When is good enough really great? (cost vs positional accuracy of in-house data)
suf ·fi ·cient sÉ’ËˆfiSHÉ’nt/ enough to meet the needs of a situation or a proposed end
There is always a cost to developing geospatial data. Cost can be in the form of time or in consultant fees.
Paid data geeks are always looking for data that are precise, accurate, and 100% complete, but this level of data almost never exists. And of course, the closer you get to 100% complete and accurate, the more it costs.
You can control costs and shorten development time by setting realistic requirements for geospatial data, recognizing what is good enough or sufficient to accomplish your project goals. When you set appropriate expectations, even though the quality of the information may be less than perfect the return on investment can be great.
Your data should:
Meet Operational Goals
Geospatial data for municipal government isn’t about creating the perfect product. It’s about enabling operations.
An inventory of street trees enables program oversight and strategic planning. A listing of properties that have “at risk” populations enables emergency management planning and incident response. Showing the relationship of rights-of-way and land use enables comprehensive planning and community visioning. The data isn’t the goal, getting something done is.
Sufficient data provides the level of detail you need to make the decision or find the asset that you’re concerned about right now.
If you’re working with limited funding, sticking within the budget is primary. Cost overruns now will likely have a negative impact on your next project. Sufficient data is built with the recognition that time and money are finite resources.
Provide a Basis for Growth
Sufficient data allows for further expansion and refinement later. You can tighten up your accuracy by using better equipment later on, as-needed, or per-project. Make sure your data today is designed with the flexibility to add-on for future projects, but isn’t bogged down in forecasting future use.