What are the best practices and tips for using network design tools and software effectively and efficiently?

To leverage network design tools and software effectively, start by defining clear objectives and scope. This initial step sets the foundation for a successful supply chain optimization process. By understanding what you aim to achieve and which areas of your supply chain require focus, you can tailor your approach to maximize efficiency and effectiveness. This strategic alignment ensures that the tools and software are utilized purposefully, leading to informed decision-making, optimized operations, and enhanced overall performance within your supply chain network.

??Protip: Keep it simple as long as you can. Choose a tool when you are certain what you need to do. Recently I have started a project where we need to define number of centers, and their locations, in order to efficiently support 15+ million shipments yearly. The objective is to minimize operation cost while keeping target service level. As with many other projects I started with a MVP model in Excel. I will switch to a more complex simulation software only when the customer will confirm initial assumptions. Otherwise I am sure I would be able to spend weeks and produce a design which would not meet the needs.

What is exactly the problem you are trying to solve and which factors affect it the most? Which resources are constraining our problem? Do you have information that fairly describes those factors (enough in quantity and quality)? If not, what′s your plan to obtain/transform that data? Which are the features the solution must have and by when? Which are the optional features and what′s their priority? Which scenarios do I want to study and what′s their probability? Who will validate the output and business validity of all the above? With all this clear and only when needed, we bring the technology in.

In terms of best practices for using network design tools, it's crucial to begin with a defined business outcome and reverse engineer to select the appropriate software and modeling processes. Effective network optimization considers costs, lead times, and carbon emissions. Flexibility, scenario frequency, and model runs are pivotal in the art of model building. Efficient practices include robust data management—distinguishing between Raw, WIP, and output files. Finally, develop a repeatable BI tool template for quick, efficient validation and presentation of model outputs to business leaders.

When choosing the right network design tool or software, consider factors such as scalability, reliability, security, performance, and cost-effectiveness. Some popular network design tools include SolarWinds Network Topology Mapper, ConceptDraw Pro, Microsoft Visio, and Dia. Each tool has its own strengths and weaknesses, so it's essential to evaluate your organization's needs and choose the tool that best fits your requirements.

Here is the list of best NO tools available in the market 1. anyLogistix NO +Simulation 2. AIMMS NO 3. Optilogic NO +Simulation 4. Coupa NO + Simulation(not sure)

Depending on the flexibility level you need you may consider as well: ?? Supply Chain Apps from LogHub in case you want something quick, relatively low pricepoint, integrated with Excel. ?? Python (with libraries like Matplotlib, Seaborn, or Plotly) in case you want to create something powerful and fully adjustable.

Before selecting the appropriate software or tool for network design, it's essential to identify your specific requirements, including network size, complexity, and desired features. Consider factors such as support, compatibility with existing systems, scalability, and ease of use while researching and comparing available options. Seek advice from industry experts and consider obtaining trial versions or demos of each tool to ensure it aligns with your needs before making a final decision.

Look for tools that offer scalability, allowing your network design to grow and evolve with your business. It’s important to select software with an intuitive interface and robust support resources to reduce the learning curve. Integration capabilities are key; ensure the tool can seamlessly work with your existing systems for data consistency. Evaluate the software’s simulation features to test network designs under various scenarios, helping you to anticipate and solve potential issues before implementation. Lastly, consider the community and support around the tool—access to a knowledgeable user base and responsive customer service can significantly enhance your experience.

Before loading data into a network optmization software, it is important to have a milestone meeting we call "Data Review/Validation" session. In the data review/validation session, I will be show summary level views of the flows and costs of the company's supply chain. The main goal is for the team to validate that the data summaries represent the business as it occurred during the data colleciton period (typically 12 months) This is an important step before moving onto modeling the network (utilizing network optimization software).

To effectively collect and validate data for network optimization software, begin by gathering essential details about your business network's structure, including its layout, devices, and typical traffic flow. Verify the accuracy and completeness of this information across different sources to ensure reliability. Utilize network monitoring protocols and tools to gather real-time performance data, and conduct regular audits to identify any discrepancies. Finally, compare the collected data to industry standards and best practices to confirm its reliability and suitability for optimization purposes.

