Excerpt from Enterprise Architecture Fundamentals:
Not by chance, these objectives can be neatly aligned with the triad of data (quality and descriptive statistics), information (logic and statistical inference), and knowledge (time-dependent risk assessment).
At the enterprise level, the relationship between time, the reliability of information, and causal chains, allows for a dynamic integration of DM processes and knowledge-based enterprise architecture (cf. chapter 9). That understanding of DM integration sheds a new light on the distinction between operational, tactical, and strategic decision-making (cf. illustration introducing this chapter):
- Operational: observed data can be directly mapped to information and put to use as knowledge, thus allowing for routine decision-making (e.g., weapons must be kept ready).
- Tactical: partial or imperfect information can be improved with additional data until causal chains are secured. Risks are managed through traceability, and the timing of decisions will depend on a cost/benefit assessment of improving trace- ability (e.g., delaying a decision until more can be known about the approaching army will leave less time to act).
- Strategic: unreliable or insufficient relevant facts and doubtful causal chains prevent cost/benefit assessments within the targeted time frame. Whenever such decisions must be taken and changes committed to, risk-management schemes are introduced to cover for ill-fated turns of events (e.g., escape route for a defeated army).
While operational and tactical decision-making are supposed to be the preserve of systems and business units, the digital transformation is amalgamating the stakes and spreading the hazards — as illustrated by the range of potential consequences of a data breach, from regulatory sanctions for noncompliance to damage to customers’ trust. Enterprise architects must therefore marshal overlapping DM levels, and the best way to do that is through the smart use of data, information, and knowledge to support decisions.