Job Performance in 3D

Thursday, May 24, 2012 - by Benjamin Ruark

The learning and development profession has amassed a great deal of knowledge on training effectiveness, performance transfer, supervisory monitoring and coaching, and rewarding excellent performance. Knowing what you know, are you more than a little dismayed with how many services you encounter daily—in companies large and small, in your city—where you walk away feeling less than wowed? Thinking, "That sure could’ve gone better." Perhaps wearing a rueful smile, you wonder that, despite all the training going on, in one form or another, the typical service transaction is so predictably mediocre; so one dimensional: as customers go, you may as well have been a cardboard cutout. And if you expressed a special need or want, or complained, the service deliverer looked peeved, got argumentative, or was indifferent at best.

If this kind of experience resonates loud and clear, it’s because you’re being treated as the object of a service transaction. You stand outside it. An a priori assumption at work, here, is that you’re not part and parcel of that service transaction per se. However effective, or not, the design and follow-through of training that a service person receives, the subtle takeaway is that no matter the particular nature of that service, it always gets done to you.

Apart from illustrating non-stellar performance, what do these five service scenarios all have in common?

  • The bank teller who counts out your cash too fast to accurately keep up;
  • The maintenance guy who replaces a bathtub drain plug, performs a quick test and pronounces it fixed—the next morning, you find the drain still leaks;
  • The store manager who gives you the overpaid difference after hearing your complaint of being charged full price on an item whose shelf-price is discounted 20%; then you get a repeat experience of the same problem a week later;
  • The sales clerk in electronics who neglects to mention, until after you’d paid for a product, that several more annoying steps need to be completed before your product is fully operational;
  • The cable-TV customer-support technician who interrupts your description of a problem with your reception by prematurely instructing you to perform the following menu of steps using the remote.

If you answered, “They’re doing it to me,” you’re absolutely correct. If this a priori assumption is the culprit of shoddy service performance, then what planted it there? Where is it rooted so deep as to ubiquitously defy casual detection?

The shortsightedness of "do to"

Back when Sidney Fine and his cohorts created functional job analysis (FJA; circa mid-1940s), the majority jobs focused on things. As more contemporary businesses and industries were born, and expanded, people and data overtook the major focus in what became a budding and apparently diehard service economy. But we’re finding out—not just from continuous quality improvement (CQI), but poignantly hearing from the human services disciplines as well—that doing to is myopic enough to risk potentially harmful service outcomes; and at minimum, delivers a partial or lackluster experience for the customer. Doing to people doesn’t equate with doing to machines.

Thus, even today, job-task analysis (JTA) remains oxygen-starved because it continues to exclude the living-breathing customer/end-user as a rightful third dimension in service delivery. The choke point in a service performance’s explicit or implicit design occurs when those who conduct such analysis—HR compensation analysts and specialists, and training and performance technologists—habitually attend only to the performer’s actions; or at best their analysis meagerly acknowledges the customer in title only.

Customers as an innate part of the service performance equation

Performance in 3-D views the customer interaction with both service and product performance as the implied (if not explicit) natural terminus of a performance task. Customers are not inanimate objects (things) service providers do something to.  They’re not machines, or intermediate products undergoing manufacturing steps. They’re live individuals interacting with a service or product experience as it gets used or consumed. This antiquated do-to mind-set I call one-dimensional performance. Yet, in complex service and manufacturing processes, service providers and operators, respectively, must interact with environmental, regulatory, and numerous other intervening conditions so as to adjust, avoid, compensate, or control for additional variables; or what I call 2-dimensional performance: at this level of complexity, if-thens and intricate algorithms abound in a performance blueprint. Finally, there are customers—introducing a third dimension of variables that help shape the service and its outcome.

Regardless of industry and job title, and depending on the type of job task and its typical performance context, any one or combination of three core human dimensions of the 3-D model is/are likely to be relevant; being worthy enough to embed in a way that resets any conventional service task’s off-target telemetry and robustly completes it. In 3-D mode, a service (or a product’s functionality for that matter) therefore focuses on doing with or for a customer based on how customers:

  1. Need to (and most frequently attempt to) interact with a service or product.
  2. Experience a service or product’s functionality in its entirety.
  3. Are impacted by a service or product; that is, the scope of satisfaction gotten from its use, short, medium, long term.

Indeed, 3-D performance and CQI are inextricably related. But 3-D is profoundly more about service task cohesiveness: service tasks require that deliverers think on their feet; anticipate and proactively respond to customers as the service transaction runs its course. The dynamics are more complex—as a more inclusive JTA should have identified and accounted for.

