Data-driven supply-and-demand planning helped Nissho break free from person-dependent processes while achieving both inventory reduction and stockout prevention.

Company Profile

• Industry: Trading company — automotive parts, electronic components, industrial materials
• Revenue: ¥50–100 billion
• Employees: 1,000–5,000

We spoke with four leaders at Nissho Corporation about why they adopted the SaaS-based SCM system PlanNEL, what they set out to achieve, and how their operations have changed since: Keisuke Hizawa, Director and Head of the Management Infrastructure Division; Emiko Uchida, Executive Officer and General Manager of the Business Administration Department; Shinji Tsujita, Deputy General Manager of the Logistics Planning Department within the Business Administration Department; and Akira Tanaka of the same Logistics Planning Department.

Could you start by telling us about your business?

Nissho was founded in 1958 as the sales arm of Nitto Denko Corporation. Today we are a specialized trading company handling industrial tapes and films, electronic materials, automotive components, and industrial materials.

Guided by our corporate message, “Contributing to our customers’ value creation through new ideas,” we serve customers across a wide range of industries — with the automotive sector at the core. Beyond simply selling products, we help optimize the entire supply chain, including procurement, logistics, and inventory management.

In recent years especially, companies are increasingly judged on how well they respond to globalization and sudden swings in demand. Reliable product supply and optimized inventory have become priorities for us as well, and we are focused on achieving both at a high level.

How are your departments organized to deliver SCM?

First, our sales division captures customer demand and passes that information to the operations teams at each site, which handle ordering and supply-demand coordination. From there, the information is shared through PlanNEL with the Logistics Planning Department inside operations, which handles inventory management, logistics strategy, and the design of processes and rules.

We do not have a dedicated department that owns SCM end to end. That is precisely why our goal is to build a structure in which every department draws on the same shared data in PlanNEL and can each make the best possible decisions.

What challenges were you facing before adopting PlanNEL?

Before PlanNEL, each person managed information in their own Excel files or relied on our in-house automated ordering system, so operations depended heavily on individual experience and know-how — everything became person-dependent. Because we relied on personal spreadsheets, data analysis took an enormous amount of effort, and balancing inventory reduction with stockout prevention was extremely difficult.

Specifically, when sales passed along customer demand and operations teams at each site were asked to hold stock, the basis for those requests came down to the salesperson’s intuition and experience — it did not exist as objective data. And on the receiving side, each person in operations responded using their own Excel file and their own methods. No one could see what anyone else was doing, data was not shared, and it was impossible to cover for one another.

We did have operating manuals, but a lot still came down to verbal handovers on the job. The result was a set of recurring problems: the rationale behind inventory settings was opaque, and the ability to respond to demand swings rested on specific individuals. Once the number of parts reached the tens of thousands, manual handling had clearly hit its limit. We needed to systematize the work to fundamentally reduce the operational burden.

How did you first learn about PlanNEL, and why did you choose it?

We first came across PlanNEL in an article in the logistics trade publication LOGI-BIZ.

At the time we were evaluating SCM systems with the goals of eliminating person-dependency and balancing inventory reduction with stockout prevention, and we compared about three products.

The other SCM systems we looked at stopped at managing inbound and outbound movement for a single site or warehouse. PlanNEL, by contrast, could optimize the entire supply chain — including the lateral connections that span multiple sites and customers — and its underlying philosophy felt like a natural fit for how we operate.

On features, too, PlanNEL manages everything from demand forecasting to demand planning, inventory planning, and replenishment planning in one place. It also brought in capabilities and ways of thinking our existing systems lacked — AI-based demand forecasting, statistical safety-stock calculation, ABC-XYZ analysis, dashboard visualization, and automatic calculation of order quantities and delivery dates. It covered everything we needed to take inventory management to a more advanced level.

As the trial progressed, we were able to thoroughly validate both the fit with our operations and the results. We also experienced the flexibility that only a SaaS solution can offer — ZIONEX quickly developed and rolled out the features we requested — along with accurate, responsive support from the ZIONEX team. All of this weighed heavily in our decision to adopt PlanNEL.

What changes and results have you seen since adopting PlanNEL?

It has been about a year since we adopted PlanNEL, and the biggest outcome is that we are shifting inventory management from “intuition and experience” to “data and logic.”

