The current economic crisis makes any investment spending difficult. Previous posts discussed how Enterprise IT will see little capital investment, slices budgets, and big cuts. Today, let’s talk about the case to invest in enterprise intangible assets.
It’s almost a given that no CEO will authorize a project just to improve “data quality”. A project that improves the return on assets – data assets in this case – and can prove it, will be considered differently.
Setting up a measure on the data ‘return on assets’ must be tied to real operational metrics—and dollars-- to have meaning. Just as improving sales data in a CRM software package is tied to objectives in sales and marketing, the use of investment dollars for enterprise IT-held data needs to be similarly evaluated. Cleaning up data with visible costs prior to data science, machine learning, or other AI projects is just as vital as preparing the ground before doing a building construction project.
Capturing a cost spreadsheet for data consolidation, database model building, and ETL costs is a start on understanding the costs of data exploitation. Capturing a cost spreadsheet for large projects where those costs would be hidden is a start on performing comparisons. The return on assets benefits from the data quality improvement may be justified in cost and risk management in the enterprise IT group alone.
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