Unlocking The Full Potential of Enterprise Data
offerings to outcome-as-a-service 18 models , some of the operational data produced by the equipment may be transmitted directly to the OEM , in a manner that bypasses the operator ’ s IT infrastructure . This creates challenges for the operators who may lack visibility into data raising significant questions about data ownership 19 . Organizations need a clear understanding of the data produced and consumed by their equipment , including data that bypasses their IT infrastructure . Furthermore , they must be aware of their rights and responsibilities towards this data , given the profound economic , legal , and technical implications .
3 LIFECYCLE OF ENTERPRISE DATA ASSETS We begin the discussion about the lifecycle of data by outlining several important principles :
• Data ( including Enterprise Data Assets ) has a lifecycle ,
• Data in industry may outlive the systems that created them or are currently storing them ,
• The lifecycle of data may be dependent on that of the physical assets they relate to , the customers they relate to , supply chains , procurement , and more ,
• Data may need to migrate to other systems during the lifecycle .
The lifecycle starts when the data is created or captured ( sensor reading , capture from an external system , etc .) and ends when this data is “ no longer needed ” ( End of Life or EoL ). At this point , the data is “ disposed of ”: deleted ( in most cases ) or in some cases , mainly in government , it is transferred to another entity for long term archival . One should distinguish between the eligibility for disposition and the moment when the actual action of disposition is executed at a technical level . This is because data may be aggregated with other data that may have different lifecycle rules . De-aggregating expired data to dispose of them separately can be very complex and impractical , let alone cost justifiable . Risk management , Legal and IT should collectively discuss these situations and agree on a pragmatic approach to address them .
In industry , the duration of the lifecycle can range from a few seconds or minutes to years and decades , depending on the data type and a variety of other considerations . The lifecycle characteristics of the data type must be expressed in policies that are formally approved and authorized by the enterprise ’ s top management .
3.1 INFORMATION LIFECYCLE MANAGEMENT
The modern principles of information lifecycle management can be traced back to the post-World War II era , when the US Federal Government recognized the need to develop a lifecycle management methodology to manage the vast quantities of paper records they had to :
• Identify records that are “ no longer needed ” and earmark them for disposal ,
18
Example : Rolls Royce TotalCare ® aka propulsion-as-a-service . https :// www . rollsroyce . com / media / our-stories / discover / 2017 / totalcare . aspx
19 https :// www . tandfonline . com / doi / pdf / 10.1080 / 2573234X . 2021.1945961 Journal of Innovation 41