When an organization undertakes a major Information Technology project, most executives, managers, and project sponsors overlook an important component in the total cost of ownership equation; “maintenance and enhancements“. I am not referring to software, hardware, and cloud hosting maintenance fees. When capitalized dollars are used as the funding source for the project, due diligence is given to these items as these costs are folded into the depreciation schedule associated with the endeavor. I am referring to the steady state costs. Based on the architecture and design patterns employed in the project, what are the future carrying expenses as enhancements and maintenance activities are performed?
It appears there is a new quest for the holy grail in Master Data Management; autonomous processing. The hypothesis is simple. Given the proper set of business rules, robust master data management algorithms, and machine learning applications, the need for human review and intervention can be eliminated from the Data Stewardship process. I would argue not so fast. For the foreseeable future, there will always be the need for manual stewardship. While the new breed of technologies should reduce the length of exception queue, nonetheless the queue will continue to exist. Manual data stewardship drives quality assurance. The data stewardship exception queue requires manual review