Searching for the Causes of Future Work

CAUSE VS. UMBRELLA CONCEPT/Image: Michael Moffa

(Part 3 of a 3-part series on recent PwC HR and workplace forecasts. See Part 1, Part 2, Part 3 )

The employment forecasts contained in the PwC report “Managing Tomorrow’s People: The Future of Work to 2010 ” analyzed in two of my recent articles critically depend on a descriptive-explanatory paradigm that identifies “individualism” (“individualistic”), “collectivism” (“collectivistic”), “fragmentation” (“fragmented”) and “integration” (“integrated”) as either the most important explanatory forces or as the most important taxonomy (descriptive classification) germane to forecasting the evolution of the workplace up to 2020.

On the one hand, the PwC report and its language, e.g., “individualism”, strongly suggests these four factors are operating as causes of the changes in the workplace and in employment; on the other, the report also seems to suggest that these are the four most insightful descriptive categories or formsunder which to classify the workplaces of the near future, e.g., “individualistic”, rather than or in addition to their prime movers and drivers of workplace evolution.

This is a very important difference—as important as the difference between “natural selection” and “Homo sapiens” in biological evolution, in which natural selection operates as a principal cause, a prime mover that accounts for the existence of Homo sapiens as a biological form and for the need for the descriptive category “Homo sapiens” as a tool of understanding the evolution of our species. Homo sapiens, as a classified animal form, is only the described effect of natural selection, not a cause comparable to natural selection. Accordingly, the descriptive category “Homo sapiens” is useful only for describing and classifying our species, not for explaining how it came to be.

Analogously, “integration”, “fragmentation”, “individualism” and “collectivism” could correspond to either “natural selection”—in virtue of being the causes of workplace evolution, or correspond to “Homo sapiens”—as an effect, product or label of that evolution. What is unclear from the PwC analysis and model is whether the four concepts function as causal explanations, germane descriptions or both.

Either way, the question remains, irrespective of which role the four play in PwC’s forecasts—explanatory or descriptive; are these the best ones? Are there no other descriptive or explanatory paradigms that could do a better job? That’s the focus of the analysis that follows.

Should We Explain, or Describe?

My article “Axes to Grind: The PwC Future Job Grid ” ended with the Hamletesque question, “To explain, or to describe?”—which allows that in some instances, e.g., the case of “Homo sapiens”, but not all, it is a forced choice between mutually exclusive purposes. In using a model or analytical paradigm to forecast the future of work and the workplace, we must choose or at least clarify: Should the model be designed to explain why the workplace will evolve as predicted, or should it serve only (or also) to classifyits evolved forms? Being curious creatures, most of us probably prefer that the concepts at least accomplish the former—a list of the forces and factors that will cause the changes and shape the evolution, rather than a mere classification of the work-world forms that will result from perhaps unknown causes.

Historically speaking, created classifications of things have preceded the formulation of their explanations. For example, the detailed biological classificationof plants and animals created by the Swedish biologist and physician, Carl Linnaeus, in the 18^th century antedated the identification of their causes by Charles Darwin by approximately a hundred years. Nonetheless, in the case of the future evolution of the world of work, we are very likely to not have much faith in a new classification of the work-world forms if we do not also have an overview of their causes.

Allowing this bias, what could possibly better explain and predict the future forms of the workplace and derivatively describe them, than the PwC four-factor scheme? For the sake of a balanced comparison with the PwC 3-worlds (“Blue”, “Green” and “Orange”), 4-factor paradigm, only 4-factor alternative causal-explanatorymodels should be generated and explored on this basis, after some indispensible preliminaries.

Here are some candidate causal factors, represented in opposed pairs that define a single “axis”. As noted in my “Axes to Grind” article“ the PwC model seems to allow the coexistence of opposites within one workplace description and along one axis, e.g., “integration” and “fragmentation” in the “Blue World”—in the form of a fragmented parent company that nonetheless has well-integrated, networked and interacting spin-off franchises. If the models developed here allow for the same kind of coexistence of causes, this will be interpreted as over-determination of the effects, rather than as a blending of the forms.

