In this blog post you can discover how Log-hub’s strategic collaboration with Huber+Suhner transforms supply chain management, overcoming challenges, enhancing end-to-end transparency, and delivering substantial business value through innovative data-driven solutions.

The initial contact between Huber+Suhner and Log-hub AG, marked by a ground-breaking network design study, quickly revealed the potential for a profound transformation through data. Huber+Suhner faced a series of complex challenges, ranging from unstructured data handling to shortcomings in standardized solutions. Addressing these challenges required not only technical expertise but also a deep understanding of the intricacies of supply chain management.

Log-hub AG responded by establishing an automated data infrastructure seamlessly integrated into Huber+Suhner’s ecosystem. Based on this infrastructure, additional key use cases in the field of supply chain management were rapidly and value-addingly implemented step by step. With each of these successfully implemented use cases, the data awareness increased and the interest increased up to the highest management levels. As data awareness grew and demand for data and dashboards heightened, the topic of “Report & Dashboard Standardization for globally distributed locations” became more central.

The focus was not only on standardization but also on establishing a new role concept. The project is now well advanced. With each iteration, internal knowledge expands, and new possibilities are discovered to generate value in close collaboration with the business.

The vision of Fabio Menegola, Head of Supply Chain Excellence at Huber+Suhner AG: “To establish a 360° Supply Chain Visibility Cockpit that is precisely tailored to the needs of Huber+Suhner and everyone at Huber+Suhner works with. This 360° Cockpit serves as a global foundation for daily supply chain monitoring and as a decision-making tool.”

Challenges

The challenges at the beginning were of organizational and evolutionary nature. Awareness of structured data handling was largely one-sided, and everyone in the business sought individual solutions for solving their individual problems independently. As a result, the added value of investing in data-related topics could only be communicated to a limited extent. Additionally, development times for data analyses were lengthy and often did not fit into the IT landscape. This led to discrepancies that needed to be overcome.

Not to be underestimated in new initiatives is the strong involvement of internal employees in existing daily business and its operational activities. The new developments had to be integrated at times with great pressure and close collaboration alongside operational activities, leading to occasionally intense and demanding periods.

Thanks to the gradual success, the value of simplifications, standardization, and new possibilities for innovations could simultaneously be demonstrated. This promoted employee motivation, increased trust, and had a positive impact on innovation capability.

With the initiation of the first use cases and a deeper experience with cloud technology many open questions could be easily addressed, and expertise could be built sustainably. The early implementation enabled to reduce fears of new technologies and processes quickly and enduringly. Simultaneously, it demonstrated the potential that such a solution could offer.

Solution – A future-proof data infrastructure

An automated data infrastructure comprised of individual components, harmonized to form an efficient and cost-effective ecosystem, consisting of Microsoft Azure, KNIME Analytics, and Microsoft Power BI. The simplicity and low-code approach enabled Huber+Suhner to process and visualize data quickly and efficiently.

Simultaneously, organizational changes have taken place, establishing a data organization that can sustainably position, coordinate, and drive forward the topics of data and analytics with many new innovations.

Business Value for Huber+Suhner:

• Increased End-to-End Transparency: Improved understanding of business processes, enhanced transparency throughout the entire supply chain, and the ability to quickly identify areas for improvement.
• Trust in Data: Consistent and reliable provision of data.
• Efficiency Gains: Faster, more efficient, and simpler data provisioning, leading to a quicker time-to-market.
• Reduction in Operational Effort: Automation and standardization result in reduced efforts and save costs at the same time.
• Employee Motivation: The introduction and involvement in new technologies significantly boost employee motivation.
• Higher Data Awareness: Within Huber+Suhner, the subject of data has been positively established, raising awareness and importance of data within the organization.

Value of Log-hub

Huber+Suhner highly values the collaboration with Log-hub on a partnership level.

Fabio Menegola says, “Log-hub provides both technical and domain expertise, allowing them to bridge both worlds. The rapid successes achieved in a short period and the high quality of work have enabled us to gain recognition up to the highest management levels relatively early on. Log-hub consultants are committed, communicative, flexible, and contribute their ideas. They deliver what they promise and often more. I look forward to further collaboration.”

