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As I settled down to pen this piece amidst the festive holiday vibes, my mind drifted towards the games I enjoyed playing during my downtime - chess or poker. These games offer not only a refreshing break from routine but also a practical understanding of how and can be utilized in your organization's autonomous enterprise journey.
The term 'autonomous enterprise' at Digitate embodies an entity that operates primarily on s for repetitive tasks while involvement remns key for strategic decision-making. The question then arises, which tasks should s handle? The answer lies in understanding the nature of data involved: defined or undefined?
Tasks with defined data offer all necessary information and instructions needed to execute them – like a rulebook clearly ld out before you. No ambiguity exists about what needs to be done or how it must be carried out. This makes such activities ripe for management, as algorithms can be trned on historical patterns to make informed decisions.
On the other hand, tasks with undefined data are characterized by incomplete information that requires intuition, interpretation, analysis, deduction and even guessing. These activities involve uncertnty, where assumptions about avlable data or behavior under specific conditions must guide actions - a challenge for s without adequate trning and context.
Chess is an exemplary case of defined tasks. The rules are clear; every move has been mapped out in strategy and history. This makes chess an ideal fit for algorith process patterns, predict outcomes based on input data and execute moves automatically, once enough 'teaching' has been done by s.
Poker, conversely, falls into the realm of undefined tasks with its reliance on incomplete information, intuition about opponents’ strategies and the ever-changing dynamics of chance. These complexities make it difficult for even advancedto predict outcomes accurately without continuous learning from past experiences - a process that is still evolving in technology's pursuit of mastering such games.
The journey towards an autonomous enterprise at Digitate follows these steps:
Manual: intervention alone manages tasks, lacking support.
Augmented: Specific routines are implemented to alleviate repetitive tasks but require trigger.
Automated: s react autonomously upon ticketing or incident reports, executing pre-coded procedures without oversight.
Autonomous: A learning period allows s to suggest and execute actions proactively - improving performance or preventing incidents - with minimal need for intervention.
At Digitate, we've built our flagship platform ignio specifically as an autonomous solution for IT operations management. Once it has mastered its 'learning' phase, ignio can filter through the noise of a production environment to focus on what actions are truly needed. Its library contns over 10,000 customizable use cases that cover every conceivable action - making it more than just a tool for specific needs but an integral part of transforming your IT operations into an autonomous enterprise.
To see ignio in action and experience its capabilities firsthand, request a demo here.
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Author: Ugo Orsi
Chief Customer Officer Digitate
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