Ensuring Data Quality in Supply Chain Processes The quality of inputs drives the quality of outputs in any process. Here are practical steps for data collection and validation: 1. Iterative Data Collection: Start with a sample, validate it, and then collect the full dataset. 2. Identify Data Quality Issues: Quickly spot null values or unexpected negatives. 3. Clear Data Definitions: Ensure clear, shared definitions, especially when requesting data from Corporate IT via business/supply chain teams. For example, "shipment history data" might vary in meaning. 4. Obtain Sign-Off: Secure approval on data elements used in models. 5. Stakeholder Involvement: Engage stakeholders when making assumptions or filling data gaps.

Firstly, clearly define project objectives and requirements to guide tool selection. Prioritize user-friendly interfaces and robust features that align with project needs. Ensure compatibility with existing systems for seamless integration. Regularly update software to access the latest features and security patches. Implement version control to track changes and facilitate collaboration. Invest in training to maximize proficiency among team members. Validate data inputs meticulously to prevent errors that could cascade into larger issues. Employ simulation capabilities to anticipate network behavior under different scenarios. Lastly, maintain documentation to capture design decisions and facilitate troubleshooting.

‘Garbage in, garbage out’ - your tool is only as good as the quality of your data. While validating the data, it’s important to make sure the stakeholder teams are all aligned on the inputs going in the model. For instance, while solving strategic network design problems, we factor in business growth to understand strain/impact of growing volumes (organic or otherwise) on our supply chain. This growth percentage should be the number that both finance and sales (and any other team concerned) agree on.

Once the Historical Baseline is validated, one can build the multiple potential scenarios. If more detailed KPIs is needed to track over time, one should go for simulation based optimization. One of the best tool avaiable in the market which has this capabilty is anyLogistix by anylogic.

Prioritize simplicity and clarity in network models. Maintain accurate documentation and version control to track changes and facilitate collaboration. Regularly validate and update models to reflect changes in infrastructure or requirements. Utilize automation features for repetitive tasks to save time and reduce errors. Consider scalability and flexibility when designing networks to accommodate future growth and changes. Collaborate with stakeholders and incorporate their feedback throughout the design process. Finally, invest time in training to maximize proficiency with the chosen tools and stay updated on new features and best practices.

Always run more scenarios in Network Optimisation Models than fewer. These models can have long solving times, especially with integer, binary, and order set variables. To avoid delays, build models with scenario runs in mind [Design for Manufacturability ;-)]. Running more scenarios generates better and cleaner ideas, such as adding a Hub for Slow-Movers or more Greenfield DCs, and adjusting the number of DCs. This approach enhances strategic value and optimises your network design. Remember, 80% of logistics costs are determined once you design the network. Running more scenarios helps identify opportunities to bring value. Ensure you have a robust analytical and comparison workflow to review cost, service, resiliency, etc.

Running and comparing scenarios is where the real value of network design tools comes into play. In my view, scenario analysis is indispensable for identifying the best possible design among various alternatives. I encourage a systematic approach to scenario testing, where each scenario is thoroughly assessed for potential risks and rewards. This practice not only helps in making the right choices but also prepares the team for any unexpected challenges.

Use the tool to create and analyze different scenarios. Compare these scenarios to understand the trade-offs and impacts of various design choices. This helps in making informed decisions.

Network Optmization software is just a tool and many other factors must be considered before moving forward in the implementation of an “optimal” solution for a firm which is aligned with its own strategy. For example, how does the solution help not to lose sales, gain additional sales or meet customer service expectations? What are the risks, complexity, disruption costs associated with the recommended solution? How flexible is the solution with changes from growth assumptions? How transparent is the solution to customers? Additionally, there are other costs which should be considered that are not typically included in the model – taxes and tax incentives, detailed site selection, and labor availability to name a few.