Next Steps

The partnership is an ongoing process with the aim of continuously increasing data maturity, evolving the organization, and implementing new, exciting use cases with business value. This next phase of collaboration promises even more innovative solutions and perspectives, bringing Huber+Suhner one step closer to the vision of the 360° Supply Chain Cockpit every day.

Data is present in almost every discussion about innovation and digitalization. Nevertheless, a lot of our customers face uncertainty, insecurity or helplessness when discussing data.

They store a significant amount of data in their company, but they haven’t effectively coordinated or utilized it. As a result, they struggle to efficiently analyze the information content of the data and leverage the results to their advantage. Some of our customers explain this as a lack of time, complexity, insufficient resources, inadequate IT support, a lack of focus, etc.

Most of the time, a small group of stakeholders recognizes the value that proper data handling can bring, but mostly they often have higher priorities, political differences and other challenges that take precedence. Without compelling arguments, they frequently fail to secure support from top management. In such cases, the right ideas and a suitable presentation of a potential implementation become essential. The controversy lies in whether one should halt daily work to analyze and improve the situation or invest in parallel, leading to a high strain for a limited period. Convincing top management requires an investment in shaping the future incrementally.

This raises the question: How can you start the journey to get more value from data?

There are different approaches and ideas for commencing a data-focused journey. The best way to start is by enhancing awareness of data to achieve strategic commitment from top management and integrate it into the company’s strategy. When the data topic is firmly embedded in the strategy, everyone recognizes its importance, and resources are allocated. However, it’s crucial to note that this approach is not the standard one. To make data relevant, you must make it tangible for top management. They need to see its business value before focusing on data and incorporating it into their overall strategy. This is the point where we aim to help our potential customers.

Our goal is to address the question: How can we raise awareness of the data topic?

There are several ways to increase data awareness within your company:

• Speak with your top management and present, at a conceptual level, the importance of data and the potential for optimization or cost savings. You can support your arguments with research references or KPI’s from other markets.
• Prepare your own small use case. Make it clear to your top management how important it is to store data securely, transform it efficiently and visualize it in a meaningful way. This makes the matter more tangible for your top management and helps them better understand the idea and necessity.
• Compare your company’s data maturity level with that of your competitors. Most of the time, your top management is more willing to invest when they see competitors focusing on a specific topic, for instance data.
• Accompany top management to conferences, events and meetings centered around data. Over time, they will see the business value of data as they gain a deeper understanding of its structure and complexity behind.
• Build up partnerships and talk with partners and colleagues from different companies regarding their data maturity level and their ongoing data-related projects. Identify trustworthy collaborators in your field and establish positive relationships where top management actively participates.
• Collaborate with like-minded individuals within the company to form interdepartmental workgroups that can influence various stakeholders. You can align your ideas and actions to raise awareness. Be aware to marketize your achievements.
• Consider taking bold actions to attract attention, even if it involves causing a disruption because sometimes it is the only way. If you find yourself in a continuous downward spiral, and you always accept overtime, overworked employees and no outbreak of the uncertain situation, you need to take special circumstances into consideration and stage a special event, that requires a lot of courage, to break the cycle. Announce such situations several times in written to avoid surprises. 

Challenges during data awareness creation

In all the aforementioned strategies to raise awareness, the most important step is to do effective expectation management and show your stakeholders what you have accomplished so far, both qualitatively and quantitatively. Be transparent and truthful and avoid talking solely about positive things. The truth will eventually surface. Start with small and continuous steps rather than attempting a big change with high potential for failure. Stick to your initial goals during execution, do not overload but leave room for incorporating new requirements in future steps. There is always an opportunity to insert new requirements in upcoming steps. However, you should proceed with caution as there may be various challenges during the data awareness creation:

• Wrong Expectation management – The top management may hear a lot of stories from the big players, colleagues from other companies about how easy it is to work with data, leading to unrealistic expectations.
• Terminology misunderstandings – The understanding of different terms such as AI and Digital Twin may vary between top management and data analysts. You should establish a common language to ensure mutual understanding. The better the top management understands what you are doing the better they can represent your work.
• Overburdening steps – Avoid overloading your initial steps. Every day there are new features, technological opportunities and ideas. When you decide to take a step you are mostly already outdated which is ok and normal. Focus on defined objectives and accept that you can iterate and improve over time. Create something small instead of nothing.
• Less time – Time is mostly limited. Therefore, you need to be fully aware of it and try to coach people and scale your efforts within your environment.
• Focus on daily work – Prioritize new initiatives that can save time in the long run amidst the numerous daily tasks.
• Too Expensive – Before you grow, you need to invest. Focus on the most relevant aspects of data and your needs. Start based on your current and not on your future needs in 5 years.