Allow me to further illustrate the curse of do-to in our contemporary world. My guinea pig for this example is traditional healthcare. If you perused various related journals, you’d witness how patient advocates are in a heated debate over healthcare's hard-to-forsake "do to" stance. Under the current do-to regime it’s not uncommon to see a physician administering his/her expertise to a passive, marginally-engaged patient. The presenting health issue and its treatment occupy center stage, and the submissive patient is expected to comply without personally investing intelligent thought and weighing his/her decisions.

On the other side of the dividing line, the do-with/for patient advocates urge physicians to engage patients to form a therapeutic alliance. This much more collaborative working relationship integrates patient-raised issues such as quality of life, long-term (whole patient) care, and so forth in a co-constructed treatment plan. Supporting my contention that do-to is potentially harmful and too narrow of focus: in 2007, while traditional healthcare continues to reign, Judith Hibbard and fellow researchers conducted a survey of patients. Her findings identified a paltry 23% of respondents who actually adopted prescribed healthcare-adherent behaviors, but also admitted they lacked confidence in maintaining them if they encountered significant events of stress or crisis. Twelve percent of her sample profiled as full-blown passive-recipients; 29% either didn’t believe they had all the facts, or didn’t fully understand their health regimen; and the remaining 36% said they had insufficient confidence and skills to act on the medical facts they had. Returning to those five mediocre service examples at the head of this article, they’re repeated in the table, below, for comparison with how they would appear if JTA had incorporated 3-D performance. (See Table below.)

In some respects, customers are knowledge experts of their service experience. Of their own volition, they test, modify, and occasionally even upgrade the performance capability of a service, or of a product’s functionality. They carry an encyclopedia of live data potentially useful to the service provider or product manufacturer. That said, in order to capture 3-D performance, JTAs would hereafter need to enlist customer collaboration in redefining and resizing any service task. Several modified and supplementary methods therefore must be added to the usual JTA cadre of analytical processes.

Supplemental and modified JTA methods

For example, instead of observing only an SME’s performance, you would assign a second analyst to observe customer interaction and a service’s full impact; but also capture the customer’s narrative or summary of the total experience. Other methods would include modified versions of:

  • Critical incident analysis that deftly incorporates customers’ experience;
  • Focus groups that clarify how customers perceive their interaction with a service;
  • Functional ABC (also called Behavioral) analysis—‘ABC’ stands for antecedents, behaviors, consequences (modified ABC was applied in the do-with/for 3-D examples of the maintenance worker and cable-TV scenarios);
  • A scaled-down quality function deployment (QFD). QFD’s ‘house of quality’ template enables analysts to translate customer non-technical perceptions and expressed needs and wants into detailed specifications for how a performance will transpire, or how a product will perform;
  • Lastly, customer exit interviews could capture the entire experience and scope of impact or extent of satisfaction delivered by service.

If some of these approaches are unknown to you, they can be researched on the Internet. Whichever approach(es) you choose, catching the interaction of customer use with performer actions (or product functionality) better informs the performance equation about which components work fine, as originally conceived; but also clarifies which components need to be integrated or further enhanced. Depending on the type of service involved, when live customer interaction is the rule, JTA identifies a best-fit, synthesized performance envelope equipped to: interact responsively with customers; acknowledge and satisfy the whole experience as customers most likely perceive it; and as best as is humanly possible, stretch the scope of satisfaction to outermost limits. Conversely, when service isn’t live and/or in real time, you’re dealing with a hypothetical customer. In this instance, JTA is tasked to sample the same 3-forked profile—interaction-with, perceived experience, scope of satisfaction—using a stratified collection of experimental customers. Analysts need to set a sufficient sample size and demographic representation so that inferences drawn from their data yield safe conclusions for retrofitting service performance.

Implications

Job performance in 3-D entreats us to go the distance in job-task analysis. Further, that training and performance transfer strategies ensure the customer’s stake in interaction with a service or product carries through; that the interaction reflects do-with/for instead of the parsimonious do-to. So, if this article’s premise were adopted, mainstream, it means that (a) the definition of "task" needs revising, (b) task analysis hereafter is bicentric: focusing on a synthesis of two central characters, giving greater emphasis to how a customer most probably interacts—generally, or specifically—with that service. The time is long overdue to make the paradigmatic break from obsolete do-to, to highly customer-embedded service blueprints and product functionality in today’s marketplace-christened manner of do-with/for.

Job Aid

Improved Service Job Aid

Communities of Practice:   Learning & Development

Authored By

  • Benjamin Ruark
    Benjamin Ruark
    Benjamin E. Ruark is a senior instructional and performance transfer designer.