Data Challenges

Data integrity is a significant hurdle in land use decision making.  Often in consulting assignments, information is provided by the client with the expectation on both sides that it is sufficient and vetted.  Often this is not the case and the consultant must identify gaps where the information is lacking.  In a surprising number of engagements, the gaps cannot be filled – the data doesn’t exist – so assumptions must be made.  The decision must still be made, however.  If organizations waited for perfect data, then nothing would ever happen. 

Data gaps as they relate to land use decision making often relate to performance management.  Often building owners do not track energy usage, for example.  Or they combine financial statements for several assets into one report so individual asset performance is not readily established.  This makes it difficult to determine which assets, if any, should be redeveloped, sold, or retained.  It is also difficult to compare assets within a portfolio to rank and prioritize optimization initiatives.  In a private sector context, financial performance is a paramount metric and closely monitored.  In a public-sector context, financial performance is not as important.  An asset is a means to an end, so the performance relates to the use of the asset in the execution of a service.  Those with a private-sector mind-set may find this hard to grasp – after all even in government value for money is an important metric.  This is different than financial performance though.  A homeless shelter may offer excellent value for money insofar as it is less expensive to serve this vulnerable group of people in a shelter environment than in an emergency health care or correctional environment.  However, looking at financial performance of the shelter itself is misleading since the users don’t pay rent and therefore there isn’t an income line to offset the expenses at this granular level.  This type of value for money performance is hard to manage through quantified metrics, and therefore the data for land use decisions becomes more qualitative and subjective. 

Portfolio Data 

Land use decision making can be at a very strategic portfolio level, a programmatic level for groups of like assets, or at the individual site level.  Strategic questions may include: Does this asset fit the needs of current and future tenants?  Is it in the correct location, given the expected densification of this neighbourhood?  Is there a rationale for the retention of ownership of the asset, as opposed to retaining access through a leasehold?  Demographics plays a significant role in these decisions as this data will indicate where population densities will shift, how generational changes may impact regions, and the requirements for the suite of land uses to meet those changing needs.  Major landowners such as governments can have significant impact on the communities around them through their land use decisions.  Municipalities and regional districts have extensive planning and land use guidance development to structure the changes within their communities.

For portfolio level decisions, the data needs are more aggregated and forward looking.  This relates to aligning the portfolio with the organization’s mandate and overall vision.  This is where an organization will consider whether they are in the business of ownership, and if not, why are they owners?  There may be good and valid reasons to retain asset ownership besides mandate fulfilment, however these need to be articulated and rationalized.  There is also the opportunity to roll those assets into another organizational structure to effectively manage them. 

Data for portfolio level decisions looks at changes and opportunities – demographics, neighbourhood revitalization, economics.  Can your apartment buildings accommodate the rising senior’s population?  Are you positioned in emerging neighbourhoods where redevelopment may be viable in the medium to long term?  Is your office building attractive to the budding tech sector?  Are we well located relative to future transportation corridors?  Depending on your organization’s vision and mission, these high-level factors will impact your portfolio decisions.  You may choose to acquire lands in emerging neighbourhoods in anticipation of a new transit corridor.  Your organization may limit its risk exposure by divesting out of areas prone to flooding as water levels rise as a result of climate change.  At a portfolio level, generally land use decisions result in realignment over time rather than a wholesale change in portfolio composition. 

Program Data

Decision making at a programmatic level requires more granular data and trends between and among assets within the portfolio.  Capital asset management programs will utilize comprehensive building performance data to capture energy usage and efficiency as well as scheduled and deferred maintenance requirements.  This type of analysis requires considerable data, not just on the asset itself, but benchmarks against which performance is measured.  Presented as a program of work, the data can provide for symbiotic scheduling of projects, or common procurement processes for several buildings.  It also provides for objective prioritization of projects over the portfolio. 

The ongoing operating costs and capital requirements feature prominently in land use decisions relating to redevelopment.  Assets which cost more to repair than to replace inspire larger land use discussions to determine what the future state of the asset may be.  There is a caveat relating to heritage or special purpose assets which are constrained in their future state opportunities, however the data requirements in these cases are often increased rather than decreased for decision making purposes.  Many municipalities have designated specific properties or areas for heritage conservation which limits the land use options available.  Data requirements for the maintenance of that heritage asset become more complex as repair and replacement options must conform to specific guidelines established by the municipality or by a specialist consultant. 

Site Data

For individual assets, there is a direct relationship between the data and the land use decisions being made.  In a private sector context, considerable effort is expended to capture financial performance metrics for the asset.  Once the highest and best use is no longer the current use, the owner and their consultants will start the process of identifying alternative uses for the property.  An owner will develop a business case or feasibility study to determine viability of an alternative development.  In creating this document, they will look to public planning guidance (zoning, OCP), market metrics (rents, vacancy), construction costs, interest rates, among a variety of others.

In a public-sector context, site-specific land use decisions are focused on filling a need.  Do we still need this school site?  Does this hospital need a new wing?  What lands do we need to acquire in anticipation of a new highway?  There is less of a focus on the traditional highest and best use, however data points such as construction costs, interest rates, and demand all are used to determine the value for money and the need to be fulfilled.    There are still negotiations required with municipal officials regarding public service land use decisions.  There are many examples of housing for vulnerable peoples which have been squelched by municipal officials as not conforming to the neighbourhood wishes.  Even with pronounced need, public-sector agencies are still required to meet planning requirements set by the communities.

Data as Guide

Land use decisions, good ones at least, are data driven decisions.  Whether they are at a regional level or site-specific, the decisions being made have generational impact and significant financial ramifications.  To ensure that these decisions are the best ones, the data used to make them must be comprehensive, accurate, and relevant.   Each level of decision making has different data focusses, however each feeds the next.  Site specific decisions that don’t fit into the portfolio strategy become ad hoc.  Program decisions that don’t consider the site particulars will not be implementable.  Using data as the guide and foundation for decision making ensures each decision is the best it can be.