Q&A: What We're Learning from Decision Engineering — Part 2: Retiring the Term 'Knowledge Worker'
Perhaps you've been using the term 'knowledge worker' in your process modeling without giving it too much thought. But does 'knowledge worker' allow you to make the distinctions needed for engineering operational business decisions and automating white-collar work?
In the first part of this three-part Q&A[1] I argued that it doesn't. So what terms are better suited? How will those terms help you better understand workers' relationships with both operational business decisions and business rules? How are the distinctions among them important for engineering smarter business solutions? Read on to find out the answers to these and other timely questions.
Q: Is 'knowledge worker' a suitable term for decision engineering?
A: No. In a day and age where the automation of operational business decisions is increasingly the goal, I maintain that 'knowledge worker' is not a helpful term at all. It's simply too broad. Instead I use the terms 'white-collar worker' and 'gold-collar worker'.
Q: What's the key differentiation between white-collar workers and gold-collar workers?
A: The work of gold-collar workers involves non-routine problem solving, which requires a combination of convergent, divergent, and creative thinking.
The work of white-collar workers, in contrast, involves fairly repetitious sets of tasks, which at least in theory should produce relatively consistent results. Also, white-collar workers generally receive much less training than gold-collar workers.
Although the boundary between the two categories is a bit fuzzy, I believe they can be generally distinguished. Relevant questions include: How routine is the work? How consistent should results of the work be? And how much training is required?
Q: Can you give an example?
A: Consider loan officers in a bank, handling applications for mortgages. White-collar or gold collar work?
I'd call their work relatively routine. Even though each loan application is different and might involve special cases or exceptions, the work is always about mortgages.
What about consistency? You'd like to think different loan officers could produce consistent results on similar kinds of loan applications. At least in theory they should be able to.
What about training? Although loan officers do receive significant training and mentoring, it's not on the order of years as for gold-collar workers.
So based on those three criteria — routineness, consistency, and training — I believe loan officers clearly fall into the white-collar category.
Q: Do organizations currently achieve desirable levels of consistency in white-collar work?
A: No. I've seen studies comparing results across peers with roughly the same training and experience. The numbers are significantly lower than you might expect. That's not good at all for either customer experience or the well-being of the organization.
Q: Can white-collar decision-making work be automated?
A: Automating white-collar decision-making work is exactly the focus of business rules and decision engineering. For example I'm certain from experience that at least 50% to 80% (maybe more) of the decision work for mortgage applications can be automated, especially if the organization is willing to standardize and simplify the adjudication rules some. Huge benefits can be achieved in terms of consistent customer experience, higher productivity, and directly-provable compliance.
Q: Can you differentiate between white-collar work and gold-collar work in that the latter cannot be automated?
A: In a day and age when IBM Watson can win at Jeopardy, it's probably foolish to try.
But I don't think that's the right question. Instead, I would ask whether the problem spaces are sufficiently distinct that they require different approaches. The answer to that question is definitely yes. That's one reason I think the term 'knowledge worker' is not a useful one — one size simply doesn't fit all.
Companies pay gold-collar workers for their professional insight, creativity, and ability to digest expansive amounts of knowledge on a continuous basis. Novel, unexpected results that fit the data better are at a premium.
That's not what companies pay white-collar workers for — or at least it shouldn't be. Instead, they should pay white-collar workers to produce consistent results on decisions reached through directly-traceable logic — that is, business rules. Unexpected results represent a failure — of an individual worker, a training regimen, or the rules themselves.
Q: Should white-collar workers themselves be blamed for inconsistency in results?
A: More often than not, I think the problem actually lies with the rules. In many companies, we ask humans to make operational business decisions in a fog of byzantine rules — rules often far more complex than reasonable (or profitable). In addition, the 'real' rules are frequently more tacit or inaccessible than anyone cares to admit.
In my view we simply have never been serious about defining, organizing, and managing the rules in white-collar decision-making in a reasonable, scalable manner. And most organizations certainly haven't yet harnessed the power of computers to help with the business-side problem of rule management.
Q: Can you differentiate knowledge workers by how much improvising or innovating is desired?
A: Some people argue that a knowledge worker is anyone paid to improvise or innovate, a factor distinct from the amount of training the worker receives. By this criterion even blue-collar workers can be considered knowledge workers if they constantly improvise or innovate.
I don't find that notion helpful. In my mind, a blue-collar worker who is constantly improvising or innovating has become an engineer — which is gold-collar, not blue-collar.
With respect to white-collar work, many (or most) organizations suffer from what I call 'white-collar entropy', the cumulative result of continuous and counterproductive improvising over time. A vacuum of coordination filled with too much information simply does not translate into a more productive organization. The more likely result is inconsistency, the enemy of good customer experience.
