Enterprises competing in digital environments must read through massive and continuous flows of data and information, a task that involves four intertwined undertakings:
- Reducing uncertainty
- Establishing reliable causal chains
- Assessing and managing risks
- Enacting commitments and carrying out operations
These undertakings are best achieved when aligned with the OODA (Observation/Orientation/Decision/Action) loop supported by ontologies integrating mediums (thesauruses, models, graphs), contents (data, information, knowledge), and functions (observation, reasoning, decision-making):
- Uncertainties (observations): facts are not gold nuggets ready to be picked from river beds; their meanings are mined from data after proper labelling (thesauruses) and refining (models).
- Causalities (orientation): competing in digital environments means that root causes and rationales, once set upfront, must now be reassessed on a continuous basis. Dealing with the induced causal mazes can only be achieved through the integration of data analytics and information models.
- Risks (decisions): since business competition is by nature a time- dependent, nonzero-sum game, decisions can be weighed until the “last responsible moment,” when delaying a commitment would reduce the range of options or the expected returns. That make room for reassessment for changes in uncertainties (data) and causal chains (information); that can be best achieved with knowledge graphs.
- Operations (action): decisions taken at the enterprise level usually involve sets of intertwined commitments and deeds whose efficiency is determined by the alignment of operations with organization. Set in digital environment, that alignment can benefit from direct observations feedback.
That integration of the different dimensions will ensure the traceability (observation/orientation) and accountability (decision/action) of decision-making processes. More generally it will reinforce the fusing of individual experience and creativity into collective learning.