This large life sciences company was challenged in understanding utilization of its property portfolio. In order to do this, they needed to effectively analyze security badge swipe data.

JLL Technologies implemented a solution that helped them:

• Save 30+ hours per week through automation, resulting in $140,000 in time savings to date
• Achieve ROI in less than six months
• Extract data insights that provided:
• Footfall trend analysis, including peak and average footfall
• Long-term annual trends analysis
• Year-over-year change
• Aggregation of data at building, campus, business unit, and portfolio level
• Filter data by parameters, such as date/time, building, and staff type
• Breakdown of building usage by each FM supplier

This global life sciences company was challenged in understanding utilization of their property portfolio. The COVID-19 pandemic meant that this customer needed to quickly understand which locations were being utilized and by which business units and types of employees, so they could keep their employees safe and maintain crucial operations. In order to do this, they needed to effectively analyze security badge swipe data, but they faced the following issues:

• Fragmented and inconsistent data – different security software and hardware was used across the portfolio, so the customer was lacking a single source of truth to provide effective reporting
• Manual processing of swipe data – data gathering and processing was time consuming
• Static reporting in Excel – reports were functional but lacked analytical insights to help make business decisions

Phase 1: Understanding the Data

In response to the COVID-19 pandemic, the JLL Account Team was tasked with designing a manual process to collect, cleanse, and analyze the badge swipe data to quickly build some base-level reporting. The process included designing data mapping files that could identify data quality issues, such as duplicate records and incorrect formatting. The end result was a robust manual process that quickly provided the customer with daily building usage reporting.

Phase 2: The Analytics Platform

Building upon phase 1, JLL Technologies (JLLT) was then asked to develop and deploy a full analytics solution, which included:

• A data upload application, using an automated extract, transform, load (ETL) process to blend the security data from different sources into a single, consistent, analytics-ready data source; this included custom workflows for each data security system
• A suite of interactive visual dashboards designed to provide the customer with insights about utilization across their portfolio
• Automated reporting of a set of well-established reports required by senior leadership to ensure that continuation of this service provided by JLL

JLLT’s analytics solution has enabled the customer to gain greater insights into the utilization of their portfolio. They now understand what parts of the portfolio are being heavily utilized at the building, campus, or business unit level as well as by staff type (such as direct, contractor, visitor, and supplier). Also, with return-to-office being a key focus, the customer is now using this data to help make business decisions about their portfolio in light of the new hybrid workplace environment.

Other specific results include:

• 30+ hours per week saved through automation, resulting in $140,000 in time savings to date
• ROI < 6 months
• The data insights provided included:

• Footfall trend analysis, including peak and average footfall
• Long-term annual trends analysis
• Year-over-year change
• Aggregation of data at building, campus, business unit, and portfolio level
• Filter data by parameters, such as date/time, building, and staff type
• Breakdown of building usage by each FM supplier