Why Should Business Invest In Data?

Data management professionals often lament that the business just doesn't get the value of data. Unfortunately, most data management people don't understand the language of value in business. So they can't effectively communicate the value to the business. This presentation will introduce the data management professional to the vocabulary and concepts that financially knowledgeable business professionals use to quantify business value. It will also present practical advice on how the data management professional can work with the business professional to ensure they understand the value of investing in their data.

Specific topics we will cover include:

How business generates value through executing business capabilities/processes
How business measures value through concepts such as Net Present Value (NPV) and Internal Rate of Return (IRR)
How the value generated by business capabilities can be improved by improving the data
How the improvement to the value produced by business capabilities by improving the data can be estimated
How the value of investing in data can be compared to the value of investing in other corporate assets such as physical capital, financial capital, human capital, etc. so the case can be made for investing limited funds in data

With over 40 years of experience, Richard Howey has been involved in data management and governance since the early days of relational databases to the current emerging world of big data. He has been a consultant with big 5 consulting firms as well as an employee at Fortune 50 companies. This has given him the opportunity to be a part of many successful and unsuccessful strategic data management initiatives at numerous companies. This experience has taught him that the primary reasons for lack of data management success are non-technical and generally outside the control of a data management project. He is currently working on a doctorate degree where his research dissertation is examining how the culture of a business enterprise affects the success of data sharing initiatives such as master data management.