Ascertaining the Level of Work Difficulty for Work Planning (for grant proposals)

This slideshow explores some initial ways to assess the difficulty of proposed work (such as for a grant proposal), in order to accurately estimate the amount of labor, time, resources, and other elements needed to actualize the work. A common challenge in this space involves various cognitive biases, including optimism bias, which leads to inaccurate estimates. These can lead to missed deadlines, project cost overruns, and other even project failure. In grant applications, inaccurate understandings lead to infeasible estimates and the declination of funding. Understanding work difficulty not only makes a grant proposal more competitive but enhances work plan feasibility.

1. Ascertaining the Level
of Work Difficulty for
Work Planning
(for grant proposals)

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3. Overview
•This slideshow explores some initial ways to assess the difficulty
of proposed work (such as for a grant proposal), in order to
accurately estimate the amount of labor, time, resources, and
other elements needed to actualize the work. A common
challenge in this space involves various cognitive biases,
including optimism bias, which leads to inaccurate estimates.
These can lead to missed deadlines, project cost overruns, and
other even project failure. In grant applications, inaccurate
understandings lead to infeasible estimates and the declination of
funding. Understanding work difficulty not only makes a grant
proposal more competitive but enhances work plan feasibility.
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4. Why Work Difficulty is
Difficult to Gauge?
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5. A Lack of Metrics Based on Actual Work
History
•In cases where there is no history of specific work in the
discipline, in the organization, on which to project necessary
inputs (of labor, of time, of resources), the work team will have to
find less direct ways to projecting the necessary inputs.
•Wholly novel projects may be difficult to anticipate because of the
known knowns, known unknowns, unknown knowns, and
unknown unknowns.
•Analogical projects may not be true comparables.
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6. Human Cognitive Biases
•Human cognitive biases are tendencies in human thinking that
conflict with rationality and neutral decision-making. They
confound logic in many ways. They affect human perception,
sense-making, decision-making, and various thinking.
•Many may not be aware of their cognitive biases.
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7. Examples of Human Cognitive Biases
•People tend to believe that they have more expertise than they
actually do, even if they have no background or training or
experience in the topic. (Dunning-Kruger effect) (“the
democratization of expertise”)
•People tend to act to protect their sense of self-esteem, by taking
credit for outcomes that make them look good but blaming
outside factors for non-salutary outcomes. (self-serving bias)
•People have a tendency to take in information that aligns with
what they already believe. (confirmation bias)
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8. Examples of Human Cognitive Biases (cont.)
•People have a tendency to believe that internal factors to an
individual led to an outcome instead of considering the effect of
external in-world factors. (attribution bias)
•People tend to believe others are aligned with their own beliefs.
(false consensus effect)
•People tend to like others who are similar to themselves based on
various dimensions. (affinity bias)
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9. Examples of Human Cognitive Biases (cont.)
•People tend to believe what comes to mind easily instead of
critically considering what they are thinking. (availability heuristic)
•People tend to be amenable to particular decisions based on
particular presentation frameworks. (framing effects)
•People may be affected by being exposed to a particular number
early on. (anchoring bias)
•People tend to believe that random events will even out over time,
so if there is a run of poor luck, some good luck may be in the
future. (Gambler’s fallacy)
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10. Some Effects of Human
Cognitive Biases on
Work Projections
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11. Minimization of Work Challenges
•The development team can work through challenges even if they
do not have direct professional training or experience in that area
of work. (Dunning-Kruger effect)
•The development team is very capable. (self-serving bias)
(confirmation bias)
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12. The Over-Emphasis on Self-Will
•Others’ internal factors affect their performance as the team’s
internal factors will lead to success. Outside-world factors may
be controllable. (attribution bias)
•The grant funders and external grant evaluators will think like the
team does and assume that all assertions made in the work plan
are solid. (false consensus effect)
•The grant funders and external grant evaluators are people like the
applicant team. They know the discipline. (affinity bias)
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13. Self-Deservingness
•The development team feels positive. It feels like there are
tailwinds in the grant funding effort. One can imagine success so
close! (availability heuristic)
•The organization has positive media coverage, which should be a
net positive for the grant funder. (framing effects)
•The applicant team is asking for the full amount available per
project, even if the entire amount is not necessarily needed.
(anchoring bias)
•Because the organization has had a run of non-funded grant
applications, this next one is due for being funded. (Gambler’s
fallacy)
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14. Ways to Assess Work
Difficulty
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15. Project Novelty
•A project that is a “known quantity” offers some basis by which to
understand the necessary inputs and the costs (labor, time, resources,
etc.).
•The “priors” enable some basis by which to project what is necessary.
•A novel project, which involves plenty of unknowns, may be harder to
describe in an anticipated way.
•Building from scratch offers more leeway but also more room to mis-
anticipate.
•The mapping of new processes requires ingenuity and doggedness.