Where each person used to manage inventory in their own Excel files or systems, PlanNEL let us standardize the work. As a result, the reasoning — “this figure moved this way, so we’re setting inventory at this level for this reason” — is now transparent to both staff and managers. With the data visualized, departments share a common understanding, and handing over or covering work has become far easier. Our operations teams hold a weekly meeting, and we run study sessions for other departments as well to drive adoption even further.

We have also seen major time savings in day-to-day work. Building the PSI (Production, Sales, Inventory) management table, for instance, used to take about a week for the complex cases; now it is already complete the moment we open PlanNEL. On top of that, roughly 90% of the ordering we once did by hand has been replaced by automatic ordering through PlanNEL, which has significantly lightened the workload.

What would you like to do with PlanNEL going forward?

We want to make active use of PlanNEL for the plan-versus-actual inventory management and variance analysis that we simply never had the capacity for before. And as we use PlanNEL more, more and more data accumulates in the system — so we want to use that data to push demand-forecast accuracy even higher and further advance stockout prevention and inventory optimization.

We also want to integrate PlanNEL with our core business system to automate data ingestion, connecting it to even greater optimization across the entire supply chain.

Finally, do you have a message for readers of this case study?

Many companies that struggle with inventory management are wrestling with how to balance inventory reduction and stockout prevention.

We faced the same challenges, but we approached PlanNEL not as a mere system rollout but as an opportunity for business transformation.

What matters is not introducing the system itself, but using it to standardize operations and build a culture of data-driven decision-making. Within our company, we like to say: “It’s fine if you don’t master it perfectly — just don’t go back to the old way of doing things.”

PlanNEL is, we believe, a powerful system that supports that transformation from the ground up. We will keep improving and continue working to build an even stronger supply chain.

The post Elevating PlanNEL from a System Rollout into Company-Wide Business Transformation appeared first on Zionex Inc..

Industry: Outdoor Equipment & Apparel
Annual Revenue: ¥10–50 Billion
Employees: 500–1,000

We spoke with Mr. Takeshi Kawakami of the Sales Planning Department at Snow Peak about the reasons behind the adoption of the SaaS-based supply chain planning platform, the challenges the company faced before implementation, and the benefits realized afterward.

Could you tell us about Snow Peak’s business?

Snow Peak is an outdoor lifestyle company founded in 1958 in Sanjo City, Niigata Prefecture in Japan, a region well known for its manufacturing heritage.

Under our corporate message, “Bring the Outdoors into Everyday Life,” and our mission to “connect people with nature and with one another, restoring humanity through outdoor experiences,” we develop camping equipment and apparel while expanding globally into areas such as food and beverage, regional revitalization, and business solutions.

How is your SCM organization structured?

Our headquarters planning department develops company-wide policies based on inventory and sales data and coordinates allocation decisions across the organization.

Although each domestic and international location has its own personnel responsible for planning activities, headquarters takes the lead in making key decisions regarding procurement, inventory allocation, and supply planning.

What challenges were you facing before implementing PlanNEL?

Before adopting the supply chain platform, demand for camping products surged during the COVID-19 pandemic, creating a situation in which supply could not keep up with demand.

At that time, our highest priority was meeting customer demand. Rather than focusing on sophisticated planning processes, we concentrated on securing as much production capacity as possible throughout the supply chain.

As the business continued to grow, however, a fundamental question emerged:

“Is our current ordering process really sufficient for the future?”

This discussion eventually led to the establishment of our Sales Planning Department.

Previously, orders were often placed whenever production capacity became available, without a structured process for evaluating whether those orders were truly aligned with future demand. We needed a framework that would enable more informed and objective decision-making.

Initially, we managed a basic PSI (Production, Sales, and Inventory) planning process using Excel. However, managing global operations with a small team created a tremendous workload.

Excel also made version management difficult. Since master data could not be managed effectively across planning cycles, separate files had to be created each month. As a result, comparing plan versions, tracking changes, and performing continuous analysis became extremely challenging.

After discussions with external SCM consultants, we concluded that implementing a dedicated supply and demand planning system was the best solution.

How did you learn about PlanNEL, and why did you choose it?

Our evaluation process began after consulting with Professor Yoshinobu Ueno of Kanazawa Institute of Technology Graduate School.

Naturally, we evaluated several alternative solutions. However, when balancing functionality against cost, PlanNEL was the only solution that met our requirements.

To be honest, the decision came down to two options:

“Implement PlanNEL, or continue operating as we were.”