Conclusion

The most controversial point to take into consideration is the expertise. Sometimes, internal employee’s expertise and opinions are not 100% valued by the top management. Strangely, top management may not see the expertise of an internal employee as credible as the input of an external consultant. External companies can help you position the data topic in a more sophisticated and accepted manner by considering internal expertise and opinions. Combining these elements can persuade top management effectively.

In the dynamic world of supply chain management, conventional forecasting methods can lead to stockouts and overstocks, leaving businesses and customers dissatisfied. Explore our groundbreaking approach that leverages Data Analytics and AI to revolutionize demand forecasting. Learn how to reduce stockouts and overstocks by 20% – 40% with a solution customized to your company.

Forecasting is the backbone of successful businesses, and its quality directly impacts inventory management and supply chain efficiency. The conventional approach of using standard forecasting models often falls short, as it fails to consider various critical factors that influence demand. At Log-hub AG, we believe that a personalized approach to forecasting, integrating advanced Data Analytics and AI solutions, can revolutionize the way businesses manage their supply chains. In this blog post, we explore the challenges faced by conventional forecasting methods and how our tailored approach can drive efficiency and cost savings for your company.

Challenges in Conventional Forecasting

Standard forecasting methods, often provided by SAP or Salesforce, have limitations in capturing essential variables that influence demand. As a result, businesses might encounter inaccuracies in their forecasts, leading to stockouts, dissatisfied customers, or excessive inventory costs. Overcoming these challenges and achieving accurate demand forecasting requires a comprehensive solution that adapts to specific business needs and considers a wider range of variables.

Having it all in mind, the most frequent forecasting challenges are the following:

• Volatility: Market predictions and consumer behavior are often unpredictable and can change rapidly, making it difficult to interpret.
• Inaccurate Forecasting: Frequently, not all relevant factors are considered for accurate forecasting.
• Seasonality: Many companies experience seasonal fluctuations in demand, making the forecasting process more complex.
• Long-term vs. Short-term Forecasting: Properly focusing the forecast and defining both short-term and long-term forecasts is not always straightforward.
• Preparation of Forecasting Data: Often, complex and diverse datasets are required, which demand in-depth knowledge of correct and automated data preparation. Inaccurate or incorrect data directly impacts the quality and reliability of forecasting.
• Technological Limitations: Companies often feel constrained and inadequately supported by the technological limitations of their current systems.

Our Approach

Recognizing the limitations of traditional forecasting models, Log-hub AG presents a groundbreaking approach to demand forecasting. Our solution involves:

1. In-depth Analysis: We begin by conducting a thorough analysis of your current forecasting process, identifying challenges and potential areas for improvement.

2. Customized Solution: Together with your team, we define your precise forecasting needs, considering your unique datasets, industry-specific variables, and desired outcomes.

3. Data Preparation and AI-driven Modeling: We process your data, ensuring it is clean, normalized, and ready for analysis. Leveraging a combination of advanced algorithms and a neural network, our AI-driven modeling provides accurate predictions for your demand forecast.

4. Validation and Implementation: Our experts validate the forecast against existing data and demand patterns. Once the model is confirmed to be accurate, it is implemented into your supply chain process, ensuring a seamless transition.

Business Value and Benefits

By adopting our tailored forecasting solution, your business can unlock a range of benefits, including:

1. Enhanced Efficiency: The optimized forecasting process allows for better planning and resource allocation, reducing stockouts and overstocks by 20% – 40%.

2. Improved Customer Satisfaction: With fewer supply chain disruptions, your customers experience smoother operations and timely deliveries, leading to increased satisfaction and loyalty.

