Build, Buy, Partner: Three Considerations for Effective Data Strategy Development
By Raj Bhatti, SVP Client Solutions at Cherre
The real estate industry lagged behind its peers in the area of digital transformation. However, the pandemic and resulting market uncertainty created a paradigm shift within the industry to better leverage data and insights as a source of a sustainable competitive advantage. Now the question for companies is whether to build their own technologies, buy existing solutions or work with third-party partners.
Build, buy, and partner are not mutually exclusive choices. Many successful implementations have a combination of all three. The mix is a function of the in-house talent and initiative complexity:
Where in-house resources and expertise exist and the initiative is core to generating alpha, “build” is likely the right choice
Work that can be done quicker and cheaper using pre-built vendor products is a relatively easy “buy” decision
If technology is outside a company’s complete expertise, “partnering” might be the best solution
Below are additional key factors to consider when making the build-buy-partner decision.
Make Connected Data Your Foundation
It can be easy for companies—especially those that are trying to play catch-up—to go directly to flashy tools that promise an ability to unlock boundless efficiency and opportunity. However, real estate companies must understand that success comes from clean, connected data to feed more advanced tools. Despite its importance, only a small portion of large commercial real estate investors, lenders and underwriters have connected data.
The first step to creating an effective data and analytics strategy is to centralize and connect the data. Firms often rely on a mix of internal data, subscription data and public data. These data sets require standardization so they can be connected in a meaningful way. This is what makes a data management platform that can create a “single source of truth” so vital.
Once data is connected, companies can focus on building data warehouses to enable and support business intelligence (BI) activities.
Pay Attention to Maintenance
One “gotcha” expense that is often initially overlooked are maintenance costs. Creating a data warehouse and BI tools for guiding business decisions is not a “set it and forget it” task. Companies must continuously keep the data warehouse operating efficiently, while monitoring for potential risks and other issues. Technical maintenance and data maintenance requires specialized skills that many real estate enterprises do not have on hand if they go the “build” route.
Additionally, the demand for insights and information stemming from the data warehouse may shift. As such, the data warehouse should be able to integrate data from new sources. At the same time, the data warehouse needs to remain effective enough to eliminate unnecessary data sources from its catalog.
Prepare for a Talent Battle
The Great Resignation, the Great Reshuffle, the Great Reset: The current talent landscape has earned many nicknames. The competition for tech talent is high. Real estate enterprises embarking on build solutions will likely need to poach and retain tech talent from traditional tech companies. This requires matching or surpassing perks and culture offered by the technology industry’s largest companies.
The way around this is to work with a partner or consultant. Partners have the talent and expertise that many real estate enterprises don’t. They have the knowhow to connect and clean data and keep it secure, while maintaining the infrastructure, and developing new capabilities to keep up with the rapidly changing market.
Analyze, then Decide
Once an organization evaluates the state of its data, ability to support in-house maintenance and current talent mix, it can determine what build-buy-partner mix is best. Honesty is essential when evaluating these factors—buying or partnering where weaknesses exist and building where there are strengths. Such an analysis will help create a strong and sustainable data strategy that can evolve as markets change.
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