Because our product portfolio and planning requirements are relatively straightforward, we did not require extensive customization. We determined that PlanNEL’s standard SaaS functionality was more than sufficient for our needs.

Initially, our primary objective was to improve forecasting accuracy through AI-driven demand forecasting.

However, through discussions with ZIONEX, we learned that PlanNEL could provide an integrated solution covering:

• AI Demand Forecasting
• Sales Planning
• Replenishment Planning

all within a single platform.

This was extremely attractive to us.

Using separate systems would have required significant effort to transfer and synchronize data. PlanNEL eliminates that complexity by providing a unified platform for the entire planning process.

Previously, planning relied primarily on forecasts generated by local teams and Excel-based analysis. With PlanNEL, we can now compare and evaluate both human forecasts and AI-generated forecasts side by side.

In addition to improving forecast accuracy, this enables us to provide objective, data-driven explanations whenever stakeholders ask:

“Why are these the numbers?”

That capability has been especially valuable.

What benefits have you experienced since implementing PlanNEL?

We have seen two major benefits.

1. A New Approach to Inventory Management

Initially, our focus was on preventing stockouts.

As our operations matured, however, the focus shifted toward maintaining inventory at the optimal level.

Previously, we applied the same safety stock policy across all products.

After implementing PlanNEL, we adopted ABC-XYZ Analysis, classifying products according to their sales contribution and demand variability within a nine-cell matrix. This allowed us to establish inventory policies tailored to each category.

Although multiple improvement initiatives contributed to these results, inventory levels have steadily declined.

At the same time, stockout rates have also decreased, demonstrating significant improvements in inventory planning accuracy and effectiveness.

2. Significant Reduction in Planning Workload

For products with stable demand patterns, we rely largely on PlanNEL’s forecast recommendations.

For products with greater demand variability, such as seasonal items, planners apply their expertise and judgment to refine the forecasts.

This hybrid approach has dramatically improved planning efficiency.

As the Sales Planning Department has matured, the reduction in operational workload compared with our previous Excel-based process has been substantial.

Another feature we highly value is the ability to document planning assumptions and decisions directly within the system.

Because these notes are retained across planning versions, we can easily review historical plans and understand:

• What events occurred
• Why specific planning decisions were made
• What assumptions supported those decisions

As our team grows, preserving and sharing this knowledge has become increasingly important.

How do you plan to use PlanNEL going forward?

Currently, we generate demand forecasts centrally across all warehouses and distribute the resulting figures to each location.

Going forward, we would like to move toward a collaborative planning model in which local sites contribute their own forecasts and planning inputs.

Our vision is to assign qualified demand and supply planners at each location. These planners will combine PlanNEL forecasts with local market intelligence to create plans that are then consolidated into a company-wide plan.

We have already improved inventory management across Snow Peak as a whole, but detailed inventory optimization between individual locations remains an area for improvement.

In the future, we plan to leverage PlanNEL to support more efficient inventory transfers and balancing activities between locations.

Any final message for companies considering PlanNEL?

PlanNEL is particularly well suited for organizations that want to establish a single set of numbers across the enterprise and use those numbers as the foundation for decision-making and communication.

Every company faces situations where forecast-based demand projections differ from budget targets.

When this happens, organizations often face a difficult choice:

Should we order based on the budget, or based on actual demand?

Many companies have experienced the consequences of ordering according to budget targets and ending up with excess inventory.

In these situations, PlanNEL provides a powerful foundation for objective decision-making.

Because discussions can begin from a common understanding of:

• The planning logic
• The forecasting algorithms
• The current optimal recommendation

teams can focus on determining the actions needed to close gaps between budget and forecast.

For example, discussions can shift toward questions such as:

• How should merchandising be adjusted?
• What promotional activities should be implemented?
• What actions will help achieve business objectives?

PlanNEL provides strong support for these strategic decisions.

For companies managing large SKU portfolios in particular, the efficiency gains can be substantial. If your organization faces similar challenges, PlanNEL is well worth exploring.

The post Breaking Free from Excel-Based Planning appeared first on Zionex Inc..

Accordingly, the audit report will also be posted on our website, so please refer to it.
You can download the audit report file by clicking the link below in this article.

1. Zionex Co., Ltd. 2025 Audit Report
2. Zionex Co., Ltd. 2025 Consolidated Audit Report

Thank you.