There is never something as 'the best scenario' to recommend. There are only scenarios which have different pros & cons. I remember a project where moving from 5 to 3 DCs in the region would allow decrease operating costs by ~15% (fixed costs would go down which would be offset partially by higher transportation costs). However, actually the executive team choice was keep 4 locations in order to mitigate operational risks with business growth in mind.

Communicating and implementing results is where strategic insights are translated into actionable steps. I’ve learned that effective communication is key to ensuring that everyone involved understands the design’s objectives, benefits, and implementation plan. Clear and transparent communication helps in securing buy-in from stakeholders and ensures a smooth implementation process. I also believe in continuous feedback loops during implementation to make necessary adjustments in real-time.

Choose tools that align with project scope and complexity. Familiarize yourself with the software's features through training or tutorials. Organize data logically and accurately input parameters for accurate results. Collaborate with team members, leveraging tools for shared access and version control. Regularly back up work to prevent data loss. Document processes and outcomes for future reference and knowledge sharing. Continuously update skills and stay informed about new tools and updates. Lastly, prioritize security measures to safeguard sensitive information throughout the design process. Efficient use of network design tools ensures optimal outcomes and streamlined communication of results.

Would put it differently - you need to communicate to find the best network! Every logical step of the way, you communicate & then the best network emerges. Example: you want to move from a Single-Tier (Plant -> DC -> Customers) network to a Multi-Tier (Plant -> Hub -> DC -> Customer) for certain products (slow-movers, etc). But if you haven't communicated with, say, Corporate IT, if your ERP can support POs to move material from plant to hub to DC, etc. How much time it may take to change the ERP configuration. If that time is not efficient, then the best network on paper is just that - best on Paper! Ensuring one understands the right stakeholders & then communicates effectively is very important for implementing the results!

??Protip: Learn from the best. PEPSICO has a 'road to market' process which is run in yearly cycles. They review periodically what targets they want to achieve, and how they want to model their supply chain to actually deliver those targets.

?? Currently, the different geopolitical and environmental variables generate a lot of instability in logistics networks, make sure you always have a contingency plan designed and tested that allows you to transition from one network to another with the least possible turbulence. ??Both plans, the main and the contingent, must constantly be updated.

Regularly updating your network design is crucial for maintaining operational efficiency and responsiveness to market changes. By continuously integrating feedback and monitoring data, you ensure your network adapts to evolving demands and conditions. Additionally, staying informed about emerging trends and technologies can provide a competitive edge, enabling you to refine your network for optimal performance.

Network design is not a one-time task. Regularly review and update your network design to adapt to changes in demand, supply chain disruptions, technological advancements, and other dynamic factors.

Summary: ??Do not buy software that is fashionable for the design of your network, evaluate several alternatives and purchase the one that best meets your needs and budget. ??Network design is based on data, make sure you get the most reliable ones. ??Keep your main logistics network updated, as well as the contingencies network. ??As in any process, communication is vital: It involves all the stakeholders who will participate as users of that network. ??From day zero, implement your KPIs and periodically evaluate their results. ??Teamwork is crucial, lone heroes often fail!

User Training: Ensure that users are adequately trained on the chosen tool or software. This maximizes the effectiveness and efficiency of the tool. Integration with Other Systems: Integrate the network design tool with other supply chain systems such as ERP, TMS, and WMS for seamless data flow and better decision-making. Sensitivity Analysis: Conduct sensitivity analyses to understand the impact of changes in key variables on your network design. This helps in identifying potential risks and opportunities. Collaborative Approach: Involve cross-functional teams in the network design process. This brings diverse perspectives and fosters collaboration, leading to more robust designs.

Effective supply network design hinges on high-quality data. This requires collecting diverse information from various sources while breaking down organizational silos through cross-functional collaboration.Implementing centralized repositories and master data management practices helps overcome data silos. Regular audits, sensitivity analyses, and quality checks ensure data robustness. Fostering a data-sharing culture across departments is crucial. Continuous improvement of data processes and staying updated on industry benchmarks further enhances network design accuracy and effectiveness. By focusing on these aspects, companies can significantly improve their supply chain decision-making capabilities.