Q: More than simply apply rules, don't knowledge workers also invent rules?
A: That's what people in the improvise-and-innovate camp say. But hang on a minute. To take a real-life example, do we really want police officers (officers on the beat) inventing rules?! I think not. Their job is to apply rules (laws), not invent them. Otherwise we'd be living in a police state.
In a well-run organization, just as in society, above all you want consistency at the operational level. If I call my bank ten different times, I should get the same answer ten different times. If I apply for a mortgage from the same bank at ten different branches, I should get the same result ten different times.
In my experience, that's hardly the norm. Why? If staff works in an environment where many of the rules are tacit, contradictory, ambiguous, poorly implemented, inaccessible, and/or unintelligible, of course the staff will improvise.
Contrary to what some believe, well-defined rules do not lessen creativity. That's simply not the way it works. Absence of rules is literally anarchy — and only the bad guys look clever in that context.
Q: What do you mean by 'creativity' here?
A: I mean the space to improvise and innovate about how to get desired results. For example a good police officer should be improvising and innovating all the time — within the framework of the law. There's no contradiction there whatsoever.
Q: How do service workers fit with white-collar and gold-collar workers?
A: The term 'pink-collar worker' is sometimes used in the U.S. at least to refer to a job in the service industry. Many people find the term off-putting because it traditionally referred to jobs relegated to women.
I avoid the term for several other reasons. For one thing, the category includes such people as nurses and teachers, who are clearly gold-collar. For another, it includes such roles as buyers, loan interviewers, dieticians, administrative assistants, etc., whose work at the high-end should be considered white-collar. Finally, it includes workers providing personal services on an individual basis, rather than business services in the usual sense. Examples include midwives; hairdressers and barbers; baby sitters and nannies; personal shoppers and fashion stylists; etc.
To deliver services many businesses have extensive staff that is neither white-collar nor gold-collar. Examples include retail workers, sales staff, flight attendants, hotel housekeepers, counter attendants, receptionists, etc. I just call them 'service workers' since they don't have any traditional uniform color — white, blue, or otherwise.
Q: Are service workers subject to business rules?
A: Of course. Generally the rules are behavioral rules rather than decision rules though, since their jobs do not focus on operational business decisions.
Q: What's the difference between behavioral rules and decision rules?
A: Behavioral rules are rules people can violate; decision rules are rules that shape knowledge or information. Decision rules cannot be violated — knowledge or information just is what it is defined to be.[2]
Q: In what ways are service workers subject to business rules?
A: Service workers are obviously subject to obeying behavioral rules. For example a cashier must obey the rule: A credit card must not be accepted for a purchase under $10.
Service workers are also often subject to enforcing certain behavioral rules. For example, flight attendants must ensure that passengers buckle their seat belts for each take-off and landing.
Service workers are subject to operational business decisions made by white-collar workers but do not play a significant role in making such decisions themselves.
Q: What's the relationship between business rules and white-collar workers?
A: White-collar workers are typically involved in business processes where operational business decisions are made. Examples include: Should this loan applicant be given a mortgage? What flight crew should be assigned to this flight?
White-collar workers generally do not define decision rules themselves — that's typically work for gold-collar workers. Where such rules are incomplete, unspecified, or contradictory, however, white-collar workers generally rely on personal heuristics and experience to make decisions. This approach puts the main goals for white-collar work — consistency and traceability — at serious risk.
White-collar workers, like all workers, are subject to obeying behavioral rules. Examples include: A loan officer must not handle a loan application placed by a family member. The website description for a new product must be approved by two senior managers.
Q: What's the relationship between business rules and gold-collar workers?
A: Gold-collar workers are responsible for non-routine, knowledge-intensive work. The primary goal for such work is that it be insightful — for example a medical diagnosis that fits the available data better — or that it be creative — for example a new marketing strategy. That type of work is generally beyond the scope of decision rules.
Although gold-collar workers often conduct their work in relatively-independent fashion, the work is generally subject to "very close normative control from organizations they work for."[3] Think medical malpractice or following generally-accepted principles of accounting. These normative controls, since they can be violated, are sets of behavioral rules.
In the third and final part of this three-part series, I will detail how professionals should now be thinking about and developing business process models.
For further information, please visit BRSolutions.com
References
[1] Ronald G. Ross, "Q&A: What We're Learning from Decision Engineering — Part 1: Tackling White-Collar Work," Business Rules Journal, Vol. 16, No. 1 (Jan. 2015), URL: http://www.BRCommunity.com/a2015/b792.html
[2] Ronald G. Ross, "Decision Rules vs. Behavioral Rules," Business Rules Journal, Vol. 14, No. 7 (July 2013), URL: http://www.BRCommunity.com/a2013/b709.html
[3] "Knowledge Worker," Wikipedia
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