Zionex Management Support Team

The post Disclosure of the 27th (2025) Audit Report appeared first on Zionex Inc..

1. Type and number of shares to be sold : 6,000 common shares of Zionex Co., Ltd.
2. Stock Acquirer : Intervalue No. 6 Patent Technology Commercialization Investment Association
3. Purpose of financing : Acquisition and post-closing operation related to AI companies for the introduction of new technologies
   Purpose of raising funds
4. Face value per share : 5,000 won
5. Sale price per share : 100,000 won
6. Total sale amount : 600,000,000 won (600 million won)
7. Payment date of sale amount: April 21, 2026
8. Financial institution and place to be paid: Shinhan Bank Sangam-dong Financial Center
9. Counterparty to the transfer : In accordance with Article 335-3 of the Commercial Code, all of the above sold shares
   Intervalue No. 6 Patent Technology Commercialization Investment Association to acquire
   
   

March 27, 2026

CEO Ryu Dong-sik (Employee Strategy)

Zionex Co., Ltd. 9th Floor, R Tower, 396 World Cup Buk-ro, Mapo-gu, Seoul (Sangam-dong, Nuri Dream Square)

The post Announcement of sale of treasury shares (allocation to a third party) appeared first on Zionex Inc..

On August 20, 2025, Zionex was invited to participate in the AI Café Tainan session, organized by the Institute for Information Industry (III) and the Artificial Intelligence Innovation Application Promotion Association (AIF). As a speaker and industry representative, we shared insights on the applications of AI in manufacturing and brand operations.

The topic of the presentation was “Breaking the Five Major Myths of AI in Enterprise Applications.” Through real-world case studies and interactive discussions, we guided attendees in overcoming common misconceptions and gaining a renewed understanding of the true value of AI in sales forecasting and operational improvement.

Five Major Myths and Case Studies Sharing

Myth 1: Is AI / ML Really Necessary?

This question doesn’t really have a single “standard” answer. Traditional statistical models are indeed useful — they rely on fixed formulas and trend extrapolations, which can provide good results under stable conditions. But the strength of machine learning models lies in their ability to continuously learn from data and dynamically adjust, especially when demand is complex and influenced by multiple factors.

A real-world example:
We worked with a globally renowned food company (its main products are tofu and related food items). Their demand patterns were highly complex — not only affected by seasonality and promotions, but also by health and dietary trends as well as channel strategies. In the past, relying only on historical data and simple statistical methods often led to overstocking or stockouts.

After introducing an AI-based forecasting model, the system was able to incorporate both internal sales records and external market factors, while selecting different models for different product lines. The results were significant: forecast accuracy improved, production plans became more closely aligned with actual demand, and inventory pressure was greatly reduced.

So, going back to the question: “If we only have historical data, do we still need machine learning?”

The answer is: it depends on the complexity of demand.

If the market is relatively stable with little variation, traditional methods are sufficient. But if demand fluctuates greatly and is influenced by many factors, that’s where AI / ML can truly demonstrate its value.

Myth 2: If AI Isn’t Accurate Enough, Is It Not Worth Using?

Let’s start with a sharp question:

“If AI’s accuracy is only 85% or 90%, and it can’t reach 95% or even 98%, does that mean it’s not worth using?”

This concern is actually quite common among enterprises.
But the truth is — no model can ever be 100% accurate, because demand itself is inherently uncertain.

The value of AI does not lie in delivering a perfect answer, but in providing early, directional signals.

For example:
If AI can improve forecast accuracy by just 10%, for a company managing thousands of SKUs across multiple channels, that difference could translate into tens of millions in business value.

That 10% improvement brings more than just a number — it enables:

• More precise inventory allocation
• Fewer stockouts and less waste
• More stable production planning

Myth 3: Can a Single Model Forecast All Products?

At the event, many attendees also asked: “Can we just use one model to forecast all of our products?”
This is a common expectation among enterprises, but in practice, it’s very difficult to achieve.

The reason is simple: different products have very different demand patterns.
Some products have high and stable sales, some fall into the low-frequency long-tail category, while others fluctuate wildly. If you force a single model to handle all products, the outcome is usually that some products forecast well, but others are completely off the mark.

Our approach is to first help clients classify their products.
For example, through ABC-XYZ analysis, we group products based on sales value, volatility, and data completeness:

• Some products are suitable for machine learning models.
• Some can be handled well enough with statistical methods.
• Others require customized forecasting strategies.

