When we look at project outcomes, assuming that the resources required for the project are adequately provided as planned\u2014or even despite that assumption\u2014we usually encounter four fundamental results:<\/p>\n\n\n\n
These four situations are generally valid whether it\u2019s a robot design project, a construction project, or even a trade fair organization project. But why?<\/p>\n\n\n\n
In February 2002, then U.S. Secretary of Defense Donald Rumsfeld said:<\/p>\n\n\n\n
\n\u201cThere are known knowns. There are things we know that we know.
There are known unknowns. That is to say, there are things that we now know we don\u2019t know.
But there are also unknown unknowns. There are things we do not know we don\u2019t know.\u201d<\/em><\/p>\n<\/blockquote>\n\n\n\nInspired by this statement and expanding it a little, at the beginning of a project we actually face four types of knowledge (or lack of knowledge):<\/p>\n\n\n\n
\n
- Known knowns<\/strong> \u2013 Facts known by us and by most others.<\/li>\n\n\n\n
- Unknown knowns<\/strong> \u2013 Facts unknown to us but known by others (we don\u2019t know that we don\u2019t know them).<\/li>\n\n\n\n
- Known unknowns<\/strong> \u2013 Facts we know that we don\u2019t know, but we know others know them.<\/li>\n\n\n\n
- Unknown unknowns<\/strong> \u2013 Facts unknown to anyone, not yet experienced or discovered.<\/li>\n<\/ol>\n\n\n\n
When planning a project, types 1 (known knowns)<\/strong> and 3 (known unknowns)<\/strong> are not real problems.<\/p>\n\n\n\n
\n
- 1 is already in hand.<\/li>\n\n\n\n
- 3 can be addressed by scheduling research or obtaining consultancy. If planning fails to account for type 3 issues, that\u2019s a planning error.<\/li>\n<\/ul>\n\n\n\n
Example: If a construction project is planned without a soil survey, delays are highly likely. Even with a soil survey, delays may occur if underground obstacles exist that measuring equipment cannot detect. That falls under type 4.<\/p>\n\n\n\n
But types 2<\/strong> and 4<\/strong> are the main culprits behind project schedule failures.<\/p>\n\n\n\n
\n\n\n\nType 2: Unknown Knowns<\/h3>\n\n\n\n
For type 2, the project team cannot do much on their own, because they are missing details they don\u2019t even know they\u2019re missing. These cannot logically be foreseen during planning, so the schedule slips and resources prove insufficient.<\/p>\n\n\n\n
Example: While developing a heavy-load factory transport robot, if you don\u2019t know that in high-tonnage tests the robot\u2019s wheels may slip and spin in place under load, you cannot plan a \u201cwheel redesign\u201d task at the project\u2019s outset.<\/p>\n\n\n\n
\n\n\n\nType 4: Unknown Unknowns<\/h3>\n\n\n\n
For type 4, the project team can do even less. This involves walking uncharted paths without awareness at the beginning that such risks exist.<\/p>\n\n\n\n
Example: If you aim to \u201cdevelop a robot that roams the factory and meets operator needs,\u201d you are stepping into artificial intelligence\u2014an area that, at one time, didn\u2019t even have a well-established theory. Many problems must be solved, but realistically, how much time can you allocate to what? What issues will emerge?<\/p>\n\n\n\n
Even if only a small part of a project involves type 4, that may be enough to derail the project\u2019s objectives. In fact, having just one component in this category is riskier, because it\u2019s easier to overlook.<\/p>\n\n\n\n
\n\n\n\nPossible Solutions<\/h3>\n\n\n\n
For type 2 (Unknown knowns):<\/strong><\/p>\n\n\n\n
\n
- A feasibility phase can include activities to \u201cuncover unknown knowns,\u201d but this is costly.<\/li>\n\n\n\n
- For every subject in which the project team lacks practical expertise<\/strong> (not theoretical), consultancy from experts or institutions can be sought to gain foresight at the planning stage.<\/li>\n\n\n\n
- Since it is unclear where gaps exist, every subject lacking practical expertise<\/em> must be examined. Simply spending more time on research rarely helps, because the team doesn\u2019t even know what kind of problem to look for.<\/li>\n<\/ul>\n\n\n\n
Example: In the robot project mentioned earlier, consultancy could have been sought from someone experienced in indoor heavy-load vehicles (like forklifts, tow tractors) to foresee wheel\u2013gearbox system issues.<\/p>\n\n\n\n
\n
- Alternatively, instead of incurring consultancy costs across multiple fields, the project team may deliberately choose the mindset: \u201cWe know we don\u2019t know everything, delays are possible, but we accept this consciously,\u201d<\/em> and adjust expectations accordingly.<\/li>\n<\/ul>\n\n\n\n
For type 4 (Unknown unknowns):<\/strong><\/p>\n\n\n\n
\n
- If the entire project falls under this type, the best measure is to reduce risks and losses by breaking it into smaller subprojects<\/strong> focused on critical components, gradually eliminating uncertainties.<\/li>\n\n\n\n
- If only part of the project falls under type 4, the challenge is greater. During feasibility and planning, every detail must be scrutinized almost paranoidly<\/em>. Still, detection is unlikely, and delays are almost inevitable.<\/li>\n<\/ul>\n\n\n\n
\n\n\n\nConclusion<\/h3>\n\n\n\n
Because type 2 (unknown knowns)<\/strong> and type 4 (unknown unknowns)<\/strong> are transformed into type 1 (known knowns) after the project is completed, when we look back at delays or failures, they are usually blamed on the planner\u2019s incompetence or negligence.<\/p>\n\n\n\n
But if one shows the wisdom to conduct a sound analysis instead of taking the easy way out, it becomes clear that even completing a project with type 2 or type 4 issues is, in itself, a significant achievement in project execution.<\/p>\n","protected":false},"excerpt":{"rendered":"
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