To make these alternatives comparable to the PwC “individualism-collectivism” X-axis and the “fragmentation-integration” Y-axis featured in the PwC report, each of the possible causal factors (in boldface) proposed below will also represent one of the two axes in a 4-factor model. Of course, the causes to be identified will have to be selected on the basis of the effects we are most interested in knowing about.

This is a crucial point. For example, if we are mainly interested in where work will be done, we will model the future in terms of variables that determine global, regional or local work location; if it is age-distribution of employees, the model will incorporate causal variables that influence the age demographics of the workforce; if it is work ethic that is to be predicted, variables that affect work loyalties, ethics and goals will be the most central. Likewise, if the main phenomenon of interest is government control and regulation, entirely different sets of causal variables will have to be identified, e.g., trends toward nationalization of industries and regulatory legislation.

On the other hand, if we are merely interested in describing the future world(s) of work, a single descriptive category, like “integrated”, can encompass many of these disparate dimensions of work, e.g., integrated communications, integrated supply chains, integrated employee workplace and home services, culturally integrated staff and operations, and integrated corporate and community values.

Alternative Causes of the Future of Work

That caveat stated, it is a worthwhile exercise to identify alternative variables that are likely to significantly influence the evolution of the work-world and to then develop a 2-axis model analogous to PwC’s, based on combinations of two of these factor pairs.

Start with the variables that are alternatives to PwC’s four, each represented as a pair of opposites on one axis, on analogy with “fragmentation-integration” or “individualism-collectivism”. Then decide whether these alternatives are likely to more dramatically influence the future of work and the workplace in ways that are important to you, to work and to recruitingthan are the PwC variables. After identifying these, mix and match the independent single axes to create 2-axis models that have good predictive, explanatory and strategic potential:

Here are some possible alternatives to the PwC model, on analogy with “individualism vs. collectivism and fragmentation vs. integration” (as two causally independentaxes representing continua, dichotomies and n-chotomies of causes and forces, rather than as merely descriptive labels). Boldfaceterms designate the core causal factors:

Affordable Energy Supplies: Increasing vs. Decreasing
“Agflation” (Costs of Agricultural Products and Supplies):Increasing vs. Decreasing [Notice how these first two on the list, like many others below, are NOT causally independent of each other, although conceptually distinct.]
Artificial Intelligence (A.I.): Increased vs. Decreased Roles for Human Intelligence, Rate of Growth of Man-Machine Hybrids
Capital costs (land, labor, money, information, etc.):Increasing vs. Decreasing
Career trajectories:Lattice vs. Ladder Employment
Centralization of control:Centralized vs. Decentralized Control (micro/macro-economic and/or political)
Children’s impact:High vs. Low Impact (economic, environmental, etc., per child)
Climate: Crises vs. Non-Crises (Heating vs. Cooling vs. Oscillation vs. Stability)
Cultural diffusion: Increasing vs. Decreasing
Credit: Expansion vs. Contraction
Credit Default Swaps and Other Derivatives: Expansion vs. Contraction, Regulation vs. (Continued) Deregulation
Currency: Appreciation vs. Depreciation (or Revaluation vs. Devaluation)
Demographics: Births vs. Deaths
Educational competitiveness: Increasing vs. Decreasing
Enterprise localization: (Re)Localized vs. Outsourced
Environment:Degradation vs. Enhancement
Epidemics: Severe vs. None
Food Supply: Abundance vs. Famine
Fractalization of systems: Increase vs. Decrease of Self-Similar Organizational Structures (like Chinese boxes within Chinese boxes or a tree diagram of branches that branch into identical branches that branch into identical branches that branch into…)
Geopolitical conflicts: Severe vs. Mild (Cultural vs. Racial vs. Ideological vs. Strategic)
GNR (Genetics-Nanotechnology-Robotics): Controlled vs. Uncontrolled Development of Self-Replicating, Self-Directing, Self-Aware Technologies)
Governance: Expanding vs. Contracting (National vs. Regional vs. Global vs. Local)
Human lifespan:Extension vs. Reduction
Information flow: Diffusion vs. Secrecy
Income and wealth distribution: Increasing vs. Decreasing Rich-Poor Gap (through concentration of wealth)
Infrastructure:Improving vs. Deteriorating
Innovation:Increasing vs. Decreasing (technological, political, etc.)
Interest rates: Low vs. High
Knowledge management: Increasingly Manageable vs. Unmanageable Information Loads
Labor source: Human vs. Non-Human Labor (automation, robots, animals, plants, “planimals”—i.e., genetically engineered hybrids)
M&A:Increasing vs. Decreasing Mergers and Acquisitions (numbers and scale)
Migration: Acceleration vs. Deceleration
Money supply level: Expansion vs. Contraction
Money supply source: National Treasury-Issued vs. Central Bank-Issued
Ownership: Governmental vs. Privatized
Political stability: Stable vs. Unstable
Population: Growth vs. Decline
Production: Goods vs. Services
Regulatory environment: Regulation vs. Deregulation
Resource extraction: Renewable vs. Non-Renewable
Savings rates: Increasing vs. Decreasing
Security:Increasing vs. Decreasing (national, home, employment, etc.)
Sovereignty and autonomy: National vs. Corporate
Spending: Increasing vs. Decreasing, Essential vs. Discretionary
Tax burden: Increasing vs. Decreasing (per tax group)
Tax schemes: Trends Toward Progressive vs. Proportional vs. Regressive
Unemployment: Low vs. High
War on Drugs: Success vs. Failure
Work Ethic: Pride of Production vs. Pride of Consumption Focus