Next, we design a multi-model strategy, such as:

• Prophet: good for seasonal and elastic demand.
• Croston: effective for intermittent demand.
• XGBoost: well-suited for highly volatile, high-dimensional data.

The truly effective method is not “one model rules them all,” but dynamically selecting the best combination to match different product characteristics.

In addition, we emphasize hierarchical forecasting. This ensures that:

• Headquarters can view aggregate numbers,
• Marketing can focus on brands,
• Supply chain teams can look at SKUs,

all starting from the same forecasting logic.

This design guarantees that forecasts across levels do not contradict each other, and the final results can actually be collaboratively used, executed, and trusted in production and scheduling.

Myth 4: Once AI Software Is Implemented, Will Forecasts Run Automatically?

Many clients, when first introduced to the system, often ask: “Once the AI system goes live, does it run completely on its own without human intervention?”

Here’s how we usually respond, supported by actual practices:

• Step 1: The ML model generates an initial forecast (Baseline Forecast).
• Step 2: Different departments collaboratively adjust the forecast to ensure it aligns with real business situations.
• Step 3: We continuously monitor the gap between forecasts and actual outcomes, identify discrepancies, and refine the model through a PDCA cycle (Plan–Do–Check–Act).

AI is not a plug-and-play magic box. It creates value, but only when embedded into a company’s daily processes. Through ongoing collaboration and optimization, forecasts become increasingly accurate and practical, effectively supporting production, scheduling, and decision-making.

In short, AI is not a “set-it-and-forget-it” system — it is an intelligent tool that requires continuous engagement and adjustment in order to become a reliable foundation for business operations.

Myth 5: After Implementing AI Forecasting, Should We Only Focus on Accuracy?

Accuracy is certainly important — but the true value lies in improving resource allocation and operational outcomes.

Take a high-tech electronics company as an example:
Their product portfolio was very broad, ranging from high-frequency standard items to highly customized, long lead-time products.

In the past, they applied a single approach to all products, which often led to either material shortages or excessive inventory.

Zionex helped them by implementing product segmentation and differentiated forecasting strategies:

• Stable products: Used baseline forecasts combined with inventory stocking.
• Volatile products: Applied demand planning with rolling adjustment mechanisms.
• Long-tail or customized products: Relied entirely on orders, enabling rapid response through a make-to-order (MTO) strategy.

Results achieved:

• On-time delivery rate improved to 97%
• Unsellable inventory reduced to 3%
• Inventory turnover days improved by 45%
• Delivery lead time shortened by 65%

This proves that implementing AI forecasting isn’t just about chasing accuracy. The key is combining it with product characteristics and operational strategies so that AI can truly transform into tangible business value.

If you’d like to learn more, please fill out your contact information, and our team will reach out to you!

The post 【Event Highlights】 Zionex Invited to Speak at AI Café — Breaking the Five Major Myths of AI, from Sales Forecasting to Operational Improvement appeared first on Zionex Inc..

Zionex provides the Dynamic Task Manager (DTM) as an add-on solution for the Aras Innovator PLM (Product Lifecycle Management) platform. As a partner of Aras Corporation, Zionex participated in the ACE2025 event held from March 31 to April 3, 2025, with a 4-person team including Executive Officer and DTM Business Manager, Mr. Ito at Zionex Japan.

The event took place at the Hilton Boston Park Plaza, under the theme “Connected Intelligence.”
This report shares Mr. Ito’s impressions and findings from the event.

Objectives of Zionex’s Participation in ACE2025:

1. To understand the future direction and initiatives of Aras Corporation.
2. To exchange insights with Japanese customers and partners overseas.
3. To technically validate the compatibility of DTM with Aras Innovator SaaS as an ISV Partner.
4. To explore business opportunities in the US and European markets.

Key Highlights:

Aras introduced the concept of “Aras InnovatorEdge”, aiming to provide APIs that allow external integration and extend the capabilities of its SaaS components, including the Product Data Platform, Application Library, and Low-Code Development suite.

The conventional method of customizing by modifying code trees and referencing physical files is being replaced by API-based data access. Zionex intends to continue monitoring the evolving specifications of Aras InnovatorEdge.

