Arriving at an answer to the question, however, is no simple task. Facility management is a very complex service function that depends on a large number of interrelated variables: management processes, different types of space, age of facilities, service menus, lease/own policies, occupancy density, employee churn, and as many as 40 other significant factors.

The staffing level question can be answered, and in fact it has been done effectively, through the use of a new mission-based headcount analysis methodology. Mission-based Headcount Analysis is a fresh approach to correlating FM staffing levels with the complexity of many interrelated facility management variables. Devised by Tradeline Inc. founder Steve Westfall, Ph.D., who has gathered real-world data from 90 facility management organizations, the analysis plots facility management headcount and the number of workers served against a Mission Complexity Score (MCS), a statistically-based number reflecting a company’s particular set of management and mission variables. The analysis provides a meaningful staffing level guide applicable to a wide variety of business entities and industries.

Mission Complexity Score: Scope, Space, and Services

To account for the multiplicity and interrelatedness of variables in facilities management, the MCS quantifies information in three key areas: mission scope, space portfolio, and services offered. Westfall plots Mission Complexity Scores for all firms in his study against their actual facilities management headcounts.

Mission Scope variables include population served, own/lease practices, lease types, occupancy density, age of the space portfolio, and churn, along with special management features such as the use of FM technologies.

The Space component of the MCS calculation involves the amount of different types of space under management. This includes 10 different space types such as vacant space, warehouses, public space, offices, manufacturing, and research labs. Space weights for each type are expressed as multiples of the office space weight, which is assigned the value of 1.00 (according to a modeling technique developed by IBM’s corporate real estate group in the 1980s).

The Services Offered component is the numerically weighted menu of services offered from a list of 25 commonly provided FM services, such as real estate services, engineering, planning and space management, operations and maintenance, moves, EHS, custodial, and security.

Revelations

Westfall pulls several examples from the pool of MCS study participants to illustrate what the graphical plots of staffing versus Mission Complexity Scores can reveal.

First, they illustrate how organizations with very different FM strategies and organizational approaches can be compared to a common staffing standard. The point is not whether an organization has a high or low staffing ratio, but whether it is high or low relative to its Mission Complexity Score.

“The very lean Microsoft Corp., for example, which maintains an aggressive outsourcing approach to its portfolio of owned office facilities, has one of the lowest MCS numbers in the reference panel, thus occupying one of the lowest points on the graph,” Westfall notes. “The Federal Reserve Bank of Boston, which occupies ‘old-ish’ owned office facilities in an urban area and outsources virtually nothing, falls midrange on the regression line. Both organizations show as being essentially ‘on the line’ and thus properly staffed for their respective missions.”

Dangers of Same-Industry Benchmarks

The MCS analytical methodology also reveals the dangers of relying on intra-industry benchmarking. For instance, in the automotive world, Ford Motor Co. shows in the graphical plot as having a high MCS with a correspondingly high staffing ratio, while General Motors is very low on the chart. To explain the difference, it’s necessary to look at the respective management missions for the reporting units.

“The Ford entity on the chart is its R&D headquarters building, 50 percent of which is space for research and development labs. This facility is owned by Ford, and very little is outsourced. The General Motors entity, on the other hand, is its leased office headquarters facility where most all services are 100 percent outsourced. Thus, Ford and GM in this instance have very different FM missions, which are reflected in very different staffing models and FM headcounts,” he emphasizes. “Similar differences exist between different pharmaceutical companies and between divisions in the same company. The fact that you are in the same industry as another facility management group, or even a division within the same corporation, does not mean you will automatically have anywhere near the same facility management mission or staffing model.”

Production Support vs. Facilities

Another MCS-based headcount analysis revelation is the common confounding factor that shows up in ultra-specialized organizations that have porous borders between conventional facilities management services and production support services. The failure or inability to make a clear distinction between the two can put some facility groups—such as those at some (but not all) of the National Labs and some (but not all) pharmaceutical sites with manufacturing facilities—literally off the chart in terms of a high ratio of FM headcount to population served.

Why?

“Where facilities workers are used to do more than what most organizations define as strictly facilities management work,” he explains, “the headcount data point will plot out above the standard regression line. What the MCS-based headcount analysis tells you is how many of those heads should be allocated to FM work and how many to production support.”

Westfall cites one such firm in the study with production support challenges in its management mission. The MCS-based analytical process has been helpful in developing a new way to think about and dialogue with top management about the facilities mission. According to Westfall, the company is now using ‘what-if’ MCS analysis to look for ways to streamline the assigned mission, which includes the production support activity.

