How do you report data warehousing ROI?

Explanation provides a clear understanding of ROI in the context of data warehousing. Additionally, it may be beneficial to include a total cost of ownership (TCO) analysis over the lifespan of the data warehouse. This provides a more comprehensive view of ROI, taking into account factors like depreciation and the potential need for future investments in infrastructure or optimization.

In my experience, there are 4 main categories when it comes to the ROI of a data warehouse initiative. These include revenue generation, risk mitigation, increased operational efficiency, and enhanced experience (both employee and customer/member). Once you have categories to work with, it becomes a little easier to start thinking through specific use cases for each category as they tie to your business and your KPIs. My advice is to not let perfect get in the way of good. You are exploring a data warehouse for a reason, so don't get too hung up on having exact numbers! You can do simple exercises like time studies or sampling to deduce the numbers needed to calculate ROI.

If you are able to get intangible benefits through customer reviews , you will automatically can get to tangible benefits. Always focus your data warehousing solution through customer focused .

Data can be used to improve existing processed through daily operations, or directly by automating some decisions such as recommendations. The latter is easy to measure since it's a technical process, but the former leads to gradual improvement over time in most users. So, perhaps quantifying usage is a good starting point to measure if it's helpful at all. To find out how much of an impact data has - ask the data users what they think would happen if you took it away. Would they not care? Or is data vital to reach goals?

This is not an easy goal to accomplish. Data warhouses definitely have tangible benefits, they also have several intangible benefits. Some of the tangible benefits are increased utilization of resources, and improved production throughout. ROI for such tangible benefits are relatively easy to calculate. When it comes to intangible benefits, this becomes harder. For example, improved customer service, thus customer retention and more upsell and cross-sell opportunities. It is not easy to allocate or measure the contribution of a Data warehouse towards that goal.

For intangible benefits, consider also utilizing analytics and data mining to uncover insights into customer behavior or operational efficiency. This quantitative data can supplement the qualitative data collected through surveys and interviews, providing a more rounded view of the intangible benefits.

It may also be helpful to consider and measure the opportunity costs, for instance, the alternative benefits that could have been realized had the resources been allocated elsewhere. This provides a more holistic understanding of the investment made in data warehousing.

Consider utilizing interactive dashboards that allow stakeholders to delve into different aspects of ROI. This interactive approach can provide a deeper understanding and engagement with the ROI analysis, making the reporting more impactful.