CEO and CTO Sessions:

In his keynote, Aras CEO Roque Martin emphasized the 25th anniversary of the Aras Community, highlighting the values of innovation, community, and connection. He reflected on the challenges of the Y2K era, the origin of the company’s name by founder Peter, and the technological evolution that parallels Aras’s own journey over the past 25 years.

CTO Rob McAveney, in his “What if” session, reviewed Aras’s technological development. Mr. Ito found the session nostalgic, noting how the rapid rise of AI within just 25 years underscores the accelerated pace of technological change.

Customer & Partner Engagement:

Zionex had the opportunity to meet both new and familiar Japanese customers and partners, engaging in valuable discussions and exchanging ideas. The feedback received will be reflected in future product improvements.

Technical Collaboration with Aras:

To ensure compatibility with Aras Innovator SaaS, DTM must support .NET 8 and run in Linux containers. Zionex had paused development for about a year due to various constraints, but used ACE2025 as an opportunity to resume technical discussions with Aras engineers.

Once the DTM application is ready, it will go through the CI/CD pipeline, undergo UAT and staging validation, and be prepared for deployment to the production environment. Zionex aims to make DTM available to users as soon as possible.

Zionex extends special thanks to John Sperling, Aihoa Borowicz, Benjamin Chaillon, Grant Killian, and the team at Aras Japan for their coordination and support.

Additional Activities:

• Zionex participated in the Aras DevOps training sessions, gaining a solid understanding of the development processes required for SaaS compatibility.
• During the “Aras in the Round” session on April 2, project management functionality emerged as a key discussion topic, which was of strong interest to Zionex.
• In Japan, Zionex is currently conducting a joint promotion campaign with Aras under the theme “Build with Aras.” Zionex was eager to gauge awareness of the company and the DTM product.
• During the reception, executives including Peter, Roque, Rob, and Leon shared positive recognition, stating, “We know Zionex and DTM!”—a response that further motivated Zionex to introduce DTM more actively and continue evolving its offerings through ongoing dialogue and feedback.

Final Thoughts:

Mr. Ito noted that the area within a 40-minute walk from the Hilton Hotel offered a peaceful and scenic atmosphere. He enjoyed invigorating morning jogs, watching lively dogs in the parks, and dining at excellent restaurants—allowing him to fully appreciate the calm charm of Boston. (MIT campus with the “Dome” is visible across the Charles River as shown in this photo.)

The post ACE2025@Boston Participation Report appeared first on Zionex Inc..

ISO 27001 is an international standard jointly established by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). It assesses a company’s ability to systematically protect and manage information assets. ISO 27017 provides security controls and implementation guidelines for cloud service providers, ensuring a safer cloud-based environment for both providers and users.

With these certifications, Zionex has demonstrated that its information security framework meets international standards. Notably, the cloud security of its SaaS-based SCM solution, PlanNEL, has been officially validated. This milestone strengthens Zionex’s global competitiveness.

PlanNEL is a SaaS solution that supports the entire SCM process, including demand planning, inventory planning, replenishment planning, and supply planning. Developed with AI/ML algorithms and statistical methodologies, it allows businesses to select and integrate the necessary modules based on their unique requirements. This flexibility enables quick deployment and easy expansion, helping companies establish a cost-effective supply chain management system.

By optimizing inventory, PlanNEL helps businesses reduce unnecessary costs and make data-driven decisions more quickly, enhancing operational agility. This allows companies to minimize repetitive tasks and focus on their core operations.

Zionex CEO Dongsik Yoo stated, “Achieving these certifications is a significant milestone, proving that Zionex meets the highest security standards across all environments, including cloud services. Moving forward, we will continue to prioritize the security of our customers’ valuable information assets and build long-term trust.”

The post Zionex Achieves ISO Certifications for Information Security appeared first on Zionex Inc..

– Ah Rae –

1. Date and time: Thursday, March 27, 2025 at 9:30 a.m.
2. Venue: Our conference room (9th floor, R Tower, 396 World Cup Buk-ro, Mapo-gu, Seoul (Sangam-dong, Nuri Dream Square))
3. Purpose of the meeting
   A) Reports: Sales reports, reports on appointment of outside directors
   B) Agenda item
   () Proposal No. 1: Approval of Financial Statements for the 26th Term (2024.01.01 ~ 2024.12.31)
   () Proposal No. 2: Appointment of Outside Directors
   () Proposal No. 3: Disposal of retained earnings (cash dividends)
   () Proposal No. 4: Partial Amendments and Additions to the Articles of Incorporation
   () Proposal No. 5: Establishment of Regulations on Prohibition of Retirement of Executives
4. Management Reference
   In accordance with the provisions of Article 542-4, Paragraph 3 of the Commercial Act, management reference information is provided at the head office, so please refer to it.
5. What to prepare when attending the general meeting of shareholders
   A) Direct Event: ID Card
   B) Proxy event: Power of attorney (personal information of shareholders and representatives, seal stamp), ID card of the representative
6. Other
   Souvenirs of the general meeting of shareholders are not given to reduce company expenses.

