Data plays a crucial role in decision-making in the dynamic world of multifamily real estate. However, the overabundance of data can complicate the decision process. Rather than assuming that more data always results in better decisions, it's worth championing a 'quality over quantity' approach.
Challenging Prevailing Notions
While "big data" remains, a buzzword echoing in multifamily circles, the reality is that our industry primarily operates within the realm of small data. Despite the acknowledgment that multifamily encounters massive datasets, a considerable portion of our analytical endeavors revolve around managing, interpreting, and deriving insights from more modest-sized datasets—often measured in kilobytes, megabytes, or gigabytes. In this blog, we delve into the nuanced landscape of small data, shedding light on its transformative potential in an industry that frequently navigates the intricacies of smaller datasets. Embracing the unique characteristics of our data environment, we challenge prevailing notions and showcase how, in multifamily, it's often the small data that catalyze significant breakthroughs.
Embracing 'Less is More'
As we challenge prevailing notions in the multifamily realm and embrace the reality of primarily working with smaller datasets, a pivotal revelation emerges less is more. In an industry fixated on "big data," our focus on managing more modest datasets sparks a transformative perspective. The shift from sheer volume to the strategic curation of relevant, high-quality data becomes the cornerstone of our analytical approach. It's not about drowning in a sea of information but rather about navigating purposefully, extracting meaningful insights from the depths of meticulously chosen data.
Transformative Potential of Quality Data
In a shift away from the industry's fixation on "big data," our strategic emphasis on smaller datasets transforms our analytical perspective. An article from McKinsey reinforces this approach, highlighting the move from volume-centric data to the strategic curation of high-quality, relevant information. An illustrative example in the article demonstrates how a multifamily application leveraged both traditional and nontraditional data to forecast Seattle's three-year rent per square foot with over 90 percent accuracy, further emphasizing the opportunities that quality data curation allowing teams to explore the value nontraditional data brings to predictive models, reshaping decision-making at both individual building and portfolio levels. This approach not only reshapes decision-making within individual buildings but also transcends conventional data boundaries, offering a new era of insights and possibilities for the industry.
Quality data serves as a common currency among multifamily teams, centering activities and focus on strategic projects (and decisions) that will move the business forward. Collaboration through data enables cross-departmental alignment to corporate goals – leading multifamily companies toward greater performance. Experience how quality data acts as a cohesive force, empowering multifamily teams to work collectively to hit their targets.
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