Actualités

25.05.2017 []

Classification synthétique des data (suite à l'atelier de la réunion 1)

Lors de l’atelier sur les data et les enjeux nous nous sommes essayés à « définir » quelques classes de haut niveau (cad significative au travers de toute entreprise et perceptible par les dirigeants) afin de structurer les informations selon différents types d’enjeux de gouvernance et de gestion.

Ci-après pour vos commentaires et suggestions une tentative de synthèse selon 3 dimensions.

PS, le Club Urba-EA s’essayant aussi à une ouverture internationale des contenus, la suite est en globish

“Legal & Regulatory Data” complying to legal and business regulation obligations

• Risk & Quality driven – risk possibly high : financial penalties, rights to operate, reputation…
• No (real) choice – constrained by external authorities
• level of compliancy and risk for not complying to be defined at enterprise level (Bus. Heads, Legal, HR, Finance, Quality, Security, CIO…)
• Legal obligations to be consistently managed at enterprise level taking into account national rules (Legal, Finance, HR, Security…)
• Business regulatory obligations to be managed at enterprise and business levels (Bus. Heads, Quality, CIO…)

“Vital & Strategic Data” critical to secure vital operations in crisis contexts, preserve legal and financial rights, drive market value and competitive advantage

• Value & Security driven – risk upon failure is as high as the value is : Enterprise survival – Enterprise success …
• Most sensitive and valuable data enterprise-wide
• Policy imperatives and management rules to be defined at enterprise and business levels (Bus. Heads, Bus. Strategist, Operation Officers, Security, Legal, CIO…)

“Operational Data” used in the course of enterprise activities and operations

• Efficiency driven – optimizing value vs. risk vs. cost – quality vs. agility vs. security, depending on business contexts (automation, baseline, production, customer focus, assessments/investigations, innovation, disruption…)
• Intangible assets supporting enterprise management, operations, decisions making, R&D, partners and customers transactions, services value, income generation…
• To be managed as most appropriate for each data and usage under each entity authority (business, affiliate, country…), according to enterprise data policy and management global rules