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16. Project Novelty (cont.)
•Some creative problems cannot be addressed directly, only
indirectly.
•Getting a project started can be challenging. Even finding a way in
can be perplexing.
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17. Project Complexity
•A work project’s complexity is an important factor in terms of what
is needed.
•Some dimensions of complexity include the following:
•The number of disciplines involved
•The number of collaborators (and the need for coordination)
•The objectives of the work
•The novelty of the work
•The project’s scope and scale
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18. Project Complexity (cont.)
•It may take some time to even realize how big the work is.
•Projects may involve elements of non-obviousness that only
reveal in time. The full complexity cannot be anticipated.
•The level of rigor of testing based on high performance
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19. Cognitive Load of the Projected Work
•The ambitions and objectives of the work involve some level of
intrinsic load, that is, the inherent difficulty of the project.
•The cognitive load of the work may be made worse based on poor
work design (extraneous cognitive load).
•In the absence of prior information, the germane cognitive load
becomes even more difficult. The mental effort required is much
higher to make connections that have not already been made.
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20. Work Pacing
•The anticipated pace of the work is an indicator of the work
difficulty.
•The pacing is likely not consistent and non-continuous (sporadic).
Perhaps punctuated equilibrium is the typical progress profile
during parts of the work. Steady progress is a goal vs. the stalling
out of progress.
•The work pacing may not be sustainable over time.
•In creative work, there is a level of incubation needed for ideas
and methods to gestate.
•The team will have different levels of preparedness.
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21. Project Scope and Scale
•The size of the project affects the work difficulty. This includes the
project scope and scale.
•As the work proceeds, there are new understandings.
•Scope creep is inevitable. Some of it is absolutely necessary.
Work projects are not fully defined by the work plan.
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22. Elusive Breakthroughs
•Work projects experience various “emergences”. Various factors
arise in the process of the work.
•There are dead ends, mistakes, work trail dependencies and
holdups (temporary and permanent), shifts in objectives, shifts in
methods, shifts in availabilities of technologies and equipment,
and surprises (some nasty).
•Necessary breakthroughs do not arrive on schedule, if they arrive
at all.
•Negative externalities may arise and cause various harms.
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23. Staffing Changes
•For many teams, people move on. This is especially so for longer-
term projects. This is so for more difficult work.
•Each move may mean some loss of function. [If it is a toxic team
member, it may result in a net gain of function.]
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24. Political Headwinds
•Human frictions and clashing visions and personalities can be a
major headwind to projects.
•Necessary buy-ins may not be forthcoming.
•Political support may be fragile. Such support is always
conditional.
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25. External Competition
•There may be pressure from external competitors.
•Competition can be an inspiration. For some, it may be
intimidating.
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26. Learning as One Goes
•During the work, the team will find out what it actually takes to get
to particular project milestones and deliverables.
•The team will learn about each other’s level of functioning. (It is
difficult to assess others’ level of knowledge, skills, and abilities
from documented work and reputation alone.)
•Work troubleshooting along the way is par for the course. There
may be compounding difficulties and cascades. There may be
challenges external to the direct work. Catching errors and issues
early may benefit the work. It may enable early recovery and
redirection.
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27. Learning as One Goes (cont.)
•The team will need to build anti-fragility in along the way. They will
have to fight against the risks of non-completion at every step.
•The meta-awareness of team progress, team dynamics, work
phases, and such, benefits the work.
•There are different ways of knowing, some computational, others
basically observational. Each provides a perspective.
•There is room for constant adaptation and improvement, in a
project management sense.
•All project tools are in service of the team (the principals)…and
the work.
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28. Building in Some
Additional Margin
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29. True Difficulty
•Work designs for projects (and grant applications) require a close
adherence to real-world logics and realities.
•It is a risk to trivialize expertise. It is a risk to simplicity-wash (to
address complexity as if it were simple). It is a risk to engage in
wishful thinking about imaginary capabilities.
•It is a risk to go with the imaginary vs. the real, truth claims vs. the
actuals.
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30. Building Margin
•In some cases, margin may be built into the work design, the work
scheduling, the staffing, the budgeting, and so on. There is some
room for maneuver in the labor, the time, and the assigned
resources.
•In many cases, margin is not possible. The room for error is thin.
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31. Conclusion and
Contact
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32. A 100% Work Plan?
•No work designer will get the work plan 100%.
•The goal is to create a work plan that enables quality, speed,
flexibility, and achievements. Ultimately, the success of the work
project is dependent in part on the planning and then the adapting
to the plan.
•Getting the difficulty of the work project right benefits in terms of
planning out the work.
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34. Conclusion and Contact
•Dr. Shalin Hai-Jew
•[email protected]
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