How We Know What Will Work
The method is based on a mathematical framework that turns out to predict automation outcomes reliably.
Work consists of decisions, and each decision in a process falls into one of two categories.
Explicit Decisions
Follow rules that can be written down completely.
These can be automated.
Tacit Decisions
Require judgment that cannot be fully specified.
These cannot be automated, regardless of what technology you use.
Most processes contain both types. The question is the ratio, and where the tacit decisions occur. A process where tacit judgment concentrates in rare exception handling has a different automation profile than one where it pervades the main workflow.
Why This Works
The distinction between explicit and tacit knowledge is not new. It traces back to work by Shannon on information theory, Turing on computability, and Wiener on control systems. What they established, in different ways, is that there are mathematical limits to what can be formalized and processed by machines. These limits are not technological; they are structural. No amount of better software changes them.
What we do is apply this mathematical framework to business processes. We map out where the decisions are, classify each one, and calculate what percentage of the process can actually be automated. The result is not a subjective assessment but a structural analysis grounded in the same mathematics that underpin every computing system.
Four Steps to Clarity
Decomposition
We map the complete process: every decision point, every exception path, every handoff. This often reveals complexity that does not appear in existing documentation because processes evolve faster than their documentation does.
Classification
Each decision is classified as explicit (fully rule-based), heuristic (partially specifiable with clear boundaries), or tacit (judgment-based, dependent on experience). The classification follows consistent criteria derived from the mathematical framework.
Analysis
We calculate the ratio of explicit to tacit across the process. We identify where tacit knowledge concentrates. We assess what would break under automation and what dependencies exist that current plans may not account for.
Recommendation
We tell you one of three things: proceed as planned because the structure supports it, restructure the process first to make tacit knowledge explicit, or do not automate this work because the structural barriers cannot be overcome. With the evidence behind the recommendation.
What Others Miss
Most technology assessments ask whether a given software can handle a given process. This is the wrong question. The right question is whether the process itself is automatable, independent of what technology you use.
A process full of undocumented judgment calls will fail regardless of what software you use. A process with fully documented rules will likely succeed with any competent implementation. We answer this prior question, telling you whether the conditions for success exist before you evaluate vendors.
Apply the Method
Before your next automation investment, find out whether the structure supports it.
The Predictive Power of Structure
Process structure determines automation outcomes. By analyzing structure before investment, we can predict success or failure with high confidence.