March 10, 2025
Zionex Corporation
CEO Ryu Dong-sik (Employee Strategy)

Appendix – Amendments and Additions to the Articles of Incorporation (Describing only each clause of the Articles of Incorporation)

Article 5 Total number of shares to be issued by the company, Article 6 Amount of one share, Article 8 Types of shares, Article 9 Warrants
Article 10 Stock Purchase Option, Article 11 Date of Calculation of Dividends of New Shares, Article 12 Agent of Name
Article 13 Closure of the Register of Shareholders and Record Date, Article 14 Issuance of Convertible Bonds
Article 15 Issuance of warrants, Article 16 Convocation, Article 17 Notice of Convocation, Article 18 Chairman
Article 20 The Chairman’s Right to Maintain Order, etc., Article 21 Resolutions, Article 22 Voting Rights, etc., and Article 23 Non-Unified Exercise of Voting Rights
Article 24 Restriction of Voting Rights on Reciprocity, Article 25 Minutes of the General Meeting, Article 26 Number of Directors,
Article 27 Appointment of Directors, Article 28 Term of Directors, Article 29 Duties of Directors, Article 30 Duties of Directors
Article 31 Remuneration of Directors, Article 32 Severance Pay, Article 33 Composition and Convocation of the Board of Directors
Article 35 Minutes of the Board of Directors, Article 36 Appointment of the CEO, Article 37 Duties of the CEO, Article 38 Number of Auditors
Article 39 Appointment of Auditors, Article 40 Term and By-election of Auditors, Article 41 Duties of Auditors, etc.
Article 42 Audit Remuneration and Severance Pay, Article 43 Business Year, Article 44 Preparation of Financial Statements, etc.
Article 45 Disposal of Retained Earnings, Article 46 Profit Distribution, Article 47 Matters Other than those Stipulated

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Recap from NRF 2025: Retail’s Big Show

The NRF 2025: Retail’s Big Show took place from January 12-14, 2025, at the Jacob K. Javits Convention Center in New York City. This premier event attracted top industry leaders from across the retail sector, offering a platform for innovation, collaboration, and exploration of the latest trends shaping the future of commerce.

The event featured over 1,000 exhibitors and more than 100 sessions, providing attendees with opportunities to explore cutting-edge technologies, compare solutions, and build vital partnerships. Specialized pavilions like the NRF 2025 Innovators Showcase, Startup Hub, and Foodservice Innovation Zone offered immersive experiences into emerging technologies and innovative concepts transforming the retail landscape.

Keynote sessions included insights from prominent figures such as Tommy Hilfiger, who shared his experiences on brand evolution and storytelling, and Amazon Stores CEO, who discussed the potential of AI in spawning new retail formats. The event also highlighted the growing importance of AI in retail, with discussions on how companies like L’Oréal, Lowe’s, and Walmart are successfully integrating AI to enhance customer experiences and operational efficiency.

In addition to the sessions and exhibits, the Exhibitor Big Ideas sessions provided a platform for solution providers to demo their latest products and share insightful case studies, while the Foodservice Innovation Zone offered an interactive exploration of technologies transforming the customer foodservice experience.

Participating in NRF 2025 allowed us to engage with retailers, exchange ideas, and showcase how PlanNEL, our advanced supply chain planning solution, can transform supply chain management for e-commerce and retail businesses.

A Stunning Arrival in New York City

Arriving in New York for NRF 2025 was an experience in itself. Flying into Newark Airport, we were greeted with a breathtaking view of Manhattan’s iconic skyline as we made our way toward the Javits Center. The sight of towering skyscrapers across the Hudson River, including architectural marvels like the VIA 57 West pyramid-shaped building, set the stage for an exciting week ahead.

