Are you optimizing or improving space usage?

Many software vendors claim their solutions optimize space usage.  In complex situations such as campus and regional plans, it's more likely that they are “improving” space usage, not “optimizing" it.  With many different ways to relocate workers, free up vacant space, and dispose of it, planners may be overlooking ways to save even more money and improve productivity.

While improvements are definitely beneficial, for organizations in competitive and cost-conscious environments, optimization is even better.  With its mathematical search algorithms, Core Planning builds on opportunities other systems find by searching through the alternatives to find the best ways to capitalize on these opportunities, moving closer to optimizing space usage.  

For example, on one regional plan we had 3,600 workers located across 17 properties, which included 9 lease expirations and 4 cancellations options. Core Planning identified an overlooked solution that saved an additional $1 million, reduced capital investments, and kept more workers in the suburbs where they wanted to stay.

The following questions illustrate the challenges planners face in sorting through alternative solutions with intuition and trial-fit spreadsheet and drag-and-drop approaches.  With each possible business group relocation, planners must consider the following questions as well as consider how this relocation will impact where other groups are able to relocate.

  • For which spaces, if any, can occupancy costs be reduced when space is vacated?
  • Will moving workers require renovation and added infrastructure in their new location, offsetting occupancy cost reductions?
  • Which relocations can maintain, and preferably improve, adjacencies? 
  • Can these adjacencies be maintained as groups grow or shrink?

With Core Planning, search algorithms evaluate these questions as they sort through the alternative relocations and facility strategies, in minutes rather than the hours and days required for manual trial-fit approaches.  By automating the trial-fit process and quantitative assessment, planners and decision makers have more time and better information to evaluate qualitative issues, balance key cost, productivity and risk issues, and negotiate conflicting business priorities.

Many people question whether a mathematical approach can also capture planners’ insights and expertise.  Core Planning was specifically designed to do just that.  Watch for a future post that compares Core Planning with Google searches to illustrate how insights and search algorithms can be combined to make finding the best answers faster and easier. 

As with Google, we may still not find the optimal solution, or the best website, but with advanced search algorithms, Core Planning can do more to capitalize on the opportunities that other systems identify to improve, and possibly, optimize space usage.