Measuring Productivity Improvement Over Time

Business landscapes can change dramatically from year to year for a variety of reasons—growth, divestitures, organizational restructuring, changes in geographical locations, real estate portfolio changes, and shifts in product, service, or market focus. Flux in the business landscape makes it almost impossible to track real improvements in facility management productivity.

“Using conventional FM measurement systems, you can’t even benchmark your own organization against what it was five years ago if the mission has changed,” Westfall advises. “If you make the denominator a mission complexity score, which puts a number on the mission five years ago and a number on what it is today, you can see productivity gains or losses against whatever changes in the business landscape have taken place as measured by the mission complexity score.”

For one pharmaceutical company in the study, mission complexity scores calculated four years apart uncovered the opportunity for a significant reduction in FM headcount. Over the four-year time period, its campus changed from research to office occupancy, but the number of facility management service heads relative to the population served stayed the same. The new MCS number for this site predicted that headcount should have dropped dramatically simply because office-space portfolios and office workers require less labor to support than lab portfolios and lab workers. In this case Westfall estimates that it was a $4 million per year expense issue.

“Overstaffing as well as understaffing situations can be hidden in the cost per square-foot analysis, but those situations become quite evident when you factor in the particular mission that your FM organization is charged with,” he explains.

Uncompleted Change Initiatives

MCS-based headcount analyses can also reveal realignment opportunities in cases involving major outsourcing or FM automation initiatives where the re-formed, in-house organizations haven’t changed as much as was planned or expected. In other words, the analysis can flag gains still to be realized in uncompleted change initiatives.

Westfall cites the example of one firm in the study that spent $12 million on new FM software systems intended to help streamline its facilities operations. At the end of three years, with the system implemented, the number of FM heads per 1,000-workers-served plotted out on the MCS chart as essentially unchanged, signaling no productivity improvement.

“Automation packages by themselves don’t automatically streamline management. Someone has to force these benefits,” says Westfall. “It wasn’t until the ‘show-me-the-headcount-reduction’ call went out that the department was reorganized to drive the staffing level down. The result was a decrease of 140 heads, translating into roughly $8 million in annual savings on the original $12 million investment.”

Heads Count

Westfall zeros in on headcount because it is top management’s main control variable for business performance, as daily news headlines chronicling both job cuts and job creations attest.

“The currency of C-level managers is headcount,” he contends, pointing out, “In classical economics, there are two main resources that a captain of industry deals with: capital and labor. Talking in terms of square feet is not part of C-level language when it comes to corporate missions unless your institution is in the retail or real estate business.

“In the facility management section of income and expense statements, labor (headcount) represents more than 50 percent of the facility management cost for most companies and institutions,” he says. “Headcount is also the key cost-control lever, in that you can change your facility management costs tomorrow either by adding or taking away people. Headcount is also the key performance resource, meaning that it takes heads to do the mission.”

Finally, Westfall argues that in contrast to all the metrics based on definitions of a square foot (rentable, net, gross, assignable, etc.), heads are easy to count. There is no debate here: a head is a head, as payroll departments can readily confirm.

The Big Spread in Missions

For a facilities management group, supporting the corporate or institutional mission translates into serving a defined population of workers. Westfall’s methodology starts by tallying up facility management heads per 1,000-workers-served, thus normalizing facilities groups to the size of their missions so that different sized entities can be compared against each other. Included in the facility management headcount are all service heads from operations and maintenance to space planning, engineering, security, and 21 other categories of service personnel, depending on the organization’s particular service menu.

Westfall’s ongoing statistical study of some 90 organizations documents an extremely broad range of staffing ratios, from a low of one FM head per 1,000 people served all the way up to 100 FM heads per 1,000 people served, suggesting a huge diversity in FM missions that should be explainable. In general, companies with very high service ratios of service heads per 1,000 workers served tend to: outsource only minimally; own (not lease) their facilities; have a large percentage of lab or other technical space; have more square feet per occupant; offer a large number of services in their service menus; and operate in older buildings. At the opposite end of the spectrum, those organizations with very low ratios of service heads per 1,000 are mainly office-based organizations; occupying leased facilities; offering a limited menu of services; and having outsourced the majority of their service functions.

“Facilities management is a very complex service proposition with many interrelated variables. That’s why any approach to model it cannot be simplistic,” he warns.

By Nicole Zaro Stahl