3. Cost Savings: Early planning and accurate forecasting lead to efficient resource allocation, resulting in direct cost savings for your business.

4. Environmental Impact: The precise forecasting helps coordinate transportation and production, reducing waste and the overall carbon footprint, thus positively contributing to the environment.

Accurate demand forecasting is a game-changer for businesses striving to achieve supply chain excellence. At Log-hub AG, we firmly believe that a personalized approach leveraging Data Analytics and AI is the key to unlocking the full potential of forecasting. By partnering with us, your business can witness substantial improvements in efficiency, customer satisfaction, and overall cost savings.

Contact us today to embark on the journey of transforming your demand forecasting process and staying ahead in today’s dynamic business landscape. Let’s embrace innovation and shape a better future for your company!

In the dynamic modern business, data reigns supreme, empowering decision-making across departments. Yet, amidst this data abundance lies a challenge that many organizations face – the lack of standardized processes for reporting and dashboard creation.

In today’s data-driven business landscape, reports and dashboards play a vital role in decision-making across various departments. However, the lack of standardized processes and varying data structures often lead to inefficiencies and challenges in data utilization. At Log-hub AG, we recognize the importance of standardization in fostering a harmonious and transparent reporting environment. In this blog post, we delve into the significance of report and dashboard standardization, the challenges organizations face, and the transformative benefits it brings to businesses.

The Pitfalls of Non-Standardization

Within organizations, the creation of reports and dashboards may vary widely in terms of data quality, professionalism, and tools used. The absence of a unified approach often results in duplicated data connections, inconsistent data preparation methods, and discrepancies in key performance indicators (KPIs) across different reports. This lack of standardization not only hinders synergy but also makes it difficult for decision-makers to trust and effectively utilize the insights derived from these reports.

Moreover, without a dedicated team or defined process in place, the development and maintenance of reports and dashboards become disjointed, leading to confusion and inefficiencies. As the demand for data-driven insights continues to rise, businesses must address these issues to unlock the full potential of their data resources.

The Power of Standardization

Standardizing the structure and process of report and dashboard development can bring significant advantages to organizations. Here are some of the key benefits:

1. Streamlined Development: Standardized processes enable faster and more reliable development of reports, making data insights readily available to decision-makers.

2. Enhanced User Experience: With standardized templates and visualization elements, reports and dashboards become more user-friendly and consistent, increasing user acceptance across the organization.

3. Improved Transparency: A well-defined structure provides clarity on data access rights, report ownership, and associated costs, promoting transparency and accountability.

4. Data Awareness and Compliance: Standardization fosters a culture of data awareness and compliance, ensuring that data is handled securely and adheres to regulatory requirements.

5. Reliable Insights: Reports and dashboards built on standardized data pipelines are more trustworthy, leading to better-informed decision-making.

Initial steps of Standardization

1. Establish a Dedicated Team: Create a team responsible for overseeing the application’s development, cost, security, compliance, and structure.

2. Define Access Rights: Set a standardized set of access rights for all employees to ensure data is accessed only by authorized individuals.

3. Provide Templates: Offer standardized templates to maintain consistency in work processes and the appearance of reports and dashboards.

4. Adopt Naming Conventions: Implement a naming convention for reports and dashboards to facilitate easy identification and organization.

5. Standardize Visualization Elements: Define preferred visualization elements to maintain consistency across reports and dashboards.

6. Optimize Data Transformations: Determine a structured approach for data transformations, minimizing redundancies within reports and dashboards.

7. Consider Compliance and Security: Incorporate IT compliance, security, and data protection requirements into the standardization process.

8. Conduct Training Sessions: Ensure all users understand the standardized structure and expectations when working with the application.

Standardizing report and dashboard development is essential for any organization seeking to leverage its data effectively. At Log-hub AG, we guide businesses through the process of standardization, empowering them to unlock the full potential of their data-driven insights. By embracing standardization, organizations can achieve data harmony, drive strategic growth, and make informed decisions that propel them ahead in today’s competitive landscape.

Are you ready to unleash the true power of your data? Partner with Log-hub’s Data, Analytics, and AI Consulting Services today, and let us take your reporting capabilities to the next level. Book a call with us to embark on a transformative journey towards efficiency, insights, and success.