Manufacturing network design software focuses on optimizing plant locations, capacity, and product flow paths. It can span what-ifs on internal production optionality versus outsourced production. Since COVID-19, companies need more flexibility and agility in scenario analysis, so they can ensure their networks are resilient to continued disruption. Thus, planners are faced with the need to balance cost-saving opportunities, resilience, and agility. With manufacturing network design software, planners can determine the best arrangement of manufacturing operations to meet the organization’s objectives in a world of unprecedented change.
What Is Manufacturing Network Design Software?
In most instances, manufacturing software isn’t suitable as manufacturing network design software. Supply chains are becoming more complex and, in order to remain competitive, companies need significantly more agility and high-quality decision-making than in the past. Traditional software used for optimizing the manufacturing network fails to provide a holistic, accurate picture of operations across manufacturing plants, sourcing options, capacity, flow paths, and more, nor do they have the capabilities to determine the most effective arrangements across multiple markets.
Consequently, manufacturing network design planners often have a limited overview of operations, and local silos impede attempts to find opportunities for profit growth.
Few off-the-shelf solutions exist. Granted, there’s a multitude of manufacturing software packages on the market, but most are intended for managing single plants or focus on a limited portion of the network. Additionally, few incorporate user-friendly scenario analysis capabilities that enable planners to, with confidence, frequently (monthly) stress-test and query their network for new cost-saving or profit-driving opportunities.
We’ve come up with ten characteristics to look for in your manufacturing network design software.
10 Key Characteristics to Look for in Your Manufacturing Network Design Software
Prescriptive analytics has largely become the go-to solution whenever there’s a need to determine an optimal solution. Based on well-proven optimization theory, prescriptive analytics software is now a practical proposition for almost every organization. Here are several key characteristics to consider when choosing manufacturing network design software.
1. A digital twin for network modeling that doesn’t require Data Scientists
Look for a network modeling solution that requires little to no support from Data Scientists with respect to creating, modifying, and querying optimization models. This will enable the flexibility and agility planners to quickly and easily model and stress-test the manufacturing network in intricate detail. Select prescriptive analytics software packages with intuitive model building capabilities. Look for solutions in which the relationships across your manufacturing network are established via pre-defined, embedded mathematical formulae that don’t require additional programming to generate.
While it’s possible that you may initially need assistance from software vendors or external specialists, code-free programming solutions save time, are simpler to work with, easy to modify, and require detailed visibility into the underlying workings of your model.
Increasingly, the market is referring to such models as a “digital twin” of your supply chain or value chain.
2. Consumes near real-time data
The ability to read and use real-time data means solutions are dynamic and relevant. This means there’s no need to manually upload information for each run, and the models reflect current realities. Determine how often your data needs to be updated. Often, for manufacturing networks, the data doesn’t need to be real-time. Usually, it can be updated on a weekly or monthly basis, without sacrificing the quality of decision-making and scenario runs.
Find the right balance between the quality of decisions, speed of scenario analysis, and accuracy of your data. Oftentimes, having that real-time data can actually hinder decision-making agility without significantly improving the quality of decisions. Test this, and determine your right approach.
3. Models a single, end-to-end view
The model (or digital twin) should ideally provide a single view of the entire network—procurement, production, distribution, pricing, promotions, and capital allocation. This approach breaks down silos and ensures information flows freely without hindrance. The model acts as a digital twin, mimicking not only the manufacturing network but also components of the network that can impact or are impacted by manufacturing.
Oftentimes, companies will begin by representing pieces of their network in the digital twin and then expand as the scope of manufacturing network design expands. At a minimum, make sure the digital twin includes appropriate operational and financial aspects. (The requirements should include sourcing, production optionality, different product flows, and financial ratios per unit across each step of the process.)
4. Provides robust financial modeling out of the box
Crucial manufacturing network design software models incorporate robust financials. These encompass compliance with internal and external GAAP accounting requirements. This feature ensures models reflect real-world realities, bridging the gap between managerial and financial accounting processes. Additionally, the flexibility to run the software monthly in sync with corporate reporting adds weight and credibility to manufacturing network design software solutions.
5. Empowers the business user via modern user experience and reporting capabilities
A solution that offers a familiar and intuitive user experience is easier to adapt to and understand. For example, software that offers similar functions and controls as popular office programs like Microsoft Office shortens the learning curve. Find a solution that enables your business users (non-technical users) to take advantage of and blend advanced analytical capabilities like Python and R.
6. Represents all your unique business constraints
Manufacturing network design software must effectively model constraints. A constraint is any limit that has to be respected. Constraints may be financial, physical, regulatory, or operational. Think of elements like duties, tariffs, platform production limitations, blending requirements, quality variations, and so on. Not all technology can effectively model these complexities, thus resulting in sub-optimal or (worse) infeasible scenario outcomes.
7. Provides optimization capabilities
Gartner loosely defines prescriptive analytics to include two techniques: heuristics and optimization. Heuristics is the application of a set of business rules intended to find a solution to problems quickly. Laudable as this is, heuristics cannot find the best or optimal solution. Manufacturing network design software solutions need true mathematical optimization techniques.
8. Enables rapid what-if scenario analysis
Possibly the most crucial aspect of manufacturing network design software is an ability to evaluate different scenarios. This capability allows manufacturing planners to consider the impact of different possible scenarios and determine robust and optimal solutions.
9. Gives you the scale, flexibility, and cost-saving benefits of the cloud
Consider scalability, flexibility, and cost. SaaS cloud solutions offer easy connectivity, scalability, and security. They facilitate connecting with and uploading data from diverse sources. Data can reside on customers’ hardware or in the cloud.
Not only that, selecting a vendor that offers solutions via a platform better enables your business to undergo a digital transformation journey with a single vendor, in a stepwise manner.
10. Provides multiple software integration options and easy management
The ability to connect with multiple data sources is crucial. This includes data repositories, corporate ERPs, spreadsheet uploads, and other management solutions. This is a key factor in terms of data processing.
Make sure it provides bi-directional data integration to and from source systems, in addition to cradle-to-grave audit tracking for data lineage, data transforms, and applied business logic.
Lastly, the solution should offer business and technical workflows, so the solution can be incorporated into a standard process, or a new process can be established.