This article is part of the Site Selection Playbook 2024 series, providing strategic insights and practical advice for manufacturing executives. Published by Area Development Magazine, the series aims to guide businesses through the complexities of site selection to ensure successful project outcomes: The Role of Data-Driven Site Selection in Modern Manufacturing; Crafting Effective Incentive Packages; Ensuring Compliance and Maximizing Incentive Benefits; Understanding the Importance of Speed in Closing Deals; Optimizing Incentive Approval Timelines; Navigating Non-Disclosure Agreements in Site Selection; Engaging Local Stakeholders for Site Selection Success (10/9); Managing Community Sentiment and Activism (10/9)
The landscape of site selection is evolving. Historically, site selection was driven largely by relationships and subjective assessments. However, the advent of data-driven methodologies is transforming how companies identify and evaluate potential locations. This shift towards objective, data-driven site selection is crucial for manufacturing executives seeking to make informed decisions that maximize operational efficiency and profitability.The Scoring Matrix: A Tool for Objectivity
One of the most significant advancements in data-driven site selection is the development of scoring matrices. These matrices allow companies to evaluate potential sites based on a wide range of criteria, ensuring a comprehensive and objective assessment. Doug Heinz from Kroll highlighted the importance of such a tool, emphasizing its ability to bring objectivity to a traditionally relationship-driven process.
The scoring matrix developed by Kroll evaluates criteria at the county level, including property tax, sales and use tax, income tax, land costs, and payroll expenses. By analyzing these factors, companies can ensure that they are considering all relevant aspects of a potential site, rather than relying solely on existing relationships or anecdotal evidence.
Benefits of Data-Driven Selection
Adopting a data-driven approach to site selection offers several key benefits. First, it helps avoid the pitfalls of overlooked communities and counties. Traditional methods often rely on existing relationships, which can result in potentially excellent sites being ignored simply because they are not on the radar of key decision-makers. By using a scoring matrix, companies can objectively evaluate all potential sites, ensuring that no stone is left unturned.
Second, data-driven site selection enables companies to make informed decisions based on comprehensive data. This approach reduces the risk of unforeseen costs or challenges that can arise from subjective assessments. For example, a site that appears attractive based on relationships might have hidden costs or regulatory challenges that become apparent only through a detailed, data-driven analysis
Case Studies
Several case studies illustrate the benefits of data-driven site selection. For instance, Kroll's use of their scoring matrix helped identify a rural community that was well suited for a large company’s relocation project. Despite its rural location, the community's strong collegiate presence and cohesive local leadership made it an ideal site that might have been overlooked using traditional methods
Another example is the site selection for a petroleum company. By leveraging data on existing pipelines and operations, Kroll was able to identify the optimal site for a carbon capture project, demonstrating the power of data-driven selection in making informed decisions.
Takeaway
Data-driven site selection represents a significant advancement in the way manufacturing executives can identify and evaluate potential locations. By utilizing tools like scoring matrices, companies can ensure a comprehensive and objective assessment of all potential sites. This approach not only helps avoid overlooked communities but also reduces the risk of unforeseen costs and challenges, ultimately leading to more informed and profitable site selection decisions. Manufacturing executives are encouraged to adopt data-driven methodologies to stay competitive in an increasingly complex site selection landscape.