When 1=2 and 2=1

Some of these “axes” may, as suggested above, misleadingly seem to be independent of each other, when they are not. Others may misleadingly appear to be dependent, in the sense that changes in degree of one correlate with changes in the degree of the other. Consider for example, “centralization of control” and “regulatory environment”. Despite appearances, these are conceptually distinct axes and variables: An economy can have relatively highly centralized governmental control with, however, few regulatory constraints on a given business, as the 2008 S&L debacle illustrated; on the other hand, control can be decentralized, as it was in various stages of Japanese and European feudalism, but with a high degree of regulation, e.g., of the minutiae of a serf’s daily life and duties.

By the same token, “money supply source” and “tax burden” may appear to be independent, but if critics of the Federal Reserve are right, the current crushing tax burden and the source, viz., Fed fiat money, are two sides of the same fiat coin. Clearly, raising taxes to service the “national debt”, rather than to pay for maintenance or improvement of public infrastructure, will have huge implications for spending, jobs, transportation, distribution and profits.

Modeling and Preparing for Future Work

The daunting, but important challenge is to wisely select the factors that are most germane to your professional and personal priorities, and to describe, predict, explain, prepare for and possibly control the future of your work and your workplace.

This may mean selecting variables different from those PwC identified as most relevant, apparently germane to the “topology” of work, i.e., to the question of whether future-work will feature seamlessly being “a part of” or atomistically being “apart from” other components, much like the contrast between the “integrated”, “collectivistic” connectedness of all points on the surface of the Sun and the “fragmented”, “individualistic” disconnectedness between Sun as a whole and all the other stars in the cosmos, as isolated points of light. Within this frame of reference, the free-lance guild software engineer will work “apart from” the company whose project he has undertaken, while being “a part of” the network that got him the job. It is in this sense that the PwC is a topological model, in it that defines its three worlds in terms of the (dis)connectedness of the components of each.

Because it is a plausible model, it may also seem to be a necessary one. However, as the list of alternative causal factors is perused, it become evident that the work pie may be sliced in more than one way and modeled in dynamic, demographic and other terms, instead of in (dis)connected forms of modeling clay.

The task that lies ahead for you or theoretical model builders is to choose and combine two of the boldfaced factors listed above to create an alternative 4-factor model and decide whether they generate explanations, predictions and classifications of future work-worlds that are as good or better than PwC’s—with the added hope that they can prepare you for what they predict well before that future arrives and leaves you behind.

By Michael Moffa