About the Customer
QuadReal Property Group is a Canadian real estate investment, development, and management company operating on a global scale.
Scope and Challenges
Aiming to double the value of its real estate portfolio in five years, QuadReal’s decision-makers need timely, accurate insight into portfolio data scattered across many disparate source systems. Paying into a retirement fund is commonly regarded as a prudent, low-risk investment—but the performance of pension funds depends on the diligence and skill of fund managers to keep your capital growing year after year. When a fund invests in a portfolio of real estate, it needs to ensure that the commercial, residential and industrial properties within that portfolio are well-managed and maintained to maximize the return on that investment.
Outcome and Implications
By building advanced analytics capabilities on carefully governed business data, QuadReal can equip decision-makers across all parts of the business with the insights they need to drive the growth of its asset portfolio, and optimize return on investment. Some of QuadReal’s personnel are now using reports from the platform to drive their end-of-month reporting and day-to-day activities.
IBM Maximo is a comprehensive solution for managing physical assets on a common platform. With Maximo, you can maintain all asset types, check their health in real time and streamline global operations, from procurement to contract management. Choose from several implementation methods on-premises or in the cloud with two Software-as-a-Service (SaaS) options to fit your business requirements.
“Even though our data migration is still in progress, we wanted to focus on delivering use cases for portfolios of assets we could report on, and provide our users with simpler ways to consolidate the data. We are always looking for better ways to harness our data to help our people make decisions, comments Wong. We see great potential in using predictive and prescriptive modeling to enhance the decision-making process. For example, by mining our lease data for hidden patterns, we could create a churn model to alert our people when we detect occupants who are unlikely to renew. Similarly, we could combine data on residential rates with the regional average to identify the optimal time to renovate a rental suite.”-said Sam Wong, Head of Analytics and Data Science at QuadReal.
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