Clients & Case Studies
A Global IT Services Company
CRE Director, Technology Company
John Lucas, Juniper
How to Use Benchmarking to Achieve Results: A Case Study
BY PETER HOLLAND, RON ZAPPILE and RAYMOND NOMIZU
Accurate and meaningful data allowing for cross-company comparisons has been problematic and very difficult to find in the CRE industry. With BenchCoRE, corporate real estate executives now have a practical tool to escape the narrow limits of introverted experience and intra-company analytics. This case study reveals the power of data and benchmarking.
By investing in a rigorous data validation process, BenchCoRE provides members with a consistent, trusted and reliable set of industry peer data that can be analyzed at increasing levels of specificity to pinpoint significant opportunities. The BenchCoRE member featured in this case study was able to identify the causes behind their overall cost position and utilize the data in a focused way to prioritize the largest and most achievable opportunities.
Comparing cost to space utilization drivers
Informed with BenchCoRE’s opportunity analysis, the real estate team ran a report comparing their cost per FTE for office space in a target geography, and discovered that they were operating at the high end of the range, both within and outside their own industry peer group. An example of a Cost per FTE report follows, showing an average of $9,350 and a wide range of outcomes from under $6,000 per FTE to over $12,000 per FTE:
In the graph, the yellow bars represent the company’s own industry peer group, whilethe green bars represent a different peer group of office users that they examined to augmentthe comparison set. Note that consistent with our protocols, we have masked the actual values, but the bar chart itself is otherwise unaltered. The chart represents cost per FTE for office properties and the system allowed the member to select for geography, exclude the impact of virtual FTE’s, and eliminate surplus properties.
By reviewing the individual data points, the member was able to identify not only their cost versus the average – which is how most benchmarking comparisons are done – but also the range of individual values. This detail and visibility into the real numbers provide valuable additional insight. By way of example, a real estate executive using the above chart would quickly observe a large clustering in the $6,000 to $7,000 range, indicating that this performance level is realistically achievable.
Using BenchCoRE analytics, the member further “drilled down” to additional performance driver metrics, including:
- Square Feet per Seat
- Number of FTE’s per Seat
- Cost per Square Foot
The member was able to see an immediate graphic display that revealed that their space efficiency metrics (i.e., square feet or square meter per seat and FTE per seat) were generally in line with their peer set. For instance, the square feet per seat metric ranged from about 180 to about 320, with the member coming in close to 240.
Cost per Square Foot Comparisons, Down to the City Level, Were Examined
The BenchCoRE participant learned that its cost per square foot for office space was higher than its industry peers, which in turn drove an opportunity to reduce its high occupancy costs vis-à-vis the peer group and other office users. However, because its cost profile of owned vs. leased properties differed, the real estate team needed to differentiate the company’s cost profile by ownership type. Leveraging BenchCoRE’s report filtering capabilities, the participant prepared a targeted report that revealed detailed cost metrics for owned vs. leased office properties within the study area geography.
For owned properties, the company learned that its property depreciation was higher than that peer group companies – a fact reflecting a series of recent, high-cost investments in new facilities. The team also learned that their operating expenses – which are more controllable – were actually fully in line, if not somewhat better than, the peer group average, possibly as a result of these capital investments. The senior CRE executive recognized that their investment decisions led to a higher G&A cost profile, and that there were more productive initiatives than pursuing aggressive cost management initiatives in the owned-property portfolio.
For leased properties, the company learned that they had one of the highest cost footprints among their peers. Because BenchCoRE allows executives to target costs by geography and down to the city level, the end-user team ran comparative reports at the city level, targeting their largest locations. As a result, using the market data from other CoreNet members, they were quickly able to identify the specific leases that were driving their overall cost position.
From this analysis, the team was able to prioritize the major cost saving opportunities and, furthermore, tie back each of these individual initiatives to an overall projected portfolio average. The team intends to use the BenchCoRE system to continue to benchmark their portfolio, thus creating a longitudinal view of their performance over time, both relative to their baseline and to their peers.
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