Engaging with Industry Leaders

Being part of NRF Big Show meant being surrounded by some of the biggest names in retail technology. We had the opportunity to connect with decision-makers from major brands, e-commerce companies, and logistics providers who are actively looking for scalable and intelligent supply chain solutions.

Highlights from the Event

1. The Grand Entrance – Energy and Innovation at Javits Center

The NRF Big Show kicked off with an electrifying atmosphere at the Javits Center, where thousands of attendees gathered to witness the latest innovations in retail technology. The expo hall was massive, with towering displays and interactive booths. The registration area was buzzing with energy as exhibitors and attendees checked in, preparing for three days of networking and learning.

2. Iconic Heinz Bottle at NRF

One of the fun and unexpected highlights at the show was the giant Heinz ketchup bottle display. This playful and eye-catching installation embodied the creative marketing approach that many brands brought to NRF this year.

3. NVIDIA – The Powerhouses of AI in Retail

At the heart of retail AI solutions, NVIDIA collaborated to showcase how AI is driving innovation in demand forecasting, fraud prevention, and personalized shopping experiences. These industry giants continue to shape the future of AI-powered retail automation.

4. AWS – Cloud-Powered Retail Transformation

AWS took center stage with its solutions for scalable retail infrastructure. They emphasized how businesses can leverage cloud-based analytics and machine learning to optimize customer journeys and improve supply chain efficiency.

Key Takeaways from NRF Big Show

1. Retailers Are Prioritizing AI and Automation
   • Many discussions revolved around how AI-powered solutions can enhance supply chain efficiency. Retailers are increasingly adopting predictive analytics and automation to optimize inventory levels and reduce operational costs.
2. Sustainability and Supply Chain Transparency Are Growing Concerns
   • Brands are focusing on sustainable logistics and ethical sourcing. Solutions like PlanNEL, which provide end-to-end visibility and optimize transportation routes, align well with these priorities.
3. Omnichannel Retail Demands More Agility
   • Retailers are struggling to balance demand across multiple channels. The ability to adapt to fluctuating demand in real-time is a must-have feature for modern supply chain platforms.

Challenges and Lessons Learned

Exhibiting at such a large-scale event also came with its own set of challenges. Standing out among hundreds of exhibitors required us to refine our messaging and ensure that our booth attracted the right audience. We learned the importance of concise storytelling, interactive demos, and having a strong follow-up strategy to convert leads into potential clients.

Additionally, logistics and setup were crucial elements. Having the right booth materials, promotional content, and demo equipment ready ahead of time made a significant difference in our ability to engage attendees effectively.

Exploring Times Square After the Show

After a long and productive day at the NRF Big Show, we ventured into Times Square, the heart of New York City’s dazzling nightlife. The bright lights, massive billboards, and the bustling energy of the area provided the perfect contrast to the structured environment of the exhibition hall.

Times Square’s Neon Glow

Stepping into Times Square, we were met with towering LED screens, flashing advertisements, and the unmistakable hum of the city that never sleeps. The vibrant red glow neon signs and the immersive digital ads reminded us of how retail and branding dominate even the streets of New York.

As we walked further, we encountered glowing digital displays stretching high above the streets. The sidewalks were filled with tourists, locals, and street performers, making the experience truly immersive.

Our final stop in Times Square was a spot where people gathered to take photos and enjoy the vibrant energy of the city. The mix of tourists, performers, and illuminated signs truly captured the essence of New York’s retail and entertainment power.

Looking Ahead

Our experience at NRF Big Show reinforced the growing demand for smarter, more efficient supply chain solutions. We left the event with valuable connections, insights, and a clearer understanding of market needs. As we move forward, we’re excited to continue refining PlanNEL and expanding our reach within the retail sector.

If you visited our booth or would like to learn more about how PlanNEL can transform your supply chain operations, feel free to reach out—we’d love to continue the conversation!

The post Showcasing PlanNEL at NRF Big Show ’25 appeared first on Zionex Inc..

We kicked off the new year with an amazing team gathering at Zionex, and the energy in the room was absolutely electric! Surrounded by this incredible group of colleagues, we celebrated our past achievements and set our sights on the exciting challenges and opportunities that lie ahead.

Here’s to pushing boundaries, embracing innovation, and achieving great milestones together in 2025. Let’s make this our best year yet!

#Zionex #TeamSpirit #NewYearKickoff #2025Goals #Innovation #CollaborationZionex 2025 Kickoff

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