption of the compliance monitoring platform. As digital ecosystems grow in complexity, organizations can no longer rely on periodic manual checks to ensure regulatory adherence. Modern platforms integrate AI compliance monitoring to analyze vast data streams in real time, transforming oversight into a continuous operational safeguard. By evaluating activity patterns across applications and databases, these systems identify irregularities the moment they emerge, drastically reducing the window between risk detection and remediation.

The technical core of these platforms relies heavily on anomaly detection. Rather than searching for known violations through static rules, machine learning algorithms establish baselines of "normal" behavior. This allows the system to flag subtle deviations that might signal emerging threats or undocumented policy gaps. Such predictive intelligence is essential for maintaining institutional integrity in high-velocity environments where thousands of transactions occur every second.

Furthermore, the shift toward real-time risk monitoring provides stakeholders with immediate visibility into the health of their digital operations. This immediacy is particularly critical for fraud detection, where suspicious activities often appear legitimate in isolation but reveal coordinated schemes when correlated across multiple systems. By analyzing transaction timing, user access, and workflow progression simultaneously, the platform serves as a proactive defense against financial and reputational damage.

Implementing these systems effectively requires integrating data across all operational layers and establishing clear response protocols. When monitoring is woven into the fabric of the enterprise, it does more than satisfy regulators; it drives operational efficiency by reducing the cost of manual oversight and uncovering process bottlenecks. Ultimately, a sophisticated monitoring framework ensures that as an organization scales its automated workflows, it remains resilient, transparent, and fully aligned with global governance standards.

In a world driven by data, the ability to capture accurate information quickly and seamlessly has become a competitive advantage. Automatic Identification and Data Capture (AIDC) technologies—such as barcodes, RFID, biometrics, smart cards, and voice recognition—are reshaping how organizations collect and manage data across industries. From retail checkouts and hospital patient tracking to warehouse automation and airport security, AIDC is deeply embedded in modern operations. As businesses accelerate digital transformation, the demand for faster, error-free, and real-time data capture is pushing AIDC from a support function to a strategic priority.

At its core, the AIDC market revolves around improving efficiency, accuracy, and visibility. Traditional manual data entry is not only time-consuming but also prone to errors that can disrupt supply chains and customer experiences. AIDC eliminates these gaps by enabling automated data collection and system integration. Today, companies are no longer asking whether to adopt AIDC, but how quickly they can scale it. The technology’s role in enabling traceability, authentication, and real-time monitoring makes it vital in sectors where precision matters most, including healthcare, logistics, manufacturing, and retail.

Several growth factors are accelerating market expansion. The rapid rise of e-commerce has created a need for robust inventory tracking and last-mile visibility. Warehouses and fulfillment centers increasingly rely on barcode scanning and RFID systems to manage high order volumes. Secondly, the push toward Industry 4.0 and smart factories is driving adoption of machine-readable identification and sensor-based tracking. Thirdly, labor shortages in many economies are encouraging automation, where AIDC plays a foundational role. Additionally, stricter regulations in pharmaceuticals and food safety are compelling companies to implement reliable traceability systems.

Current trends and innovations are making AIDC smarter and more connected. Integration with IoT platforms allows real-time asset tracking and predictive insights. Cloud-based AIDC solutions enable centralized data management across multiple locations. Mobile computers and wearable scanners are improving worker productivity on the warehouse floor. Biometric authentication is also gaining traction for secure access control in corporate and government environments. Recent industry developments show growing collaboration between hardware manufacturers and software providers to deliver end-to-end visibility solutions rather than standalone tools.

Despite strong momentum, the market faces challenges. High initial investment costs can be a barrier for small and medium enterprises. Data privacy concerns, particularly around biometric systems, require careful compliance with regulations. System integration complexities may also arise when connecting legacy infrastructure with modern AIDC platforms. However, falling hardware costs and subscription-based software models are gradually lowering entry barriers.

Looking ahead, opportunities remain substantial. The expansion of smart cities, digital healthcare, and omnichannel retail will further strengthen demand for reliable identification and tracking technologies. Businesses that invest in AIDC gain more than operational efficiency—they gain actionable intelligence. Real-time data enables faster decisions, better customer service, and improved risk management. As analytics and AI increasingly pair with captured data, the value of AIDC multiplies.

Sanjay Kumar Mohindroo Sanjay Kumar Mohindroo. skm.stayingalive.in Hyper-automation is not a tech upgrade—it’s a leadership challenge. Discover why bold IT leaders are driving the shift. Hyper-automation is no longer just a buzzword. It’s the lifeline for large enterprises that want to survive the next ten years. With rising operational costs, inconsistent manual processes, and growing…